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Richard G. Niswonger

Publications and source records attributed to Richard G. Niswonger.

At least 19 recordsLinked to original sources
USGS2026

Assessing future hydrologic extremes using an integrated hydrology and river operations model in the Russian River watershed

Study region The Russian River watershed, situated in coastal, northern California, experiences hydrologic extremes, including periodic droughts and flooding. Water managers are working to maintain sustainable water supplies and environmental flows, while mitigating flood risks. Study focus This paper introduces an integrated hydrology and river operations model for the Russian River watershed. This model is distinct from models in previous studies because it represents surface-groundwater interactions and uses climate forcings to estimate dynamic water use demands that are superimposed onto both reservoir operations and water supply constraints. The model was used to examine three historical (1990–2015) and eight future (2016–2099) water use and climate change scenarios. New hydrological insights for the region The direct connection between streams and aquifers facilitated both annual aquifer replenishment by high winter streamflows and streamflow depletion by groundwater wells (19 % of pumped groundwater in alluvial aquifers from stream leakage) during critical low flow periods. Simulated streamflow changes included 59 % longer and 54 % more severe streamflow droughts, 26 % lower seasonal low streamflows, and up to 125 % higher peak streamflows, averaged over future climate and water use scenarios, suggesting increased future flood and water availability risks. Results showed the importance of reservoir operations for mitigating the impacts of increased hydroclimatic volatility, despite a decrease in reservoir reliability at Lake Mendocino, suggesting that reservoir management may be used to decrease future risks.

California↗
USGS2025

Harmonization of a water withdrawal dataset for the conterminous United States

The U.S. Geological Survey is developing nationally consistent water-use modeling approaches to replace previous methods relying on locally specific reported and estimated data. These national assessments require datasets that incorporate water withdrawal variability across the United States and over long periods. However, source data often have unclear definitions, missing or varied units, differing temporal resolutions, varied data quality, and inconsistent formats, which hinder automation and require individualized processing. The public-supply datasets described in this paper were used in machine learning models to estimate annual and monthly public-supply water use for 2000–2020 for the conterminous United States (CONUS) and in a model to estimate public-supply deliveries. Public-supply withdrawal data were acquired for the CONUS and the District of Columbia; however, 11 states had annual data for only 1 year, and 10 states had no monthly data. Annual withdrawal data were acquired for 81% of public-supply water service areas, and monthly withdrawal data were acquired for 47% for at least 1 year from 2000 to 2020. These datasets and methods provide the most comprehensive collection of reported public-supply withdrawals to date and can be used by water-use managers, the scientific community, and the broader public. The extensive data processing described herein can be applicable to datasets representing other categories of water use.

conterminous United States↗
USGS2025

Water withdrawal and consumption trends for thermoelectric-power plants in the conterminous United States, 2008-2020

Freshwater-using utility-scale thermoelectric (TE) plant water-use estimates were evaluated for annual trends from 2008 to 2020 across the conterminous United States (CONUS) and within hydrologic regions. Overall, TE water withdrawal and consumption trends declined across CONUS by 14,335 and 278 million liters/day, respectively. Decreasing water withdrawal and consumption trends for TE plants are driven largely by switching from coal-fired plants to other generation technologies. TE plant cooling system technology has also changed, with large declining trends for TE plants using once-through cooling systems and small increasing consumption trends for TE plants using recirculating tower cooling systems. Fifteen hydrologic regions have decreasing trends in withdrawals and consumption. The largest decreases are for coal-fired plants using once-through freshwater cooling systems in the Great Lakes and Ohio hydrologic regions. Natural gas combined cycle plants with recirculating tower cooling systems have increased water consumption trends across most of the CONUS hydrologic regions. Some TE plants with recirculating tower or once-through cooling systems withdraw water volumes that on average are close to or exceed average simulated streamflows. Most of these situations occur in the central and eastern U.S., potentially leading to water availability issues among competing water needs, ecosystem impacts from thermal pollution, and power generation constraints.

conterminous United States↗
USGS2025

Public supply water delivery analysis and estimation for the conterminous United States

Public supply water withdrawals represent 14% of all withdrawals in the conterminous United States (CONUS), supplying approximately 87% of the population with fresh water. Deliveries for public water supply are crucial for associating water use amounts with populations because they often differ from total withdrawals due to wholesales, transfers, losses, and other factors. Understanding these differences helps identify the drivers for each type of delivery. The goal of this study was to compile all available public water supply delivery data for the CONUS and develop a data-driven model to estimate deliveries for all water service areas within the CONUS. Annual deliveries were estimated between 2010 and 2020, encompassing total water deliveries; combined commercial, industrial, and institutional deliveries (CII); and domestic deliveries. Data were compiled for 2,744 water service areas to produce the most comprehensive public water supply delivery data set for the CONUS to date. Three ensemble modeling approaches were developed to estimate total, CII, and domestic per capita (DPC) deliveries using a gradient boosted regression tree modeling approach. Estimates of daily domestic and CII per capita deliveries were generated from these models for approximately 18,800 water service areas, covering most public water systems in the CONUS. Domestic delivery was found to be lowest in the midwestern region and higher in the southern and southwest regions of the United States. Results indicate that climate and land use can be associated with regional differences in DPC delivery. Population metrics and land use were identified as significant contributors to CII delivery estimates.

conterminous United States↗
USGS2025

Updating and recalibrating the integrated Santa Rosa Plain Hydrologic Model to assess stream depletion and to simulate future climate and management scenarios in Santa Rosa, Sonoma County, California

The Santa Rosa Plain Hydrologic Model (SRPHM) was developed and published in 2014 through a collaboration between the U.S. Geological Survey (USGS) and Sonoma Water to analyze the hydrologic system in the Santa Rosa Plain watershed, help meet the increasing demand for fresh water, and prepare for future uncertainties in water resources. The original model simulated hydrological conditions and water use from water years 1975 to 2010. Recently (2023), the USGS, in cooperation with Sonoma Water and the California State Water Resources Control Board, updated the SRPHM model to extend its simulation period to the end of the 2018 calendar year, incorporate new estimates of rural and agricultural water use, and use efficient input format for climate variables. The updated model was recalibrated, and evaluation of the new model calibration is included in this report. This report presents the results of comparing the hydraulic heads, streamflow, and groundwater budget simulated by the updated model with those generated by the original model and observed data. The main difference in the simulated budget between the original and updated SRPHM is the estimates of agricultural pumping, rural domestic pumping, and return flow generated from rural water use that was not simulated in the original model. The revised agricultural pumping is simulated using the agricultural package, which constrains pumping to available groundwater. The use of the agricultural package leads to a more realistic estimation of agricultural water use, with revised agricultural pumping being one-third less than that in the original model. The revised rural pumping is about half of the pumping in the original model because of using detailed parcel data to estimate population density in rural areas instead of coarse census tracts. Overall, average total inflows for water years 2006–10 simulated by the updated model were about 2 percent less than the original model, and the average total updated outflows were nearly 5 percent less than the original model. The updated model was then used to generate stream depletion maps, simulate climate change scenarios during 2019–99, and simulate water rights allocation using the Model for Decision Support in Integrated River Basin Management (MODSIM). The results from simulating eight future climate scenarios indicated either an increase in groundwater storage or no significant change in the next 80 years, along with an increase in recharge, an increase in actual evapotranspiration in six out of eight climate projections, and an increase in surface runoff. The increases in the simulated future groundwater storage, recharge, evapotranspiration, and runoff in most climate projections are mainly driven by the projected increase in precipitation in most of the future climate scenarios. The updated model also was used to test a pilot case study demonstrating water-resource allocation among different users with different water rights using the integrated MODSIM-Groundwater and Surface-Water Flow Model (GSFLOW) platform. The updated SRPHM serves as a valuable tool for analyzing historical and future hydrologic conditions in the Santa Rosa Plain watershed and preparing for future uncertainties.

California↗
USGS2025

Simulation of the impacts of projected climate change on groundwater resources in the urban, semiarid Yucaipa Valley watershed, southern California using an integrated hydrologic model

Managing water resources in semiarid watersheds is challenging due to limited supply and uncertain future climate conditions. This paper examines the impact of future climate changes on an urban watershed in southern California using an integrated hydrologic model. GSFLOW modeling software is used to simulate the nonlinear relationships between climate trends and precipitation partitioning into ET, runoff, and subsurface storage. Four global circulation models (GCMs), each with two greenhouse-gas scenarios, RCP45 and RCP85 are used to project future climate conditions. GCMs include the CanESM2, CNRM-CM5, HadGEM2-ES, and MIROC5 models. The model's simulated hydrologic conditions are compared with historical data to assess changes in water budgets and groundwater supply. Results indicate decreased groundwater storage in most scenarios due to increased natural evapotranspiration, vegetation consumptive use, and streamflow out of the watershed. Only scenarios with substantially increased future precipitation show increased groundwater storage. The study also highlights increased future aridity despite the rise in precipitation and large precipitation events forecast by GCMs, which increase the risk of urban floods and decrease stream leakage and water available to vegetation.

California↗
USGS2025

Automating physics-based models to estimate thermoelectric-power water use

Thermoelectric (TE) power plants withdraw more water than any other sector of water use in the United States and consume water at rates that can be significant especially in water-stressed regions. Historical TE water-use data have been inconsistent, incomplete, or discrepant, resulting in an increased research focus on improving the accuracy and availability of TE water-use data using modeling approaches. This paper describes and benchmarks new code that was developed to automate and update a physics-based TE water use model that was previously published. Utilizing the automated physics-based model, monthly TE-power water withdrawal and consumption were calculated for a total of 1341 TE power plants for the 2008–2020 historical reanalysis. The updated and automated physics-based thermoelectric-power water-use model provides spatially and temporally relevant TE water-use estimates that are consistent, reproducible, transparent, and can be generated efficiently for water-using, utility-scale TE-power plants across conterminous United States (CONUS).

Environmental Modelling and Software↗
USGS2025

Estimating irrigation consumptive use for the conterminous United States: Coupling satellite-sourced estimates of actual evapotranspiration with a national hydrologic model

Irrigation consumptive use is crucial information for water resource management and this information is generally not available for most regional and national assessments. From 2000 to 2020, daily estimates of consumptive use were produced for the conterminous U.S. at the 12-digit hydrologic unit code watershed level. Using the Simplified Surface Energy Balance model within the OpenET tool on Google Earth Engine, actual evapotranspiration estimates were derived from Landsat land surface temperature data. These estimates were mapped to the National Hydrologic Model (NHM) spatial units for irrigated areas defined by the Landsat Irrigation Dataset (LANID). The NHM allows for simultaneous estimation of consumptive use and effective precipitation. Results were compared to the 2015 USGS water use report, revealing annual maximum difference in consumptive use of 37 cm, with an average absolute difference of 13 cm and a bias of 2.7 %. Comparisons to field resolution irrigation withdrawals reported by growers in 4 major irrigation regions across the nation were made using efficiencies reported in the literature. These comparisons resulted in root mean square errors that ranged between 10 and 18 cm per year and biases of −18.2 to 15.8 %. Significant differences in these different reported estimates represent challenges in accurate data availability and inconsistent methods and definitions used in assessments. Annual consumptive use in the U.S. can vary by 37 % due to droughts, particularly in regions more heavily dependent on precipitation. Significant increases in consumptive use were noted over the 20-year period in western states, especially the Colorado River basin from 2010 to 2020, exacerbating water supply declines.

conterminous United States↗
USGS2024

Next generation public supply water withdrawal estimation for the conterminous United States using machine learning and operational frameworks

Estimation of human water withdrawals is more important now than ever due to uncertain water supplies, population growth, and climate change. Fourteen percent of the total water withdrawal in the United States is used for public supply, typically including deliveries to domestic, commercial, and occasionally including industrial, irrigation, and thermoelectric water withdrawal. Stewards of water resources in the USA require estimates of water withdrawals to manage and plan for future demands and sustainable water supplies. This study compiled the most comprehensive conterminous United States water withdrawal data set to date and developed a machine learning framework for estimating public supply withdrawals and associated uncertainty for the period 2000–2020. The modeling approach provides service area resolution estimates to allow for annual and monthly water withdrawal estimation while incorporating a complex array of driving factors that include hydroclimatic, demographic, socioeconomic, geographic, and land use factors. Model results reveal highly variable and lognormally distributed per-capita water withdrawal, spanning from 30 to 650 gallons per capita per day (GPCD), across community, regional, and national scales, with pronounced seasonal variations. Analysis of estimated withdrawal trends indicates that the national annual average withdrawal experienced a decline at a rate of 0.58 GPCD/year during the period from 2000 to 2020. Model interpretation reveals a complex interplay between public supply withdrawal and key predictors, including population size, warm-season precipitation, counts of large buildings and houses, and areas of urban and commercial land use. The developed models can forecast future public supply driven by various climate, demographic, and socioeconomic scenarios.

conterminous United States↗
USGS2024

Development and evaluation of public-supply community water service area boundaries for the conterminous United States

The water service area dataset, derived from the National Boundary Dataset for public-supply water systems in the United States, offers a detailed resolution surpassing county-level assessments, emphasizing water-centric land use. Crucial for linking populations and infrastructure to system withdrawals, it supports the creation of a national public-supply water-use model, enhancing accuracy in estimating water use and distinguishing between publicly supplied and self-supplied domestic water use. Integrating tabular water system data strengthens the national water-use model by enabling tracking of withdrawal locations, source water, and water quality. Evaluated against U.S. Census-derived population datasets, 16 state-provided water service area datasets, and two national land use datasets, the study covers 22,849 community water systems, excluding most small systems serving fewer than 1000 people. Robust correlations between water service areas (WSAs) and satellite-sourced urban and exurban land use types facilitate tracking changes over time. A comparison of state and national datasets for population and WSAs reveals discrepancies ranging from 5% to 73% in state-level populations and 0% to 167% in state-level WSAs. Significant differences can be attributed to the exclusion of sizable incorporated and unincorporated areas in the state-based datasets. Additional comparisons of major metropolitan areas exhibit differences ranging from 2% to 56%.

conterminous United States↗
USGS2024

Declining groundwater storage expected to amplify mountain streamflow reductions in a warmer world

Groundwater interactions with mountain streams are often simplified in model projections, potentially leading to inaccurate estimates of streamflow response to climate change. Here, using a high-resolution, integrated hydrological model extending 400 m into the subsurface, we find groundwater an important and stable source of historical streamflow in a mountainous watershed of the Colorado River. In a warmer climate, increased forest water use is predicted to reduce groundwater recharge resulting in groundwater storage loss. Losses are expected to be most severe during dry years and cannot recover to historical levels even during simulated wet periods. Groundwater depletion substantially reduces annual streamflow with intermittent conditions predicted when precipitation is low. Expanding results across the region suggests groundwater declines will be highest in the Colorado Headwater and Gunnison basins. Our research highlights the tight coupling of vegetation and groundwater dynamics and that excluding explicit groundwater response to warming may underestimate future reductions in mountain streamflow.

Nature Water↗
USGS2024

A probabilistic approach to training machine learning models using noisy data

Machine learning (ML) models are increasingly popular in environmental and hydrologic modeling, but they typically contain uncertainties resulting from noisy data (erroneous or outlier data). This paper presents a novel probabilistic approach that combines ML and Markov Chain Monte Carlo simulation to (1) detect and underweight likely noisy data, (2) develop an approach capable of detecting noisy data during model deployment, and (3) interpret the reasons why a data point is deemed noisy to help heuristically distinguish between outliers and erroneous data. The new algorithm recognizes that there is no unique way to split the training data into noisy and clean data, and thus produces an ensemble of plausible splits. The algorithm successfully detected noisy data in synthetic benchmark problems with varying complexity and a real-world public supply water withdrawal dataset. The algorithm is generic and flexible, making it suitable for application across a broad range of hydrologic and environmental disciplines.

Environmental Modelling & Software↗
USGS2023

An agricultural package for MODFLOW 6 using the Application Programming Interface

An agricultural water use package has been developed for MODFLOW 6 using the MODFLOW Application Programming Interface (API). The MODFLOW API Agricultural Water Use Package (API-Ag) was based on the approach to simulate irrigation demand in the MODFLOW-NWT and GSFLOW Agricultural Water Use (AG) Package. The API-Ag Package differs from the previous approach by implementing new features and support for additional irrigation providers. New features include representation of deficit and over-irrigation, Multi-Aquifer Well and Lake Package irrigation providers, and support for structured, vertex, and unstructured grid models. Three example problems are presented that demonstrate how the API-Ag Package improves representation of highly managed systems and are further used to validate the irrigation demand and delivery formulations. Irrigation volumes simulated in the three example problems show excellent agreement with the MODFLOW-NWT AG Package.

Groundwater↗
USGS2023

Assessing potential effects of changes in water use in the middle Carson River Basin with a numerical groundwater-flow model, Eagle, Dayton, and Churchill Valleys, west-central Nevada

During the economic boom of the mid part of the first decade of the 2000s in northwestern Nevada, municipal and housing growth increased use of the water resources of this semi-arid region. In 2008, when the economy slowed, new housing development stopped, and immediate pressure on groundwater resources abated. The U.S. Geological Survey, in cooperation with the Bureau of Reclamation, began a hydrogeologic study of the middle Carson River Basin. The first half of the study reviewed and synthesized previous geologic studies and contributed new datasets that served as a foundation for a three-dimensional, transient numerical model of groundwater and surface-water flow for the middle Carson River Basin extending from Eagle Valley to Churchill Valley. The model can be used to evaluate the effects of proposed alternative management strategies on groundwater sustainability, flows in the Carson River, and routine operation of Lahontan Reservoir and can also provide a basis for basin-wide investigations seeking to quantitatively evaluate the effects of climate change or yet-to-be-determined alternative management strategies. The middle Carson model was constructed using the U.S. Geological Survey groundwater modeling software MODFLOW-NWT. MODFLOW is widely used groundwater modeling software and is well-suited for evaluating groundwater and surface-water interactions. The model uses 550-feet square grid cells that align with the previously published model for Carson Valley (adjacent upstream valley). Six grid layers with more finely resolved vertical resolution near the perimeter of the active model domain and near surface-water features, compared to other areas of the active model domain, hone the simulated groundwater and surface-water exchanges. In addition to simulating groundwater and surface-water interaction, crop and phreatophyte evapotranspiration, lake evaporation, mountain-front recharge, recharge from irrigation return flows, and groundwater pumping are also simulated. Surface-water flow entering the model domain, including the Carson River, tributary inflow from perennial streams in Eagle Valley, and trans-basin imports through the Truckee Canal (surface water diverted from the Truckee River) are specified according to U.S. Geological Survey streamgage records. Groundwater pumpage and surface-water diversions to 10 agricultural ditches and the managed release from Lahontan Reservoir, at the end of the middle Carson River Basin, are specified according to water-manager records. The model simulation period extended from 2000 through 2010 (January 1, 2000, to December 31, 2010) using 574 weekly stress periods, with a single steady-state stress period at the beginning of the simulation that establishes initial conditions by approximating average conditions during the transient simulation period. All available observations for this period were used during the model calibration process, performed using automated parameter-estimation software. Calibration targets included observations of groundwater elevations in wells, streamflow, differences in observed streamflow between successive streamgages and actual evapotranspiration from irrigated lands. Among all 5,296 simulated and observed groundwater level pairs, the mean error was 1.42 feet; the mean absolute error, 7.71 feet; and the percent bias was −0.1 percent. Three alternative management scenarios, run using the entire period of analysis (2000–10), were simulated to improve understanding of the potential effects of (1) loss of irrigated agricultural lands following conversion of water-rights to municipal groundwater rights; (2) reclaiming treated wastewater with induction wells; and (3) exercising permitted but under-utilized groundwater rights. Scenarios 2 and 3 were further explored using two and four subscenarios, respectively. Simulated scenario results ranged from having little effect on the groundwater system relative to a baseline simulation to having spatially extensive and large groundwater-level declines (10 to 20 feet) compared to the baseline simulation. None of the simulated scenarios increased delivery of river flows to Lahontan Reservoir. On the contrary, one of the subscenarios under alternative management scenario 3 led to surface-water delivery shortfalls of more than 10,000 acre-feet per year. Future model improvements may include an extension of the model simulation period backward and forward in time and directly linking it to the upstream Carson Valley groundwater model. Furthermore, converting this MODFLOW model to a GSFLOW model, which fully integrates groundwater and surface-water flows including precipitation runoff and infiltration, may provide an improved tool for comprehensive management of water-resources in the middle Carson River Basin.

Nevada↗
USGS2023

Can hydrological models benefit from using global soil moisture, evapotranspiration, and runoff products as calibration targets?

Hydrological models are usually calibrated to in-situ streamflow observations with reasonably long and uninterrupted records. This is challenging for poorly gage or ungaged basins where such information is not available. Even for gaged basins, the single-objective calibration to gaged streamflow cannot guarantee reliable forecasts because, as has been documented elsewhere, the inverse problem is mathematically ill-posed. Therefore, the inclusion of other observations, and the reproduction of other hydrological variables beyond streamflow, become critical components of accurate hydrological forecasting. In this study, six single- and multi-objective model calibration schemes based on different combinations of gaged streamflow, global-scale gridded soil moisture, actual evapotranspiration (ET), and runoff products are used for the calibration of a process-based hydrological model for 20 catchments located within the Lake Michigan watershed, of the Laurentian Great Lakes. Results show that the addition of gridded soil moisture to gaged streamflow in model calibration improves the ET simulation performance for most of the catchments, leading to the overall best-performing models. The monthly streamflow simulation performance for the experiments using gridded runoff products to inform the model is outperformed by those using the gaged streamflow, but the discrepancy is mitigated with increasing catchment scale. A new visualization method that effectively synthesizes model performance for the simulations of streamflow, soil moisture, and ET was also proposed. Based on the method, it is revealed that the streamflow simulation performance is relatively weak for baseflow-dominated catchments; overall, the 20 catchment models simulate streamflow and ET better than soil moisture.

Lake Michigan↗
USGS2021

Integrated hydrology and operations modeling to evaluate climate change impacts in an agricultural valley irrigated with snowmelt runoff

Applying models to developed agricultural regions remains a difficult problem because there are no existing modeling codes that represent both the complex physics of the hydrology and anthropogenic manipulations to water distribution and consumption. We apply an integrated groundwater – surface water and hydrologic river operations model to an irrigated river valley in northwestern Nevada/northern California, United States to evaluate the impacts of climate change on snow-fed agricultural systems that use surface water and groundwater conjunctively. We explicitly represent individual surface water rights within the hydrologic model and allow the integrated code to change river diversions in response to earlier snowmelt runoff and water availability. Historically under-used supplemental groundwater rights are dynamically activated within the model to offset diminished surface water deliveries. The model accounts for feedbacks between the natural hydrology and anthropogenic stresses, which is a first-of-its-kind assessment of the impacts of climate change on individual water rights, and more broadly on river basin operations. Earlier snowmelt decreases annual surface water deliveries to all water rights, not just the junior water rights, owing to a lack of surface water storage in the upper river basin capable of capturing earlier runoff. Conversely, downstream irrigators with access to reservoir storage benefit from earlier runoff flowing past upstream points of diversion prior to the start of the irrigation season. Despite regional shifts toward greater reliance on groundwater for irrigation, crop consumption (a common surrogate for crop yield) decreases due to spatiotemporal changes in water supply that preferentially impact a subset of growers in the region.

California↗
USGS2020

Baseflow age distributions and depth of active groundwater flow in a snow‐dominated mountain headwater basin

Deeper flows through bedrock in mountain watersheds could be important, but lack of data to characterize bedrock properties limits understanding. To address data scarcity, we combine a previously published integrated hydrologic model of a snow‐dominated, headwater basin of the Colorado River with a new method for dating baseflow age using dissolved gas tracers SF 6 , CFC‐113, N 2 , and Ar. The original flow model predicts the majority of groundwater flow through shallow alluvium (<8 m) sitting on top of less permeable bedrock. The water moves too quickly and is unable to reproduce observed SF 6 concentrations. To match gas data, bedrock permeability is increased to allow a larger fraction of deeper and older groundwater flow (median 112 m). The updated hydrologic model indicates interannual variability in baseflow age (3–12 years) is controlled by the volume of seasonal interflow and tightly coupled to snow accumulation and monsoon rain. Deeper groundwater flow remains stable (11.7 ± 0.7 years) as a function mean historical recharge to bedrock hydraulic conductivity (R/K). A sensitivity analysis suggests that increasing bedrock K effectively moves this alpine basin away from its original conceptualization of hyperlocalized groundwater flow (high R/K) with groundwater age insensitive to changes in water inputs. Instead, this basin is situated close to the precipitation threshold defining recharge controlled groundwater flow conditions (low R/K) in which groundwater age increases with small reductions in precipitation. Work stresses the need to explore alternative methods characterizing bedrock properties in mountain basins to better quantify deeper groundwater flow and predict their hydrologic response to change.

Colorado↗