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

LaFontaine, Jacob H.; Hart, Rheannon M.; Hay, Lauren; Farmer, William; Bock, Andrew R.; Viger, Roland J.; Markstrom, Steven L.; Regan, R. Steven; Driscoll, Jessica M.

doi:10.3133/sir20195039

Cited by 17 publications

(24 citation statements)

References 3 publications

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“…The National Hydrologic Model Infrastructure application of the Precipitation-Runoff Modeling System (NHM-PRMS) [10][11][12][13]26] was used to simulate daily streamflow at all gaged locations in this study from 1 October 1983 to 30 September 2016. The data are available in a USGS data release [27].…”

Section: Data From a Process-based Modelmentioning

confidence: 99%

“…Daily values of observed precipitation and maximum and minimum air temperature from the Daily Surface Weather and Climatological Summaries version 3 [29][30][31] were used for each hydrologic response unit to compute potential evapotranspiration, actual evapotranspiration, sublimation, snowmelt, streamflow, infiltration, and groundwater recharge [11]. Physical characteristics used include topography, soils, vegetation, geology, and land cover.…”

Section: Data From a Process-based Modelmentioning

confidence: 99%

“…This National Hydrologic Model infrastructure (NHM) allows for process-based, distributed modeling that can provide information for ungaged basins. While the NHM could be adapted for use with many hydrologic simulation models, the current (2020) NHM uses the USGS Precipitation-Runoff Modeling System (PRMS) [11][12][13] to compute daily streamflows.…”

Section: Introductionmentioning

confidence: 99%

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Comparing Trends in Modeled and Observed Streamflows at Minimally Altered Basins in the United States

Hodgkins

Dudley

Russell

et al. 2020

Water

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We compared modeled and observed streamflow trends from 1984 to 2016 using five statistical transfer models and one deterministic, distributed-parameter, process-based model, for 26 flow metrics at 502 basins in the United States that are minimally influenced by development. We also looked at a measure of overall model fit and average bias. A higher percentage of basins, for all models, had relatively low trend differences between modeled and observed mean/median flows than for very high or low flows such as the annual 1-day high and 7-day low flows. Mean-flow metrics also had the largest percentage of basins with relatively good overall model fit and low bias. The five statistical transfer models performed better at more basins than the process-based model. The overall model fit for all models, for mean and/or high flows, was correlated with one or more measures of basin precipitation or aridity. Our study and previous studies generally observed good model performance for high flows up to 90th or 95th percentile flows. However, we found model performance was substantially worse for more extreme flows, including 99th percentile and annual 1-day high flows, indicating the importance of including more extreme high flows in analyses of model performance.

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Section: Data From a Process-based Modelmentioning

confidence: 99%

Section: Data From a Process-based Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Comparing Trends in Modeled and Observed Streamflows at Minimally Altered Basins in the United States

Hodgkins

Dudley

Russell

et al. 2020

Water

Self Cite

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“…Another key limitation is the static input parameters (such as the soil permeability and gwflow_coef ) that control the flow into and out of subsurface reservoirs. However, recent developments to PRMS have incorporated dynamic parameters for several parts of the water cycle [50,51]. These static or dynamic parameters are spatially distributed throughout the CONUS, but their application is dependent on the GF discretization and size of HRUs, and thus, may not represent smaller-scale values.…”

Section: Nhm-prmsmentioning

confidence: 99%

“…The default parameters for NHM-PRMS [48] were calibrated for each HRU using CONUS-extent data sets of water cycle components, referred to as the "byHRU" calibration [51,52]. In this calibration procedure, the underlying calibration scheme of the Shuffled Complex Evolution method was used [53][54][55], which determined optimal parameter sets by minimizing the error between NHM-PRMS-simulated water budget components and each CONUS-extent water cycle component.…”

Section: Nhm-prmsmentioning

confidence: 99%

Estimation of Base Flow by Optimal Hydrograph Separation for the Conterminous United States and Implications for National-Extent Hydrologic Models

Foks

Raffensperger

Penn

et al. 2019

Water

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Optimal hydrograph separation (OHS) uses a two-parameter recursive digital filter that applies specific conductance mass-balance constraints to estimate the base flow contribution to total streamflow at stream gages where discharge and specific conductance are measured. OHS was applied to U.S. Geological Survey (USGS) stream gages across the conterminous United States to examine the range/distribution of base flow inputs and the utility of this method to build a hydrologic model calibration dataset. OHS models with acceptable goodness-of-fit criteria were insensitive to drainage area, stream density, watershed slope, elevation, agricultural or perennial snow/ice land cover, average annual precipitation, runoff, or evapotranspiration, implying that OHS results are a viable calibration dataset applicable in diverse watersheds. OHS-estimated base flow contribution was compared to base flow-like model components from the USGS National Hydrologic Model Infrastructure run with the Precipitation-Runoff Modeling System (NHM-PRMS). The NHM-PRMS variable gwres_flow is most conceptually like a base flow component of streamflow but the gwres_flow contribution to total streamflow is generally smaller than the OHS-estimated base flow contribution. The NHM-PRMS variable slow_flow, added to gwres_flow, produced similar or greater estimates of base flow contributions to total streamflow than the OHS-estimated base flow contribution but was dependent on the total flow magnitude.

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Predictability of flow metrics calculated using a distributed hydrologic model across ecoregions and stream classes: Implications for developing flow–ecology relationships

et al. 2022

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Developing environmental flow standards requires an empirical understanding of the relationship between species' ecology and instream flow. However, when congruent biological and hydrologic data are lacking, the accurate simulation of hydrologic metrics (HMs) corresponding to the locations of biological data is needed. Methods to predict HMs vary in formulation (i.e., statistical vs. process‐based hydrologic models), ability to simulate HMs across the full range of the hydrologic regime (i.e., magnitude, duration, frequency, rate of change and timing) and ability to transfer HMs from gaged to ungaged locations. Yet, despite the breadth of modelling approaches, less attention has been paid to the variability in HMs associated with each approach. In this study, we apply a distributed hydrologic model to the diverse watersheds of South Carolina to examine the predictability of HMs from simulated daily time series of streamflow across ecoregions, stream classifications and level of human alteration. In doing so, we contextualize the predictability of HMs, giving managers and researchers in South Carolina the flexibility of choosing HMs that are best suited for quantifying flow–ecology relationships based on the location, flow regime components of interest and uncertainty of HMs. We found that at least one HM within each of the five flow regime components (out of a selected subset of 41 non‐redundant HMs) was consistently and accurately predicted across the diverse streams of the study area. We discuss the patterns of predictability related to site characterizations and individual HMs and their implications for developing environmental flow standards.

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

Cited by 17 publications

References 3 publications

Comparing Trends in Modeled and Observed Streamflows at Minimally Altered Basins in the United States

Comparing Trends in Modeled and Observed Streamflows at Minimally Altered Basins in the United States

Estimation of Base Flow by Optimal Hydrograph Separation for the Conterminous United States and Implications for National-Extent Hydrologic Models

Predictability of flow metrics calculated using a distributed hydrologic model across ecoregions and stream classes: Implications for developing flow–ecology relationships

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