Search Results - "Gupta, Hoshin V"

What Role Does Hydrological Science Play in the Age of Machine Learning? by Nearing, Grey S., Kratzert, Frederik, Sampson, Alden Keefe, Pelissier, Craig S., Klotz, Daniel, Frame, Jonathan M., Prieto, Cristina, Gupta, Hoshin V.

“…This paper is derived from a keynote talk given at the Google's 2020 Flood Forecasting Meets Machine Learning Workshop. Recent experiments applying deep…”
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On the Requirements for Inferring Aquifer‐Scale T and S in Heterogeneous Confined Aquifers by Naderi, Mostafa, Gupta, Hoshin V.

“…We study the sensitivity of aquifer‐scale estimates of transmissivity (T) and storativity (S) to the variance and correlation length scale of aquifer…”
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Uncertainty in hydrologic modeling: Toward an integrated data assimilation framework by Liu, Y, Gupta, H.V

“…1 Despite significant recent developments in computational power and distributed hydrologic modeling, the issue of how to adequately address the uncertainty…”
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Towards a comprehensive assessment of model structural adequacy by Gupta, Hoshin V., Clark, Martyn P., Vrugt, Jasper A., Abramowitz, Gab, Ye, Ming

“…The past decade has seen significant progress in characterizing uncertainty in environmental systems models, through statistical treatment of incomplete…”
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A process-based diagnostic approach to model evaluation: Application to the NWS distributed hydrologic model by Yilmaz, Koray K., Gupta, Hoshin V., Wagener, Thorsten

“…Distributed hydrological models have the potential to provide improved streamflow forecasts along the entire channel network, while also simulating the spatial…”
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Deep learning rainfall–runoff predictions of extreme events by Frame, Jonathan M, Kratzert, Frederik, Klotz, Daniel, Gauch, Martin, Shelev, Guy, Gilon, Oren, Qualls, Logan M, Gupta, Hoshin V, Nearing, Grey S

“…The most accurate rainfall–runoff predictions are currently based on deep learning. There is a concern among hydrologists that the predictive accuracy of…”
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The delusive accuracy of global irrigation water withdrawal estimates by Puy, Arnald, Sheikholeslami, Razi, Gupta, Hoshin V., Hall, Jim W., Lankford, Bruce, Lo Piano, Samuele, Meier, Jonas, Pappenberger, Florian, Porporato, Amilcare, Vico, Giulia, Saltelli, Andrea

“…Miscalculating the volumes of water withdrawn for irrigation, the largest consumer of freshwater in the world, jeopardizes sustainable water management…”
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Trends in water balance components across the Brazilian Cerrado by Oliveira, Paulo Tarso S., Nearing, Mark A., Moran, M. Susan, Goodrich, David C., Wendland, Edson, Gupta, Hoshin V.

“…We assess the water balance of the Brazilian Cerrado based on remotely sensed estimates of precipitation (TRMM), evapotranspiration (MOD16), and terrestrial…”
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Toward a Multi‐Representational Approach to Prediction and Understanding, in Support of Discovery in Hydrology by De la Fuente, Luis A., Gupta, Hoshin V., Condon, Laura E.

“…Key to model development is the selection of an appropriate representational system, including both the representation of what is observed (the data), and the…”
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Framework for Understanding Structural Errors (FUSE): A modular framework to diagnose differences between hydrological models by Clark, Martyn P., Slater, Andrew G., Rupp, David E., Woods, Ross A., Vrugt, Jasper A., Gupta, Hoshin V., Wagener, Thorsten, Hay, Lauren E.

“…The problems of identifying the most appropriate model structure for a given problem and quantifying the uncertainty in model structure remain outstanding…”
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On the Accurate Estimation of Information-Theoretic Quantities from Multi-Dimensional Sample Data by Álvarez Chaves, Manuel, Gupta, Hoshin V, Ehret, Uwe, Guthke, Anneli

“…Using information-theoretic quantities in practical applications with continuous data is often hindered by the fact that probability density functions need to…”
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On the use of spatial regularization strategies to improve calibration of distributed watershed models by Pokhrel, Prafulla, Gupta, Hoshin V

“…Hydrologic models require the specification of unknown model parameters via calibration to historical input‐output data. For spatially distributed models, the…”
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Dual state–parameter estimation of hydrological models using ensemble Kalman filter by Moradkhani, Hamid, Sorooshian, Soroosh, Gupta, Hoshin V., Houser, Paul R.

“…Hydrologic models are twofold: models for understanding physical processes and models for prediction. This study addresses the latter, which modelers use to…”
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Improved treatment of uncertainty in hydrologic modeling: Combining the strengths of global optimization and data assimilation by Vrugt, J.A, Diks, C.G.H, Gupta, H.V, Bouten, W, Verstraten, J.M

“…Hydrologic models use relatively simple mathematical equations to conceptualize and aggregate the complex, spatially distributed, and highly interrelated…”
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What do we mean by sensitivity analysis? The need for comprehensive characterization of "global" sensitivity in Earth and Environmental systems models by Razavi, Saman, Gupta, Hoshin V.

“…Sensitivity analysis is an essential paradigm in Earth and Environmental Systems modeling. However, the term “sensitivity” has a clear definition, based in…”
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Improving robustness of hydrologic parameter estimation by the use of moving block bootstrap resampling by Ebtehaj, Mohammad, Moradkhani, Hamid, Gupta, Hoshin V.

“…Modeling of natural systems typically involves conceptualization and parameterization to simplify the representations of the underlying process. Objective…”
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A new framework for comprehensive, robust, and efficient global sensitivity analysis: 1. Theory by Razavi, Saman, Gupta, Hoshin V.

“…Computer simulation models are continually growing in complexity with increasingly more factors to be identified. Sensitivity Analysis (SA) provides an…”
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Rainfall distributional properties control hydrologic model parameter importance by Meles, Menberu B., Goodrich, Dave C., Unkrich, Carl L., Gupta, Hoshin V., Burns, I. Shea, Hirpa, Feyera A., Razavi, Saman, Guertin, D. Phillip

“…Semi-arid region of the Western United States of America in 16.6 km2 WS10 watershed using data from the highly instrumented Walnut Gulch Experimental Watershed…”
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Computing Accurate Probabilistic Estimates of One-D Entropy from Equiprobable Random Samples by Gupta, Hoshin V., Ehsani, Mohammad Reza, Roy, Tirthankar, Sans-Fuentes, Maria A., Ehret, Uwe, Behrangi, Ali

“…We develop a simple Quantile Spacing (QS) method for accurate probabilistic estimation of one-dimensional entropy from equiprobable random samples, and compare…”
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Modeling the distributed effects of forest thinning on the long-term water balance and streamflow extremes for a semi-arid basin in the southwestern US by Moreno, Hernan A, Gupta, Hoshin V, White, Dave D, Sampson, David A

“…To achieve water resource sustainability in the water-limited southwestern US, it is critical to understand the potential effects of proposed forest thinning…”
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