Satellite-informed simulation of irrigation in South Asia: opportunities
The irrigated area expansion in South Asia brings challenges to water
resources management, and the combination of irrigation and climatic
variability has caused periodic water shortages in many parts of the
region. In this context, monitoring and predicting the influences of
irrigation and water extraction on the water balance has become
increasingly important for local governments and decision-makers. In
this study, we apply a demand-driven irrigation scheme to an existing
hydrological monitoring system that uses the Noah-MultiParameterization
land surface model within the NASA Land Information System framework.
Including prognostic simulation of irrigation generally improves the
simulated ET compared to diagnostic satellite-based products, though
uncertainty in observations limits the confidence of this conclusion.
Results for soil moisture were mixed, with improved agreement with
observation in Pakistan but degraded in parts of India. Including
irrigation has a significant benefit in the simulation of groundwater
depletion compared to in-situ and satellite-derived observations.
Additionally, a sensitivity analysis is carried out to study the
relative contribution of different input combinations to the
hydrological cycle. These input combinations include choices of
precipitation, soil texture, irrigation fraction map, groundwater
fraction of irrigation, and greenness vegetation fraction (GVF)
estimates. The results indicate that irrigation estimation and ET is
most sensitive to irrigation fraction and soil texture datasets while
the simulated soil moisture is more sensitive to soil texture datasets
and the GVF approach. The study highlights the need to generate more
consistent and reliable irrigation parameter datasets by incorporating
local or remote sensing-based measurements for South Asia.