A geo-informatics approach for estimating water resources management components and their interrelationships

Handle URI:
http://hdl.handle.net/10754/620902
Title:
A geo-informatics approach for estimating water resources management components and their interrelationships
Authors:
Liaqat, Umar Waqas ( 0000-0001-9027-5232 ) ; Awan, Usman Khalid; McCabe, Matthew ( 0000-0002-1279-5272 ) ; Choi, Minha
Abstract:
A remote sensing based geo-informatics approach was developed to estimate water resources management (WRM) components across a large irrigation scheme in the Indus Basin of Pakistan. The approach provides a generalized framework for estimating a range of key water management variables and provides a management tool for the sustainable operation of similar schemes globally. A focus on the use of satellite data allowed for the quantification of relationships across a range of spatial and temporal scales. Variables including actual and crop evapotranspiration, net and gross irrigation, net and gross groundwater use, groundwater recharge, net groundwater recharge, were estimated and then their interrelationships explored across the Hakra Canal command area. Spatially distributed remotely sensed estimates of actual evapotranspiration (ETa) rates were determined using the Surface Energy Balance System (SEBS) model and evaluated against ground-based evaporation calculated from the advection-aridity method. Analysis of ETa simulations across two cropping season, referred to as Kharif and Rabi, yielded Pearson correlation (R) values of 0.69 and 0.84, Nash-Sutcliffe criterion (NSE) of 0.28 and 0.63, percentage bias of −3.85% and 10.6% and root mean squared error (RMSE) of 10.6 mm and 12.21 mm for each season, respectively. For the period of study between 2008 and 2014, it was estimated that an average of 0.63 mm day−1 water was supplied through canal irrigation against a crop water demand of 3.81 mm day−1. Approximately 1.86 mm day−1 groundwater abstraction was estimated in the region, which contributed to fulfil the gap between crop water demand and canal water supply. Importantly, the combined canal, groundwater and rainfall sources of water only met 70% of the crop water requirements. As such, the difference between recharge and discharge showed that groundwater depletion was around −115 mm year−1 during the six year study period. Analysis indicated that monthly changes in ETa were strongly correlated (R = 0.94) with groundwater abstraction and rainfall, with the strength of this relationship significantly (p < 0.01 and 0.05) impacted by cropping seasons and land use practices. Similarly, the net groundwater recharge showed a good positive correlation (R) of 0.72 with rainfall during Kharif, and a correlation of 0.75 with canal irrigation during Rabi, at a significance level of p < 0.01. Overall, the results provide insight into the interrelationships between key WRM components and the variation of these through time, offering information to improve the management and strategic planning of available water resources in this region.
KAUST Department:
Division of Biological and Environmental Sciences and Engineering; Water Desalination & Reuse Research Cntr
Citation:
Umar Waqas Liaqat, Usman Khalid Awan, Matthew Francis McCabe, Minha Choi, A geo-informatics approach for estimating water resources management components and their interrelationships, Agricultural Water Management, Volume 178, December 2016, Pages 89-105, ISSN 0378-3774, http://dx.doi.org/10.1016/j.agwat.2016.09.010.
Publisher:
Elsevier BV
Journal:
Agricultural Water Management
Issue Date:
21-Sep-2016
DOI:
10.1016/j.agwat.2016.09.010
Type:
Article
ISSN:
0378-3774
Sponsors:
This research was supported by Space Core Technology Development Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (NRF-2014M1A3A3A02034789). Matthew McCabe was supported by the King Abdullah University of Science and Technology, Saudi Arabia. The authors acknowledge the various NASA services for providing free and unrestricted access to MODIS products.
Additional Links:
http://www.sciencedirect.com/science/article/pii/S037837741630347X
Appears in Collections:
Articles

Full metadata record

DC FieldValue Language
dc.contributor.authorLiaqat, Umar Waqasen
dc.contributor.authorAwan, Usman Khaliden
dc.contributor.authorMcCabe, Matthewen
dc.contributor.authorChoi, Minhaen
dc.date.accessioned2016-10-11T06:01:59Z-
dc.date.available2016-10-11T06:01:59Z-
dc.date.issued2016-09-21-
dc.identifier.citationUmar Waqas Liaqat, Usman Khalid Awan, Matthew Francis McCabe, Minha Choi, A geo-informatics approach for estimating water resources management components and their interrelationships, Agricultural Water Management, Volume 178, December 2016, Pages 89-105, ISSN 0378-3774, http://dx.doi.org/10.1016/j.agwat.2016.09.010.en
dc.identifier.issn0378-3774-
dc.identifier.doi10.1016/j.agwat.2016.09.010-
dc.identifier.urihttp://hdl.handle.net/10754/620902-
dc.description.abstractA remote sensing based geo-informatics approach was developed to estimate water resources management (WRM) components across a large irrigation scheme in the Indus Basin of Pakistan. The approach provides a generalized framework for estimating a range of key water management variables and provides a management tool for the sustainable operation of similar schemes globally. A focus on the use of satellite data allowed for the quantification of relationships across a range of spatial and temporal scales. Variables including actual and crop evapotranspiration, net and gross irrigation, net and gross groundwater use, groundwater recharge, net groundwater recharge, were estimated and then their interrelationships explored across the Hakra Canal command area. Spatially distributed remotely sensed estimates of actual evapotranspiration (ETa) rates were determined using the Surface Energy Balance System (SEBS) model and evaluated against ground-based evaporation calculated from the advection-aridity method. Analysis of ETa simulations across two cropping season, referred to as Kharif and Rabi, yielded Pearson correlation (R) values of 0.69 and 0.84, Nash-Sutcliffe criterion (NSE) of 0.28 and 0.63, percentage bias of −3.85% and 10.6% and root mean squared error (RMSE) of 10.6 mm and 12.21 mm for each season, respectively. For the period of study between 2008 and 2014, it was estimated that an average of 0.63 mm day−1 water was supplied through canal irrigation against a crop water demand of 3.81 mm day−1. Approximately 1.86 mm day−1 groundwater abstraction was estimated in the region, which contributed to fulfil the gap between crop water demand and canal water supply. Importantly, the combined canal, groundwater and rainfall sources of water only met 70% of the crop water requirements. As such, the difference between recharge and discharge showed that groundwater depletion was around −115 mm year−1 during the six year study period. Analysis indicated that monthly changes in ETa were strongly correlated (R = 0.94) with groundwater abstraction and rainfall, with the strength of this relationship significantly (p < 0.01 and 0.05) impacted by cropping seasons and land use practices. Similarly, the net groundwater recharge showed a good positive correlation (R) of 0.72 with rainfall during Kharif, and a correlation of 0.75 with canal irrigation during Rabi, at a significance level of p < 0.01. Overall, the results provide insight into the interrelationships between key WRM components and the variation of these through time, offering information to improve the management and strategic planning of available water resources in this region.en
dc.description.sponsorshipThis research was supported by Space Core Technology Development Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (NRF-2014M1A3A3A02034789). Matthew McCabe was supported by the King Abdullah University of Science and Technology, Saudi Arabia. The authors acknowledge the various NASA services for providing free and unrestricted access to MODIS products.en
dc.language.isoenen
dc.publisherElsevier BVen
dc.relation.urlhttp://www.sciencedirect.com/science/article/pii/S037837741630347Xen
dc.rights© <2016>. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectSEBSen
dc.subjectSEBSen
dc.subjectGroundwater abstractionen
dc.subjectGroundwater rechargeen
dc.subjectremote sensingen
dc.titleA geo-informatics approach for estimating water resources management components and their interrelationshipsen
dc.typeArticleen
dc.contributor.departmentDivision of Biological and Environmental Sciences and Engineeringen
dc.contributor.departmentWater Desalination & Reuse Research Cntren
dc.identifier.journalAgricultural Water Managementen
dc.eprint.versionPost-printen
dc.contributor.institutionDepartment of Civil and Environmental Engineering, College of Engineering, Hanyang University, Seoul 133-791, Republic of Koreaen
dc.contributor.institutionInternational Center for Agricultural Research in the Dry Areas (ICARDA), Cairo, Egypten
dc.contributor.institutionWater Resources and Remote Sensing Laboratory, Department of Water Resources, Graduate School of Water Resources, Sungkyunkwan University, Suwon 440-746, Republic of Koreaen
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
kaust.authorLiaqat, Umar Waqasen
kaust.authorMcCabe, Matthew Francisen
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