Contributions to the hydrology of the United States, 1929
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The Precipitation-Runoff Modeling System (PRMS) model of the U.S. Geological Survey was used to simulate the hydrologic effects of timber management in 11 small, upland drainage basins of the Coast Range in Oregon. The coefficients of determination for observed and simulated daily flow during the calibration periods ranged from 0.92 for the Flynn Creek Basin to 0.68 for the Priorli Creek Basin; percent error ranged from -0.25 for the Deer Creek Basin to -4.49 for the Nestucca River Basin. The coefficients of determination during the validation periods ranged from 0.90 for the Flynn Creek Basin to 0.66 for the Wind River Basin; percent error during the validation periods ranged from -0.91 for the Flynn Creek Basin to 22.3 for the Priorli Creek Basin. In addition to daily simulations, 42 storms were selected from the time-series periods in which the 11 basins were studied and used in hourly storm-mode simulations. Sources of simulation error included the quality of the input data, deficiencies in the PRMS model-algorithms, and the quality of parameter estimation. Times-series data from the Flynn Creek and Needle Branch Basins, collected during an earlier U.S. Geological Survey paired-watershed study, were used to evaluate the PRMS as a tool for predicting the hydrologic effects of timber-management practices. The Flynn Creek Basin remained forested and undisturbed during the data-collection period, while the Needle Branch Basin had been clearcut 82 percent at a midpoint during the period of data collection. Using the PRMS, streamflow at the Needle Branch Basin was simulated during the postlogging period using prelogging parameter values. Comparison of postlogging observed streamflow with the simulated data showed an increase in annual discharge volume of approximately 8 percent and a small increase in peak flows of from 1 to 2 percent. The simulated flows from the basins studied were generally insensitive to the number of hydrologic-response units used to replicate basin surface detail. The average number of hydrologic-response units used in the storm-period simulations was one-half the average number of hydrologic-response units used in the daily period simulations. With the exception of one basin, however, the coefficient of determination between observed and simulated daily flow differed by only 3 percent. Calibration and validation of the PRMS for 11 basins--that encompass a variety of forest, soil, and topographic conditions--provided regionalized parameter values. The parameter values assist the PRMS hydrologic simulations of other gaged and ungaged basins in the Coast Range with landscape conditions similar to those of the basins studied.
Despite recent interest, ecosystem services are not yet fully incorporated into private and public decisions about natural resource management. Cultural ecosystem services (CES) are among the most challenging of services to include because they comprise complex ecological and social properties and processes that make them difficult to measure, map or monetize. Like others, CES are vulnerable to landscape changes and unsustainable use. To date, the sustainability of services has not been adequately addressed and few studies have considered measures of service capacity and demand simultaneously. To facilitate sustainability assessments and management of CES, our study objectives were to (1) develop a spatially explicit framework for mapping the capacity of ecosystems to provide freshwater recreational fishing, an important cultural service, (2) map societal demand for freshwater recreational fishing based on license data and identify areas of potential overuse, and (3) demonstrate how maps of relative capacity and relative demand could be interfaced to estimate sustainability of a CES. We mapped freshwater recreational fishing capacity at the 12-digit hydrologic unit-scale in North Carolina and Virginia using a multi-indicator service framework incorporating biophysical and social landscape metrics and mapped demand based on fishing license data. Mapping of capacity revealed a gradual decrease in capacity eastward from the mountains to the coastal plain and that fishing demand was greatest in urban areas. When comparing standardized relative measures of capacity and demand for freshwater recreational fishing, we found that ranks of capacity exceeded ranks of demand in most hydrologic units, except in 17% of North Carolina and 5% of Virginia. Our GIS-based approach to view freshwater recreational fishing through an ecosystem service lens will enable scientists and managers to examine (1) biophysical and social factors that foster or diminish cultural ecosystem services delivery, (2) demand for cultural ecosystem services relative to their capacity, and (3) ecological pressures like potential overuse that affect service sustainability. Ultimately, we expect such analyses to inform decision-making for freshwater recreational fisheries and other cultural ecosystem services.
A stream classification and associated datasets were developed for the Apalachicola-Chattahoochee-Flint River Basin to support biological modeling of species response to climate change in the southeastern United States. The U.S. Geological Survey and the Department of the Interior’s National Climate Change and Wildlife Science Center established the Southeast Regional Assessment Project (SERAP) which used downscaled general circulation models to develop landscape-scale assessments of climate change and subsequent effects on land cover, ecosystems, and priority species in the southeastern United States. The SERAP aquatic and hydrologic dynamics modeling efforts involve multiscale watershed hydrology, stream-temperature, and fish-occupancy models, which all are based on the same stream network. Models were developed for the Apalachicola-Chattahoochee-Flint River Basin and subbasins in Alabama, Florida, and Georgia, and for the Upper Roanoke River Basin in Virginia. The stream network was used as the spatial scheme through which information was shared across the various models within SERAP. Because these models operate at different scales, coordinated pair versions of the network were delineated, characterized, and parameterized for coarse- and fine-scale hydrologic and biologic modeling. The stream network used for the SERAP aquatic models was extracted from a 30-meter (m) scale digital elevation model (DEM) using standard topographic analysis of flow accumulation. At the finer scale, reaches were delineated to represent lengths of stream channel with fairly homogenous physical characteristics (mean reach length = 350 m). Every reach in the network is designated with geomorphic attributes including upstream drainage basin area, channel gradient, channel width, valley width, Strahler and Shreve stream order, stream power, and measures of stream confinement. The reach network was aggregated from tributary junction to tributary junction to define segments for the benefit of hydrological, soil erosion, and coarser ecological modeling. Reach attributes are summarized for each segment. In six subbasins segments are assigned additional attributes about barriers (usually impoundments) to fish migration and stream isolation. Segments in the six sub-basins are also attributed with percent urban area for the watershed upstream from the stream segment for each decade from 2010–2100 from models of urban growth. On a broader scale, for application in a coarse-scale species-response model, the stream-network information is aggregated and summarized by 256 drainage subbasins (Hydrologic Response Units) used for watershed hydrologic and stream-temperature models. A model of soil erodibility based on the Revised Universal Soil Loss Equation also was developed at this scale to parameterize a model to evaluate stream condition. The reach-scale network was classified using multivariate clustering based on modeled channel width, valley width, and mean reach gradient as variables. The resulting classification consists of a 6-cluster and a 12-cluster classification for every reach in the Apalachicola-Chattahoochee-Flint Basin. We present an example of the utility of the classification that was tested using the occurrence of two species of darters and two species of minnows in the Apalachicola-Chattahoochee-Flint River Basin, the blackbanded darter and Halloween darter, and the bluestripe shiner and blacktail shiner.
Basic hydrologic data available in the field offices of the U. S. Geological Survey and reports issued by the Survey furnish evidence that saline water (defined in this report as water containing more than 1,000 parts per million of dissolved solids) is available under diverse geologic and hydrologic conditions throughout the United States. The number of areas in which undeveloped supplies of fresh water are available has diminished considerably with the rapid growth of industries and population in the past decade. Many areas previously considered to have relatively unlimited water resources have reached the point at which water-supply shortages exist or are threatened.
Hydrologic research and operations make extensive use of streamflow time series. In most applications, these time series are estimated from rating curves, which relate flow to some easy-to-measure surrogate, typically stage. The conventional stage-discharge rating takes the form of a segmented power law, with one segment for each hydrologic control at the stream gauge. However, these ratings are notoriously difficult to estimate with numerical methods, so that most are still developed manually. A few automated algorithms have emerged, but their use is sporadic, and their relative merits have not been rigorously assessed. One recently developed approach, the generalized power-law, avoids the segmenting problem by representing the power-law exponent as a Gaussian process. On the one hand, this representation is more flexible and easier to fit, but its flexibility might allow unrealistic solutions, so it needs to be tested under a range of conditions to assess its operational viability. This study evaluates the generalized power-law rating curve model by applying it to observations from 180 streams in Iceland, Sweden, and the United States. Overall, the model proved flexible and computationally robust, generating convincing rating curves across a range of geographic settings and was comparable to curves generated by a segmented rating model. Lastly, we propose a model-selection algorithm based on information theory to help identify the best rating curve model for a particular stream gauge.
The U.S. Geological Survey’s Precipitation-Runoff Modeling System (PRMS) is widely used to simulate the effects of climate, topography, land cover, and soils on landscape-level hydrologic response and streamflow. This study developed, calibrated, and assessed a PRMS model that simulates near-native or naturalized streamflow conditions in the Upper Rio Grande Basin. A PRMS model framework of 1,021 hydrologic response units was constructed for the basin. Subbasins within the larger Upper Rio Grande Basin range from snow-dominated northern basins to monsoon driven southern basins. The 1,021 hydrologic response units were grouped into 133 subareas within the basin, and solar radiation and potential evapotranspiration data were used to calibrate corresponding PRMS parameters in each subarea independently. Nine subbasins with streamgages distributed across the basin were identified as “near-native” subbasins, or those basins with low anthropogenic disturbance. Model parameters that affect streamflow were calibrated for the near-native subbasins, and the calibrated parameters were distributed to the remaining hydrologic response units on the basis of terrain, soil, and vegetation conditions linked to a distribution and weighting algorithm developed for this study. The parameter distribution method was validated in three of the nine near-native subbasins. Calibration results demonstrated that the PRMS model developed in this study with distributed model parameters for the entire Upper Rio Grande Basin was successful in applying local information to improve model performance over the National Hydrologic Model, and that the new model is appropriate to use to simulate near-native conditions throughout the basin. The result is a model that can simulate naturalized flow and other variables that affect the water budget (including soil moisture, evapotranspiration, recharge) at the daily time step for current and future climate conditions, and that can also be used in conjunction with other models developed for the basin.
Atmospheric rivers (ARs) significantly influence precipitation and hydrologic variability in many areas of the world, including the western United States. As ARs are increasingly recognized by the research community and the public, there is a need to more precisely quantify and communicate their hydrologic impacts, which can vary from hazardous to beneficial depending on location and on the atmospheric and land surface conditions prior to and during the AR. This study leverages 33 years of atmospheric and hydrologic data for the western United States to 1) identify how water vapor amount, wind direction and speed, temperature, and antecedent soil moisture conditions influence precipitation and hydrologic responses (runoff, recharge, and snowpack) using quantile regression and 2) identify differences in hydrologic response types and magnitudes across the study region. Results indicate that water vapor amount serves as a primary control on precipitation amounts. Holding water vapor constant, precipitation amounts vary with wind direction, depending on location, and are consistently greater at colder temperatures. Runoff efficiencies further covary with temperature and antecedent soil moisture, with precipitation falling as snow and greater available water storage in the soil column mitigating flood impacts of large AR events. This study identifies the coastal and maritime mountain ranges as areas with the greatest potential for hazardous flooding and snowfall impacts. This spatially explicit information can lead to better understanding of the conditions under which ARs of different precipitation amounts are likely to be hazardous at a given location.
Climate change and climate variability, population growth, and land use change drive the need for new hydrologic knowledge and understanding. In the mountainous West and other similar areas worldwide, three pressing hydrologic needs stand out: first, to better understand the processes controlling the partitioning of energy and water fluxes within and out from these systems; second, to better understand feedbacks between hydrological fluxes and biogeochemical and ecological processes; and, third, to enhance our physical and empirical understanding with integrated measurement strategies and information systems. We envision an integrative approach to monitoring, modeling, and sensing the mountain environment that will improve understanding and prediction of hydrologic fluxes and processes. Here extensive monitoring of energy fluxes and hydrologic states are needed to supplement existing measurements, which are largely limited to streamflow and snow water equivalent. Ground‐based observing systems must be explicitly designed for integration with remotely sensed data and for scaling up to basins and whole ranges.
The U.S. Geological Survey 's precipitation-runoff modeling system was tested using 2 year 's data for the daily mode and 17 storms for the storm mode from a basin in southeastern Montana. Two hydrologic response unit delineations were studied. The more complex delineation did not provide superior results. In this application, the optimum numbers of hydrologic response units were 16 and 18 for the two alternatives. The first alternative with 16 units was modified to facilitate interfacing with the storm mode. A parameter subset was defined for the daily mode using sensitivity analysis. Following optimization, the simulated hydrographs approximated the observed hydrograph during the first year, a year of large snowfall. More runoff was simulated than observed during the second year. There was reasonable correspondence between the observed snowpack and the simulated snowpack the first season but poor the second. More soil moisture was withdrawn than was indicated by soil moisture observations. Optimization of parameters in the storm mode resulted in much larger values than originally estimated, commonly larger than published values of the Green and Ampt parameters. Following optimization, variable results were obtained. The results obtained are probably related to inadequate representation of basin infiltration characteristics and to precipitation variability. (USGS)
Hydrologic-landscape regions in the United States were delineated by using geographic information system (GIS) tools combined with principal components and cluster analyses. The GIS and statistical analyses were applied to land-surface form, geologic texture (permeability of the soil and bedrock), and climate variables that describe the physical and climatic setting of 43,931 small (approximately 200 km 2 ) watersheds in the United States. (The term “watersheds” is defined in this paper as the drainage areas of tributary streams, headwater streams, and stream segments lying between two confluences.) The analyses grouped the watersheds into 20 noncontiguous regions based on similarities in land-surface form, geologic texture, and climate characteristics. The percentage of explained variance (R-squared value) in an analysis of variance was used to compare the hydrologic-landscape regions to 19 square geometric regions and the 21 U.S. Environmental Protection Agency level-II ecoregions. Hydrologic-landscape regions generally were better than ecoregions at delineating regions of distinct land-surface form and geologic texture. Hydrologic-landscape regions and ecoregions were equally effective at defining regions in terms of climate, land cover, and water-quality characteristics. For about half of the landscape, climate, and water-quality characteristics, the R-squared values of square geometric regions were as high as hydrologic-landscape regions or ecoregions.
Variability and trends in water-year runoff efficiency (RE) — computed as the ratio of water-year runoff (streamflow per unit area) to water-year precipitation — in the conterminous United States (CONUS) are examined for the 1951 through 2012 period. Changes in RE are analyzed using runoff and precipitation data aggregated to United States Geological Survey 8-digit hydrologic cataloging units (HUs). Results indicate increases in RE for some regions in the north-central CONUS and large decreases in RE for the south-central CONUS. The increases in RE in the north-central CONUS are explained by trends in climate, whereas the large decreases in RE in the south-central CONUS likely are related to groundwater withdrawals from the Ogallala aquifer to support irrigated agriculture.
Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing tidal marsh management decisions at the Cape May and Supawna Meadows National Wildlife Refuges in New Jersey. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of 13 marsh management units within the refuges and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that would be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per marsh management unit, that would maximize total management benefits at different cost constraints at the refuge scale. Results indicated that, for the objectives and actions considered here, total management benefits may increase consistently up to approximately $ 785,000, but that further expenditures may yield diminishing return on investment. Management actions in optimal portfolios at total costs less than $ 785,000 included applying sediment to the marsh surface (thin layer deposition) in seven marsh management units, controlling the invasive reed Phragmites australis in four marsh management units, remediating hydrologic alterations in two marsh management units, and planting native vegetation in one marsh management unit. The management benefits were derived from expected improvements in the capacity for marsh elevation to keep pace with sea-level rise, increases in numbers of spiders (as an indicator of trophic health) and tidal marsh obligate birds, and increased cover of native vegetation. The prototype presented here provides a framework for decision making at the Cape May and Supawna Meadows National Wildlife Refuges that can be updated as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuges.
A model was developed to simulate inflow to reservoirs and watershed runoff to streams during three high-flow events between September 2004 and June 2006 for the main-stem subbasin of the Delaware River draining to Trenton, N.J. The model software is a modified version of the U.S. Geological Survey (USGS) Precipitation-Runoff Modeling System (PRMS), a modular, physically based, distributed-parameter modeling system developed to evaluate the impacts of various combinations of precipitation, climate, and land use on surface-water runoff and general basin hydrology. The PRMS model simulates time periods associated with main-stem flooding that occurred in September 2004, April 2005, and June 2006 and uses both daily and hourly time steps. Output from the PRMS model was formatted for use as inflows to a separately documented reservoir and riverrouting model, the HEC-ResSim model, developed by the U.S. Army Corps of Engineers Hydrologic Engineering Center to evaluate flooding. The models were integrated through a graphical user interface. The study area is the 6,780 square-mile watershed of the Delaware River in the states of Pennsylvania, New Jersey, and New York that drains to Trenton, N.J. A geospatial database was created for use with a geographic information system to assist model discretization, determine land-surface characterization, and estimate model parameters. The USGS National Elevation Dataset at 100-meter resolution, a Digital Elevation Model (DEM), was used for model discretization into streams and hydrologic response units. In addition, geospatial processing was used to estimate initial model parameters from the DEM and other data layers, including land use. The model discretization represents the study area using 869 hydrologic response units and 452 stream segments. The model climate data for point stations were obtained from multiple sources. These sources included daily data for 22 National Weather Service (NWS) Cooperative Climate Station network stations, hourly data for 15 stations from the National Climatic Data Center, hourly data for 1 station from the NWS Middle Atlantic River Forecast Center records, and daily and hourly data for 7 stations operated by the New York City Department of Environmental Protection. The NWS Multisensor Precipitation Estimate data set for 2001-2007 was used for computing daily precipitation for the model and for computing hourly precipitation for storm simulation periods. Calibration of the PRMS model included regression and optimization algorithms, as well as manual adjustments of model parameters. The general goal of the calibration procedure was to minimize the difference between discharge measured at USGS streamgages and the corresponding discharge simulated by the model. Daily streamflow data from 35 USGS streamgages were used in model calibration. The streamflow data represent areas draining from 20.2 to 6,780 square miles. The PRMS model simulates reservoir inflow and watershed runoff for use as input into HECResSim for the purpose of evaluating and comparing the effects of different watershed conditions on main-stem flooding in the Delaware River watershed draining to Trenton, N.J. The PRMS model is useful as a planning tool to simulate the effects of land-use changes and different antecedent conditions on local runoff and reservoir inflow and, as input to the HEC-ResSim model, on flood flows in the main stem of the Delaware River.
Spatial and temporal variability in the frequency, duration, and severity of hydrological droughts across the conterminous United States (CONUS) was examined using monthly mean streamflow measured at 872 sites from 1951 through 2014. Hydrological drought is identified as starting when streamflow falls below the 20th percentile streamflow value for 3 consecutive months and ending when streamflow remains above the 20th percentile streamflow value for 3 consecutive months. Mean drought frequency for all aggregated ecoregions in CONUS is 16 droughts per 100 years. Mean drought duration is 5 months, and mean drought severity is 39 percent on a scale ranging from 0 percent to 100 percent (with 100% being the most severe). Hydrological drought frequency is highest in the Western Mountains aggregated ecoregion and lowest in the Eastern Highlands, Northeast, and Southeast Plains aggregated ecoregions. Hydrological drought frequencies of 17 or more droughts per 100 years were found for the Central Plains, Southeast Coastal Plains, Western Mountains, and Western Xeric aggregated ecoregions. Drought duration and severity indicate spatial variability among the sites, but unlike drought frequency, do not show coherent spatial patterns. A comparison of an older period (1951–82) with a recent period (1983–2014) indicates few sites have statistically significant changes in drought frequency, drought duration, or drought severity at a 95-percent confidence level.