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File Information This report proposes an approach for breaking the current logjam in the prediction of Cumulative Watershed Effects resulting from timber harvest in regions such as the coastal redwood region of northern California. We preface the proposal with a review of the nature of Cumulative Watershed Effects (CWEs) of timber harvest and a critique of current methods for assessing them. We propose that responsibility for the assessments be taken out of Timber Harvest Applications and given to a new unit of a State agency, which would make whole-watershed assessments of how land use alters the risk of damage to ecosystem values. The risk assessments would be made through spatially registered mathematical simulation of watershed processes, using recently developed methods of modeling and spatial data acquisition and processing. The model-based assessments of risk would then be used by CDF or other agencies in formulating policies for watershed management, considering rates of cutting, locations requiring specific technologies, and the management of risks to particular ecosystem components and functions. The process would involve: multi-stakeholder accord on conceptual models of the target watershed values; agreement about what models need to be implemented and for what purpose; and concurrence on the necessary and appropriate data and predictions for the purpose of decision-making. We also describe how these watershed-scale CWEs could be linked to ongoing efforts in regional-scale assessments, Timber Harvest Plan applications, monitoring, and research.
Authors
Power, Mary :
Resh, Vincent H
Professor   Entomologist-AES
Aquatic insects; life history patterns and population dynamics, in particular, the use of these organisms as indicators of environmental quality
Rodrigues, Kimberly A
Cooperative Extension Specialist, Emeritus
Administration; Environmental Science, Policy and Management; Collaborative Science
Standiford, Richard B
Cooperative Extension Forest Management Specialist, Emeritus
Resource economics; forest management; hardwood rangelands; silviculture
Publication Date Jul 9, 2001
Date Added Sep 16, 2008
OCR Text
A Scientific Basis for the Prediction of Cumulative Watershed Effects by The University of California Committee on Cumulative Watershed Effects WILDLAND RESOURCES CENTER Division of Agriculture and Natural Resources University of California Berkeley , California 94720 Report No . 46 June 2001 A Scientific Basis for the Prediction of Cumulative Watershed Effects by The University of California Committee on Cumulative Watershed Effects Professor Thomas Dunne ( chair ) , University of California Santa Barbara Professor James Agee , University of Washington Professor Steven Beissinger , University of California Berkeley Professor William Dietrich , University of California Berkeley Professor Donald Gray , University of Michigan Professor Mary Power , University of California Berkeley Professor Vincent Resh , University of California Berkeley Director Kimberly Rodrigues , University of California Division of Agric . And Nat . Resources Edited by Richard B . Standiford and Rubyann Arcilla , University of California Center for Forestry WILDLAND RESOURCES CENTER Division of Agriculture and Natural Resources University of California Bekeley , California 94720 Report No . 46 June 2001 Copies of this and other reports published by the Wildland Resources Center may be obtained from : Wildland Resources Center University of California 145 Mulford Hall MC3114 Berkeley , CA 94720 - 3114 ( 510 ) 642 - 0095 The University of California prohibits discrimination against or harassment of any person employed by or seeking employment with the University on the basis of race , color , national origin , religion , sex , physical or mental disability , medical condition ( cancer - related ) , ancestry , marital status , age , sexual orientation , citizenship , or status as a Vietnam - era veteran or special disabled veteran . The University of California is an affirmative action / equal opportunity employer . The University undertakes affirmative action to assure equal employment opportunity for underutilized minorities and women , for persons with disabilities , and for Vietnam - era veterans and special disabled veterans . University policy is intended to be consistent with the provisions of applicable State and Federal law . Inquiries regarding this policy may be addressed to the Affirmative Action Director , University of California , Agriculture and Natural Resources , 300 Lakeside Drive , 6th Floor , Oakland , CA 94612 - 3560 ; ( 510 ) 987 - 0097 . Table of Contents Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Chapter 1 : Statement of the Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Chapter 2 : Responsibilities of the Committee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Chapter 3 : Nature of Cumulative Watershed Effects and the Problem of Identification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Context . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Difficulties of Identifying CWEs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 Interdisciplinary Nature of the CWE Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Chapter 4 : TechnicalAspects of the Current Process forAssessing CWEs in Timber Harvest Plans and Sustained Yield Plans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 Chapter 5 : A Scientific Basis for Predicting Cumulative Watershed Effects . 29 Proposal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Need for a Risk - based Approach to the Prediction of CWEs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Modeling Basis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 Spatially Registered Simulation Models and Gaming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 Personnel and Other Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 Focal Watersheds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 Stakeholder Identification and Mobilization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 Construction of Conceptual Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 Accumulation of databases and choice of models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 Application of Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 Relationship of Process - based Simulation and Gaming to Other Forms of Watershed Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 Chapter 6 : Impediments to the Application of the Proposed Methods for the Recognition , Evaluation and Prediction of CWEs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 1 ) Legal Impediments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 2 ) Conceptual impediments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 3 ) Information and knowledge impediments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 4 ) Economic and social impediments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 Chapter 7 : Removing Technical Impediments to the Evaluation and Prediction of Cumulative Watershed Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 1 ) Legal impediments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 2 ) Conceptual impediments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 3 ) Information and knowledge impediments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 4 ) Economic and social impediments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 Appendix : The Evolving Toolbox : Illustrations of Modeling Capability . . . . . . . . 75 I . Cumulative Effects on Terrestrial Vertebrates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 II . Cumulative Effects on Riparian Biota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 III . Cumulative Hydrological Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 IV . Cumulative Effects of Watershed Changes on Sediment Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 V . Sediment Supply and Sediment Routing Along Channel Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 VI . Modeling Geomorphic Response and the Formation of Aquatic Habitat to Sediment Delivery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 VII . Cumulative Effects on Aquatic Habitat and Aquatic Biota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 VIII.Cumulative Effects on Water Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 IX . Methods for Regional GIS - based Assessments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 X . Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 Executive Summary This report proposes an approach for breaking the current logjam in the prediction of Cumulative Watershed Effects resulting from timber harvest in regions such as the coastal redwood region of northern California . We preface the proposal with a review of the nature of Cumulative Watershed Effects ( CWEs ) of timber harvest and a critique of current methods for assessing them . We propose that responsibility for the assessments be taken out of Timber Harvest Applications and given to a new unit of a State agency , which would make whole - watershed assessments of how land use alters the risk of damage to ecosystem values . The risk assessments would be made through spatially registered mathematical simulation of watershed processes , using recently developed methods of modeling and spatial data acquisition and processing . The model - based assessments of risk would then be used by CDF or other agencies in formulating policies for watershed management , considering rates of cutting , locations requiring specific technologies , and the management of risks to particular ecosystem components and functions . The process would involve : multi - stakeholder accord on conceptual models of the target watershed values ; agreement about what models need to be implemented and for what purpose ; and concurrence on the necessary and appropriate data and predictions for the purpose of decision - making . We also describe how these watershed - scale CWEs could be linked to ongoing efforts in regional - scale assessments , Timber Harvest Plan applications , monitoring , and research . The basic elements of the procedure in each watershed would be : 1 ) Identification of stakeholders and their communal conceptual model of system functions under the leadership of the proposed analytical unit . 2 ) Agreement about the nature of the holistic assessments that need to be made for the purpose of decision - making , and the models to be used for them . 3 ) Data acquisition using currently available spatial databases , sometimes supplemented by new acquisitions through remote sensing and field surveys . 4 ) Use of linked models to calculate the effects of particular land - use scenarios on watershed - scale ecosystem functions . The models would assimilate not only the planned , or reasonably foreseeable timber - harvest patterns , but also stochastic patterns of environmental fluctuations , as they are estimated from environmental records or other projections . Running the simulations many times with this range of input data would allow calculations of the relative risk of water quality deterioration , flooding , habitat degradation , and declines in biotic populations from different management scenarios . The watershed - scale implications of various policies and Best Management Practices 1 could also be assessed . This strategy is called â?? gaming â?? in the following text . Expressing the results in terms of altered risk to resources places them in a form that planners , administrators , economists , lawyers , and the public commonly use in their own decision - making . The models would be implemented as planning models in the manner used to support decision - making in fields such as economic policy , climate and energy policy , risk assessment , or various resource allocations , rather than as models are used in scientific investigations for structuring detailed tests of hypotheses . The process would involve a wider range of skills and a higher level of training than is currently available to Registered Professional Foresters ( RPFs ) and the specialists upon whom they currently call . There are advantages to be gained by separating responsibilities according to scale , both spatial and temporal . Thus , CDF or other State agency , could take on responsibility for defining risk of cumulative watershed impacts at the spatial scale of entire watersheds and over the time scale of a cutting cycle , and the individual RPF could assume responsibility for recognizing local cumulative effects ( hillslope - to - small - watershed - scale ) and their relation to the larger context , as it is defined by the watershed - scale risk analysis . Related work , currently in place , on region - scale assessments and research would be contracted out to the private sector and academia respectively . Figure 1 outlines the relationships between the modeling and gaming strategy for predicting CWEs and the other decision - support activities that are needed for resource management . 2 Figure 1 : The process - based modeling and gaming strategy ( Box 2 ) described in this report would be conducted simultaneously with other decision - support activities , as outlined in the text . Each activity , except for the policy setting ( Box 3 ) , would involve a significant component of fieldwork . We emphasize that Cumulative Watershed Effects cannot be predicted through the existing parcel - by - parcel analysis for Timber Harvest Plan applications , even if it were based on the best current understanding . Nor can future effects be predicted on the basis of short - term empirical studies of past events , although long - term monitoring of post - project effects would gradually build a database for improving and facilitating modeling efforts . As in many other forms of planning and risk management , it is necessary to base assessments of the uncertain future on our current , communal understanding of how systems function , and then to fully evaluate uncertainties , which might be reduced through targeted research . However , there is likely to be enough uncertainty about environmental processes for the foreseeable future that judgment and skill will always be at a premium in CWE assessments and in consequent policy formulation . Thus , to implement the proposed gaming strategy for predicting CWEs the State will have to recruit personnel with a type and level of training that is not currently represented among the professionals conducting CWE analyses . 3 A Scientific Basis for the Recognition and Prediction of Cumulative Watershed Effects â?? There is nothing more difficult to take in hand , more perilous to conduct , or more uncertain in its success , than to take the lead in the introduction of a new order of things . â?쳌 â?? Niccolo Machiavelli Chapter 1 : Statement of the Problem The non - federal forest lands of California are managed under the guidance and regulation of the State government , which has a policy of managing them for multiple sustainable uses , including timber production , maintenance of water quality , wildlife and fish habitat , and recreation . The State has apparently never explicitly acknowledged the need to protect the runoff regulating functions of forests , but is gradually being forced to confront that function also as human settlements spread into forested lands . Some of these uses are in conflict , and the State has taken on the responsibility for maintaining a balance between the activities so that none precludes or diminishes the others over the long term . Striking such a balance is particularly difficult because much of the land is owned privately , and respect for the rights of individual owners to use and profit from their land is crucially important . Thus , decisions to regulate and balance must be made with care , on the basis of credible and authoritative methods for society to agree on the probable environmental effects of altering the forest ecosystem by one means or another . Of course , credible and authoritative methods are also needed for agreeing on the economic and other policy aspects of altering the forest ecosystem , but those methods are beyond the purview of this committee . The challenge is to facilitate decision - making so that both economic activity and the protection of ecosystem services and values can be made more efficient and secure . Differences of opinion about the probable nature and extent of land - use effects on biological resources , water quality , and other values stymie many regulatory and planning decisions . An important component of this debate is the concept of Cumulative Effects , which , in its simplest form , states that two or more influences of land use , or changes on two or more parcels of land , can interact to produce a magnified effect on the functioning of an ecosystem or other resource , even if each influence alone would have been relatively small or benign . Among the entire set of cumulative effects that have been described , Cumulative Watershed Effects ( CWEs ) are significant , adverse influences on water quality and biological resources that arise from the way watersheds function , and particularly from the ways that disturbances within a watershed can be transmitted and magnified within 4 channels and riparian habitats downstream of disturbed areas . Many of these CWEs occur at considerable distance downstream from the original site of landscape alteration , and are mixed with other effects that are not driven by land use . The land - use signal may thus be hard to define in quantitative terms . CWEs have been of great concern to resource managers and regulators in forested mountain regions , where the goals of timber harvest may conflict with other social goals for water quality or biodiversity . Various land - use regulations , including the California Environmental Quality Act Guidelines , require that CWEs be identified . Prominent among the regulated actions is the granting of permits for timber harvest on the basis of a Timber Harvest Plan ( THP ) , submitted by the landowner for each proposed logging operation . The THP must be prepared by a Registered Professional Forester ( RPF ) , and reviewed by a multiagency team with representatives from the Departments of Fish and Game , Forestry and Fire Protection , the Division of Mines and Geology , and the relevant regional water quality board . Public input is invited during a brief period thereafter . Based on all of this input the Director of Forestry makes a decision as to whether the THP conforms to the rules of the Board of Forestry . The Forest Practice Rules of the California Department of Forestry and Fire Protection ( CDF ) require that for such a THP to be granted the applicant must specify that the operation will not cause any significant adverse cumulative watershed effects . After that review , the THP may still be granted even though the effects are present . Regardless of whether any effects are recognized to be â?? cumulative â?쳌 , the THP must incorporate measures for mitigating damage , offsetting habitat loss , or regenerating forests . The applicant typically is not required to defend the assessment of CWEs , but is simply asked if he recognizes the possibility of their existence . The preparer is also not required to examine the entire watershed into which the THP site drains , but rather an area of the applicantâ??s choice is selected for comment . No study is required of those selected areas . Furthermore , the applicant may claim that any effect that he does recognize will simply be mitigated out of existence by application of a set of engineering or conservation techniques called Best Management Practices that have been reviewed for on - site effectiveness by professional foresters . This state of affairs has come under widespread criticism from a number of quarters . Resource managers and other interest groups concerned with water quality , esthetics , biodiversity , and other ecological values claim that the process allows easy denial of manifest cumulative watershed effects . Landowners and professionals who prepare THPs claim that they have no guidance on how to define CWEs , and that the reception of their plans varies according to which agency or interest group reviews them , causing uncertainty and delay in their operations . Regulators report that they are unable to make defensible judgments of THPs , even when they suspect that environmental damage will result , because they have no guidance or tools for consistent evaluation and no resources with which to make a thorough evaluation . Little or no credence is given to the experience and knowledge of local residents , who are told 5 that , as non - professionals , they are not qualified to render opinions on natural resources . Reviewers such as the Little Hoover Commission ( 1994 ) have repeatedly called for the streamlining of the THP process and the establishment of a true assessment of cumulative watershed effects , but no one has yet described in concrete terms how this might be done . The Commission concluded that the multi - agency review process is â?? complex , lengthy , and costly , resulting in inconsistency and inequity . â?쳌 Furthermore , in the cover letter to its report the Commission concluded that the process was fundamentally ineffective , and that â?? the environment is not being protected because of the flawed concept that â?¦ ecology can be addressed on a parcel - by - parcel basis . â?쳌 It was pointed out that the Stateâ??s focus is almost entirely on procedural steps rather than on outcomes , and that there is no mechanism for linking any demonstrated effectiveness of mitigation to future policy directives . The Stateâ??s emphasis on process rather than outcome is understandable because there is no generally agreed upon methodology for analyzing or predicting environmental consequences of proposed large - scale land transformations such as timber operations . In particular , no one has yet proposed a convincing method for analyzing or predicting CWEs . The authoritative review of cumulative effects of forest practices in Oregon ( Beschta et al . 1995 ) , for example , concluded only with a â?? conceptual framework â?쳌 for analyses , and the large - scale analysis of CWEs by a team of consultants to the US Forest Service ( Hawkins and Dobrowolski 1994 ) was essentially a region - wide statistical analysis of watershed conditions . It is thus not surprising that in all of the years since 1974 in which the Stateâ??s Timber Harvest Plan documents have required CWE assessments in the coastal redwood region of northern California , only rarely and very recently have any professional preparers of such plans acknowledged that a CWE is likely to occur . Members of this committee have been told explicitly by some RPFs that , in preparing a THP , they would never conclude that a CWE is likely because of the unnecessary regulatory burden that such an admission would bring . Denials of the likelihood of CWEs are repeated regularly by applicants and reviewers , despite the widespread recognition among environmental scientists that , in the aggregate , timber harvest in coastal California has resulted and continues to result in radical alterations of water quality , habitat conditions , and perhaps flood risk . A key component missing in previous proposals for addressing CWE is the concept of prediction . The fundamental regulatory purpose of requiring a CWE as part of a forest management decision ( THP approval ) is to state explicitly what is likely to happen as a consequence of the proposed actions . Not only must the individual THP under consideration be evaluated , in the context of past activities , but it must be linked to probable future activities and conditions . Without a forward - looking , predictive analysis , the inevitable consequence is that each THP will be seen in its own narrow context , and be described as just another small drop in the bucket , with the hard decision about limiting or modifying activities being 6 handed off progressively into a receding future . Thus , the State needs a method of assessing CWEs that is : 1 ) predictive ; 2 ) conceptually sound and supported by scientific methods ; 3 ) objective and easily understood ; 4 ) transparent and allowing the participation and contribution of all stakeholders ; and 5 ) designed to be continually improved as new insights , observations , analyses and methodologies become available . This report proposes an approach to building such a capacity . 7 Chapter 2 : Responsibilities of the Committee In view of the lack of an effective method for analyzing and predicting CWEs in timberlands , this University of California committee was asked to address the following questions : â?¢ Is there a scientific basis for the prediction of Cumulative Watershed Effects that is applicable to environmental conditions and land use in the coastal redwood region of northern California ? â?¢ If so , what is the basis and how should the analyses and predictions be made ? In Chapter 1 , we have reviewed the historical and administrative background of the need for recognizing and predicting CWEs . Chapter 2 defines the responsibilities of this committee . Chapter 3 describes the essential features of CWEs , some of the difficulties in defining them , and the interdisciplinary nature of the studies needed to define and predict them . In Chapter 4 , we describe and critique the current process for identifying CWEs in California timberlands . Chapter 5 presents our fundamental proposal for CWE analysis and prediction . It involves spatially registered mathematical mod eling of the risks of land - use effects on ecosystem characteristics ( habitat , populations , water quality ) in an environment that is subject to stochastic fluctuations , economic conditions , or other chosen scenarios . These risks must be predicted in the face of considerable uncertainty about both the future and the watershed characteristics themselves . We make suggestions for how the modeled risk assessments would be designed and conducted by a new unit of a State agency through a multi - stakeholder process the results of which are accessible to all interested parties . The results would then be used by the State in a transparent process to develop timber - harvest policies for entire watersheds based on the communally recognized risk to certain ecosystem values . Timber Harvest Plans could then emphasize what they can reasonably be expected to address : the local impacts , realistic analyses of the effectiveness of Best Management Practices , and the relationship of the planned harvest to the probable CWEs identified through the holistic watershed - scale modeling exercise . Chapter 6 outlines impediments that currently stymie the identification and prediction of CWEs in the processing of THPs in the North Coast redwood region of California . In Chapter 7 , we propose some ways of removing these impediments . 8 Finally , the Appendix is a description of some of the tools ( concepts , modeling , database development , fieldwork ) for accomplishing these tasks . We expect this toolbox to evolve rapidly , and so we present only examples . The methods we propose are not complete , and in fact should be expected to evolve along with improvements in data acquisition , system understanding , and stakeholder experience with the process . The report does not include an extensive literature review to establish the existence of cumulative watershed effects . Many authors and committees have compiled and evaluated the scientific literature concerning the effects of land use on water quality and ecological values , both on - site and downstream . The literature is vast , and it credibly documents what the Little Hoover Commission ( 1994 , p . iii ) called the â?? substantial and tangible â?쳌 impacts of timber operations . Watershed effects that have been shown to result from timber harvest include effects on : sediment , water temperature , in - channel volumes of organic debris , chemical contamination , increases in peak discharges during storm runoff , and reduction of spawning and rearing habitat for fish ( e.g . Beschta et al . 1995 ) . Some of the factors cited by the literature as possible CWE impacts are listed and described in Board Technical Rule Addendum # 2 ( CDF 2000 ) . The technical and administrative literature , however , consists of a largely unsorted accumulation of reports on intense , moderate , and smaller effects and their interactions . It does not provide the Board of Forestry or other policy makers with a coherent means of striking a balance between the resources referred to above . The literature documents what researchers have been able to find out so far , but not all of what policy makers need to know . All of the committee members are familiar with this literature , and see little value in repeating its review in the current report . The interested reader can pursue the details of this documentation in , for example , reports by NCASI ( 1999 ) , Beschta et al . ( 1995 ) , Reid ( 1993 , pp 91 - 149 ) , Bunte and MacDonald ( 1999 ) . 9 Chapter 3 : Nature of Cumulative Watershed Effects and the Problem of Identification â?? Society can not wait for scientists to understand the world scientifically . â?쳌 â?? J . Ortega y Gasset Context The nature of cumulative watershed effects has both scientific and institutional aspects . Scientific aspects relate to natural processes over differing spaces and times , how activities affect these processes , and to determining resultant impacts and risks . Institutional elements relate to how activities are evaluated , permitted , and conducted . Inevitably , the institutional aspects involve decisions about how much environmental and other risks are acceptable in a project . Before the institutional evaluation can be made , however , the risks of CWEs need to be identified in some transparent manner . Both the scientific and institutional aspects of cumulative impacts in California are complex . Scientific understanding is evolving and improving , but will always be imperfect . The institutional aspects , which also evolve , include a set of laws , administrative regulations , court decisions , and attitudes about various resources and the rightful way to use them . Prominent among the relevant laws is the California Environmental Quality Act ( CEQA ) and its implementing CEQA Guidelines . Under the â?? functional equivalent â?쳌 concept , CEQA has been applied to timber operations under the Zâ??Berg - Nejedly Forest Practice Act . This has created a complicated institutional context for assessment of cumulative effects on private and state forestlands in California . Thus , timber operations are governed by Forest Practice Rules , adopted by the State Board of Forestry and Fire Protection , which combine CEQA terminology , legal structure , and standards of review with general and site - specific operational and procedural rules that govern timber harvest . In all of this complexity , one rule sets the context for cumulative impact analysis . This rule ( 14 CCR 897.1 ( b ) ( 2 ) ( 2 ) ) states that â?? Individual THPs shall be considered in the context of the larger forest and planning watershed in which they are located , so that biological diversity and watershed integrity are maintained within larger planning units , and adverse cumulative impacts , including impacts on the quality and beneficial uses of water are reduced . â?쳌 Other rules do not mention cumulative effects directly , but are intended to avoid such effects by modifying operations or keeping them away from steep slopes , sensitive or erosion - prone areas , and streams . 10 Definition Cumulative impacts are defined in the Board of Forestry Forest Practice Rules ( CDF 2000 ) by reference to the CEQA Guidelines ( Section 14 CCR 15355 ) . Paraphrased , they are defined as two or more individual effects , which , when considered together , make a significant ( usually adverse ) change to some biological population , water quality , or other valued resource , or which compound or increase other environmental effects . The individual effects may be changes resulting from a single project or a number of separate projects . The cumulative impact of a single project is the change in the environment , which results from the incremental impact of that project added to those of â?? closely related , past , present , and reasonably foreseeable , probable , future projects . â?쳌 Elsewhere , the Forest Practice Rules ( 14 CCR 912.9 , 932.9 , 952.9 ) require answers to the following questions : 1 ) Does the assessment area of resources that may be affected â?¦ contain any past , present , or reasonably foreseeable future projects ? 2 ) Are there any continuing , significant , adverse impacts from past land - use activities that may add to the impacts of the proposed project ? 3 ) Will the proposed project , as presented , in combination with past , present , and reasonably probable future projects â?¦ have a reasonable potential to cause or add to significant cumulative impacts in any of the following resource areas ; watershed , soil productivity , biological â?¦ other ? â?쳌 The concern , therefore , is with â?? significant , adverse â?쳌 environmental impacts of a project . After a cumulative effect has been proven to exist , there is still the requirement to recognize whether it is significantly adverse to some resource . Cumulative impacts can result from individually minor but collectively significant projects taking place over a period of time . They may occur at a site through repetition of a change caused by successive operations , or through two or more results of an operation , or they may occur at a site remote from the original land transformation and with some time lag . The concern about cumulative effects arises because it is increasingly acknowledged that , when reviewed on one parcel of terrain at a time , land use may appear to have little impact on plant and animal resources . But a multitude of independently reviewed land transformations may have a combined effect , which stresses and eventually destroys a biological population in the long run . More complex aspects of cumulative effects are reviewed by Reid ( 1993 , pp . 31 - 59 ) , who also provides examples of how CWEs arise . Cumulative Watershed Effects ( CWEs ) constitute special kinds of cumulative effects that result from the hydrologic functioning of watersheds . Watersheds are ensembles of hillslopes that interact with 11 the stream channels at their bases and transmit the material and energy fluxes ( water , sediment , organic debris , chemicals , and heat ) resulting from those interactions downstream along hierarchical networks of channels with relatively numerous small channels draining into a few larger channels . When land use increases the magnitude of any of those fluxes , they accumulate along channel networks , are transmitted downstream , and concentrated in some reaches . Generally speaking , the larger the proportion of the land surface that is disturbed at any time , and the larger the proportion of the land that is sensitive to severe disturbance , the larger is the downstream impact . These land - surface and channel changes can : increase runoff , degrade water quality , and alter channel and riparian conditions to make them less favorable for a large number of species that are valued by society . The impacts are typically most severe along channels immediately downstream of land surface disturbances and at the junctions of tributaries , where the effects of disturbances on many upstream sites can interact . Some CWEs are listed in Technical Rule Addendum No . 2 of the Forest Practice Rules ( CDF , 2000 , p . 34ff ) . Both on - site and off - site ( downstream ) interactions of land - use effects are possible , but in addition to spatial interactions ( say between nearby watersheds at a tributary junction or between a site and a downstream reach of channel ) , the Forest Practice Rules mention the potential for interactions between project effects and features or processes triggered by some past or â?? reasonably foreseeable â?쳌 future project . Thus , one could imagine a case where the historical cycle of timber harvest emplaced large amounts of sediment along valley floors , and modern , project - related increases in sediment transporting flows ( even without large new additions of sediment ) might enhance the capacity of streams for conveying that sediment downstream and depositing it in fish habitat or reaches vulnerable to flooding . In other watersheds , past land use may have elevated sediment loads and simplified channel habitat so that even a minor increase in runoff , debris - flow occurrence , or sediment load may be undesirable . Both the spatial and temporal scales of cumulative effects can be large ( many kilometers and decades ) , although it will usually be easier to recognize an interaction over decades in the past than to predict its trajectory accurately over a similar time period in the future . Technical Rule Addendum No . 2 specifies the factors to be considered and the situations where such impacts are likely to occur . However , the document offers no real methodology guiding the RPF in how to â?? evaluate watershed impacts â?쳌 or their â?? significance . â?쳌 Although earlier versions of the document state , â?? No actual measurements are intended â?쳌 in evaluating impacts , the 2000 version allows that â?? Actual measurements may be required if needed to evaluate significant environmental effects . â?쳌 The Forest Practices Rules allow account to be taken of the mitigation of project effects by on - site conservation methods , called Best Management Practices ( BMPs ) . As implemented by CDF , the Rules focus mitigations in the plan area ( including connected roads and landings ) . Mitigations may be directly related to the impact of current timber operations , or may treat problems from other sources such as past logging . CDF almost never considers mitigations outside of the plan area . 12 However , widespread experience in most types of terrain and land uses ( forestry , agriculture , urbanization , mining , etc . ) has proven that mitigation by on - site BMPs is usually imperfect , and much of the induced perturbation ( say of runoff or sediment ) â?? escapes â?쳌 or â?? leaks â?쳌 from the impoundment device or from the surface protection , and accumulates downstream , though at a reduced level . It is because of the limited effectiveness of on - site mitigation that CWEs have been identified widely by environmental scientists . Watershed impacts that have been shown to result from timber harvest ( and other land â?? cover manipulations ) include effects on : sediment , water temperature , in - channel volumes of organic debris , chemical contamination , the amount and physical nature of aquatic habitat , and increases in peak discharges during storm runoff . However , determination of the significance of these effects for some aspect of water quality or biodiversity requires taking into account biological populations , ecological functions , and the role of the above - mentioned physical and chemical characteristics in determining the quality of habitat . Thus , our report is much broader than the treatment of â?? Cumulative Watershed Effects â?쳌 in the CDF ( 1998b ) document , which states ( p 2 , parag . 1 ) that â?? CWEs refer to the combined effect of multiple activities involving the processes of water and sediment transport â?쳌 and that â?? CWEs are a sediment routing problem â?쳌 . However , we are not concerned with the broader range of cumulative effects that are not related to watershed functioning , outlined in the California Forest Practice Rules , which include such effects as traffic , visual impacts , and soil productivity . Although CWEs are currently defined only in terms of adverse impact on some resource , there is no fundamental reason for this . It is also possible to identify and predict positive CWEs resulting from rehabilitation projects . Such accounting would provide opportunities for planning and promoting reconstruction of ecosystems rather than simply identifying potential adverse impacts for purposes of regulation . Thus , if one sees a CWE prediction as a tool not only for constraining timber harvest and other watershed disruptions , but also as a method for evaluating any kind of watershed management proposal , then agencies would need a CWE prediction of the positive values of watershed restoration as well . If , for example , it is proposed to de - activate and re - engineer roads , wise decision - making would be served if predictions could be made of the extent to which that strategy , in combination with the other features and activities in the watershed would achieve the intent of preserving or restoring waterways . Of course the two purposes of CWE predictions ( reducing the risk of damage and designing rehabilitation ) might be required in the same watershed that is undergoing both active timber harvest and rehabilitation such as de - activation of roads , planting and development of riparian zones , loading of large woody debris into channels , etc . Such predictions are likely to be needed in watersheds with a complex mixture of land use , where it is not possible to â?? get ahead of â?쳌 some foreseeable wave of change such as a harvest cycle in a mature forest . 13 At one level , therefore , there appears to be a considerable number of detailed measures with which to define the absence or presence of Cumulative Watershed Effects . Given the widespread nature of the watershed effects of timber harvest listed above in many disturbed landscapes , one would expect frequent identification of Cumulative Watershed Effects , â?? even if the ecological significance of some effects could be debated . In practice , however , virtually no one filing a THP admits to the presence of any CWE , and CDF and resource agencies in other states have been unable to promulgate any defensible methodology for defining the presence and source of any CWE , even when they have consulted the scientific community . Thus , there is little effective technical basis for enforcement of available regulations designed to protect aquatic resources . There is an escape from every rule . Difficulties of Identifying CWEs The recognition of CWEs is not always an easy matter , especially because there is rarely any monitoring or census of conditions before , during , or after a timber harvest project or cycle . Many of the effects referred to are diffuse in space ( e.g . shallowing of pools several kilometers downstream of a non - contiguous , multi - owner , asynchronous concentration of harvest activity ) , and irregular in time ( e.g . the triggering of landslides in a rainstorm several years after tree removal , or enhanced turbidity levels during certain flows , but not in others ) . It is often difficult to prove that such an effect is â?? significant â?쳌 , even if it is acknowledged to have occurred . Aquatic biologists have so far been unable to compute , or even define consistently , the biological consequences of habitat changes that are below the level of a complete eradication of function ( complete filling of rearing pools , smothering of spawning gravels with fine sediment , etc . ) . This is partly because some habitat - population relationships are hypothesized rather than established , and partly because the effects of any transient perturbation of habitat conditions over a logging cycle interacts with life - history processes and with external factors such as ocean rearing conditions and fishing pressure to obscure links between population dynamics and habitat condition . The difficulty is enhanced because , almost by definition , particular changes of process intensity or landscape morphology occur as a result of the interaction between the timber operation and large episodic rainstorms , wetter - than - average seasons , or other disturbances . Some people obfuscate this issue and thus misdirect the discussion of CWEs by asking such questions as whether timber harvest or large rainstorms cause a habitat change , or a flood , or higher levels of turbidity . If the analysis of the resulting , unwelcome changes is reduced to defining which of these agents is â?? to blame â?쳌 , it misses the point that a land - cover change and associated infrastructure can often increase the risk of a landscapeâ??s unwelcome response to rainstorms . 14 Altering the condition of a land surface is ( in the game - theoretic sense ) a game played in a stochastic environment . A hillslope clear - felled in a run of dry years may subsequently escape any intense rainstorm , allowing the land to recover a resistant tree cover before its stability is again tested by a large storm . A road system may be installed without triggering frequent landsliding , debris flow , or debris torrent during the same relatively dry period . A nearby similar project involving tree removal and road engineering under identical landscape conditions may be initiated during a wet period and suffer much greater impact from landsliding with dramatic downstream effects . These triggering rainstorms remain essentially unpredictable , but we can estimate the risk of such erosion events and their downstream consequences . We can also estimate the increase in risk of landsliding and habitat damage in the same storm as a result of timber harvest . Other differences in the response of landscape to timber harvest result from geographical differences in topography and geotechnical properties of the landscape materials . Again , there is usually no mystery about such differences in the eye of the landscape scientist , unless there is undisciplined throwing around of undigested statistics from the literature , as often happens in environmental disputes . Still other uncertainties and confusion arise through the lack of precise definition of which process or part of a watershed system is causing the recognized or anticipated perturbation . For example , tree removal from a watershed can cause increases in the amount of water available for flood generation . At the same time harvest roads and skid trails can intersect subsurface flow high on hillslopes and convey it quickly into streams . The former change is a transient effect , subject to recovery and to staggering in time across the landscape . The window of vulnerability for such a disturbance to cause flooding is much smaller than in the case of roads and skid trails , which are quasi - permanent features , spreading cumulatively across the landscape and altering its runoff conveyance capacity , typically increasing the drainage density by 20 to 67 % ( Montgomery 1994 ) . Even when decommissioned as traffic routes , these roads and skid trails intercept drainage , and intensify the evacuation of water from hillslopes . Hillslope runoff theory indicates the sign of this effect , that its magnitude should vary regionally and between rainstorms ; and that it should interact with the effects of tree removal on runoff , being largest in absolute terms when tree cover is reduced . Such differences and interactions , although expectable from knowledge of runoff processes , make the quantitative recognition and prediction of this particular CWE difficult in a short field study . Even with sophisticated statistical studies of multi - decade flow records , controlled for differences in storm size , the effect , though recognizable can be quantified only approximately ( Jones and Grant 1996 ) . Yet cautious interpretation of the results in the light of current understanding of runoff processes suggests that the effect of timber harvest on flood runoff may be considerable in some regions . But it is unlikely that the issue will ever be resolved and quantified empirically in the manner of laboratory experiments or agronomic fertility trials ( UC Committee on Cumulative Watershed Effects 1999 ) . The 15 general nature , sign , and approximate magnitude of the effect may be established , and the risk of its occurrence estimated quantitatively , but the acceptability of the risk will have to be interpreted in the context of prevailing laws , policies , and attitudes to the threatened resource . This is the nature of the judgment call that policy makers need to make about the risk of cumulative watershed effects . Despite the difficulties of identifying CWEs , the field evidence of environmental change in timberlands has led successive groups of scientists ( e.g . Beschta et al . 1995 ; Bunte and MacDonald 1999 ) to document the widespread occurrence of cumulative watershed effects . Although there is often no steady - state , extant or foreseeable condition against which one can measure or predict in a deterministic , exact way the effects of land management , some changes due to land use are so radical and widespread that they are widely acknowledged , even by land managers as well as resource management scientists . In some cases , there are easily recognized metrics for land - use impact ( e.g . the extent of old - growth forest and , by implication , its attendant biota ) . In other cases ( such as turbidity or other measures of streamwater quality ) the measures are obvious but the available data are sparse . And in yet other cases it has proven less easy to develop a useful metric ( e.g . the grain size and extent of spawning gravels , large woody debris , and other aspects of channel - habitat complexity ) . Interdisciplinary Nature of the CWE Problem The origin and nature of CWEs require knowledge and skills that are normally the purview of several different branches of science . CDF has thus involved multiple agencies and scientific disciplines in CWE analysis . The complexity of CWEs has slowed the development both of consensus about the â?? significance â?쳌 of adverse effects and of techniques for their recognition and prediction . The significance of some adverse change in watershed condition is often expressed in the aquatic biology of stream channels or riparian zones . Thus , it is difficult for a physical scientist working alone to establish whether an anticipated increase in streamwater turbidity , for example , is likely to have a significant adverse impact on some ecosystem process . Biologists , on the other hand , may identify undesirable physical changes in habitat , but have not yet conducted the studies to connect these changes with biological effects , except in extreme cases . Furthermore , they have been reluctant to express anything more precise than general concern about the direction and cumulative nature of ecosystem changes that have occurred simultaneously with a region - wide decline in populations of many birds , fishes , and terrestrial fauna . Even to understand the original perturbation triggering CWEs involves knowledge from different branches of science and technology . For example , the nature and risk of landsliding are complex biophysical issues . Landslides commonly involve the mechanical failure of unconsolidated earth materials ( soil , fractured and weathered rock , or artificially emplaced fill material ) reinforced to various degrees by 16 plant roots ( Gray and Leiser 1982 ) . Thus , knowledge of force balances and material properties from geomorphology and geotechnical engineering needs to be combined with a quantitative understanding of the nature of plant roots as these vary from one region or substrate to another and through plant succession at a single site . Landslides occur when these materials become weakened as their water content is increased by rainstorms , snow melt , or engineered drainage modifications . Prediction of the increase in soil - water content and pore pressure requires an understanding of hydrologic processes to quantify the role of water input rate , canopy interception , soil hydraulics , hillslope length , gradient , and shape . Insights from silviculturists are crucial because forest covers , which influence root strength , canopy interception of rainfall , and evapotranspiration , varies spatially with climate and substrate conditions and temporally through fire and managed succession . The requirement for extensive road networks and their management requires knowledge of forest engineering . Thus , analysis of the causes and prevention of landslides in forested mountains requires expertise not normally obtained within a single discipline or agency . The complex requirements of CWE analysis explains the interdisciplinary constitution of this committee , and the range of knowledge that must be organized and made available to RPFs who are responsible for making final determinations of the likelihood and nature of CWEs . Improvements in the analysis and prediction of CWEs is going to require the hiring of people with interdisciplinary training in environmental science at a higher level than is typical among the current cadre of professionals involved in THPs . We know of no licensing procedure or professional examination that currently assures that appropriately trained individuals are analyzing CWEs . 17 Chapter 4 : TechnicalAspects of the Current Process forAssessing CWEs in Timber Harvest Plans and Sustained Yield Plans â?? In theory there is no difference between theory and practice . In practice there is . â?쳌 â?? Yogi Berra The State requires that all Timber Harvest Plans ( THPs ) include an analysis of the potential for Cumulative Watershed Effects , and that these Plans be written and reviewed by Registered Professional Foresters ( RPFs ) . The work involves mainly the application of the Forest Practice Rules , which are numerous , but which concentrate on physical conditions of the assessment area , and are not easy to relate to the protection of biological and water resources downstream . The administrative process of reviewing THPs by CDF , other interested agencies , and the public has been described by the Little Hoover Commission ( 1994 , pp . 24 - 45 ) . After it approves a Plan , CDF takes responsibility for defending it on behalf of the applicant against public criticism , often in court . Cumulative impacts are currently addressed only on a case - by - case basis in a Timber Harvesting Plan , or by longer - range Sustained Yield Plans ( SYP ) , or for small owners , in Non - industrial Timber Management Plans ( NTMP ) . Seven categories of cumulative impacts are defined ( Secs . 912.9 , 932.9 , 952.9 ) : Watershed , Soil Productivity , Biological , Recreation , Visual , Traffic , and Other . Each category must be checked off in one of three boxes : â?? Yes , there will remain impacts even after mitigation â?쳌 ; â?? No , cumulative impacts will not remain even after mitigation â?쳌 ; or â?? No , no reasonable , potential , cumulative impacts from this project are likely to join with the impacts of any other project ( within the same ownership ) . â?쳌 To assist the professional forester in assessing cumulative effects , CDF ( 1994 ) provides a set of guidelines , which follow the arrangement and content of the Forest Practice Rules on cumulative impacts . The guidelines on CWEs lead the applicant through the following ten steps . Editorial comments by this committee follow each step . 1 ) Establish on - site and downstream beneficial uses of water â?? that you are aware of . â?쳌 Comment : This step does not specify that channels or riparian zones need to be considered , and does not consider hazardous aspects of water such as flooding or the triggering of landslides . How much effort is expected of the applicant in becoming â?? aware â?쳌 ? ) 2 ) Describe the watershed assessment area , including the reasons for the selected boundaries . The boundaries are those of â?? planning watersheds â?? defined by CalWater . 18 Comment : Examples we have seen have not included the entire watershed into which a site drains , but include some seemingly arbitrary adjacent drainage areas . 3 ) Classify the â?? condition â?쳌 of stream - channel segments that lie within the project boundary and have a drainage area of at least 300 acres . Rating classes are â?? none â?? , â?? slight â?? , â?? moderate â?? , and â?? severe â?? . Features to be classified include such examples as : â?? gravel embeddedness â?? , â?? pool filling â?? , â?? scouring â?? , â?? canopy reduction â?? , â?? recent flooding â?? , and an optional overall â?? condition rating â?? . Comment : Little guidance is given to the forester for making these assessments . Arriving at a single defensible classification based on all of these variables would require a certain sophistication in the fields of fluvial geomorphology and habitat analysis that we have not encountered in our reviews and interviews . 4 ) Are you â?? aware â?쳌 of any current stream channel conditions outside of the project boundary but within the assessment area that are contributing to a reduction in the beneficial uses of water ? â?쳌 Comment : What is the required level of effort in becoming â?? aware â?? ? 5 ) Are you â?? aware â?쳌 of any current stream channel conditions , outside of the project area but within the assessment area , or any that occur outside of the assessment area , and which are contributing to a reduction in the beneficial uses of water ? â?쳌 Comment : See 4 above . 6 ) Have past projects resulted in any of a list of impacts dealing with channel condition , water temperature , and chemical loading of stream water ? Comment : The changes in channel morphology and water quality that are suggested would require either some kind of a historical record ( photographic or instrumental ) or considerable skill in the reconstruction of landscape history from field evidence . 7 ) What is the potential ( â?? high â?? , â?? moderate â?? , â?? low â?? ) for the project â?? as mitigated â?쳌 to produce certain listed individual effects on channels at or near the project site ( such as sediment input , increased water temperature , chemical inputs , increased peak flows , alterations of organic debris loads , future supplies of organic debris ) . Comment : No methodology is suggested for arriving at such a conclusion . 19 8 ) Given the foregoing , are the identified future projects likely to result in the same set of effects ? Comment : No indication of how assiduously and specifically the â?? future projects â?쳌 must be identified , but in the THPs that we reviewed there was no treatment of future harvesting and road construction foreseeable in the watershed . 9 ) What is the potential for developing adverse cumulative watershed impacts in the assessment area ( â?? high â?? , â?? moderate â?? , â?? low â?? ) ? Comment : No methodology is suggested for arriving at such a conclusion . 10 ) Will the project , â?? after mitigation â?쳌 , have a reasonable potential to cause or add to significant cumulative impacts to watershed resources ? ( â?? yes â?? or â?? no â?? ) . Will there be positive effects on watershed condition and existing CWEs ? Comment : No methodology is suggested for arriving at such a conclusion . The attempt to arrive at a single - word answer , as if a single threshold of concern could be defined that would make the answer for a regulating office , is not realistic . Elsewhere , consistent with a CEQA - like framework , the Forest Practice Rules require a determination of whether there are â?? any continuing , significant , adverse impacts from past land - use activities that may add to the impacts of the proposed project . â?쳌 As mentioned in Chapter 3 , the concern is with â?? significant , adverse â?쳌 environmental impacts of a project . After a cumulative effect on the physical condition of the assessment area has been proven to exist , there is still the requirement to recognize whether that impact is significantly adverse to some resource , such as water quality , biodiversity , or a particular valued species . Yet the only clarification provided in the Forest Practice Rules for defining a significant , adverse impact is : â?? a substantial , or potentially substantial , adverse change in any of the physical conditions within an area affected by the project . â?쳌 The Rules also state â?? a social or economic change related to a physical change may be considered in determining whether the physical change is significant . â?쳌 It is not clear how social or economic factors alter the biological significance of a physical change . They may alter the decision about what weight to give to the adverse impact in view of other social needs , but they do not alter the degree of the adverse impact itself . The Appendix to Technical Rule Addendum # 2 ( p . 34 , 2000 Rules ) provides further definitions and examples of CWEs , and indicates that â?? actual measurements may be required if needed to evaluate significant environmental effects . â?쳌 However , it offers no real methodology guiding the RPF in how to â?? evaluate watershed impacts â?쳌 or their â?? significance . â?쳌 In almost all cases , no quantitative biological information is required in determining whether the physical change is significant . Thus , although it may be 20 true that â?? The Timber Harvest Plan process has not proven effective in achieving a sound balance between economic and environmental concerns â?쳌 ( Little Hoover Commission , 1994 , p . v ) , we would add that the guidelines provided to the RPF guarantee that the analysis is inadequate , and this is borne out by the THPs reviewed by us , which have not adequately represented either economic or environmental concerns . A process with such limited guidance is vulnerable to arbitrary interpretations , political forces , enthusiasm for timber harvest or for the implications of species listings , traditional attitudes that have developed within agencies , or traditional competition between agencies for influence . There is obviously a competition among agencies for which of them gets to say what risk to a species is acceptable . Thus , in interviewing technical personnel involved in initiating and reviewing CWE assessments , we found that the outcome , and especially the decision that some impact is â?? less - than - significant â?? depends mainly on the attitude or predisposition of the person doing the â?? analysis â?? . With such limited guidance , and with the primary goal of the 1973 Forest Practice Act being to allow timber harvest with â?? appropriate regulation â?? , it is hardly surprising that neither applicants nor CDF regulators recognize that any significantly adverse , cumulative effects are likely to result from timber harvest . This is particularly true when all participants , at least publicly , adhere to the belief that , should any adverse impact arise , it can be mitigated out of existence by application of a Best Management Practice . At present , therefore , virtually all rules are written with escape clauses . We confirmed many of the observations made by CDF ( 1999 ) in its review of Cumulative Impacts Analysis . Information provided in individual THPs that we examined was often incomplete or too subjective to assess current resource conditions , lingering cumulative effects , or the potential for additional impacts . The boundaries of the assessment areas are arbitrary , and may be limited to that landownerâ??s property . The burden of proof falls upon the public agencies to establish cumulative effects , and upon plan approval CDF advocates on behalf of the approved plan in disputes with other agencies and private stakeholders . Our reviews of THPs and discussions with CDF officers responsible for reviewing applications indicate that the training of Registered Professional Foresters is not adequate for the legally mandated multidisciplinary assessments of CWEs . The Committee reviewed two summaries of recent THP applications in the redwood region , which suggest that potential environmental effects of proposed harvests are not being recognized by RPFs ( Table 1 ) . The â?? Pape â?쳌 survey was a random survey of answers to questions on all THPs in the North Coast region submitted in 1998 . The â?? MW â?쳌 or â?? Mass Wasting â?쳌 survey was a random sample of 1998 THPs in Mendocino , Santa Cruz , and Del Norte counties that had been earmarked for additional review by the California Department of Mines and Geology ( CDMG ) . Both surveys asked the question : â?? Will the proposed project cause or add to significant 21 cumulative watershed effects ? â?쳌 In Table 1 . A , the RPFs filling out the applications did recognize that cumulative effects from past activities are present in many areas , and it is not surprising that cumulative effects were identified in a higher proportion of the THPs which the CDMG had earmarked for further review ( the â?? MW â?쳌 survey ) . There was an absolute degree of confidence by plan applicants ( RPFs ) that their plans would not add to existing cumulative effects . In both surveys , not a single plan filed , of the 89 surveyed , identified a single cumulative effect that would add to the existing cumulative effects ( Table 1 . B ) . Table 1 . Two Surveys of Timber Harvesting Plans ( THPs ) A . Question 2 . Are there any continuing , significant adverse impacts from past land - use activities that may add to the impacts of the proposed project ? Survey Number Answer YES Number Answer NO Percent YES Pape Survey 22 28 44 Mass Wasting Survey 23 16 59 B . Question 3 . Will the proposed project , as presented , in combination with past , present , or reasonably foreseeable , probable future projects cause or add to the significant cumulative watershed effects in any of the following subjects ? Cumulative Pape Survey Mass Wasting Survey Category Yes No Significant No Effect Yes No Significant No Effect Impacts After Mitigation Impacts After Mitigation Watershed 0 33 17 0 27 12 Soil Productivity 0 23 27 0 20 19 Biological 0 29 21 0 23 16 Recreational 0 2 48 0 1 38 Visual 0 6 44 0 3 36 Traffic 0 7 43 0 3 36 2 Other 0 3 10 0 2 2 Notes : 1 . Plans are all 1998 THPs and each was submitted by a Registered Professional Forester . Questions are derived from the cumulative effects analysis contained as part of each THP . 2 . â?? Other â?? category has many non - respondents . 22 The survey suggests that the RPFs acknowledge the existence of past cumulative effects but believe future cumulative effects from their plans are nonexistent . This may be due some of the following possibilities : â?¢ CWEs will , in fact , be mitigated on all of these plans by measures included in the THP ( see below for discussion disputing this assumption ) ; â?¢ Additional CWEs may be created , but will not exist as they are defined in the Forest Practice Rules ( only within that ownership , based on material in the public record , and / or based on â?? practicality and reasonableness â?쳌 ) ; â?¢ RPFs are not able to distinguish the additional impact of one plan , so they conclude that any effects of the current THP they are preparing are non - significant ; â?¢ RPFs are aware that cumulative effects will occur , and mitigate them to the extent they can , but will not check the box admitting cumulative effects because they believe the THP will not be approved if the YES box is checked . Our committee did not have sufficient information to conclude which of the above circumstances applied to these THPs , or which was most dominant as a reason for non - identification of cumulative effects . The Committee also reviewed several ca . 1998 THPs in the Redwood Creek watershed , which is a sediment - impaired watershed listed under Section 303 ( d ) of the Federal Clean Water Act in 1992 . None of these plans indicated that there might be cumulative effects resulting from the proposed operations . Obvious major fault zones and unstable areas were not referenced in the THPs ; additional harvest plans in the foreseeable future were not referenced , yet were later submitted within less than 9 months on the same ownership ; fish ranges were improperly stated in the THP ; recent landslides were unreported ; recent effects of older land uses ( such as recent failures of roads constructed in previous decades ) were ignored ; and coarse woody debris deficiencies were largely not addressed . Neither CDF nor CDMG reviewers had challenged these deficiencies . From evidence we have reviewed it appears that as of 1998 CWEs were not being appropriately addressed in these THPs . There appears at a minimum to be a lack of recognition of the existence of cumulative effects , and this may , in part , be a reason why CWEs have not been successfully addressed to date . Some of the CDF and CDMG officers , who currently sign off on the judgment that no CWE is likely to result from a THP , reported to us that they do so because they have no basis for identifying CWEs since they have no tools for taking a view at a scale greater than a harvest site or a small watershed . The CDF ( 1994 ) guidelines certainly confirm this claim , as virtually all of them are concerned 23 with small watersheds , and the resources for a single THP assessment are limited . The process outlined above contains no method for recognizing damage across entire ecosystems or watersheds . For example , with this limitation , a predictable view would be that even if there is an increase in sediment supply to the channel in a third - order watershed , the channel gradient and the high flows expected in that channel are sufficient to transport the sediment â?? away â?? with little or no impact on channel morphology and habitat . In such a view , there is no possibility ( and the assessors have no tools ) for judging whether any of the increased sediment being washed downstream will travel intermittently along stream channels and spend a considerable amount of time filling fish - rearing pools , or impacting the fine - sediment content of spawning gravels , or increasing turbidity during its transport far downstream , etc . Another problem is that no standard of proof is required for the assessor to make a determination of whether the effect can be mitigated . For example , CDF field officers reported to us in a meeting that â?? We have been told that timber harvest does not cause flooding â?쳌 . They had also been told that â?? a six - inch - thick cover of gravel on a forest road mitigates sediment generation so that the road will no longer be a significant source of sediment â?쳌 , despite published evidence that similar roads elsewhere lose considerable amounts of sediment . These â?? conclusions â?쳌 are accepted by applicants , reviewers , and their technical advisors with no regard for standards of proof , relevance , or any need to investigate field evidence . A strong influence in denying the potential for CWEs in individual harvest plans seems to be that an applicant is allowed to state , usually without any burden of quantitative proof , that a deleterious effect of a proposed operation can be â?? mitigated â?쳌 ( and thus defined not to have an off - site , cumulative effect ) if some Best Management Practice ( BMP ) is prescribed . Apart from the fact that the execution of the BMP is almost never checked in California forestlands , it is the collective judgment of this committee that BMPs do NOT remove off - site impacts . They may reduce them , when the BMPs function well , but they do not remove them , especially when they are tested by severe storms . It is the collective failure of BMPs to mitigate off - site impacts that results in residual , significant cumulative effects . The CWE may be less than in earlier logging cycles , and the timber industry and all citizens can take some comfort from that fact . But CWEs are real and important in many watersheds . If a significant , adverse cumulative impact is identified in a THP , the Forest Practice Rules ( 14 CCR 897 - 898.1 ) require further discussion of possible mitigation measures to reduce impacts . The Rules ( 14 CCR 898 ) say that no THP shall be approved which fails to adopt feasible mitigation measures or alternatives as set out in the rules . Ultimately , if a plan has incorporated all feasible mitigation measures and significant adverse environmental impacts still remain , the Director may approve the plan only if the benefits outweigh unavoidable significant adverse impacts . This is done following a procedure set forth by the Board ( 14 CCR 898.1 ( g ) and ( h ) ) . The complexity , contentiousness , and delay involved in this process , and the likelihood of a successful appeal by the applicant to the Board of Forestry on the 24 grounds of economic impact , pressures both CDF technical personnel and the applicant to negotiate until the expected impacts can be declared â?? mitigated â?쳌 by some BMP , after which the permit is granted . Some large landowners are allowed to submit Sustained Yield Plans ( SYP ) for the purpose of assessing larger - scale watershed effects , both physical and biological . The intent of a SYP is a â?? maximum sustained yield of high quality timber products â?쳌 while giving â?? consideration to environmental and economic values â?쳌 ( Article 6.75 , 1091.1 ( b ) ( page 181 of 1998 Forest Practice Rules ) ) . Again , the Rules set the tone of the analysis in that they do not acknowledge from the beginning that it may not be possible to maximize timber and also provide adequate protection to other resources . The SYP process is an optional planning process by the landowner , and is intended to address the same issues that a Timber Harvest Plan ( THP ) would address , but in a more substantive and successful manner . While not substituting for a THP , the SYP , if approved , clears all THPs submitted under the SYP for watershed or fish and wildlife issues for a period of 10 years . SYPs are specifically directed to include a cumulative effects analysis . The intent of the SYP process is to expand the spatial and temporal framework for THP analysis , and is a step in the right direction . However , it does not , in its current form , solve the cumulative effects problem . Within the section on authority and intent , it states that the SYP shall be guided by â?? principles of practicality and reasonableness â?쳌 , which are left undefined . A landownerâ??s definition of this may be much broader than that of a resource specialist . This same section recognizes that landowners , and particularly smaller landowners , â?? may not have nor can reasonably be expected to obtain or project information which otherwise might be helpful . â?쳌 For the redwood region , this language effectively provides an exemption from rigorous cumulative effects analysis across a broad expanse of the land base . The issue of integrating the applicantâ??s ownership into all of the sources contributing to cumulative effects is optional ( section 1091.3 ) . There are , in fact , real constraints involved in including other ownerships , such as lack of data access for the other parcels , insufficient knowledge of projected actions on these other parcels , and legal issues associated with sharing such knowledge ( anti - trust legislation in particular ) . Nevertheless , the current SYP process will generally fall short of the mark in assessing cumulative effects . We conclude that it is not surprising that the current methods of assessing and predicting CWEs are ineffective . Attempts to define a threshold of â?? significant â?쳌 , adverse effects â?? though attractive for any agency or individual regulator , who , understandably , doesnâ??t want to make difficult decisions alone â?? are unworkable and too narrow . Secondly , the resources available for a THP are not adequate for the task of conducting a realistic , watershed - scale analysis of long - term , biologically relevant effects . RPFs do not have the training necessary for analyzing CWEs across a spectrum of physical , biological , and biogeochemical disciplines . An individual applicant , and a regulator processing a single application , do not have the time and other resources necessary for a truly cumulative , watershed - scale analysis . This 25 limitation is particularly severe for â?? small â?? landowners ( those who own less than 2500 acres of forest land ) , who own approximately 50 % of private forestlands in California ( 25 % of total forest land ) . The resulting â?? postage - stamp â?쳌 , or â?? parcel - by - parcel â?쳌 , approach , in which only the immediate project area of a single , small timber harvest is ever reviewed â?? as all other reviewers have said â?? does not capture the cumulative influence of multiple harvests over a long period of time in a large , complex watershed . The Little Hoover Commission ( 1994 , p . 55 ) , quoting the State Water Resources Control Board , arrived at the same conclusion , referring to the results as â?? Inadequate , â?? boilerplate â?? analyses and mitigation measures . â?쳌 Many THP applications are returned by CDF for reasons of incompleteness , but not technical accuracy . Our review of a sample of them suggests that CDFâ??s standards are not high , even though the timber industry complains about the resulting delays . The target time period for processing THPs is 45 days . This might be a reasonable time for reviewing the physical consequences of a harvest plan for a small area for which well - defined guidelines are available , but is totally inadequate for evaluating the impact of timber harvest on complex watershed - scale ecosystems in the absence of biologically relevant guidelines . Requiring CWE analysis to be conducted in the THP evaluation is intractable . Another reason for confusion arising in establishing the nature , magnitude and significance of CWEs is that the scientific literature is often vague or does not encompass the particular problem under discussion . In other cases , there is useful literature , but it is not known to agency technical staff , or to the consultants hired to prepare THPs . Where the scientific literature is vague or non - existent , the Board of Forestry relies on professional judgment to fashion solutions . California rulemaking law utilizes a public hearing process and an appointed Board of Forestry to judge the value of science in forestry , and to either implicitly or explicitly set the weighting of risk . Hence the Board rules define limits to silvicultural systems that may include size limits , timing , basal area requirements , leave standards , protection of nest sites , a feathered set of watercourse protection zones that include a later seral component , etc . If there are specific scientific limits ( such as a lethal stream temperature for fish or a threshold fine - sediment concentration for spawning beds ) RPFs are expected to know this and to apply it in the context of the rules and in protecting beneficial uses of water . If the RPF doesnâ??t know or apply existing knowledge , reviewing agencies have the duty to require additional mitigation . Such judgments are tenable if the issue is as straightforward as a threshold value of an environmental variable , but this is almost never the case in an ecosystem at landscape scale ( What , for example , is the stream temperature in a network of channels with pools , a range of elevation , point sources of ground water inflow , and variations of shade ? ) . So , although the idea of thresholds is attractive to regulators , thresholds are almost never relevant to the diffuse stress placed upon the reproductive success of groups of organisms in a complex environment when it is drastically altered . This is one 26 reason why so much contentiousness arises when agencies responsible for biodiversity and water quality express their right of review but rely on beliefs in thresholds . For the foreseeable future there will always be uncertainties about how even established principles from the landscape sciences ( ecology , hydrology , biogeochemistry , geomorphology ) apply to particular , local cases of landscape change . The same is true for the application of economic principles to the financial affairs of particular countries or firms , but individuals and governments find these principles worthy guides for managing our most prized possession . CWE analysis , like all other human endeavors , will have to be conducted rationally in the face of these uncertainties . Some people will be skillful at this , and will remain well informed as the technology evolves ; others will remain confused and be unable to proceed because the scientific literature does not contain the answer to their specific question . A result of the inability of agencies to establish and agree on the presence and general magnitude of CWEs is that rarely , if ever , in northern California is a case made for limiting timber harvest based on cumulative watershed effects on even the most erosion - prone land . For example , faced with an inability to establish the risk of a significant adverse impact , regulators accept denials of the potential for in - unit landslides , and prescribe Best Management Practices for roads , and then grant the harvest permit . Monitoring has focused on compliance and effectiveness of rules but not on trends . Furthermore , monitoring has concentrated on hillslope activities rather than channel effects . Since there is no long - term , systematic monitoring of the results of timber harvest on landsliding or aquatic habitat , there is no accounting of the consequences of timber harvest when a large storm arrives , and its results are classified by implication as an â?? act of God . â?쳌 Other attempts at addressing CWEs have also been inadequate . The US Forest Service uses an index of land - use intensity , known as the Equivalent Roaded Area , which is widely viewed as inadequate , and concentrates only on the potential for increases in high streamflows and sediment production without illuminating their significance for biodiversity or water quality . Other agencies have accepted unverified narrative descriptions of potential impacts of timber harvests . The most recent advance in impact assessment is Watershed Analysis , an evolving methodology exemplified by requirements of the Washington Forest Practices Board ( 1995 ) . In this approach , the analysis is divided into discipline - based modules , and some training and expertise is required for the assessor to be permitted to perform the analysis . The modules include : mass wasting , stream channels , hydrology , surface erosion , and stream habitat . Each analysis is performed and conclusions are drawn separately about causal mechanisms for each module . A synthesis report then summarizes the findings . However , no predictive modeling is included , so cumulative watershed effects of future potential land use are not assessed . The scientists performing the analyses do not propose prescriptions to remedy or avoid problems . Instead , land managers remain responsible for this , and according to Collins and Pess ( 1996 ) , performance of a Watershed Analysis in Washington led to very little beneficial change in land - use practices . Furthermore , 27 it has been recognized that the analysis did not provide adequate insight about the decline of critical species , and as a consequence of the listing of several fish , the analysis has recently been withdrawn from widespread use in Washington State . An increasing number of agencies are promoting the construction of sediment budgets ( Reid and Dunne 1996 ) as a means of addressing CWEs , but this methodology addresses only sediment and the physical alteration of habitat conditions and water quality . It does not encompass biological impacts and therefore not the critical test of whether impacts are â?? significantly adverse . â?쳌 Thus , a sediment budget approach may contribute to the analysis of CWEs , but it is by no means adequate by itself . CWE analyses would require the simultaneous evaluation of the effects of many THPs in a large watershed interacting with the specific environmental condition of that watershed and with the â?? legacy â?? effects of previous timber operations , if they are known to persist in the watershed . These â?? legacies â?? are testament to the long - term and far - reaching effects of ( say ) sediment that leaves a site or of the slowly reacting changes in forest canopies , root structures , etc . , or the effects of quasi - permanent changes to the drainage patterns of hillsides when roads are installed . Whole - watershed , or whole - ecosystem , evaluations are needed . For instance instead of assessing how a single timber harvest will affect a single species , what is needed is a determination of how the balance between different plants and animals of the ecosystem would be altered and would function differently as a result of land - use changes that are being proposed or envisioned over decades and entire watersheds ( see later our discussion of appropriate geographic scales to be considered ) . Key questions are : how can this be done ; who will bear the cost ; and how big an area should be included in an assessment of CWEs ? This process is too complex and costly to be accomplished by foresters and timber companies , even the large ones , and certainly not the small ones who cannot reasonably be expected to contract out for such an expensive service . In addition , the combination of skills required to study CWEs is not easily mobilized . Such training is distinctly lacking in the education of RPFs and most other environmental scientists , especially those with a seniority to be in leadership positions . There is a particular dearth of people trained to be the conceptual leaders of interdisciplinary studies of cumulative effects in particular watersheds . Furthermore , in nearly all cases , large scale , whole - watershed analysis would require even large landowners to perform analyses of lands they do not own and may not get access to review . Complexity , spatial scale , and cost necessitate that CWE analysis be performed by adequately trained specialists in an appropriate state agency . 28 Chapter 5 : A Scientific Basis for Predicting Cumulative Watershed Effects â?? Major reform is the victim of numerous minor reforms â?쳌 â?? Lord Acton Proposal We propose a radical restructuring of the way that CWEs are analyzed and predicted . We recommend that this burden be removed from landowners and their consultants , who generally have neither the information , nor the resources , nor the training to conduct a basin - wide analysis . Responsibility would be moved to a specialized unit within a major State agency ( preferably CDF , but if that becomes impossible , the Resources Agency ) . The scientific basis for the CWE analysis would be expressed through spatially registered mathematical models to summarize the best communal understanding of watershed processes . The analysis would use spatial data resources and models that are currently available . Since such models are likely to be improved and new ones developed , the analysis must be allowed to change continually as new insights and tools emerge . Once a model of one or more watershed processes is constructed and reviewed for its rational basis and congruence with available evidence , it would be used in simulations of stochastic events , such as weather sequences , to calculate the integrated risk of damage or improvements to resources over likely economic and management scenarios as the watershed is harvested or affected by other land use . The results would be spatially registered , i.e . recorded in map form , to link proposed cause and effect . This process of risk analysis through stochastic simulations of various scenarios will be referred to below as â?? gaming â?쳌 , and it is a common tool used to assist with other forms of decision - making . From the spatially registered calculation of risk to resources such as biodiversity , ecosystem functioning , and water quality , resource analysts could distill policies about allowable rates of cutting , differential requirements for BMPs in various parts of a region or watershed , and other guidelines , depending on the risk they are willing to accommodate . The responsible unit would be staffed with specialists trained in interdisciplinary CWE analysis and prediction , and it would be given the resources necessary to do the job very well . We assume that the lead State agency would collaborate with other State and federal agencies in designing the unit , although the unit should be free of traditional ways of conducting CWE analyses in the various agencies , all of which have proven to be inadequate . In the remainder of this chapter , we describe the strategy and 29 its relationship to other decision - support activities , including the planning of activities on the ground in the form of THPs . The Appendix then presents a sample of the tools available for implementing the model - based strategy in order to illustrate their availability and continuing evolution . The toolbox described in the Appendix is not meant to prescribe which particular models should be chosen by the responsible state unit , whenever the strategy is implemented . Our proposal for watershed - scale CWE analysis is in line with that of the Little Hoover Commission , which recommended â?? master plans for watersheds containing productive forests . â?쳌 ( p . vi ) . Our proposal for gaming is in line with the Commissionâ??s suggestion ( p . vi ) for the establishment of â?? an objective environmental - risk assessment system that would assist in the evaluation of Timber Harvest Plan approvals . â?쳌 The Commission also pointed out that â?? mutual distrust is the outcome of a process open to interpretation , â?쳌 and that â?? neither issues nor responsibilities are clearly enough defined to avoid turf battles . â?쳌 Unfortunately the technical state of the art of environmental prediction is , and for the foreseeable future will be , unable to avoid large uncertainties . Imperfect knowledge of the local variability of environmental properties and of some system operations , and the indeterminacy of many future influences ( biotic , climatic , and economic ) will keep the uncertainty high , as is the case with most decision - making challenges . But at least the ground rules for the interpretations of likely events can be formalized through strong conceptual models of the processes involved , consistent ways of evaluating them , and general agreement on letting some authoritative body be responsible for the quantitative evaluation of probable outcomes . That transparent evaluation can then be passed on to a decision - making body for final use . We also describe how the CWE prediction could fit into broader environmental analyses , conducted for other reasons , and also into the larger social process of reducing disagreement and resolving conflict among disparate stakeholders . We are not experienced in this field and we realize that this process of integration would have to be refined by others . Integration of scientific analyses into community decision - making in the face of uncertainty is an activity that is evolving rapidly , and is needed in natural - resource - rich regions of the western United States . It involves collaborative and learning - based approaches to sustainable development and environment management . We refer to sources of information on these approaches in a later section of this chapter . 30 Need for a Risk - based Approach to the Prediction of CWEs The purpose of predicting relative risks from CWEs and distilling policies from the predictions is to make good decisions about natural resources ; not to make some elegant and detailed prediction that would improve landscape science . Society needs a reduction of the risk of undesired changes in forested watersheds and attendant water and ecosystem resources as a result of land use . Risk can be reduced through avoidance or modification of certain actions ( such as deciding not to harvest certain areas or limiting the rate of harvest ) ; through requiring certain actions ( BMPs ) designed to reduce the occurrence or intensity of damaging effects ; and through restoration measures which improve ecosystem structure and function and consequently their durability under landuse - related stress . Quantitative prediction of the risks of various CWEs can enable a policy of reducing such risks wherever they are deemed unacceptable . The prediction by itself , of course , does not carry out this policy , but allows a balancing of risk and reward under a range of scenarios to facilitate the decision - making . Some resource managers , environmentalists , and downstream residents seek to constrain the available options of land users by defining the CWE issue in binary terms : â?? If it can be demonstrated that there is any accumulation of negative effects of undefined magnitude , the land use must be stopped for more detailed , possibly prohibitive review . â?쳌 But landowners and supportive agency personnel have found this constraint an easy one to elude , as the current situation illustrates . Risk analysis could provide a more realistic and flexible way of balancing competing claims . Most questions about CWEs , or about most environmental impacts are posed ( but , unfortunately , are also answered ) in an illogical way . Members of the committee have frequently been asked , or have read questions such as : â?? If timber is harvested in this watershed , will it cause landsliding ? And will that be significant ? â?쳌 Scientists are often ridiculed when they answer such a question with â?? It depends . â?쳌 But the appropriate answer really does â?? depend . â?쳌 The watershed might be logged intensively during a ten - year period of relatively dry weather with no large rainstorms , and a secondary forest with an adequate root system might be re - established before heavy rains return . Increases in sedimentation of streams due to accelerated landsliding might be small in that case . A nearby , similar watershed might be logged in the succeeding wet period , and suffer heavy damage to stream channels if a particularly large rainstorm causes landslides and debris flows from logged hillslopes and new roads to dump large volumes of sediment into channels . The sedimentation could eradicate one yearâ??s recruitment of salmon fry from many reaches , and make copious amounts of sediment available for degrading spawning redds and rearing pools for several successive year - classes of salmon . In this latter case , those people primarily interested in the fate of salmon would blame the timber harvest , whereas timber interests would blame the rainstorm . There is often no satisfactory answer to the question : â?? Did the harvest or the rainstorm cause the sedimentation ? â?쳌 , and even less of a basis for 31 saying whether the next harvest will cause sedimentation . They both , together , caused the sedimentation , and their concatenation is not a natural event , or an â?? Act of God . â?쳌 It makes more sense to ask whether the harvest increased the risk of the slope failures and sedimentation , whether a future harvest will increase such risk , and whether the risk will be larger after harvesting in area A or area B , with technology C or D . The same can be said of flood hazard . Timber companies have often diverted the debate about whether timber harvest aggravates flooding or sedimentation by pointing to the fact that large floods and intensified erosion occur in large rainstorms . They avoid the question of whether logging has increased the risk of flooding of a certain magnitude , or erosion of a certain intensity . Of course , there are many local examples where forensic analysis can identify that a collapsed logging road or a blocked culvert was the cause of destruction of some aquatic resource . There are also a few statistical studies that show increased spatial frequency of landsliding in clearcut and roaded terrain over that in undisturbed terrain . But it is difficult to make quantitative predictions from these studies . At the scale of watersheds , the aggregate effect of these and other perturbations has been difficult to identify , given the usual limited pre - disturbance information , the complexity of watershed conditions and processes , and the difficulty of obtaining adequate information on topography , material properties , and other features needed for a detailed analysis or prediction . Thus , our ability is limited for predicting specific habitat or biotic changes from realistic data resources . Damage is contingent upon the land use , the weather , local variations of geotechnical or biotic conditions , and population dynamics of either valued organisms or their predators . Nevertheless , some changes due to land use are so radical and widespread that they are widely agreed to have occurred , even by land managers as well as resource management scientists . The concept of risk combines a statement of probability of an event with an identification of its magnitude ( its severity or potential improvement ) . Examples would be : â?? there is a 0.01 probability of a stand re - setting wildfire occurring in this watershed in any one year â?쳌 , or â?? there is a 10 % chance of the occurrence of 5 channel - intersecting landslides per square kilometer of watershed within 5 years of timber harvest â?쳌 , or â?? there is a 20 % chance that the average annual production of salmon smolts from this watershed will decline below 5000 for the decade following timber harvest . â?쳌 Conscientious analysis of the risk itself then allows ( or requires ) the responsible decision maker to assess how risk might change with different land uses and what level of risk is acceptable or desirable to society , given the benefits or dangers to be expected . ( Again , even the benefits of an investment in rehabilitation can only be estimated in our uncertain world . ) Bloomfield ( 1985 ) provides an introduction to the literature on risk analysis , and focuses its concepts on hazard analysis in timber regions . He also elaborates different kinds of risks relevant to decision making in the face of uncertainty : background risk , the incremental risk from a project , and the 32 marginal risk of the cumulative effects of successive projects . He also discusses the need for identifying appropriate physical , biological , and social boundaries of a risk analysis . Such an analysis will not replace judgment , contention , or the taking of ultimate responsibility , but it offers the promise of formalizing them and facilitating action as opposed to the widespread stalemates that currently bedevil resource allocation , conservation , and rehabilitation . Lee ( 1993 ) and Lee and Rieman ( 1997 ) have also explored the assessment of risk to salmonid populations at whole - watershed scale by combining models of watershed condition with population viability models in a Bayesian Belief Network . Such decision - support systems explicitly recognize uncertainty in both the reasoning about system operation and the quality of information about system characteristics . Nevertheless , they provide a rational and transparent basis for decision - making and problem solving based on the recognition of risks to resources . Haas et al . ( 1991 ) and Olson et al . ( 1990 ) discuss other ecological applications of the approach . Modeling Basis We have previously established that CWE analyses and predictions need to be comprehensive in both geographical terms ( they should refer to whole watersheds of a significant size , which we will discuss below ) and in resource terms ( they should describe all major characteristics and values of the landscape ) . We also proposed that it makes sense only to define CWEs in terms of the risk ( probability and magnitude ) and the changes of risk that some resource will be damaged or enhanced as a result of management actions . We , and other reviewers , have concluded that the postage - stamp approach of parcel - by - parcel analysis required of THP applications can never address the interactions between many independent land - use actions in diverse terrain and under the influence of an unknown future regime of weather and economics . It is impossible to analyze and predict the long - term consequences of land use on erosion , sedimentation , ecosystem structure and function , or aquatic habitat through experiments or other empirical approach because to do so would require monitoring large , complex watersheds during land use of varying nature and intensity for many decades of variable weather . Even if the costs of such a strategy could be borne , the results would be available only after much disruption had already occurred . Instead , the prediction and auditing of interacting events in complex watersheds under uncertain future conditions can only be done through the formal and systematic examination of how risk changes under hypothetical scenarios . This does not mean that empirical studies are not valuable . In fact , such studies are needed to motivate , inform and evaluate hypotheses . Furthermore , monitoring will be required to 33 assess whether prescriptions guided by CWE analysis are effective . But these are activities do not constitute the prediction of CWEs . In the natural and social sciences , as well as in planning and engineering , the formal term for predicting the consequences of some system change under hypothesized conditions is â?? modeling â?쳌 , and we suggest that it be used as the basis for the analysis and prediction of CWEs in California forestlands . The term â?? modeling â?? describes activities that are linked , but which range from structured , qualitative expressions of how systems work ( which we will here call conceptual models ) to mathematical descriptions of the various mechanisms comprising the system ( which we will call process - based mathematical models ) . Intermediate levels of complexity are found in statistical models , â?? rules - based â?쳌 models , and other labels are used along the continuum . Models allow us to envision and represent our best communal understanding of how whole , complex systems behave , and then to discuss and analyze the consequences of that behavior in a rational , structured manner . They also allow us to examine how a system will behave under some future condition , if each of its parts interacts in the way we envision in the model . Of course , from time to time we get surprised because the system behaves in an unexpected way , and that is why scientists continually re - evaluate their conceptual and mathematical models by monitoring real systems . The defining characteristic of a scientific approach is the continual re - evaluation of its own prevailing ideas through empirical investigations . It is unlikely that models of complex interactions at the scale of whole watersheds can be tested in the same manner that models can be tested at laboratory or plot scales . It is also unlikely that data on system characteristics can ever be adequate for accurate , high - resolution predictions . Thus , tests that scientists usually consider necessary for validation of theories are not possible at watershed scale . That is why even watershed hydrology , the most quantitatively developed of the sciences discussed here , does not rest on experimentally validated theories , but rather on a consensus about how watershed hydrology works ( see the Appendix ) . Models used for predictions of CWEs will have to consist of components that have been validated to various degrees through observations and process studies , connected by theoretical reasoning and calibrated against measurements under representative conditions . This is a problem shared with all uses of model - based approaches to decision - making about environmental issues from CWEs up to global warming . Despite the lack of experimental validation , using models of various kinds is familiar to all of us because we often make decisions about cause and effect , even if we do not think of the activity in the explicit ways summarized in this document . We are also familiar with using models when thinking of risk in our lives . If I wear a seat belt while driving to work , will I decrease my risk of risk of injury ? Is my risk of injury greater if I donâ??t wear my seat belt and I drink alcohol immediately before driving ? Is the risk to my 34 retirement savings greater if I invest them in real estate or the stock market over a period of three years ? Ten years ? Should I buy a house close to a nuclear power plant , or a fault zone ? Even if people have only sparse empirical information about these matters , the best informed among us make assessments on the basis of a summary of their best estimate of how things work . If we are making sound judgments , we can articulate this conceptual model to others , seek advice for refining it , and defend our decision as being rational . If two people develop different conceptual models , others can judge the basis for those models . Professionals trained , or at least practiced , in decision - making are even more familiar with formalized ways of using models to structure their thinking about risk . Their methods may range from the conceptual models of decision making in a multi - stakeholder political system , to statistical models used in various environmental sciences , and to more detailed mathematical representations of mechanisms employed by engineers , economists and natural scientists . In particular , risk can be represented , examined , and discussed in each of these models . Many people , including many resource professionals , express suspicion when the use of models is proposed , even though , at some level they utilize models frequently in their lives and work . It is claimed that models ( by which skeptics usually mean mathematical models of processes ) can obfuscate , mislead , and give inflated credence to assertions about which there is great uncertainty . Models can only represent the effects of mechanisms that are known about or agreed upon , and the accuracy of their predictions is vulnerable to unanticipated factors . It is also claimed that models are fundamentally anti - democratic because they are not accessible to all interested parties , and often are comprehensible only to the cadre of specialists ( often inexperienced in the field aspects of what they are modeling ) , who can therefore manipulate results to present their masters â?? preferences in a positive light . We agree that models can be used imperfectly in all of these ways . However , when they are openly and responsibly used and communicated , models can assure exactly the opposite results . At whatever level of elaboration is considered necessary , models can be used to summarize explicitly our communal understanding , or the bases of our disagreement . They can be used to express our communal beliefs about the relations between processes or characteristics , â?? even if only the direction of an effect is agreed upon , such as whether the density of primary haul roads can or cannot be confidently related to suspended sediment concentrations in streams on a uniform rock type . Models can be read by anyone with sufficient diligence and training ( recruited by any stakeholder in a debate ) , whether the â?? reading â?? involves examining the existence , direction , and thickness of arrows on a box - and - arrows representation of a conceptual model or the algorithms written in a computer code . Even the most complex mathematical algorithms are explicit , exact , and can be exposed by direct reading or by running of the model with different data inputs . They are by definition , of course , simplified expressions of environmental processes 35 and relationships , and one link in a model or series of linked models may be particularly crude , limiting the applicability of all of the other steps for the needs of policy makers . Let us specify an example of how mathematical models of watershed effects might be misused to illustrate the point that model - use needs to be managed carefully by a responsible agency . Suppose that we have constructed a model of the loading of large organic debris into channel networks during a timber harvest cycle , and the results are expressed as maps of the number of wood pieces or the volume of wood per unit length of channel . We might even imagine that we have related the number of pieces per unit length to the number or volume of pools per unit length of channel as a measure of aquatic habitat . The developer of the model , or any person experienced in environmental modeling , would understand that predictions made with typical data inputs in a stochastic world would relate to actual field conditions only within quite wide tolerances ( i.e . individual estimation errors would be large , even if predicted averages were approximately correct ) . The model would be useful for making comparisons , for example , between two strategies for gradually building up debris loads and pool occurrence in streams , or for interpreting large differences between pool frequency under various physiographic or management conditions , or for setting a management course that would rehabilitate streams . Such comparisons indicate the relative differences between model outcomes . However , if the same model were used to design a management strategy and to claim ( for example ) that within a specific time period the woody debris load of a particular channel reach would meet some numerical threshold , an experienced modeler would argue that the model was being used beyond its capability and was likely to mislead rather than to shed light on the situation . The prediction would be suspect because the propagation of uncertainties from data inputs and spatially variable initial conditions would render the numerical prediction sufficiently unreliable that it should not be compared with a fixed threshold value in order to justify some policy . Of course , as we have argued above , much of this problem would arise because of the inadvisability of depending on threshold values for environmental policy - making , as they are intractably difficult to define with current levels of understanding and biological data . Apart from our communal , imperfect understanding of landscape mechanisms ( which bedevils us when we envision , plan , and debate only in words at least as much as when we use models ) , the biggest limitation in using models is that once the model is formulated it requires us to specify input values for its variables and parameters . Again , our ignorance is exposed . We are forced to do our best : to measure appropriate values ; to transfer values from comparable basins or regions ; or to estimate them from some fundamental knowledge of nature ( such as knowledge of atmospheric physics ) . Do we know the magnitude of the largest daily rainstorm likely to occur over Arcata during the planned logging cycle for a nearby basin ? Can we estimate the probability of more than 7 inches of rain occurring in a day within that same logging cycle ? Can we estimate the reduction in the number of species or individuals if a given acreage of mature forest is removed or regenerated , or if large woody debris is gradually recruited to a 36 stream network and over the long term there is no change in weather , ocean conditions , harvesting or other factors influencing anadromous fish ? An important word in the questions above is â?? estimate â?쳌 . No one would claim that we can answer these questions in an exact manner for a complex landscape both because of our own uncertainty about system operation and its large spatial and temporal variation of properties , and because we simply donâ??t know the future sequence of events that might befall our landscape or ecosystem . But to an extent that is useful for informed debate and decision - making , the answer to the questions above is â?? Yes , with various degrees of confidence . â?쳌 The estimates can be made with various degrees of precision , but always in the face of uncertainty about the poorly known existing properties of the system , the course of future events , and their biological consequences . Probably more important than any specific degree of confidence is the facility through modeling ( a ) to express uncertainty , resulting either from our reducible or irreducible ignorance , and ( b ) to continuously check and refine our understanding expressed through the models . It is in this sense that modeling is inherently self - critical and democratic , when like other forms of democratic debate it is conducted and communicated in a skillful , responsible , and transparent fashion . The expression of uncertainty does not reflect impotence and confusion . It simply highlights the fundamental fact that , in all of human affairs , decisions must be made in the face of uncertainty , which in this case is definable to some extent . We trust our lives daily to models of complex engineered systems , operating in uncertain environments . Governments adjust economic policy on the basis of estimates from models of financial and social processes in ways that affect the economic success of competing stakeholders , and timber companies make estimates of market behavior and other business conditions through similar means . In other kinds of land use problems , such as soil erosion and sedimentation in agricultural regions , mathematical models are used for predicting the transfer of soil material , pollutants , and nutrients to waterways under various land - use scenarios and weather patterns in order to decide whether or how soil conservation subsidies should be invested . Models of biological populations are used to evaluate the risk of extinction to highly endangered species . Even in commercial forestlands , decisions concerning safety ranging from the design of flood - conveyance capacities at bridge crossings to the magnitude of insurance premiums are quantified through the use of models . It is curious , therefore , that the debates about CWEs in forested regions have made so little use of the information - organizing power that could derive from well - managed modeling efforts . We understand , of course , through our own experience in constructing and using models , that they are not perfect instruments , and like the words , tables and graphs that are the currency of most environmental debates and policy decisions , models can be used deliberately or inadvertently in counterproductive ways . Self - delusion is just as common among the users of models as it is among persuasive and committed writers and debaters , and responsible policy makers weigh all of these 37 imperfections . But models can be systematically checked and gradually improved because they are formalized expressions of our collective understanding of the systems we seek to influence . They can also be summarized in simplified terms to make them accessible to all of the participants in a debate ; and this simplification can be checked and validated by observers of the more complex level . For example , a hydrologist might use a complex , process - based mathematical model to calculate that , in a basin of a given size , wintertime flood peaks should be expected to increase to some degree because of forest canopy removal and road construction . He could reduce the results to a simpler form for use in a conceptual model for decision - making , and could express and explain the reasons for the results in a manner that could be checked by his professional peers , and then ( with greater difficulty ) by monitoring or analysis of historical records . In summary , we propose that the analysis and prediction of CWEs be conducted through modeling of risks to chosen resources , expressed first of all as communally developed conceptual models , and subsequently in mathematical form . We do so with the full acknowledgement that models are not the only tools that are needed for reducing uncertainty and guiding policy . In fact , we encourage both modelers and users of their predictions to read the rather harsh criticism of the history of prediction in public policy - making by Sarewitz et al . ( 2000 ) . The contributors to the volume ( few if any being practicing modelers ) document many failings of both prediction and the use of predictions in policy - making , but conclude , grudgingly ( p . 386 ) , that model - based prediction is necessary , at least as a part of making good decisions . Even this rather lop - sided review has important lessons about what to avoid in the use of science - based predictions . Spatially Registered Simulation Models and Gaming A CWE prediction needs to have at least the following characteristics : 1 ) It should establish causal linkages between land use and ecosystem condition ( e.g . fish and bird populations or water quality ) , and should be able to quantify how these ecosystem values will probably respond to future land use or restoration programs . 2 ) It should be spatially registered . The locations of the disturbance and of potential impacts need to be explicitly defined . 3 ) It should take account of the fact that the perturbation being considered ( timber harvest , road de - activation , loading of LWD into channels , allocation of streamflow withdrawals , etc . ) will occur in an environment , which is stochastic . In other words , the perturbation will 38 interact with rainstorms , floods , off - site ( even off - continent ) ecological conditions , and economic pressures that are essentially unpredictable . Skill in prediction of some of these factors is gradually rising , but it is still so crude that it can largely be discounted for the present purpose . The interactions will occur : a . in a landscape which contains a large amount of spatial variability of topographic form and material properties , including transient properties such as evolving tree - root reinforcement of hillside soils , or aquatic primary production , all of which may be sufficiently variable that it is impractical to measure or map them with foreseeable resources in a particular application ; b . in a sequence of weather events ( climate ) which is essentially unknowable in advance but which drives streamflows , rainstorm and fire occurrence ; c . amid biological perturbations such as disease , ocean - rearing conditions , and in a matrix of nonlinear processes driving population dynamics ; and d . in an economic and political environment that may drive the demand for timber in ways that are difficult to predict far in advance . 4 ) The prediction should preferably emphasize causal relations based upon an understanding of processes , rather than statistical association alone . A mechanistic expectation ( hypothesis ) can be developed and agreed upon , even by competing interests , and can be tested and refined through directed research . Even if the precision of predictions made from mechanistic conceptual models is low at a particular time , they are better guides to corporate and public policy than are statistical searches for needles in haystacks of environmental variability . Moreover , approximate predictions that are rationally based on an understanding of processes can often be refined gradually with better data or more realistic representations of the system . Simply agreeing on the expected sign of a change represents an opportunity for making decisions and monitoring responses . 5 ) Therefore , CWE predictions should be based on sound , broadly agreed - upon conceptual models of how complex watershed systems work . For some decision - making purposes , such as controlling turbidity , it may suffice to construct only a simple conceptual model of the effects of land use on the budget ( sources , generation rate , and transport rate and timing ) of fine - grained sediment . For purposes of conserving or rehabilitating aquatic habitat and animal populations , it may be necessary to link physical models of habitat formation ( involving the budget of channel - bed sediment and of turbidity - producing fine 39 sediment , interactions of sedimentation with large woody debris or valley confinement , and the control of channel morphology with spawning gravels , pools , shade , and other refuges ) and biological models involving habitat quality , spawning success , predation , and growth . 6 ) These conceptual models should be formalized as mathematical relations and applied to digital representations ( computerized maps ) of the watershed of interest to predict the location of expected changes , including source areas of material flux or other changes . These latter will often be downstream of the initial alteration , but not always in the case of terrestrial wildlife . The mathematical relations could vary in complexity , such as in the following examples of components of integrated models : a . simple , â?? rules - based â?쳌 models , such as predictions of the number of salmon fry emerging from spawning grounds as influenced by the percentage of fines in the bed , based on data collected from numerous other watersheds . b . mechanistic rules describing the spatial pattern of a process , such as the hillslope locations that are expected to attain a low â?? factor of safety â?쳌 with respect to landsliding in rainstorms with some specified probability of occurrence , or the gradients on which sediment coarser than a certain grain size is expected to accumulate for extended periods of time c . process - based ( dynamic ) models of large woody debris recruitment from riparian zones and hillslope failure sites d . dynamic models of wood and sediment supply , downstream transport , and habitat creation e . spatially distributed , individual - based fish population models . 7 ) The degree of spatial elaboration ( the resolution of the terrain representation to which the model is applied ) may vary with the nature of the problem , the decision - making needs , and the resolution of the available data . Applications with differing resolutions may be used in sequence . One might first do a rapid , coarse - grained assessment for the purpose of highlighting the most significant problem watersheds ( getting ahead of the problem that land use has already impacted most watersheds of California and decisions about some resources must be made immediately ) . Later ( or more slowly ) , a more complete and elaborated process model could be applied to a higher - resolution representation of the watershed , including its climate and proposed land use or rehabilitation . 40 8 ) The model should be applied to the watershed in a â?? gaming â?? format . That is , the model should be used to calculate scenarios covering the range of conditions that might occur , and the probability of each scenario should be estimated . In this way , the risk to a resource can be defined . Again , a range of approaches could be used , including examples such as : a . A calculation of the area that might be rendered vulnerable to landsliding in a rainstorm of a chosen probability , with and without timber removal and root death , either with a default assumption of no recent failures evacuating landslide source areas , or with updated estimates of recent landslides or soil depths ( Benda and Dunne , 1997a ; Dunne 1998 ; Dietrich et al . 2001 ) . b . Li
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