Estimating the water budget of major US river basins via remote sensing

Gao, Huilin; Tang, Qiuhong; Ferguson, Craig R.; Wood, Eric F.; Lettenmaier, Dennis P.

doi:10.1080/01431161.2010.483488

Cited by 135 publications

(128 citation statements)

References 46 publications

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“…It should be noted that similarly large positive bias in the seasonal range in NW/Columbia and California is also found in offline VIC simulation driven by observed meteorological forcing (Gao et al 2009) with a 2 m soil depth. This highlights the challenges in simulating/prescribing precipitation and simulating soil hydrology, as well as potential problems in the GRACE estimates in regions of complex terrain.…”

Section: Comparison Of Observed and Simulated Land Surface Water Budgetsmentioning

confidence: 97%

“…Comparisons are made between GW-5 and the control runs, and evaluated using observed 1/8°gridded temperature and precipitation data. We also used monthly mean runoff data from stream gauges (Gao et al 2009) and the University of New Hampshire Global Runoff Data Centre (UNH-GRDC) for comparison with the simulated runoff in large river basins. We obtained groundwater table data for unconfined aquifer, groundwater wells from USGS National Water Information System (http://pubs.usgs.gov/ of/2004/1238/) for a qualitative comparison with the simulated water table depth.…”

Section: Numerical Experimentsmentioning

confidence: 99%

“…The Gravity Recovery and Climate Experiment (GRACE) (Rodell et al 2004;Chambers 2006) satellites derived terrestrial water storage anomaly (DS) are used to evaluate the long term mean seasonal variations of terrestrial water storage simulated by the model. Three sets of estimates from GRACE data developed by Center for Space Research (CSR) at University of Texas, GFZ German Research Center, and Jet Propulsion Laboratory (JPL) averaged over 13 river basins are used (Gao et al 2009). In addition, soil moisture profiles from eight From time series of the simulated groundwater table depth, we noted in Sect.…”

Section: Numerical Experimentsmentioning

confidence: 99%

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Climate–soil–vegetation control on groundwater table dynamics and its feedbacks in a climate model

et al. 2010

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Among the three dynamically linked branches of the water cycle, including atmospheric, surface, and subsurface water, groundwater is the largest reservoir and an active component of the hydrologic system. Because of the inherent slow response time, groundwater may be particularly relevant for long time-scale processes such as multi-years or decadal droughts. This study uses regional climate simulations with and without surface watergroundwater interactions for the conterminous US to assess the influence of climate, soil, and vegetation on groundwater table dynamics, and its potential feedbacks to regional climate. Analyses show that precipitation has a dominant influence on the spatial and temporal variations of groundwater table depth (GWT). The simulated GWT is found to decrease sharply with increasing precipitation. Our simulation also shows some distinct spatial variations that are related to soil porosity and hydraulic conductivity. Vegetation properties such as minimum stomatal resistance, and root depth and fraction are also found to play an important role in controlling the groundwater table.Comparing two simulations with and without groundwater table dynamics, we find that groundwater table dynamics mainly influences the partitioning of soil water between the surface (0-0.5 m) and subsurface (0.5-5 m) rather than total soil moisture. In most areas, groundwater table dynamics increases surface soil moisture at the expense of the subsurface, except in regions with very shallow groundwater table. The change in soil water partitioning between the surface and subsurface is found to strongly correlate with the partitioning of surface sensible and latent heat fluxes. The evaporative fraction (EF) is generally higher during summer when groundwater table dynamics is included. This is accompanied by increased cloudiness, reduced diurnal temperature range, cooler surface temperature, and increased cloud top height. Although both convective and non-convective precipitation are enhanced, the higher EF changes the partitioning to favor more non-convective precipitation, but this result could be sensitive to the convective parameterization used. Compared to simulations without groundwater table dynamics, the dry bias in the summer precipitation is slightly reduced over the central and eastern US Groundwater table dynamics can provide important feedbacks to atmospheric processes, and these feedbacks are stronger in regions with deeper groundwater table, because the interactions between surface and subsurface are weak when the groundwater table is deep. This increases the sensitivity of surface soil moisture to precipitation anomalies, and therefore enhances land surface feedbacks to the atmosphere through changes in soil moisture and evaporative fraction. By altering the groundwater table depth, land use change and groundwater withdrawal can alter land surface response and feedback to the climate system.

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Section: Comparison Of Observed and Simulated Land Surface Water Budgetsmentioning

confidence: 97%

Section: Numerical Experimentsmentioning

confidence: 99%

Section: Numerical Experimentsmentioning

confidence: 99%

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Climate–soil–vegetation control on groundwater table dynamics and its feedbacks in a climate model

et al. 2010

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“…Cherkauer et al (2003) provides updates for cold land process and Bowling and Lettenmaier (2010) provided updates for lakes and wetlands to the basic structure of this model. The model has been widely applied for purposes such as seasonal hydrological forecasting (Nijssen et al, 2001;Yuan 2016), climate change impacts studies (Wu et al, 2012, Zhao et al, 2012, and water and energy budget studies (Haddeland et al, 2007, Gao et al, 2010, among various other applications. carried by the GPM Core observatory.…”

Section: Hydrological Modelmentioning

confidence: 99%

A scalable open-source web-analytic framework to improve satellite-based operational water management in developing countries

Biswas

Hossain

2017

Journal of Hydroinformatics

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A Scalable Open-source Web-analytic Framework to Improve Satellite -based Operational Water Management in Developing Countries Nishan Kumar BiswasChair of the Supervisory Committee: Associate Professor Faisal Hossain Department of Civil and Environmental Engineering Satellite based observations are becoming more widespread for operational and decision making activities in water resources due to their near real-time availability as well as minimization of difficulties related to ground based hydrological measurements. In this study, two crucial hurdles to advance real-world operationalization of satellite datasets are addressed. First, a simple, easy-to-access, easy-to-build, robust and consistent open-source web portal is developed connecting complex models to facilitate satellite based observations by developing nations.Second, to enhance the predictability skill of satellite-based estimations, an innovative and dynamic web analytics-based correction system is developed to reduce the uncertainty related to indirect method of measurement by the satellites. The correction system comprised of precipitation correction and streamflow correction. In precipitation correction, web crawled precipitation from different sites of government agencies of South Asia region are used to estimate bias in satellite based precipitation. This dynamically bias adjusted precipitation is then used to simulate hydrological models to obtain streamflow. Simulated streamflow is corrected using discharge climatology and gauged discharge observations. These corrected datasets are finally shared through South Asian Surface Water Modelling System (SASWMS) web portal. On an average, these dynamic correction techniques reduced RMSE in streamflow by 80-90%. The take-home message is that with the growth of open-source tools, it is now possible for any resourceconstrained water management agency to build robust and cost-effective operational web portals based on satellite data and non-proprietary software. With dynamic correction features that can also be built from open-source tools, the well-known limitations of satellite-based operationalization can be overcome for water management agencies of developing countries.v

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“…In addition, a few satellite-aided ellite-aided drought monitoring were carried out through detecting the changes in surface temperature or land cover (e.g., Li et al, 2010). Although the satellite remote sensing is promising, the non-closure of terrestrial water budgets is still an open issue (Tang et al, 2009b;Sheffield et al, 2009;Gao et al, 2010).…”

Section: Hydrological Monitoring Observations and Data Assimilationmentioning

confidence: 99%

Hydrological monitoring and seasonal forecasting: Progress and perspectives

et al. 2016

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Hydrological monitoring and seasonal forecasting is an active research field because of its potential applications in hydrological risk assessment, preparedness and mitigation. In recent decades, developments in ground and satellite measurements have made the hydrometeorological information readily available, and advances in information technology have facilitated the data analysis in a real-time manner. New progress in climate research and modeling has enabled the prediction of seasonal climate with reasonable accuracy and increased resolution. These emerging techniques and advances have enabled more timely acquisition of accurate hydrological fluxes and status, and earlier warning of extreme hydrological events such as droughts and floods. This paper gives current state-of-the-art understanding of the uncertainties in hydrological monitoring and forecasting, reviews the efforts and progress in operational hydrological monitoring system assisted by observations from various sources and experimental seasonal hydrological forecasting, and briefly introduces the current monitoring and forecasting practices in China. The grand challenges and perspectives for the near future are also discussed, including acquiring and extracting reliable information for monitoring and forecasting, predicting realistic hydrological fluxes and states in the river basin being significantly altered by human activity, and filling the gap between numerical models and the end user. We highlight the importance of understanding the needs of the operational water management and the priority to transfer research knowledge to decision-makers.

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Estimating the water budget of major US river basins via remote sensing

Cited by 135 publications

References 46 publications

Climate–soil–vegetation control on groundwater table dynamics and its feedbacks in a climate model

Climate–soil–vegetation control on groundwater table dynamics and its feedbacks in a climate model

A scalable open-source web-analytic framework to improve satellite-based operational water management in developing countries

Hydrological monitoring and seasonal forecasting: Progress and perspectives

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