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Improving Groundwater Imputation through Iterative Refinement Using Spatial and Temporal Correlations from In Situ Data with Machine Learning

CITE Title : Improving Groundwater Imputation through Iterative Refinement Using Spatial and Temporal Correlations from In Situ Data with Machine Learning Personal Author(s) : Ramirez, Saul G.;Williams, Gustavious Paul;Jones, Norman L.;Ames, Daniel P.;Radebaugh, Jani; Published Date : 2023 Source : Water, 15(6), 1236 DOI : https://doi.org/10.3390/w15061236 Journal Title : Water Ramirez, Saul G. et al. (2023). Improving Groundwater Imputation through Iterative Refinement Using Spatial and Temporal Correlations from In Situ Data with Machine Learning. 15(6). https://doi.org/10.3390/w15061236 Ramirez, Saul G. et al. "Improving Groundwater Imputation through Iterative Refinement Using Spatial and Temporal Correlations from In Situ Data with Machine Learning" 15, no. 6 (2023), https://doi.org/10.3390/w15061236 Ramirez, Saul G. et al. "Improving Groundwater Imputation through Iterative Refinement Using Spatial and Temporal Correlations from In Situ Data with Machine Learning" vol. 15, no. 6, 2023, https://doi.org/10.3390/w15061236 Export RIS Citation Information.

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Ramirez, Saul G.

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Williams, Gustavious Paul

2023 | Water, 15(6), 1236

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Obtaining and managing groundwater data is difficult as it is common for time series datasets representing groundwater levels at wells to have large g...
Building and Validating Multidimensional Datasets in Hydrology for Data and Mapping Web Service Compliance

CITE Title : Building and Validating Multidimensional Datasets in Hydrology for Data and Mapping Web Service Compliance Personal Author(s) : Jones, J. Enoch;Hales, Riley Chad;Larco, Karina;Nelson, E. James;Ames, Daniel P.;Jones, Norman L.;Iza, Maylee; Published Date : 2023 Source : Water, 15(3), 411 DOI : https://doi.org/10.3390/w15030411 Journal Title : Water Jones, J. Enoch et al. (2023). Building and Validating Multidimensional Datasets in Hydrology for Data and Mapping Web Service Compliance. 15(3). https://doi.org/10.3390/w15030411 Jones, J. Enoch et al. "Building and Validating Multidimensional Datasets in Hydrology for Data and Mapping Web Service Compliance" 15, no. 3 (2023), https://doi.org/10.3390/w15030411 Jones, J. Enoch et al. "Building and Validating Multidimensional Datasets in Hydrology for Data and Mapping Web Service Compliance" vol. 15, no. 3, 2023, https://doi.org/10.3390/w15030411 Export RIS Citation Information.

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Jones, J. Enoch ;

Hales, Riley Chad

2023 | Water, 15(3), 411

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Multidimensional, georeferenced data are used extensively in hydrology, meteorology, and water science and engineering. These data are produced, share...
Advancing global hydrologic modeling with the GEOGloWS ECMWF streamflow service

CITE Title : Advancing global hydrologic modeling with the GEOGloWS ECMWF streamflow service Personal Author(s) : Hales, Riley C.;Nelson, E. James;Souffront, Michael;Gutierrez, Angelica L.;Prudhomme, Christel;Kopp, Steve;Ames, Daniel P.;Williams, Gustavious P.;Jones, Norman L.; Published Date : 2022 Source : Journal of Flood Risk Management (2022) DOI : https://doi.org/10.1111/jfr3.12859 Journal Title : Journal of Flood Risk Management Hales, Riley C. et al. (2022). Advancing global hydrologic modeling with the GEOGloWS ECMWF streamflow service. https://doi.org/10.1111/jfr3.12859 Hales, Riley C. et al. "Advancing global hydrologic modeling with the GEOGloWS ECMWF streamflow service" (2022), https://doi.org/10.1111/jfr3.12859 Hales, Riley C. et al. "Advancing global hydrologic modeling with the GEOGloWS ECMWF streamflow service" , 2022, https://doi.org/10.1111/jfr3.12859 Export RIS Citation Information.

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Hales, Riley C.

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Nelson, E. James

2022 | Journal of Flood Risk Management (2022)

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Most people face some level of water insecurity. Wise water management prac- tices to address water security issues typically require data derived fro...
Hydrologic Modeling as a Service (HMaaS): A New Approach to Address Hydroinformatic Challenges in Developing Countries

CITE Title : Hydrologic Modeling as a Service (HMaaS): A New Approach to Address Hydroinformatic Challenges in Developing Countries Personal Author(s) : Souffront Alcantara, Michael A.;Nelson, E. James;Shakya, Kiran;Edwards, Christopher;Roberts, Wade;Krewson, Corey;Ames, Daniel P.;Jones, Norman L.;Gutierrez, Angelica; Published Date : 2019 Source : Frontiers in Environmental Science, 7 DOI : https://doi.org/10.3389/fenvs.2019.00158 Journal Title : Frontiers in Environmental Science Souffront Alcantara, Michael A. et al. (2019). Hydrologic Modeling as a Service (HMaaS): A New Approach to Address Hydroinformatic Challenges in Developing Countries. 7https://doi.org/10.3389/fenvs.2019.00158 Souffront Alcantara, Michael A. et al. "Hydrologic Modeling as a Service (HMaaS): A New Approach to Address Hydroinformatic Challenges in Developing Countries" 7 (2019), https://doi.org/10.3389/fenvs.2019.00158 Souffront Alcantara, Michael A. et al. "Hydrologic Modeling as a Service (HMaaS): A New Approach to Address Hydroinformatic Challenges in Developing Countries" vol. 7, 2019, https://doi.org/10.3389/fenvs.2019.00158 Export RIS Citation Information.

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Souffront Alcantara, Michael A. ;

Nelson, E. James

2019 | Frontiers in Environmental Science, 7

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Hydrologic modeling can be used to aid in decision-making at the local scale. Developed countries usually have their own hydrologic models; however, d...