Integrating Gravimetry Data with Thermal Infra-Red Data from Satellites to Improve Efficiency of Ope...

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" Integrating Gravimetry Data with Thermal Infra-Red Data from Satellites to Improve Efficiency of Operational Irrigation Advisory in South Asia "
Bose, Indira Hossain, Faisal

Document Type	:	Latin Dissertation
Language of Document	:	English
Record Number	:	1057605
Doc. No	:	TL56722
Main Entry	:	Bose, Indira
Title & Author	:	Integrating Gravimetry Data with Thermal Infra-Red Data from Satellites to Improve Efficiency of Operational Irrigation Advisory in South Asia\ Bose, IndiraHossain, Faisal
College	:	University of Washington
Date	:	2020
Degree	:	Master's
student score	:	2020
Note	:	79 p.
Abstract	:	The rapid decline of groundwater resources in South Asia due to excessive irrigation during dry season requires awareness of optimal on-field water allocation requirements that is now being provided to farmer cellphones through an operational Irrigation Advisory System (IAS). To minimize the cost of sending such irrigation advisory texts to farmers while maximizing impact of IAS on groundwater sustainability we integrated Gravity Recovery and Climate Experiment (GRACE) data with Landsat Thermal Infrared (TIR) Imagery to target regions in greater need of the IAS service. We demonstrated the concept of an improved IAS with the integration of GRACE and Landsat TIR data over eight irrigation districts of the Ganges and Indus basins. The Surface Energy Balance Algorithm for Land (SEBAL) was used to monitor on-field water consumption (evapotranspiration-ET) over cropped areas using Landsat TIR data at plot-scale spatial resolution. Comparison of SEBAL ET with crop water demand from Penman-Monteith (FAO56) technique quantified the extent of over-irrigation at the plot scale and provided a tangible pathway to micro-target the IAS service only to farmers with the largest groundwater use footprint, thereby maximizing the efficiency of the IAS service. Our results suggested that an operational IAS that integrates GRACE and Landsat TIR data on average can save about 85% (80 million m3) of groundwater per dry season for irrigation districts of Northern India and 87% (or 150 million m3) per year for irrigation districts of Eastern Pakistan. Our proposed enhanced IAS will also allow continuous monitoring of farmer behavioral change in reducing over-irrigation and long-term impact on groundwater resources with need-based irrigation practices via follow up assessment of GRACE TWS (after dry season) and TIR data (during dry season).
Descriptor	:	Agriculture
	:	Civil engineering
	:	Remote sensing
	:	South Asian studies
Added Entry	:	Hossain, Faisal
Added Entry	:	University of Washington