ELOHA Home       Hydrologic Foundation          River Types​
Flow + Ecology​ Policy Implementation Case Studies Bibliography


ELOHA's Hydrologic foundation is a database of daily streamflows for every analysis point under baseline (unaltered) and current (developed) conditions for a single time period.

A hydrologic foundation of streamflow data informs water managers where, when, and how much water occurs in all water bodies across the region. These data are used to characterize flows, classify river types, quantify flow alteration, relate ecological responses to flow alteration, and evaluate the status of sites relative to environmental flow standards. They should be estimated for every stream segment or sub-basin where environmental flows will be managed, where biological data have been collected, and where major flow alteration occurs. Without this information, limits on flow alteration are very difficult to permit, measure, or enforce without expensive site-specific data collection.
The basic components of a hydrologic foundation of daily or monthly streamflow data are hydrologic simulation and water use accounting. Hydrologic simulation is used to estimate streamflow conditions, while water use accounting estimates the impact of water use on streamflow conditions. Two general approaches to hydrologic simulation are regression modeling and process modeling.
Regardless of the modeling approach, the hydrologic foundation can only be as accurate as the water-use (withdrawal and return flow) data that go into it. Accurate, spatially explicit water use reporting and improved water use estimation methods and decision support systems are greatly needed. Other model input may include climate and land cover data. 
 Existing hydrologic models or decision support systems for water management may be adapted to build a hydrologic foundation for ELOHA.   Kennard et al (2009) provide guidance on selecting the period of record for estimating hydrologic metrics for ecological studies.  Murphy et al (2012) compared methods for predicting environmental flow components at ungaged sites.  Several existing streamflow databases may provide useful starting points.  
The treatment of interactions between groundwater and surface water depends on the type of hydrologic model used and on the hydrogeology. The approaches reported in our case studies range from assuming direct and immediate impacts of groundwater pumping on streamflow to using linked groundwater and surface-water models to calculate the time, place, and amount of depletion.

Although a database of daily streamflow under naturalized and current conditions remains an ideal, the lack of these data need not hinder the determination of environmental flow needs. In practice, few places have such a dataset in place at the onset, and building it usually requires considerable time and thought. Many water managers have successfully advanced other parts of the ELOHA framework while the hydrologic foundation is being developed, rather than awaiting its completion before proceeding with successive steps.

Hydrologic Foundation Case Studies

Baseline Streamflow Estimator (BaSE):  Pennsylvania, USA
The U.S. Geological Survey, in cooperation with the Pennsylvania Department of Environmental Protection, Susquehanna River Basin Commission, and The Nature Conservancy, created the Baseline Streamflow
Estimator (BaSE) to estimate baseline (naturalized) daily streamflow data for ungaged streams in Pennsylvania.  BaSE uses a methodology that equates streamflow as a percentile from a flow duration curve for a particular day at an ungaged location with streamflow as a percentile from the flow duration curve for the same day at a reference streamgage. This tool was modeled after the Massachusetts Sustainable Yield Estimator, and a similar method will be used in New York.  Download the free BaSE tool, report, and users guide.

SLURP Model:  Mekong River Basin
The Semi-Distributed Land-Use Runoff Process (SLURP) is a continuous simulation distributed hydrological model designed to make maximum use of remotely sensed data. SLURP divides a basin into subbasins, which are further divided into areas of different land covers.  For each land cover within each subbasin, the model simulates the vertical water balance, transforming daily precipitation into evapotranspiration and runoff separately, and routes the runoff downstream through the basin. 
Using only global datasets that are readily accessible on the internet, Kite (2000)  used SLURP to synthesize daily streamflow hydrographs in the 800,000-km2 Mekong River basin.  Topographic data were obtained from the United States Geological Survey (USGS) GTOPO30 public-domain DEM; land cover was obtained from the USGS 1-km digital land cover map of the world; soil parameters were obtained from the FAO Digital Soil Map of the World; and daily climate data (precipitation, temperature, dew point, and wind) were obtained from the US National Climate Data Center's Global Surface Summary of the Day (GSOD) internet database.  Radiation data were estimated from daily precipitation data.  Major dams and diversions also were included in the model.  Results of the model were converted into time-series of areas flooded, which were used to evaluate fish and irrigation productivity under different water allocation scenarios.

SWAT and SWRRB:  United States, Guatemala
(For basins with good basin characterization, but no streamflow gages.)
The U.S. Department of Agriculture developed the Simulator for Water Resources in Rural Basins (SWRRB) to predict the effects of various watershed management schemes on water and sediment yields in large, complex, ungaged rural basins (Williams et al, 1985).  The program models surface runoff, return flow, percolation, evapotranspiration, transmission losses, pond and reservoir storage, sedimentation, and crop growth to generate daily flows over multi-year time periods.  Although SWRRB is intended for use where calibration data are not available, it has been validated on 11 large agricultural watersheds in the United States (Arnold and Williams, 1987) and in a 2,671-hectare watershed in Guatemala (Maldonado et al, 2001).   Input requirements include daily temperature, solar radiation, and rainfall data (or monthly data with daily conversion parameters); soil, crop, pond, reservoir, and irrigation system characteristics; channel routing data; and other basin characteristics.
The SWRRB model has been superseded by the SWAT model, which has an improved GIS-based interface, and the ability to do much more detailed simulations.  The basic model equations are the same as in SWRRB. 
ACRU Model: South Africa
The ACRU (and ACRU2000) model  (School of Bioresources Engineering and Environmental Hydrology, 2007; Kiker et al, 2006) emerged from the Agricultural Catchments Research Unit at the University of KwaZulu-Natal in South Africa to integrate water budgeting and runoff with risk analysis.  Using a multi-layer soil water budgeting approach, ACRU simulates hydrology, crop yield, reservoir yield, and irrigation water demand/supply.  An advantage of ACRU, which has spurred its widespread use, is its flexibility of operation, depending on the availability of input data.  For example, potential and actual evaporation, interception losses, soil water retention constants, leaf area index, hydrograph routing, reservoir storage:area relationships, and crop growth periods all may be estimated by various methods according to the level of input data available or the simulation accuracy required.  The model uses daily time steps, although it accepts monthly input data.  For large catchments, ACRU operates as a spatially distributed model linked to a Geographic Information System (GIS).  ACRU was tested by simulating daily streamflows for 137 sub-catchments in the 4,387-km2 Mgeni River watershed in the KwaZulu-Natal province of South Africa over a 15-year period (1979-1993). The model satisfactorily simulated the highly variable flows that characterize southern African hydrology. The model had less success in areas encompassing large reservoir and transfer schemes combined with urban and peri-urban areas (Tarboton and Schulze, 1991; Kiker et al, 2006).
Thornthwaite-Mather Soil-Water Balance: Costa Rica, Indonesia, Kenya, Mexico
In cases where detailed watershed characteristics are difficult to obtain, lumped water balance models can often generate reliable streamflow hydrographs with few data requirements. With just rainfall and potential evapotranspiration data and generalized soil and aquifer characteristics, the lumped Thornthwaite-Mather (T-M) procedure calculates monthly water balances for relatively large watersheds (Thornthwaite and Mather, 1957).  The T-M procedure has successfully been used in its original or modified form to estimate monthly streamflow in numerous countries, including Kenya (Dunne and Leopold, 1978), Indonesia (Peranginangin et al., 2004), Mexico (Mendoza et al. 2003), and Costa Rica (Calvo, 1986).
Jha and Smaktin (2008) review the existing methods used in India for estimating flow characteristics at ungauged sites. It focuses on low and high flows, long-term mean flow, and flow duration curves. Since it lists the actual formulae, it can be used as a quick reference guide for selecting a suitable technique for various geographical, regional and/or river basins in India.
Colorado Stream Simulation Model (StateMod), Colorado, USA
StateMod is a program developed by the State of Colorado, USA, to simulate water allocation and accounting for comparing different water management scenarios in a large river basin.  StateMod is capable of simulating daily and monthly water allocation conditions over the 1975-2005 and 1909-2005  time periods, respectively.  To generate baseline conditions for ELOHA (locally known as WFET, the Watershed Flow Evaluation Tool), CDM et al (2009) changed the input files to eliminate any human influences on the river basin, including diversions and reservoir operations.  StateMod is an implementation of the Colorado Water Conservation Board's Colorado Decision Support System.













 Key Resources