(aka fixed-percentage, rule-of-thumb, standard-setting, look-up table, discharge/historical discharge, or hydrological index methods). Typically simple, primarily desktop EFMs that use hydrological data, usually long-term virgin or naturalised, historical monthly or daily flow records, to derive EF recommendations. The EFMs may incorporate various hydrological indices (VHIs)/formulae (e.g. based on hydrological & regionalisation techniques for gauged/ungauged catchments), include catchment variables, or be modified to take account of hydraulic, biological and/or geomorphological criteria. They require only hydrological and some ecological expertise. The flow indices used are commonly selected on the basis of professional judgement and/or by using a combination of statistical analysis and structured observations of rivers of similar hydrological and/or ecological type. A set proportion of flow (often an absolute “minimum flow”) represents the EFR intended to maintain river condition (i.e. whole ecosystem), the freshwater fishery or other highlighted ecological features at some designated acceptable level, on an annual/seasonal/monthly basis. Recent approaches (e.g. RVA) are more complex and hence, flexible. As a result of their rapid, non resource intensive, but low resolution outputs, and low flexibility, hydrological EFMs are most appropriate at the planning/reconnaissance level of WRDs, or in low controversy situations where the EFR estimates may be used as preliminary flow targets or as block-booked allocations. Hydrological EFMs may be used as tools within habitat simulation, holistic or combination EFMs. They have been applied in developed and developing countries.

(aka habitat retention, transect, habitat analysis or standard setting methods). One of two EFM types that utilises a quantifiable relationship between the quantity and quality of an instream resource, such as fishery habitat, and changes in Q, to calculate EFRs (see habitat simulation EFM type). They use changes in simple hydraulic variables (e.g. wetted perimeter, maximum depth, average velocity), usually measured across single (sometimes multiple) river cross-sections, with flow, as a surrogate for habitat factors known or assumed to be limiting to target species/assemblages (typically fish or benthic invertebrates). Cross-sections are placed at a river site where maintenance of flow is most critical or where instream hydraulic habitat is most responsive to flow reduction, and thus potentially most limiting to the aquatic biota (e.g. riffles). A relationship between habitat and Q, developed by plotting the hydraulic variable against discharge (often using hydraulic models), is used to derive the EFR. Commonly, a breakpoint, interpreted as a threshold below which habitat quality becomes significantly degraded, is identified on the habitat-Q response curve, or a minimum EFR is set as the Q producing a fixed percentage reduction in the particular habitat attribute. Hydraulic EFMs are combined desktop-field methods requiring limited hydrological, hydraulic modelling and ecological data and expertise. Due to their low-moderate resource intensity and complexity, and low resolution EFR output, they are of low flexibility and most appropriate for application for WRDs where no/limited negotiation of tradeoffs is required, or as a method within a habitat simulation or holistic type EFM. They represent the precursors of more advanced habitat simulation EFMs. They have been applied primarily in developed countries.

(aka (instream) habitat rating/modelling/mapping, hydro-biological or microhabitat methods). One of two types of combined desktop-field habitat-Q based EFMs (see hydraulic rating EFM type). These EFMs derive EFRs through analysis of the quantity and suitability of instream physical habitat available to target species or assemblages (typically fish or invertebrates) under different flow regimes, on the basis of integrated hydrological, hydraulic and biological response data. Typically, the flow-related changes in physical microhabitat are modelled in various hydraulic programs, using data on one or more hydraulic variables, most commonly depth, velocity, substratum composition, cover and, more recently, complex hydraulic indices (e.g. benthic shear stress), collected at multiple cross-sections within the river study reach. The available habitat conditions, simulated using various habitat modelling programs, are linked with information on the range of preferred to unsuitable microhabitat conditions for target species, lifestages, assemblages and/or activities, often depicted using seasonally defined habitat suitability index curves. The resultant outputs, in the form of habitat-Q curves for the biota, or extended as habitat time and exceedence series, are used to predict optimum flows as EFRs. Some habitat simulation EFMs consider ecosystem subcomponents in addition to instream biota (e.g. sediment transport, water quality, riparian vegetation, water dependent wildlife). Data requirements are moderate-high, and include historical flow records, hydraulic variables for multiple cross-sections, and habitat availability and suitability data for various biota. A high degree of expertise in advanced, dynamic hydrological and hydraulic habitat modelling, land surveying, and in physical habitat-flow needs of target species. The EFMs are complex, highly resource-intensive, moderately flexible, and with a moderate to high resolution EFR output. Habitat simulation EFMs are applied in cases of medium/large-scale WRDs involving rivers with economically important fisheries, of high conservation and/or strategic importance, and/or with complex, negotiated tradeoffs among water users. They may comprise tools within holistic type EFMs. They have been applied primarily in developed countries.

In holistic EFMs, which are combination desktop-field approaches, important and/or critical flow events are identified in terms of select criteria defining flow variability, for some/all major components or attributes of the riverine ecosystem (e.g. riparian vegetation, geomorphology, floodplain wetland). This is done either through a bottom-up or, more common recently, a top-down/combination process that requires considerable multidisciplinary expertise and input (often workshop or expert panel based). The basis of most approaches is the systematic construction of a modified flow regime from scratch (i.e. bottom-up), on a month-by-month (or more frequent), element-by-element basis, where each element represents a well defined feature of the flow regime intended to achieve particular ecological, geomorphological, water quality, and in some cases social or other objectives in the modified river. In contrast, in top-down, scenario-based approaches, EFRs are defined in terms of acceptable degrees of departure from the natural (or other reference) flow regime, rendering them less susceptible to any omission of critical flow characteristics or processes than their bottom-up counterparts. Holistic EFMs range from moderately to highly data intensive, requiring, among other data, within multiple river reaches/sites, historical flow records (virgin, present day), numerous hydraulic variables across multiple cross-sections, and quantitative biophysical data/models of the flow- and habitat-related requirements of all/select biota and ecosystem components. A commensurately high degree of expertise in advanced hydrological and hydraulic habitat modelling, and in the ecology of all individual biota/ecosystem components, is required. The EFMs are of moderate-high resource intensity, complexity and output resolution. The most advanced, highly flexible approaches utilise several tools from hydrological, hydraulic rating and habitat simulation EFMs, within a modular framework, for establishing EFRs, and may also incorporate social (flow related ecosystem goods and services for dependent livelihoods) and economic data. The most advanced holistic EFMs are applied in cases of medium/large-scale WRDs involving rivers of high conservation and/or strategic importance, and/or with complex, negotiated water use tradeoffs. Simpler approaches (e.g. expert panel assessments, intermediate determinations) are appropriate for lower profile cases involving limited tradeoffs. Holistic EFMs have been applied in developed and developing countries.

Combination (aka hybrid or multivariate statistical) EFMs comprise a diverse array of EFMs that possess characteristics of more than one of the four basic EFM types (hydrological, hydraulic rating, habitat simulation, holistic). They include partial holistic EFMs, which incorporate holistic elements, but within insufficiently developed methodological frameworks. The ecosystem components considered, data, expertise and other resources required, vary among approaches. The level of resolution of the output (EFR), flexibility, and appropriate level of application of the EFM also differ across techniques. The approaches have been applied in developed and developing countries.

Various other disparate methods and analytical techniques not designed for EFAs from first principles, but adapted or with potential to be used for this purpose. The ecosystem components considered, data, expertise and other resources required, vary among approaches. The level of resolution and flexibility of the output, as well as its potential for use as an EFR, are highly dependent on the nature of the individual approaches. This group of techniques are sometimes grouped with the multivariate statistical techniques of combination EFMs. They have been applied in developed and developing countries.

Often housed within holistic EFMs, are approaches that have diverged from an emphasis on the relationship between instream habitat, biota and flow, to explore other information best suited to specific river components or other connected ecosystems. They include methodologies for non-riverine wetlands, including lakes, estuaries and the nearshore coastal environment, as well as EFMs for riverine and other wetland ecosystem components, e.g. water quality, geomorphology/sedimentology, riparian/aquatic vegetation, aquatic invertebrates, fish, water-dependent vertebrates other than fish, GDEs, social dependence, recreation, aesthetics and cultural amenity. The types of data, expertise and other resources required vary among approaches, as do the level of resolution of the output (EFR), flexibility, and appropriate level of application of the EFM. The approaches have been applied in developed and developing countries.