Extending a Large-Scale Model to Better Represent Water Resources without Increasing the Model’s Complexity

The increasing impact of anthropogenic interference on river basins has facilitated the development of the representation of human influences in large-scale models. The representation of groundwater and large reservoirs have realised significant developments recently. Groundwater and reservoir repre...

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Autores principales:	Robyn Horan, Nathan J. Rickards, Alexandra Kaelin, Helen E. Baron, Thomas Thomas, Virginie D. J. Keller, Prabhas K. Mishra, Manish K. Nema, Sekhar Muddu, Kaushal K. Garg, Rishi Pathak, Helen A. Houghton-Carr, Harry Dixon, Sharad K. Jain, Gwyn Rees
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	large-scale model hydrology groundwater reservoirs Cauvery Narmada Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500
Acceso en línea:	https://doaj.org/article/51b95b952eca4048856a42121fdf06a1
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id	oai:doaj.org-article:51b95b952eca4048856a42121fdf06a1
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spelling	oai:doaj.org-article:51b95b952eca4048856a42121fdf06a12021-11-11T19:56:20ZExtending a Large-Scale Model to Better Represent Water Resources without Increasing the Model’s Complexity10.3390/w132130672073-4441https://doaj.org/article/51b95b952eca4048856a42121fdf06a12021-11-01T00:00:00Zhttps://www.mdpi.com/2073-4441/13/21/3067https://doaj.org/toc/2073-4441The increasing impact of anthropogenic interference on river basins has facilitated the development of the representation of human influences in large-scale models. The representation of groundwater and large reservoirs have realised significant developments recently. Groundwater and reservoir representation in the Global Water Availability Assessment (GWAVA) model have been improved, critically, with a minimal increase in model complexity and data input requirements, in keeping with the model’s applicability to regions with low-data availability. The increased functionality was assessed in two highly anthropogenically influenced basins. A revised groundwater routine was incorporated into GWAVA, which is fundamentally driven by three input parameters, and improved the simulation of streamflow and baseflow in the headwater catchments such that low-flow model skill increased 33–67% in the Cauvery and 66–100% in the Narmada. The existing reservoir routine was extended and improved the simulation of streamflow in catchments downstream of major reservoirs, using two calibratable parameters. The model performance was improved between 15% and 30% in the Cauvery and 7–30% in the Narmada, with the daily reservoir releases in the Cauvery improving significantly between 26% and 164%. The improvement of the groundwater and reservoir routines in GWAVA proved successful in improving the model performance, and the inclusions allowed for improved traceability of simulated water balance components. This study illustrates that improvement in the representation of human–water interactions in large-scale models is possible, without excessively increasing the model complexity and input data requirements.Robyn HoranNathan J. RickardsAlexandra KaelinHelen E. BaronThomas ThomasVirginie D. J. KellerPrabhas K. MishraManish K. NemaSekhar MudduKaushal K. GargRishi PathakHelen A. Houghton-CarrHarry DixonSharad K. JainGwyn ReesMDPI AGarticlelarge-scale modelhydrologygroundwaterreservoirsCauveryNarmadaHydraulic engineeringTC1-978Water supply for domestic and industrial purposesTD201-500ENWater, Vol 13, Iss 3067, p 3067 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	large-scale model hydrology groundwater reservoirs Cauvery Narmada Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500
spellingShingle	large-scale model hydrology groundwater reservoirs Cauvery Narmada Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500 Robyn Horan Nathan J. Rickards Alexandra Kaelin Helen E. Baron Thomas Thomas Virginie D. J. Keller Prabhas K. Mishra Manish K. Nema Sekhar Muddu Kaushal K. Garg Rishi Pathak Helen A. Houghton-Carr Harry Dixon Sharad K. Jain Gwyn Rees Extending a Large-Scale Model to Better Represent Water Resources without Increasing the Model’s Complexity
description	The increasing impact of anthropogenic interference on river basins has facilitated the development of the representation of human influences in large-scale models. The representation of groundwater and large reservoirs have realised significant developments recently. Groundwater and reservoir representation in the Global Water Availability Assessment (GWAVA) model have been improved, critically, with a minimal increase in model complexity and data input requirements, in keeping with the model’s applicability to regions with low-data availability. The increased functionality was assessed in two highly anthropogenically influenced basins. A revised groundwater routine was incorporated into GWAVA, which is fundamentally driven by three input parameters, and improved the simulation of streamflow and baseflow in the headwater catchments such that low-flow model skill increased 33–67% in the Cauvery and 66–100% in the Narmada. The existing reservoir routine was extended and improved the simulation of streamflow in catchments downstream of major reservoirs, using two calibratable parameters. The model performance was improved between 15% and 30% in the Cauvery and 7–30% in the Narmada, with the daily reservoir releases in the Cauvery improving significantly between 26% and 164%. The improvement of the groundwater and reservoir routines in GWAVA proved successful in improving the model performance, and the inclusions allowed for improved traceability of simulated water balance components. This study illustrates that improvement in the representation of human–water interactions in large-scale models is possible, without excessively increasing the model complexity and input data requirements.
format	article
author	Robyn Horan Nathan J. Rickards Alexandra Kaelin Helen E. Baron Thomas Thomas Virginie D. J. Keller Prabhas K. Mishra Manish K. Nema Sekhar Muddu Kaushal K. Garg Rishi Pathak Helen A. Houghton-Carr Harry Dixon Sharad K. Jain Gwyn Rees
author_facet	Robyn Horan Nathan J. Rickards Alexandra Kaelin Helen E. Baron Thomas Thomas Virginie D. J. Keller Prabhas K. Mishra Manish K. Nema Sekhar Muddu Kaushal K. Garg Rishi Pathak Helen A. Houghton-Carr Harry Dixon Sharad K. Jain Gwyn Rees
author_sort	Robyn Horan
title	Extending a Large-Scale Model to Better Represent Water Resources without Increasing the Model’s Complexity
title_short	Extending a Large-Scale Model to Better Represent Water Resources without Increasing the Model’s Complexity
title_full	Extending a Large-Scale Model to Better Represent Water Resources without Increasing the Model’s Complexity
title_fullStr	Extending a Large-Scale Model to Better Represent Water Resources without Increasing the Model’s Complexity
title_full_unstemmed	Extending a Large-Scale Model to Better Represent Water Resources without Increasing the Model’s Complexity
title_sort	extending a large-scale model to better represent water resources without increasing the model’s complexity
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/51b95b952eca4048856a42121fdf06a1
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Extending a Large-Scale Model to Better Represent Water Resources without Increasing the Model’s Complexity

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