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Lauren E. Hay

Publications and source records attributed to Lauren E. Hay.

At least 19 recordsLinked to original sources

Parameter estimation at the conterminous United States scale and streamflow routing enhancements for the National Hydrologic Model infrastructure application of the Precipitation-Runoff Modeling System (NHM-PRMS)

This report documents a three-part continental-scale calibration procedure and a new streamflow routing algorithm using the U.S. Geological Survey National Hydrologic Model (NHM) infrastructure along with an application of the Precipitation-Runoff Modeling System (PRMS). The traditional approach to hydrologic model calibration and evaluation, which relies on comparing observed and simulated streamflow, is not sufficient for accurately representing the non-streamflow parts of the water budget. If intermediate process variables computed by the hydrologic model are not examined, the variables could be characterized by parameter values that do not replicate those hydrological processes present in the physical system. In answer to this potential problem, alternative hydrologic process variables from the model (in addition to streamflow) are included in a calibration procedure applied to the conterminous United States (CONUS) domain. The three-part calibration procedure presented in this report considers volume (calibration by hydrologic response unit [byHRU]), timing (calibration by headwater watershed [byHW]), and measured streamflow [byHWobs]). The first part, byHRU, is considered a water-balance volume calibration that uses five alternative (non-streamflow) hydrologic quantities (runoff, actual evapotranspiration, recharge, soil moisture, and snow-covered area) as calibration targets for each hydrologic response unit (HRU). These alternative data products were derived, with error bounds, from multiple sources for each of the 109,951 HRUs in the NHM on time scales varying from annual to daily. The second part of the calibration, byHW, is considered a streamflow timing calibration that uses statistically based streamflow simulations developed using ordinary kriging for 7,265 headwater watersheds that had drainage areas of less than 3,000 square kilometers (1,158 square miles) across the CONUS. Two streamflow routing algorithms were tested in this byHW calibration: (1) continuity without attenuation of the flood pulse and (2) a new formulation of the Muskingum routing method, which was added to the PRMS as part of this study. The third part of the calibration, byHWobs, refines the model parameters using available measured streamflow using 1,417 streamgage locations. A multiple-objective, stepwise, automated calibration procedure was used to identify the optimal set of parameters for each calibration procedure. Using a variety of alternative datasets for calibration of the water budget provides users of the NHM-PRMS with improved initial parameters and helps alleviate the equifinality problem (getting the right answer for the wrong reason). Through a community effort, these alternative data products, with error bounds, can be used to improve and expand our understanding of hydrologic-process representation in models. The broader modeling community can use these data products, with error bounds, to calibrate and evaluate hydrologic models using more than streamflow.

Conterminous United States

Water resources on Guam—Potential impacts of and adaptive response to climate change

The goals of this joint U.S. Geological Survey, University of Hawaiʻi, University of Guam, University of Texas, and East-West Center study were to (1) provide basic understanding about water resources for U.S. Department of Defense installations on Guam and (2) assess the resulting effect of sea-level rise and a changing climate on freshwater availability, on the basis of historic information, sea-level rise projections, and global-climate model temperature and rainfall projections. Downscaled regional climate models, informed by a multimodel ensemble of global climate models provided projections of future climate conditions for Guam. These projected climate conditions provided input to surface-water and groundwater models developed for Guam’s hydrology. Guam’s water resources in a future climate condition (2080–99) are projected to diminish relative to the recent climate condition. Projected average temperature increases, and average rainfall decreases will lead to reduced streamflow in southern Guam and reduced groundwater recharge to the Northern Guam Lens Aquifer (NGLA). Projected average temperatures in southern Guam will increase about 5.8 °F (3.22 °C), overall rainfall will decrease about 7 percent, and streamflow will consequently decrease 18 percent in important areas of southern Guam. Similarly, across the NGLA, future groundwater recharge will be 19 percent less than estimated recharge from 2012. Reduced future streamflow will decrease water availability from the Fena Valley Reservoir; however, the reservoir is expected to be able to supply water at recent demand rates without lowering the reservoir level to the elevation of the water-supply intakes throughout the simulated period of a future climate. A twelve-year simulation indicates that the reservoir can supply about twice the 2018 demand without lowering the reservoir level to the water-supply intakes. By following mitigation strategies to increase reservoir water availability, the withdrawal rate can be increased by 1.7 percent if the water-supply intakes are lowered 5 ft, by 3.5 percent if the spillway height is raised 5 ft, and by 5.3 percent if both strategies are combined. Higher sea level and reduced future recharge will decrease water availability from the NGLA. An index of composite chloride concentration from production wells increases to 300 milligrams per liter (mg/L) for future climate conditions and at 2010 withdrawal rates, compared with 130 mg/L under historic climate conditions. Most of this increase is due to reduced recharge as higher (+3.2 ft) sea level only has a small role in increasing withdrawn water salinity. A redistributed withdrawal scenario in which the composite chloride concentration is 290 mg/L offers only slight improvement. Should future droughts reduce recharge proportionally to the decreases observed during historic droughts, the composite concentration would be about 900 mg/L, and more than 70 percent of Guam’s production wells would produce water with a composite concentration greater than 500 mg/L. Potential mitigation strategies for increasing the potable yield of the NGLA in a future climate include reducing depths of deep production wells and reducing the withdrawal rates in selected wells projected to have higher chloride concentrations. Simulations show both strategies are effective in lowering the composite concentration of the withdrawn water.

Scientific Investigations Report

Simulation of water availability in the Southeastern United States for historical and potential future climate and land-cover conditions

A study was conducted by the U.S. Geological Survey (USGS), in cooperation with the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperative (GCPO LCC) and the Department of the Interior Southeast Climate Adaptation Science Center, to evaluate the hydrologic response of a daily time step hydrologic model to historical observations and projections of potential climate and land-cover change for the period 1952–2099. The model simulations were used to compute the potential changes in hydrologic response and streamflow statistics across the Southeastern United States, using historical observations of climate and streamflow. Thirteen downscaled general circulation models with four representative concentration pathways were used to represent a range of potential future changes in climate (a total of 45 future simulations) from the Coupled Model Intercomparison Project Phase 5. The streamflow statistics were selected to describe streamflow conditions that may be most useful in defining the suitability for each river or stream to support sustaining populations of priority aquatic species across the GCPO LCC. An application of the Precipitation-Runoff Modeling System (included as part of the USGS National Hydrologic Model) was used to develop the hydrologic simulations. The results showed increases in air temperature across the study area, with the highest increases occurring in the northern part of the study area during July to September. The results showed a mix of increases and decreases in precipitation accumulation across the study area and across seasons, with decreases in precipitation accumulation across all seasons for the southwestern part of the study area. Actual evapotranspiration decreased for the southeastern part of the study area and increased for the northwestern part of the study area. The results showed general decreases in runoff across the study area, with increases in runoff in areas surrounding large metropolitan regions where potential future increases in impervious area occur. Results from a statistical analysis (Kolmogorov-Smirnov test) showed that the downscaled general circulation models generally have more skill in producing historical streamflow statistics in the duration and magnitude categories and less skill in producing historical streamflow statistics in the frequency, rate of change, and timing categories for this study area. The potential changes in the streamflow statistics and the results of the Kolmogorov-Smirnov test are available through the GCPO LCC Conservation Planning Atlas, an online science-based mapping platform built specifically for land managers and planners.

Alabama, Arkansas, Florida, Georgia, Illinois, Kan

GRACE storage change characteristics (2003–2016) over major surface basins and principal aquifers in the Conterminous United States

In this research, we characterized the changes in Gravity Recovery and Climate Experiment’s (GRACE) monthly total water storage anomaly (TWSA) in 18 surface basins and 12 principal aquifers in the Conterminous United States (CONUS) over 2003–2016. Regions with high variability in storage were identified. Ten basins and 4 aquifers showed significant change in storage. Eight surface basins and 8 aquifers were found to show decadal stability in storage. A pixel-based analysis of storage showed that New England basin and North Atlantic Coastal Plain aquifer showed the largest area under positive storage change. Whereas, the Lower Colorado basin and California aquifers showed largest area under negative change. This study found that historically wetter regions (with more storage) are becoming wetter and dryer regions (with less storage) are becoming dryer. Fourier analysis of the GRACE data showed that while all basins exhibited prominent annual periodicities, significant sub-annual and multi-annual cycles also exist in some basins. The storage turnover period was estimated to range between 6 to 12 months. The primary explanatory variable (PEV) of TWSA was identified for each region. This study provides new insights on several aspects of basin or aquifer storage that are important for understanding basin/aquifer hydrology.

Remote Sensing

Enhancement of a parsimonious water balance model to simulate surface hydrology in a glacierized watershed

The U.S. Geological Survey monthly water balance model (MWBM) was enhanced with the capability to simulate glaciers in order to make it more suitable for simulating cold region hydrology. The new model, MWBMglacier, is demonstrated in the heavily glacierized and ecologically important Copper River watershed in Southcentral Alaska. Simulated water budget components compared well to satellite‐based observations and ground measurements of streamflow, evapotranspiration, snow extent, and total water storage, with differences ranging from 0.2% to 7% of the precipitation flux. Nash Sutcliffe efficiency for simulated and observed streamflow was greater than 0.8 for six of eight stream gages. Snow extent matched satellite‐based observations with Nash Sutcliffe efficiency values of greater than 0.89 in the four Copper River ecoregions represented. During the simulation period 1949 to 2009, glacier ice melt contributed 25% of total runoff, ranging from 12% to 45% in different tributaries, and glacierized area was reduced by 6%. Statistically significant ( p < 0.05) decreasing and increasing trends in annual glacier mass balance occurred during the multidecade cool and warm phases of the Pacific Decadal Oscillation, respectively, reinforcing the link between climate perturbations and glacier mass balance change. The simulations of glaciers and total runoff for a large, remote region of Alaska provide useful data to evaluate hydrologic, cryospheric, ecologic, and climatic trends. MWBM glacier is a valuable tool to understand when, and to what extent, streamflow may increase or decrease as glaciers respond to a changing climate.

Journal of Geophysical Research F: Earth Surface

Do downscaled general circulation models reliably simulate historical climatic conditions?

The accuracy of statistically downscaled (SD) general circulation model (GCM) simulations of monthly surface climate for historical conditions (1950–2005) was assessed for the conterminous United States (CONUS). The SD monthly precipitation (PPT) and temperature (TAVE) from 95 GCMs from phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) were used as inputs to a monthly water balance model (MWBM). Distributions of MWBM input (PPT and TAVE) and output [runoff (RUN)] variables derived from gridded station data (GSD) and historical SD climate were compared using the Kolmogorov–Smirnov (KS) test For all three variables considered, the KS test results showed that variables simulated using CMIP5 generally are more reliable than those derived from CMIP3, likely due to improvements in PPT simulations. At most locations across the CONUS, the largest differences between GSD and SD PPT and RUN occurred in the lowest part of the distributions (i.e., low-flow RUN and low-magnitude PPT). Results indicate that for the majority of the CONUS, there are downscaled GCMs that can reliably simulate historical climatic conditions. But, in some geographic locations, none of the SD GCMs replicated historical conditions for two of the three variables (PPT and RUN) based on the KS test, with a significance level of 0.05. In these locations, improved GCM simulations of PPT are needed to more reliably estimate components of the hydrologic cycle. Simple metrics and statistical tests, such as those described here, can provide an initial set of criteria to help simplify GCM selection.

Earth Interactions

Characterization and evaluation of controls on post-fire streamflow response across western U.S. watersheds

This research investigates the impact of wildfires on watershed flow regimes, specifically focusing on evaluation of fire events within specified hydroclimatic regions in the western United States, and evaluating the impact of climate and geophysical variables on response. Eighty-two watersheds were identified with at least 10 years of continuous pre-fire daily streamflow records and 5 years of continuous post-fire daily flow records. Percent change in annual runoff ratio, low flows, high flows, peak flows, number of zero flow days, baseflow index, and Richards–Baker flashiness index were calculated for each watershed using pre- and post-fire periods. Independent variables were identified for each watershed and fire event, including topographic, vegetation, climate, burn severity, percent area burned, and soils data. Results show that low flows, high flows, and peak flows increase in the first 2 years following a wildfire and decrease over time. Relative response was used to scale response variables with the respective percent area of watershed burned in order to compare regional differences in watershed response. To account for variability in precipitation events, runoff ratio was used to compare runoff directly to PRISM precipitation estimates. To account for regional differences in climate patterns, watersheds were divided into nine regions, or clusters, through k-means clustering using climate data, and regression models were produced for watersheds grouped by total area burned. Watersheds in Cluster 9 (eastern California, western Nevada, Oregon) demonstrate a small negative response to observed flow regimes after fire. Cluster 8 watersheds (coastal California) display the greatest flow responses, typically within the first year following wildfire. Most other watersheds show a positive mean relative response. In addition, simple regression models show low correlation between percent watershed burned and streamflow response, implying that other watershed factors strongly influence response. Spearman correlation identified NDVI, aridity index, percent of a watershed's precipitation that falls as rain, and slope as being positively correlated with post-fire streamflow response. This metric also suggested a negative correlation between response and the soil erodibility factor, watershed area, and percent low burn severity. Regression models identified only moderate burn severity and watershed area as being consistently positively/negatively correlated, respectively, with response. The random forest model identified only slope and percent area burned as significant watershed parameters controlling response. Results will help inform post-fire runoff management decisions by helping to identify expected changes to flow regimes, as well as facilitate parameterization for model application in burned watersheds.

Hydrology and Earth System Sciences

Modelling surface-water depression storage in a Prairie Pothole Region

In this study, the Precipitation-Runoff Modelling System (PRMS) was used to simulate changes in surface-water depression storage in the 1,126-km 2 Upper Pipestem Creek basin located within the Prairie Pothole Region of North Dakota, USA. The Prairie Pothole Region is characterized by millions of small water bodies (or surface-water depressions) that provide numerous ecosystem services and are considered an important contribution to the hydrologic cycle. The Upper Pipestem PRMS model was extracted from the U.S. Geological Survey's (USGS) National Hydrologic Model (NHM), developed to support consistent hydrologic modelling across the conterminous United States. The Geospatial Fabric database, created for the USGS NHM, contains hydrologic model parameter values derived from datasets that characterize the physical features of the entire conterminous United States for 109,951 hydrologic response units. Each hydrologic response unit in the Geospatial Fabric was parameterized using aggregated surface-water depression area derived from the National Hydrography Dataset Plus, an integrated suite of application-ready geospatial datasets. This paper presents a calibration strategy for the Upper Pipestem PRMS model that uses normalized lake elevation measurements to calibrate the parameters influencing simulated fractional surface-water depression storage. Results indicate that inclusion of measurements that give an indication of the change in surface-water depression storage in the calibration procedure resulted in accurate changes in surface-water depression storage in the water balance. Regionalized parameterization of the USGS NHM will require a proxy for change in surface-storage to accurately parameterize surface-water depression storage within the USGS NHM.

North Dakota

Description of the National Hydrologic Model for use with the Precipitation-Runoff Modeling System (PRMS)

This report documents several components of the U.S. Geological Survey National Hydrologic Model of the conterminous United States for use with the Precipitation-Runoff Modeling System (PRMS). It provides descriptions of the (1) National Hydrologic Model, (2) Geospatial Fabric for National Hydrologic Modeling, (3) PRMS hydrologic simulation code, (4) parameters and estimation methods used to compute spatially and temporally distributed default values as required by PRMS, (5) National Hydrologic Model Parameter Database, and (6) model extraction tool named Bandit. The National Hydrologic Model Parameter Database contains values for all PRMS parameters used in the National Hydrologic Model. The methods and national datasets used to estimate all the PRMS parameters are described. Some parameter values are derived from characteristics of topography, land cover, soils, geology, and hydrography using traditional Geographic Information System methods. Other parameters are set to long-established default values and computation of initial values. Additionally, methods (statistical, sensitivity, calibration, and algebraic) were developed to compute parameter values on the basis of a variety of nationally-consistent datasets. Values in the National Hydrologic Model Parameter Database can periodically be updated on the basis of new parameter estimation methods and as additional national datasets become available. A companion ScienceBase resource provides a set of static parameter values as well as images of spatially-distributed parameters associated with PRMS states and fluxes for each Hydrologic Response Unit across the conterminuous United States.

Techniques and Methods

Quantifying uncertainty in simulated streamflow and runoff from a continental-scale monthly water balance model

One important component of continental-scale hydrologic modeling is quantifying the level of uncertainty in long-term hydrologic simulations and providing a range of possible simulated streamflow and/or runoff values for gaged and ungaged locations. In this paper, uncertainty was quantified for simulated streamflow and runoff generated from a monthly water balance model (MWBM) at 1575 streamgages and 109,951 hydrologic response units (HRUs), which span the conterminous United States (CONUS). A stochastic-approach, which incorporated the properties of modeled streamflow residuals back into the simulated model output, was used to create time series of upper and lower uncertainty intervals (UIs) around the simulated monthly time series. This approach was applied to an existing hydrologic regionalization implementation. Metrics used to evaluate the UIs across the CONUS (the coverage ratio, average width index, and interval skill score) indicated that on average the UIs were reliable, skillful, and sharp in being able to both contain measured streamflow observations and reduce estimates of uncertainty based on expected model predictions. These uncertainty evaluation metrics can complement each other in characterizing model skill and uncertainty over large-scale domains.

Advances in Water Resources

Fena Valley Reservoir watershed and water-balance model updates and expansion of watershed modeling to southern Guam

In 2014, the U.S. Geological Survey, in cooperation with the U.S. Department of Defense’s Strategic Environmental Research and Development Program, initiated a project to evaluate the potential impacts of projected climate-change on Department of Defense installations that rely on Guam’s water resources. A major task of that project was to develop a watershed model of southern Guam and a water-balance model for the Fena Valley Reservoir. The southern Guam watershed model provides a physically based tool to estimate surface-water availability in southern Guam. The U.S. Geological Survey’s Precipitation Runoff Modeling System, PRMS-IV, was used to construct the watershed model. The PRMS-IV code simulates different parts of the hydrologic cycle based on a set of user-defined modules. The southern Guam watershed model was constructed by updating a watershed model for the Fena Valley watersheds, and expanding the modeled area to include all of southern Guam. The Fena Valley watershed model was combined with a previously developed, but recently updated and recalibrated Fena Valley Reservoir water-balance model. Two important surface-water resources for the U.S. Navy and the citizens of Guam were modeled in this study; the extended model now includes the Ugum River watershed and improves upon the previous model of the Fena Valley watersheds. Surface water from the Ugum River watershed is diverted and treated for drinking water, and the Fena Valley watersheds feed the largest surface-water reservoir on Guam. The southern Guam watershed model performed “very good,” according to the criteria of Moriasi and others (2007), in the Ugum River watershed above Talofofo Falls with monthly Nash-Sutcliffe efficiency statistic values of 0.97 for the calibration period and 0.93 for the verification period (a value of 1.0 represents perfect model fit). In the Fena Valley watershed, monthly simulated streamflow volumes from the watershed model compared reasonably well with the measured values for the gaging stations on the Almagosa, Maulap, and Imong Rivers—tributaries to the Fena Valley Reservoir—with Nash-Sutcliffe efficiency values of 0.87 or higher. The southern Guam watershed model simulated the total volume of the critical dry season (January to May) streamflow for the entire simulation period within –0.54 percent at the Almagosa River, within 6.39 percent at the Maulap River, and within 6.06 percent at the Imong River. The recalibrated water-balance model of the Fena Valley Reservoir generally simulated monthly reservoir storage volume with reasonable accuracy. For the calibration and verification periods, errors in end-of-month reservoir-storage volume ranged from 6.04 percent (284.6 acre-feet or 92.7 million gallons) to –5.70 percent (–240.8 acre-feet or –78.5 million gallons). Monthly simulation bias ranged from –0.48 percent for the calibration period to 0.87 percent for the verification period; relative error ranged from –0.60 to 0.88 percent for the calibration and verification periods, respectively. The small bias indicated that the model did not consistently overestimate or underestimate reservoir storage volume. In the entirety of southern Guam, the watershed model has a “satisfactory” to “very good” rating when simulating monthly mean streamflow for all but one of the gaged watersheds during the verification period. The southern Guam watershed model uses a more sophisticated climate-distribution scheme than the older model to make use of the sparse climate data, as well as includes updated land-cover parameters and the capability to simulate closed depression areas. The new Fena Valley Reservoir water-balance model is useful as an updated tool to forecast short-term changes in the surface-water resources of Guam. Furthermore, the now spatially complete southern Guam watershed model can be used to evaluate changes in streamflow and recharge owing to climate or land-cover changes. These are substantial improvements to the previous models of the Fena Valley watershed and Reservoir. Datasets associated with this report are available as a U.S. Geological Survey data release (Rosa and Hay, 2017; DOI:10.5066/F7HH6HV4).

Scientific Investigations Report

Grand challenges for integrated USGS science — A workshop report

Executive Summary The U.S. Geological Survey (USGS) has a long history of advancing the traditional Earth science disciplines and identifying opportunities to integrate USGS science across disciplines to address complex societal problems. The USGS science strategy for 2007–2017 laid out key challenges in disciplinary and interdisciplinary arenas, culminating in a call for increased focus on a number of crosscutting science directions. Ten years on, to further the goal of integrated science and at the request of the Executive Leadership Team (ELT), a workshop with three dozen invited scientists spanning different disciplines and career stages in the Bureau convened on February 7–10, 2017, at the USGS John Wesley Powell Center for Analysis and Synthesis in Fort Collins, Colorado. The workshop focused on identifying “grand challenges” for integrated USGS science. Individual participants identified nearly 70 potential grand challenges before the workshop and through workshop discussions. After discussion, four overarching grand challenges emerged: Natural resource security, Societal risk from existing and emerging threats, Smart infrastructure development, and Anticipatory science for changing landscapes. Participants also identified a “comprehensive science challenge” that highlights the development of integrative science, data, models, and tools—all interacting in a modular framework—that can be used to address these and other future grand challenges: Earth Monitoring, Analyses, and Projections (EarthMAP) EarthMAP is our long-term vision for an integrated scientific framework that spans traditional scientific boundaries and disciplines, and integrates the full portfolio of USGS science: research, monitoring, assessment, analysis, and information delivery. The Department of Interior, and the Nation in general, have a vast array of information needs. The USGS meets these needs by having a broadly trained and agile scientific workforce. Encouraging and supporting cross-discipline engagement would position the USGS to tackle complex and multifaceted scientific and societal challenges in the 21st Century.

Open-File Report

The U.S. Geological Survey Monthly Water Balance Model Futures Portal

The U.S. Geological Survey Monthly Water Balance Model Futures Portal ( https://my.usgs.gov/mows/ ) is a user-friendly interface that summarizes monthly historical and simulated future conditions for seven hydrologic and meteorological variables (actual evapotranspiration, potential evapotranspiration, precipitation, runoff, snow water equivalent, atmospheric temperature, and streamflow) at locations across the conterminous United States (CONUS). The estimates of these hydrologic and meteorological variables were derived using a Monthly Water Balance Model (MWBM), a modular system that simulates monthly estimates of components of the hydrologic cycle using monthly precipitation and atmospheric temperature inputs. Precipitation and atmospheric temperature from 222 climate datasets spanning historical conditions (1952 through 2005) and simulated future conditions (2020 through 2099) were summarized for hydrographic features and used to drive the MWBM for the CONUS. The MWBM input and output variables were organized into an open-access database. An Open Geospatial Consortium, Inc., Web Feature Service allows the querying and identification of hydrographic features across the CONUS. To connect the Web Feature Service to the open-access database, a user interface—the Monthly Water Balance Model Futures Portal—was developed to allow the dynamic generation of summary files and plots based on plot type, geographic location, specific climate datasets, period of record, MWBM variable, and other options. Both the plots and the data files are made available to the user for download

Open-File Report

Spatiotemporal variability of snow depletion curves derived from SNODAS for the conterminous United States, 2004-2013

Assessment of water resources at a national scale is critical for understanding their vulnerability to future change in policy and climate. Representation of the spatiotemporal variability in snowmelt processes in continental-scale hydrologic models is critical for assessment of water resource response to continued climate change. Continental-extent hydrologic models such as the U.S. Geological Survey National Hydrologic Model (NHM) represent snowmelt processes through the application of snow depletion curves (SDCs). SDCs relate normalized snow water equivalent (SWE) to normalized snow covered area (SCA) over a snowmelt season for a given modeling unit. SDCs were derived using output from the operational Snow Data Assimilation System (SNODAS) snow model as daily 1-km gridded SWE over the conterminous United States. Daily SNODAS output were aggregated to a predefined watershed-scale geospatial fabric and used to also calculate SCA from October 1, 2004 to September 30, 2013. The spatiotemporal variability in SNODAS output at the watershed scale was evaluated through the spatial distribution of the median and standard deviation for the time period. Representative SDCs for each watershed-scale modeling unit over the conterminous United States ( n = 54,104) were selected using a consistent methodology and used to create categories of snowmelt based on SDC shape. The relation of SDC categories to the topographic and climatic variables allow for national-scale categorization of snowmelt processes.

Journal of the American Water Resources Associatio

Towards simplification of hydrologic modeling: Identification of dominant processes

The Precipitation–Runoff Modeling System (PRMS), a distributed-parameter hydrologic model, has been applied to the conterminous US (CONUS). Parameter sensitivity analysis was used to identify: (1) the sensitive input parameters and (2) particular model output variables that could be associated with the dominant hydrologic process(es). Sensitivity values of 35 PRMS calibration parameters were computed using the Fourier amplitude sensitivity test procedure on 110 000 independent hydrologically based spatial modeling units covering the CONUS and then summarized to process (snowmelt, surface runoff, infiltration, soil moisture, evapotranspiration, interflow, baseflow, and runoff) and model performance statistic (mean, coefficient of variation, and autoregressive lag 1). Identified parameters and processes provide insight into model performance at the location of each unit and allow the modeler to identify the most dominant process on the basis of which processes are associated with the most sensitive parameters. The results of this study indicate that: (1) the choice of performance statistic and output variables has a strong influence on parameter sensitivity, (2) the apparent model complexity to the modeler can be reduced by focusing on those processes that are associated with sensitive parameters and disregarding those that are not, (3) different processes require different numbers of parameters for simulation, and (4) some sensitive parameters influence only one hydrologic process, while others may influence many

Hydrology and Earth System Sciences

Parameter regionalization of a monthly water balance model for the conterminous United States

A parameter regionalization scheme to transfer parameter values from gaged to ungaged areas for a monthly water balance model (MWBM) was developed and tested for the conterminous United States (CONUS). The Fourier Amplitude Sensitivity Test, a global-sensitivity algorithm, was implemented on a MWBM to generate parameter sensitivities on a set of 109 951 hydrologic response units (HRUs) across the CONUS. The HRUs were grouped into 110 calibration regions based on similar parameter sensitivities. Subsequently, measured runoff from 1575 streamgages within the calibration regions were used to calibrate the MWBM parameters to produce parameter sets for each calibration region. Measured and simulated runoff at the 1575 streamgages showed good correspondence for the majority of the CONUS, with a median computed Nash–Sutcliffe efficiency coefficient of 0.76 over all streamgages. These methods maximize the use of available runoff information, resulting in a calibrated CONUS-wide application of the MWBM suitable for providing estimates of water availability at the HRU resolution for both gaged and ungaged areas of the CONUS.

Hydrology and Earth System Sciences

Accelerating advances in continental domain hydrologic modeling

In the past, hydrologic modeling of surface water resources has mainly focused on simulating the hydrologic cycle at local to regional catchment modeling domains. There now exists a level of maturity among the catchment, global water security, and land surface modeling communities such that these communities are converging toward continental domain hydrologic models. This commentary, written from a catchment hydrology community perspective, provides a review of progress in each community toward this achievement, identifies common challenges the communities face, and details immediate and specific areas in which these communities can mutually benefit one another from the convergence of their research perspectives. Those include: (1) creating new incentives and infrastructure to report and share model inputs, outputs, and parameters in data services and open access, machine-independent formats for model replication or reanalysis; (2) ensuring that hydrologic models have: sufficient complexity to represent the dominant physical processes and adequate representation of anthropogenic impacts on the terrestrial water cycle, a process-based approach to model parameter estimation, and appropriate parameterizations to represent large-scale fluxes and scaling behavior; (3) maintaining a balance between model complexity and data availability as well as uncertainties; and (4) quantifying and communicating significant advancements toward these modeling goals.

Water Resources Research