Environmental Flow Assessment : Methods and Applications (Hardcover)

About the Editors

Series Foreword

Preface

1 An introduction to environmental flows

Summary

What are environmental flows

Why EFA Is So Hard; Scientific Issues

Stream ecosystems are dynamic and open

Fish evolve

Streams adjust

Climate changes

Populations vary

Habitat selection is conditional

Spatial and temporal scales matter

Why EFA is So Hard: Social Issues

Social objectives evolve

Science and dispute resolution

Water is valuable

Managers or clients often want the impossible

Why is EFA so hard: problems with the literature

Why is EFA so hard: limitations of models and objective methods

Models and environmental flow assessment

Objective and subjective methods

Conclusions

2 A brief history of environmental flow assessment

Summary’

Introduction

The legal basis for environmental flow

The scope of environmental flow assessments

Methods for setting environmental flows

Conclusions

3 A Primer on Flow in Rivers and Streams

Summary

Introduction

Precipitation and runoff

Flow regimes

Describing or depicting flow regimes

Variation in flow regimes across climates and regions

Anthropogenic changes in flow regimes

Hydrologic classifications

Spatial patterns and variability within streams

Spatial complexity of flow within stream channels

The variety of channel forms

Lateral connectivity with floodplain and off-channel water bodies

Bed topography and hyporheic exchange

Managing environmental flows

Conclusions

4 Life in and around streams

Summary

Introduction

Structure of stream ecosystems

Across-channel gradients

Upstream-downstream gradient

Adaptations of stream organisms

Morphological Adaptations

Physiological adaptations

Behavioral adaptations

Adapting to extreme flows.

Synthesis

Environmental flows and fish assemblages

Conclusions

5 Tools for environmental flow assessment

Summary

Introduction

Descriptive tools

Graphical tools and images

Stream Classifications

Habitat classifications

Species classifications

Methods classifications

Literature reviews

Experiments

Flow experiments

Laboratory experiments

Thought experiments

Professional opinion

Causal criteria

Statistics

Sampling

Sampling methods

Hypothesis testing

Model selection and averaging

Resampling algorithms

Modeling

Environment‐abundance relations

Habitat association models

Drift–foraging models

Capability models

Bayesian networks

Hierarchical Bayesian models

Dynamic occupancy models

State‐dependent life‐history models and dynamic energy budget models

Hydraulic models

Hydrological models

Temperature models

Sediment transport models

Other uses of models in EFA

Hydraulic habitat indies

Hydrological indices

Conclusions

6 Environmental flow methods

Summary

Introduction

Hydrologic, habitat rating, habitat simulation, and holistic methods

Top–down and bottom–up approaches

Sample–based methods and whole system methods

Standard–setting and incremental approaches

Micro–, meso–, and river–scale methods

Opinion–based and model–based methods

Hydrological methods

The Tennant Method and its relatives

Indicators of Hydraulic Alteration (IHA)

Hydraulic rating methods

Habitat simulation methods

Habitat Association Models

Bioenergetic or drift foraging models

Frameworks for EFA

Instream Flow Incremental Methodology (IFIM)

Downstream response to imposed flow transformation (DRIFT)

Ecological limits of hydraulic alteration (ELOHA)

Adaptive management

Conclusions

7 Good modeling practice for EFA

Summary

Introduction

Modeling practice

What are the purposes of the modeling?

How should you think about the natural system being assessed?

How will the available budget be distributed over modeling efforts, or between modeling and data collection, or between the assessment and subsequent monitoring?

How will the uncertainty in the results of the modeling be estimated and communicated?

How will the model and model development be documented?

How will the models be tested?

How good is good enough to be useful?

Who will use the results of the modeling, and how will they be used?

Do you really need a model?

Behavioral issues in modeling for EFA

Data-dependent activities in developing models

Sampling

General Considerations

Spatial scale issues in sampling

Cleaning data sets

On testing models

The purpose of testing models

Why testing models can be hard

The problem with validation

The limited utility of significance tests

Tests should depend on the nature of the method being applied

Models should be tested multiple ways

The importance of plausibility

The importance of testing models with independent data

The quality of the data limits the quality of the tests

The importance of replication

Models should be tested against other models

Experimental tests of models

Flow experiments

Behavioral carrying capacity tests

Virtual ecosystem experiments

Testing models with knowledge

Testing hydraulic models

Testing EFMs based on projessional judgement

Testing species distribution models

Goodness of fit

Prevalence

Imperfect detection

Spatial scale and other complications

Conclusions

8 Dams and Channel Morphology

Summary

Introduction

Diagnosing the problem and setting objectives

Managing sediment load

Existing dams

Proposed dams

Obsolete dams

Specifying morphogenic flows

Three common approaches to setting morphogenic flows

Clear objectives needed

Magnitude

Duration

The hydrograph

Seasonality

Recurrence

Flows for managing vegetation in channels

Constraints

Minimizing cost of foregone power production and other uses of water

Preserving spawning gravels

Preventing flooding and bank erosion

Conclusions

9 Improving the use of existing evidence and expert opinion in environmental flow assessments

Summary

Introduction

Overview of proposed method

Basic principles and background to steps

Literature as a basis of an evidence-based conceptual model

Translate the conceptual model into the structure of a Bayesian Belief Network

Quantify causal relationships in the BBN using formal expert elicitation

Update causal relationships using empirical data

Case study: golden perch (Macquaria ambigua) in the regulated Goulburn River, south-eastern Australia

Evidence based conceptual model of golden perch responses to flow variation

Bayesian Belief Network structure of the golden perch model

Expert-based quantification of effects of flow and non-flow drivers on golden perch

Inclusion of monitoring data to update the golden perch BBN

Discussion

Hierarchical Bayesian methods as best-practice

Piggy-backing on existing knowledge

Resourcing improved practice

Accessibility of methods

Summary

10 Summary conclusions and recommendations

Conclusions and recommendations

A checklist for EFA