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At least 1,315 records · Page 73Linked to original sources
USGS1998

Landscape modeling for Everglades ecosystem restoration

A major environmental restoration effort is under way that will affect the Everglades and its neighboring ecosystems in southern Florida. Ecosystem and population-level modeling is being used to help in the planning and evaluation of this restoration. The specific objective of one of these modeling approaches, the Across Trophic Level System Simulation (ATLSS), is to predict the responses of a suite of higher trophic level species to several proposed alterations in Everglades hydrology. These include several species of wading birds, the snail kite, Cape Sable seaside sparrow, Florida panther, white-tailed deer, American alligator, and American crocodile. ATLSS is an ecosystem landscape-modeling approach and uses Geographic Information System (GIS) vegetation data and existing hydrology models for South Florida to provide the basic landscape for these species. A method of pseudotopography provides estimates of water depths through time at 28 ?? 28-m resolution across the landscape of southern Florida. Hydrologic model output drives models of habitat and prey availability for the higher trophic level species. Spatially explicit, individual-based computer models simulate these species. ATLSS simulations can compare the landscape dynamic spatial pattern of the species resulting from different proposed water management strategies. Here we compare the predicted effects of one possible change in water management in South Florida with the base case of no change. Preliminary model results predict substantial differences between these alternatives in some biotic spatial patterns. ?? 1998 Springer-Verlag.

Florida↗
USGS2016

Estimation of time-variable fast flow path chemical concentrations for application in tracer-based hydrograph separation analyses

Mixing models are a commonly used method for hydrograph separation, but can be hindered by the subjective choice of the end-member tracer concentrations. This work tests a new variant of mixing model that uses high-frequency measures of two tracers and streamflow to separate total streamflow into water from slowflow and fastflow sources. The ratio between the concentrations of the two tracers is used to create a time-variable estimate of the concentration of each tracer in the fastflow end-member. Multiple synthetic data sets, and data from two hydrologically diverse streams, are used to test the performance and limitations of the new model (two-tracer ratio-based mixing model: TRaMM). When applied to the synthetic streams under many different scenarios, the TRaMM produces results that were reasonable approximations of the actual values of fastflow discharge (±0.1% of maximum fastflow) and fastflow tracer concentrations (±9.5% and ±16% of maximum fastflow nitrate concentration and specific conductance, respectively). With real stream data, the TRaMM produces high-frequency estimates of slowflow and fastflow discharge that align with expectations for each stream based on their respective hydrologic settings. The use of two tracers with the TRaMM provides an innovative and objective approach for estimating high-frequency fastflow concentrations and contributions of fastflow water to the stream. This provides useful information for tracking chemical movement to streams and allows for better selection and implementation of water quality management strategies.

Water Resources Research↗
USGS1996

Progress report on daily flow-routing simulation for the Carson River, California and Nevada

A physically based flow-routing model using Hydrological Simulation Program-FORTRAN (HSPF) was constructed for modeling streamflow in the Carson River at daily time intervals as part of the Truckee-Carson Program of the U.S. Geological Survey (USGS). Daily streamflow data for water years 1978-92 for the mainstem river, tributaries, and irrigation ditches from the East Fork Carson River near Markleeville and West Fork Carson River at Woodfords down to the mainstem Carson River at Fort Churchill upstream from Lahontan Reservoir were obtained from several agencies and were compiled into a comprehensive data base. No previous physically based flow-routing model of the Carson River has incorporated multi-agency streamflow data into a single data base and simulated flow at a daily time interval. Where streamflow data were unavailable or incomplete, hydrologic techniques were used to estimate some flows. For modeling purposes, the Carson River was divided into six segments, which correspond to those used in the Alpine Decree that governs water rights along the river. Hydraulic characteristics were defined for 48 individual stream reaches based on cross-sectional survey data obtained from field surveys and previous studies. Simulation results from the model were compared with available observed and estimated streamflow data. Model testing demonstrated that hydraulic characteristics of the Carson River are adequately represented in the models for a range of flow regimes. Differences between simulated and observed streamflow result mostly from inadequate data characterizing inflow and outflow from the river. Because irrigation return flows are largely unknown, irrigation return flow percentages were used as a calibration parameter to minimize differences between observed and simulated streamflows. Observed and simulated streamflow were compared for daily periods for the full modeled length of the Carson River and for two major subreaches modeled with more detailed input data. Hydrographs and statistics presented in this report describe these differences. A sensitivity analysis of four estimated components of the hydrologic system evaluated which components were significant in the model. Estimated ungaged tributary streamflow is not a significant component of the model during low runoff, but is significant during high runoff. The sensitivity analysis indicates that changes in the estimated irrigation diversion and estimated return flow creates a noticeable change in the statistics. The modeling for this study is preliminary. Results of the model are constrained by current availability and accuracy of observed hydrologic data. Several inflows and outflows of the Carson River are not described by time-series data and therefore are not represented in the model.

Open-File Report↗
USGS2007

Hydrologic Record Extension of Water-Level Data in the Everglades Depth Estimation Network (EDEN) Using Artificial Neural Network Models, 2000-2006

The Everglades Depth Estimation Network (EDEN) is an integrated network of real-time water-level gaging stations, ground-elevation models, and water-surface models designed to provide scientists, engineers, and water-resource managers with current (2000-present) water-depth information for the entire freshwater portion of the greater Everglades. The U.S. Geological Survey Greater Everglades Priority Ecosystem Science provides support for EDEN and the goal of providing quality assured monitoring data for the U.S. Army Corps of Engineers Comprehensive Everglades Restoration Plan. To increase the accuracy of the water-surface models, 25 real-time water-level gaging stations were added to the network of 253 established water-level gaging stations. To incorporate the data from the newly added stations to the 7-year EDEN database in the greater Everglades, the short-term water-level records (generally less than 1 year) needed to be simulated back in time (hindcasted) to be concurrent with data from the established gaging stations in the database. A three-step modeling approach using artificial neural network models was used to estimate the water levels at the new stations. The artificial neural network models used static variables that represent the gaging station location and percent vegetation in addition to dynamic variables that represent water-level data from the established EDEN gaging stations. The final step of the modeling approach was to simulate the computed error of the initial estimate to increase the accuracy of the final water-level estimate. The three-step modeling approach for estimating water levels at the new EDEN gaging stations produced satisfactory results. The coefficients of determination (R2) for 21 of the 25 estimates were greater than 0.95, and all of the estimates (25 of 25) were greater than 0.82. The model estimates showed good agreement with the measured data. For some new EDEN stations with limited measured data, the record extension (hindcasts) included periods beyond the range of the data used to train the artificial neural network models. The comparison of the hindcasts with long-term water-level data proximal to the new EDEN gaging stations indicated that the water-level estimates were reasonable. The percent model error (root mean square error divided by the range of the measured data) was less than 6 percent, and for the majority of stations (20 of 25), the percent model error was less than 1 percent.

Open-File Report↗
USGS1995

Water-quality data for the Santa Clara-Calleguas hydrologic unit, Ventura County, California, October 1989 through December 1993

More than 700 water samples were collected from 232 wells and 34 surface-water sites in the Santa Clara-Calleguas Hydrologic Unit, Ventura County, California, from October 1989 through December 1993 as part of the U.S. Geological Survey's Southern California Regional Aquifer-System Analysis study. Most samples were analyzed for major ions, nutrients, selected trace elements, oxygen-18, and deuterium. Selected samples were analyzed for one or more of the following isotopes: carbon-13/12, carbon-14, strontium-87/86, sulfur-34/32, and tritium. Other samples were analyzed for one or more of the following dissolved gases: hydrogen, methane, oxygen, and freon-11. Location of sampling sites is shown on maps and the results are presented in tables.

Open-File Report↗
USGS1985

Automated derivation of hydrologic basin characteristics from digital elevation model data

Digital elevation model (DEM) data in a raster format can be used to automatically derive the drainage characteristics of an area. A procedure has been designed that is capable of operating on matrices of elevation data having no algorithmically imposed size limit, while performing within the resolution and accuracy tolerances of the DEM data. Each cell is processed as the center of a 3- by 3-cell spatial window in the raster elevation data. If a cell is a local minimum in comparison with two of its non-adjacent neighbors, it is labeled as a drainage cell. The linkages of the drainage cells within user-specified distance and elevation thresholds are established in a separate process. The products of these processing steps are digital masks of the drainage cells and the watershed basins, both in raster format. A drainage cell mask derived using this procedure is useful in computing slope values for a raster data base. Slope has traditionally been calculated for each cell by fitting a plane through the eight nearest cells. However, if the terrain represented by these cells is V-shaped, such as a gully, a plane does not fit well; in fact, the desired slope value is the slope along the bottom of the gully, regardless of the steepness of the gully sides. The automated drainage process will label such a cell as a drainage cell, and its slope can then be computed from the elevation values of neighboring drainage cells.

Conference Paper↗
USGS2020

Impacts of grade control structure installations on hydrology and sediment transport as an adaptive management strategy

The goal of this research was to examine the impacts of Grade Control Structure (GCS) installations at the Heard Scout Pueblo (HSP) study site in the City of Phoenix, Arizona, USA. The study site is around a high-use trail system and is comprised of eroded and incised channels that conduct high flows and associated sediments into a residential neighborhood downstream, a noted stormwater control problem. We established baseline conditions associated with rainfall/runoff response before structures were installed so we could have some data for comparison afterwards. Innovative monitoring equipment, including video cameras and pressure transducers (to calculate discharge); digital terrain models, sediment samplers and sediment chains (to measure erosion and deposition); soil moisture sensors in monitoring wells (to document infiltration and potential recharge); and weather stations (to track temperature and relative humidity) were established and a small Unmanned Aircraft System (sUAS) survey was completed by July, 11, 2017, in time for the typical summer monsoon season which officially runs from June 15th to September 30th. Only one pre-GCS installation rain event incurred a significant flow event (October 13, 2018). Natural Channel Design (NCD), a landscape restoration company with decades of experience, was hired through a competitive bid process to develop a novel layout of ~30 GCS installations (sills, modified one-rock dams (ORD), and plugs, as well as a modified Zuni-bowl). The American Conservation Experience (ACE) hand-built the structures based on these designs in the main channel from November 13, 2018 through December 1, 2018. ACE built another ten structures in locations adjacent to the channel from January 15 through January 18, 2019. NCD worked with the landscape forensics to identify a historic channel and reinstate it using GCS. A surface-water model was also applied, using some of the baseline measurements (terrain and hydraulic conductivity) to track the flows of water and potential infiltration associated with rainfall events before GCS installation, to assist NCD in their design. The same model was applied using the installed GCS locations to simulate impacts of the structures on flow and infiltration. Our model was able to predict the slight reduction and delay in peak flows for small events and simulate infiltration, which was measured and occurred in the channel. Results demonstrated that structures could increase infiltration by ~15% over time. More data describing geomorphology and hydrology after repeated rainfall events will allow for increased analyses. Innovative monitoring, including the large‐scale particle image velocimetry (LSPIV) were invaluable to this research. Given the arid-land location and added drought conditions, the water levels were not high enough to compute, even using the continuous slope-area method, so discharge was calculated solely using the LSPIV. The careful redundancy of data acquisition is extremely important when studying dryland hydrology. Weather data indicated that the HSP GCS installations created roughly a three-degree microclimate cooling effect for at least two days following rainfall events, as compared with the untreated channel. The cooling was attributed to increased moisture, evaporation, and latent heat expulsion from the evaporation.

Arizona↗
USGS2017

Results of hydrologic monitoring of a landslide-prone hillslope in Portland’s West Hills, Oregon, 2006–2017

The West Hills of Portland, in the southern Tualatin Mountains, trend northwest along the west side of Portland, Oregon. These silt-mantled mountains receive significant wet-season precipitation and are prone to sliding during wet conditions, occasionally resulting in property damage or casualties. In an effort to develop a baseline for interpretive analysis of the groundwater response to rainfall, an automated monitoring system was installed in 2006 to measure rainfall, pore-water pressure, soil suction, soil-water potential, and volumetric water content at 15-minute intervals. The data show a cyclical pattern of groundwater and moisture content levels—wet from October to May and dry between June and September. Saturated soil conditions tend to last throughout the wet season. These data show the hydrologic response of the monitored area to rainfall and provide insight into the dynamics of rainfall-initiated landsliding. This report details the monitoring methods and presents data collected from January 10, 2006, through January 23, 2017.

Oregon↗
USGS2006

The Model Parameter Estimation Experiment (MOPEX): Its structure, connection to other international initiatives and future directions

The Model Parameter Estimation Experiment (MOPEX) is an international project aimed at developing enhanced techniques for the a priori estimation of parameters in hydrological models and in land surface parameterization schemes connected to atmospheric models. The MOPEX science strategy involves: database creation, a priori parameter estimation methodology development, parameter refinement or calibration, and the demonstration of parameter transferability. A comprehensive MOPEX database has been developed that contains historical hydrometeorological data and land surface characteristics data for many hydrological basins in the United States (US) and in other countries. This database is being continuously expanded to include basins from various hydroclimatic regimes throughout the world. MOPEX research has largely been driven by a series of international workshops that have brought interested hydrologists and land surface modellers together to exchange knowledge and experience in developing and applying parameter estimation techniques. With its focus on parameter estimation, MOPEX plays an important role in the international context of other initiatives such as GEWEX, HEPEX, PUB and PILPS. This paper outlines the MOPEX initiative, discusses its role in the scientific community, and briefly states future directions.

IAHS-AISH Publication↗
USGS2016

Hydrologic connectivity: Quantitative assessments of hydrologic-enforced drainage structures in an elevation model

Elevation data derived from light detection and ranging present challenges for hydrologic modeling as the elevation surface includes bridge decks and elevated road features overlaying culvert drainage structures. In reality, water is carried through these structures; however, in the elevation surface these features impede modeled overland surface flow. Thus, a hydrologically-enforced elevation surface is needed for hydrodynamic modeling. In the Delaware River Basin, hydrologic-enforcement techniques were used to modify elevations to simulate how constructed drainage structures allow overland surface flow. By calculating residuals between unfilled and filled elevation surfaces, artificially pooled depressions that formed upstream of constructed drainage structure features were defined, and elevation values were adjusted by generating transects at the location of the drainage structures. An assessment of each hydrologically-enforced drainage structure was conducted using field-surveyed culvert and bridge coordinates obtained from numerous public agencies, but it was discovered the disparate drainage structure datasets were not comprehensive enough to assess all remotely located depressions in need of hydrologic-enforcement. Alternatively, orthoimagery was interpreted to define drainage structures near each depression, and these locations were used as reference points for a quantitative hydrologic-enforcement assessment. The orthoimagery-interpreted reference points resulted in a larger corresponding sample size than the assessment between hydrologic-enforced transects and field-surveyed data. This assessment demonstrates the viability of rules-based hydrologic-enforcement that is needed to achieve hydrologic connectivity, which is valuable for hydrodynamic models in sensitive coastal regions. Hydrologic-enforced elevation data are also essential for merging with topographic/bathymetric elevation data that extend over vulnerable urbanized areas and dynamic coastal regions.

Journal of Coastal Research↗
USGS1988

Data for ground-water test holes in Fresno County, western San Joaquin Valley, California, June to August 1985

Twenty-four test holes were drilled from June 3 to August 29, 1985, in the western San Joaquin Valley, California, to provide information about groundwater hydraulics and geochemistry. The study area is in western Fresno County, west of the San Joaquin River, and east of the Coast Range. Lithologic, hydrologic, and geophysical data were collected from test holes drilled at two cluster sites and at 13 additional sites. Both cluster sites have five cased test holes. A sixth test hole was drilled at one of the cluster sites but was destroyed. Each of the 10 cased test holes is perforated at a different 10-ft depth interval. Six of the 13 additional test holes were also cased. Lithology logs were constructed from descriptions of cuttings and cores recovered during drilling. Geophysical logs were made of the deepest hole at each cluster site. Initial water level measurements were made at most sites. (Author 's abstract)

Open-File Report↗
USGS2015

Numerical computation of hurricane effects on historic coastal hydrology in Southern Florida

Introduction Numerical models are critical for assessing the effects of sea level rise (SLR), hurricanes, and storm surge on vegetation change in the Everglades National Park. The model must be capable of representing short-timescale hydrodynamics, salinity transport, and groundwater interaction. However, there is also a strong need to adapt these numerical models to hindcast past conditions in order to examine long-term effects on the distribution of vegetation that cannot be determined using only the modern record. Methods Based on parameters developed for a numerical model developed for the recent 1996 to 2004 period, a hindcast model was developed to represent sea level and water management for the period of 1926 to 1932, constrained by the limited hydrology and meteorology data available from the historic past. Realistic hurricane-wind and storm surge representations, required for the hindcast model, are based on information synthesized from modern storm data. A series of simulation scenarios with various hurricane representations inserted into both hindcast and recent numerical models were used to assess the utility of the storm representation in the model and compare the two simulations. Results The comparison of the hindcast and recent models showed differences in the hydrology patterns that are consistent with known differences in water delivery systems and sea level rise. A 30x lower-resolution spatially variable wind grid for the hindcast produced similar results to the original high-resolution full wind grid representation of the recent simulation. Storm effects on hydrologic patterns demonstrated with the simulations show hydrologic processes that could have a long-term effect on vegetation change. Conclusions The hindcast simulation estimated hydrologic processes for the 1926 to 1932 period. It shows promise as a simulator in long-term ecological studies to test hypotheses based on theoretical or empirical-based studies at larger landscape scales.

Florida↗
USGS1988

Evaluation of the flood hydrology in the Colorado Front Range using precipitation, streamflow, and paleoflood data for the Big Thompson River basin

A multidisciplinary study of precipitation and streamflow data and paleohydrologic studies of channel features was made to analyze the flood hydrology of foothill and mountain streams in the Front Range of Colorado, with emphasis on the Big Thompson River basin, because conventional hydrologic analyses do not adequately characterize the flood hydrology. In the foothills of Colorado, annual floodflows are derived from snowmelt at high elevations in the mountain regions, from rainfall at low elevation in the plains or plateau regions, or from a combination of rain falling on snow or mixed population hydrology. Above approximately 7,500 ft, snowmelt dominates; rain does not contribute to the flood potential. Regional flood-frequency relations were developed and compared with conventional flood-estimating technique results, including an evaluation of the magnitude and frequency of the probable maximum flood. Evaluation of streamflow data and paleoflood investigations provide an alternative for evaluating flood hydrology and the safety of dams. The study indicates the need for additional data collection and research to understand the complexities of the flood hydrology in mountainous regions, especially its effects on flood-plain management and the design of structures in the flood plain. (USGS)

Water-Resources Investigations Report↗
USGS2003

Environmental controls on water quality: Case studies from Battle Mountain mining district, north-central Nevada

The environmental controls on water quality were the focus of our study in a portion of the Battle Mountain mining district, north-central Nevada. Samples representing areas outside known mineralized areas, in undisturbed mineralized areas, and in mined areas were chemically and isotopically analyzed. The results are related to geologic, hydrologic, and climatic data. Streams in background areas outside the mineralized zones reflect normal weathering of volcanically derived rocks. The waters are generally dilute, slightly alkaline in pH, and very low in metals. As these streams flow into mineralized zones, their character changes. In undisturbed mineralized areas, discharge into streams of ground water through hydrologically conductive fractures can be traced with chemistry and, even more effectively, with sulfur isotopic composition of dissolved sulfate. Generally, these tracers are much more subtle than in those areas where mining has produced adits and mine-waste piles. The influence of drainage from these mining relicts on water quality is often dramatic, especially in unusually wet conditions. In one heavily mined area, we were able to show that the unusually wet weather in the winter and spring greatly degraded water quality. Addition of calcite to the acid, metalrich mine drainage raised the stream pH and nearly quantitatively removed the metals through coprecipitation and (or) adsorption onto oxyhydroxides. This paper is divided into four case studies used to demonstrate our results. Each addresses the role of geology, hydrology, mining activity and (or) local climate on water quality. Collectively, they provide a comprehensive look at the important factors affecting water quality in this portion of the Battle Mountain mining district.

Nevada↗
USGS2011

Development of a precipitation-runoff model to simulate unregulated streamflow in the South Fork Flathead River Basin, Montana

This report documents the development of a precipitation-runoff model for the South Fork Flathead River Basin, Mont. The Precipitation-Runoff Modeling System model, developed in cooperation with the Bureau of Reclamation, can be used to simulate daily mean unregulated streamflow upstream and downstream from Hungry Horse Reservoir for water-resources planning. Two input files are required to run the model. The time-series data file contains daily precipitation data and daily minimum and maximum air-temperature data from climate stations in and near the South Fork Flathead River Basin. The parameter file contains values of parameters that describe the basin topography, the flow network, the distribution of the precipitation and temperature data, and the hydrologic characteristics of the basin soils and vegetation. A primary-parameter file was created for simulating streamflow during the study period (water years 1967-2005). The model was calibrated for water years 1991-2005 using the primary-parameter file. This calibration was further refined using snow-covered area data for water years 2001-05. The model then was tested for water years 1967-90. Calibration targets included mean monthly and daily mean unregulated streamflow upstream from Hungry Horse Reservoir, mean monthly unregulated streamflow downstream from Hungry Horse Reservoir, basin mean monthly solar radiation and potential evapotranspiration, and daily snapshots of basin snow-covered area. Simulated streamflow generally was in better agreement with observed streamflow at the upstream gage than at the downstream gage. Upstream from the reservoir, simulated mean annual streamflow was within 0.0 percent of observed mean annual streamflow for the calibration period and was about 2 percent higher than observed mean annual streamflow for the test period. Simulated mean April-July streamflow upstream from the reservoir was about 1 percent lower than observed streamflow for the calibration period and about 4 percent higher than observed for the test period. Downstream from the reservoir, simulated mean annual streamflow was 17 percent lower than observed streamflow for the calibration period and 12 percent lower than observed streamflow for the test period. Simulated mean April-July streamflow downstream from the reservoir was 13 percent lower than observed streamflow for the calibration period and 6 percent lower than observed streamflow for the test period. Calibrating to solar radiation, potential evapotranspiration, and snow-covered area improved the model representation of evapotranspiration, snow accumulation, and snowmelt processes. Simulated basin mean monthly solar radiation values for both the calibration and test periods were within 9 percent of observed values except during the month of December (28 percent different). Simulated basin potential evapotranspiration values for both the calibration and test periods were within 10 percent of observed values except during the months of January (100 percent different) and February (13 percent different). The larger percent errors in simulated potential evaporation occurred in the winter months when observed potential evapotranspiration values were very small; in January the observed value was 0.000 inches and in February the observed value was 0.009 inches. Simulated start of melting of the snowpack occurred at about the same time as observed start of melting. The simulated snowpack accumulated to 90-100 percent snow-covered area 1 to 3 months earlier than observed snowpack. This overestimated snowpack during the winter corresponded to underestimated streamflow during the same period. In addition to the primary-parameter file, four other parameter files were created: for a "recent" period (1991-2005), a historical period (1967-90), a "wet" period (1989-97), and a "dry" period (1998-2005). For each data file of projected precipitation and air temperature, a single parameter file can be used to simulate a s

Montana;Idaho↗
USGS2013

A comprehensive evaluation of two MODIS evapotranspiration products over the conterminous United States: using point and gridded FLUXNET and water balance ET

Remote sensing datasets are increasingly being used to provide spatially explicit large scale evapotranspiration (ET) estimates. Extensive evaluation of such large scale estimates is necessary before they can be used in various applications. In this study, two monthly MODIS 1 km ET products, MODIS global ET (MOD16) and Operational Simplified Surface Energy Balance (SSEBop) ET, are validated over the conterminous United States at both point and basin scales. Point scale validation was performed using eddy covariance FLUXNET ET (FLET) data (2001–2007) aggregated by year, land cover, elevation and climate zone. Basin scale validation was performed using annual gridded FLUXNET ET (GFET) and annual basin water balance ET (WBET) data aggregated by various hydrologic unit code (HUC) levels. Point scale validation using monthly data aggregated by years revealed that the MOD16 ET and SSEBop ET products showed overall comparable annual accuracies. For most land cover types, both ET products showed comparable results. However, SSEBop showed higher performance for Grassland and Forest classes; MOD16 showed improved performance in the Woody Savanna class. Accuracy of both the ET products was also found to be comparable over different climate zones. However, SSEBop data showed higher skill score across the climate zones covering the western United States. Validation results at different HUC levels over 2000–2011 using GFET as a reference indicate higher accuracies for MOD16 ET data. MOD16, SSEBop and GFET data were validated against WBET (2000–2009), and results indicate that both MOD16 and SSEBop ET matched the accuracies of the global GFET dataset at different HUC levels. Our results indicate that both MODIS ET products effectively reproduced basin scale ET response (up to 25% uncertainty) compared to CONUS-wide point-based ET response (up to 50–60% uncertainty) illustrating the reliability of MODIS ET products for basin-scale ET estimation. Results from this research would guide the additional parameter refinement required for the MOD16 and SSEBop algorithms in order to further improve their accuracy and performance for agro-hydrologic applications.

Remote Sensing of Environment↗