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

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Title A geo-informatics approach for estimating water resources management components and their interrelationships
 
Creator Liaqat, Umar Waqas
 
Contributor Awan, Usman
McCabe, Matthew Francis
Choi, Minha
 
Description 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.
 
Date 2016-09-10
2017-02-22T22:57:40Z
2017-02-22T22:57:40Z
 
Type Journal Article
 
Identifier https://mel.cgiar.org/reporting/download/hash/8dejH5Oc
Umar Waqas Liaqat, Usman Awan, Matthew Francis McCabe, Minha Choi. (10/9/2016). A geo-informatics approach for estimating water resources management components and their interrelationships. Agricultural Water Management, 178, pp. 89-105.
https://hdl.handle.net/20.500.11766/5864
Limited access
 
Language en
 
Rights CC-BY-NC-4.0
 
Format PDF
 
Publisher Elsevier Masson
 
Source Agricultural Water Management;178,(2016) Pagination 89-105