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Assessment of CHADFDM satellite‐based input dataset for the groundwater recharge estimation in arid and data scarce regions
Aquifer natural recharge estimations are a prerequisite for understanding hydrologic systems and sustainable water resources management. As meteorological data series collection is difficult in arid and semiarid areas, satellite products have recently become an alternative for water resources studie...
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Published in: | Hydrological processes 2021-06, Vol.35 (6), p.n/a |
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description | Aquifer natural recharge estimations are a prerequisite for understanding hydrologic systems and sustainable water resources management. As meteorological data series collection is difficult in arid and semiarid areas, satellite products have recently become an alternative for water resources studies. A daily groundwater recharge estimation in the NW part of the Lake Chad Basin, using a soil–plant‐atmosphere model (VisualBALAN), from ground‐ and satellite‐based meteorological input dataset for non‐irrigated and irrigated land and for the 2005–2014 period is presented. Average annual values were 284 mm and 30°C for precipitation and temperature in ground‐based gauge stations. For the satellite‐model‐based Lake Chad Basin Flood and Drought Monitor System platform (CHADFDM), average annual precipitation and temperature were 417 mm and 29°C, respectively. Uncertainties derived from satellite data measurement could account for the rainfall difference. The estimated mean annual aquifer recharge was always higher from satellite‐ than ground‐based data, with differences up to 46% for dryland and 23% in irrigated areas. Recharge response to rainfall events was very variable and results were very sensitive to: wilting point, field capacity and curve number for runoff estimation. Obtained results provide plausible recharge values beyond the uncertainty related to data input and modelling approach. This work prevents on the important deviations in recharge estimation from weighted‐ensemble satellite‐based data, informing in decision making to both stakeholders and policy makers.
Estimation of diffuse recharge by precipitation is highly dependent on climatic data as well as pattern and soil characteristics. In arid and semi‐arid areas, meteorological ground‐based data collection is difficult and satellite products of climatic forcing functions constitute an alternative. For the Lake Chad area, rainfall from satellite overestimates the amount of ground‐based records and shows more variability over time. Recharge rate quantification provided evidence of results from satellite precipitation and allowed the comparison with ground data. |
doi_str_mv | 10.1002/hyp.14250 |
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Estimation of diffuse recharge by precipitation is highly dependent on climatic data as well as pattern and soil characteristics. In arid and semi‐arid areas, meteorological ground‐based data collection is difficult and satellite products of climatic forcing functions constitute an alternative. For the Lake Chad area, rainfall from satellite overestimates the amount of ground‐based records and shows more variability over time. Recharge rate quantification provided evidence of results from satellite precipitation and allowed the comparison with ground data.</description><identifier>ISSN: 0885-6087</identifier><identifier>EISSN: 1099-1085</identifier><identifier>DOI: 10.1002/hyp.14250</identifier><language>eng</language><publisher>Hoboken, USA: John Wiley & Sons, Inc</publisher><subject>Annual precipitation ; Annual rainfall ; Aquifer recharge ; Aquifers ; Arid lands ; Arid regions ; Arid zones ; Atmospheric models ; Atmospheric precipitations ; CHADFDM data set ; Datasets ; Decision making ; Drought ; Field capacity ; Ground stations ; Groundwater ; Groundwater data ; Groundwater recharge ; Groundwater recharge estimation ; groundwater recharge modelling ; ground‐satellite meteorological data ; Hydrologic systems ; Hydrology ; Irrigated areas ; Irrigated lands ; Lake Chad Basin ; Lakes ; Mean annual precipitation ; Meteorological data ; Natural recharge ; Precipitation ; Precipitation-temperature relationships ; Rain ; Rainfall ; Runoff ; Runoff estimation ; Satellite data ; Satellites ; Semi arid areas ; Temperature ; Uncertainty ; Water resources ; Water resources management ; Wilting ; Wilting point</subject><ispartof>Hydrological processes, 2021-06, Vol.35 (6), p.n/a</ispartof><rights>2021 The Authors. published by John Wiley & Sons Ltd.</rights><rights>2021. This article is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a3550-e102b806f9dfc754370ebdc0171e4f3e9d6c2835bf83bd9ebfd5bcc2fbc1fc673</citedby><cites>FETCH-LOGICAL-a3550-e102b806f9dfc754370ebdc0171e4f3e9d6c2835bf83bd9ebfd5bcc2fbc1fc673</cites><orcidid>0000-0001-5075-7317 ; 0000-0002-2063-6490 ; 0000-0002-1659-6334</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Salehi Siavashani, Nafiseh</creatorcontrib><creatorcontrib>Jimenez‐Martinez, Joaquin</creatorcontrib><creatorcontrib>Vaquero, Guillermo</creatorcontrib><creatorcontrib>Elorza, Francisco J.</creatorcontrib><creatorcontrib>Sheffield, Justin</creatorcontrib><creatorcontrib>Candela, Lucila</creatorcontrib><creatorcontrib>Serrat‐Capdevila, Aleix</creatorcontrib><title>Assessment of CHADFDM satellite‐based input dataset for the groundwater recharge estimation in arid and data scarce regions</title><title>Hydrological processes</title><description>Aquifer natural recharge estimations are a prerequisite for understanding hydrologic systems and sustainable water resources management. As meteorological data series collection is difficult in arid and semiarid areas, satellite products have recently become an alternative for water resources studies. A daily groundwater recharge estimation in the NW part of the Lake Chad Basin, using a soil–plant‐atmosphere model (VisualBALAN), from ground‐ and satellite‐based meteorological input dataset for non‐irrigated and irrigated land and for the 2005–2014 period is presented. Average annual values were 284 mm and 30°C for precipitation and temperature in ground‐based gauge stations. For the satellite‐model‐based Lake Chad Basin Flood and Drought Monitor System platform (CHADFDM), average annual precipitation and temperature were 417 mm and 29°C, respectively. Uncertainties derived from satellite data measurement could account for the rainfall difference. The estimated mean annual aquifer recharge was always higher from satellite‐ than ground‐based data, with differences up to 46% for dryland and 23% in irrigated areas. Recharge response to rainfall events was very variable and results were very sensitive to: wilting point, field capacity and curve number for runoff estimation. Obtained results provide plausible recharge values beyond the uncertainty related to data input and modelling approach. This work prevents on the important deviations in recharge estimation from weighted‐ensemble satellite‐based data, informing in decision making to both stakeholders and policy makers.
Estimation of diffuse recharge by precipitation is highly dependent on climatic data as well as pattern and soil characteristics. In arid and semi‐arid areas, meteorological ground‐based data collection is difficult and satellite products of climatic forcing functions constitute an alternative. For the Lake Chad area, rainfall from satellite overestimates the amount of ground‐based records and shows more variability over time. Recharge rate quantification provided evidence of results from satellite precipitation and allowed the comparison with ground data.</description><subject>Annual precipitation</subject><subject>Annual rainfall</subject><subject>Aquifer recharge</subject><subject>Aquifers</subject><subject>Arid lands</subject><subject>Arid regions</subject><subject>Arid zones</subject><subject>Atmospheric models</subject><subject>Atmospheric precipitations</subject><subject>CHADFDM data set</subject><subject>Datasets</subject><subject>Decision making</subject><subject>Drought</subject><subject>Field capacity</subject><subject>Ground stations</subject><subject>Groundwater</subject><subject>Groundwater data</subject><subject>Groundwater recharge</subject><subject>Groundwater recharge estimation</subject><subject>groundwater recharge modelling</subject><subject>ground‐satellite meteorological data</subject><subject>Hydrologic systems</subject><subject>Hydrology</subject><subject>Irrigated areas</subject><subject>Irrigated lands</subject><subject>Lake Chad Basin</subject><subject>Lakes</subject><subject>Mean annual precipitation</subject><subject>Meteorological data</subject><subject>Natural recharge</subject><subject>Precipitation</subject><subject>Precipitation-temperature relationships</subject><subject>Rain</subject><subject>Rainfall</subject><subject>Runoff</subject><subject>Runoff estimation</subject><subject>Satellite data</subject><subject>Satellites</subject><subject>Semi arid areas</subject><subject>Temperature</subject><subject>Uncertainty</subject><subject>Water resources</subject><subject>Water resources management</subject><subject>Wilting</subject><subject>Wilting point</subject><issn>0885-6087</issn><issn>1099-1085</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><recordid>eNp1kLFOwzAQhi0EEqUw8AaWmBjSnpO4ccaqpRSpCAYYmCLHPrep0qTYrqoOSDwCz8iTYBpWptPpvv-_u5-QawYDBhAPV4ftgKUxhxPSY5DnEQPBT0kPhODRCER2Ti6cWwNACgJ65GPsHDq3wcbT1tDJfDydTR-pkx7ruvL4_flVSoeaVs1256mWPnSemtZSv0K6tO2u0ftAW2pRraRdIkXnq430VdsEFZW20lQ2-qilTkmrMLDLMHaX5MzI2uHVX-2T19ndy2QeLZ7uHybjRSQTziFCBnEpYGRybVTG0yQDLLUCljFMTYK5HqlYJLw0Iil1jqXRvFQqNqViRo2ypE9uOt-tbd934b5i3e5sE1YWMU-5iJNgGqjbjlK2dc6iKbY2PGIPBYPiN90ipFsc0w3ssGP3VY2H_8Fi_vbcKX4A5K9_EA</recordid><startdate>202106</startdate><enddate>202106</enddate><creator>Salehi Siavashani, Nafiseh</creator><creator>Jimenez‐Martinez, Joaquin</creator><creator>Vaquero, Guillermo</creator><creator>Elorza, Francisco J.</creator><creator>Sheffield, Justin</creator><creator>Candela, Lucila</creator><creator>Serrat‐Capdevila, Aleix</creator><general>John Wiley & Sons, Inc</general><general>Wiley Subscription Services, Inc</general><scope>24P</scope><scope>WIN</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7ST</scope><scope>7TG</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H96</scope><scope>KL.</scope><scope>KR7</scope><scope>L.G</scope><scope>SOI</scope><orcidid>https://orcid.org/0000-0001-5075-7317</orcidid><orcidid>https://orcid.org/0000-0002-2063-6490</orcidid><orcidid>https://orcid.org/0000-0002-1659-6334</orcidid></search><sort><creationdate>202106</creationdate><title>Assessment of CHADFDM satellite‐based input dataset for the groundwater recharge estimation in arid and data scarce regions</title><author>Salehi Siavashani, Nafiseh ; Jimenez‐Martinez, Joaquin ; Vaquero, Guillermo ; Elorza, Francisco J. ; Sheffield, Justin ; Candela, Lucila ; Serrat‐Capdevila, Aleix</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a3550-e102b806f9dfc754370ebdc0171e4f3e9d6c2835bf83bd9ebfd5bcc2fbc1fc673</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Annual precipitation</topic><topic>Annual rainfall</topic><topic>Aquifer recharge</topic><topic>Aquifers</topic><topic>Arid lands</topic><topic>Arid regions</topic><topic>Arid zones</topic><topic>Atmospheric models</topic><topic>Atmospheric precipitations</topic><topic>CHADFDM data set</topic><topic>Datasets</topic><topic>Decision making</topic><topic>Drought</topic><topic>Field capacity</topic><topic>Ground stations</topic><topic>Groundwater</topic><topic>Groundwater data</topic><topic>Groundwater recharge</topic><topic>Groundwater recharge estimation</topic><topic>groundwater recharge modelling</topic><topic>ground‐satellite meteorological data</topic><topic>Hydrologic systems</topic><topic>Hydrology</topic><topic>Irrigated areas</topic><topic>Irrigated lands</topic><topic>Lake Chad Basin</topic><topic>Lakes</topic><topic>Mean annual precipitation</topic><topic>Meteorological data</topic><topic>Natural recharge</topic><topic>Precipitation</topic><topic>Precipitation-temperature relationships</topic><topic>Rain</topic><topic>Rainfall</topic><topic>Runoff</topic><topic>Runoff estimation</topic><topic>Satellite data</topic><topic>Satellites</topic><topic>Semi arid areas</topic><topic>Temperature</topic><topic>Uncertainty</topic><topic>Water resources</topic><topic>Water resources management</topic><topic>Wilting</topic><topic>Wilting point</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Salehi Siavashani, Nafiseh</creatorcontrib><creatorcontrib>Jimenez‐Martinez, Joaquin</creatorcontrib><creatorcontrib>Vaquero, Guillermo</creatorcontrib><creatorcontrib>Elorza, Francisco J.</creatorcontrib><creatorcontrib>Sheffield, Justin</creatorcontrib><creatorcontrib>Candela, Lucila</creatorcontrib><creatorcontrib>Serrat‐Capdevila, Aleix</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>Wiley-Blackwell Backfiles (Open access)</collection><collection>CrossRef</collection><collection>Aqualine</collection><collection>Environment Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Environment Abstracts</collection><jtitle>Hydrological processes</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Salehi Siavashani, Nafiseh</au><au>Jimenez‐Martinez, Joaquin</au><au>Vaquero, Guillermo</au><au>Elorza, Francisco J.</au><au>Sheffield, Justin</au><au>Candela, Lucila</au><au>Serrat‐Capdevila, Aleix</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Assessment of CHADFDM satellite‐based input dataset for the groundwater recharge estimation in arid and data scarce regions</atitle><jtitle>Hydrological processes</jtitle><date>2021-06</date><risdate>2021</risdate><volume>35</volume><issue>6</issue><epage>n/a</epage><issn>0885-6087</issn><eissn>1099-1085</eissn><abstract>Aquifer natural recharge estimations are a prerequisite for understanding hydrologic systems and sustainable water resources management. As meteorological data series collection is difficult in arid and semiarid areas, satellite products have recently become an alternative for water resources studies. A daily groundwater recharge estimation in the NW part of the Lake Chad Basin, using a soil–plant‐atmosphere model (VisualBALAN), from ground‐ and satellite‐based meteorological input dataset for non‐irrigated and irrigated land and for the 2005–2014 period is presented. Average annual values were 284 mm and 30°C for precipitation and temperature in ground‐based gauge stations. For the satellite‐model‐based Lake Chad Basin Flood and Drought Monitor System platform (CHADFDM), average annual precipitation and temperature were 417 mm and 29°C, respectively. Uncertainties derived from satellite data measurement could account for the rainfall difference. The estimated mean annual aquifer recharge was always higher from satellite‐ than ground‐based data, with differences up to 46% for dryland and 23% in irrigated areas. Recharge response to rainfall events was very variable and results were very sensitive to: wilting point, field capacity and curve number for runoff estimation. Obtained results provide plausible recharge values beyond the uncertainty related to data input and modelling approach. This work prevents on the important deviations in recharge estimation from weighted‐ensemble satellite‐based data, informing in decision making to both stakeholders and policy makers.
Estimation of diffuse recharge by precipitation is highly dependent on climatic data as well as pattern and soil characteristics. In arid and semi‐arid areas, meteorological ground‐based data collection is difficult and satellite products of climatic forcing functions constitute an alternative. For the Lake Chad area, rainfall from satellite overestimates the amount of ground‐based records and shows more variability over time. Recharge rate quantification provided evidence of results from satellite precipitation and allowed the comparison with ground data.</abstract><cop>Hoboken, USA</cop><pub>John Wiley & Sons, Inc</pub><doi>10.1002/hyp.14250</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0001-5075-7317</orcidid><orcidid>https://orcid.org/0000-0002-2063-6490</orcidid><orcidid>https://orcid.org/0000-0002-1659-6334</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Annual precipitation Annual rainfall Aquifer recharge Aquifers Arid lands Arid regions Arid zones Atmospheric models Atmospheric precipitations CHADFDM data set Datasets Decision making Drought Field capacity Ground stations Groundwater Groundwater data Groundwater recharge Groundwater recharge estimation groundwater recharge modelling ground‐satellite meteorological data Hydrologic systems Hydrology Irrigated areas Irrigated lands Lake Chad Basin Lakes Mean annual precipitation Meteorological data Natural recharge Precipitation Precipitation-temperature relationships Rain Rainfall Runoff Runoff estimation Satellite data Satellites Semi arid areas Temperature Uncertainty Water resources Water resources management Wilting Wilting point |
title | Assessment of CHADFDM satellite‐based input dataset for the groundwater recharge estimation in arid and data scarce regions |
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