Spatiotemporal analysis of crop water requirements in Lower Chenab Canal (LCC) Irrigation System for the better management of water resources

Agriculture production in Pakistan mainly depends on irrigation water, and about 90% of production relies on irrigation water. For better assessment and management of irrigation water requirements, an accurate estimation of evapotranspiration (ET) from agriculture area is essential. Also, ET is a key climate variable linking water, energy, and carbon cycles. Conventional ET measurement techniques are point-based and representative of the local scale only. Satellite remote sensing with large area coverage and high temporal frequency provides measurements of several relevant biophysical parameters required for estimation of ET at regional scales. This study uses the Surface Energy Balance System (SEBS) model to calculate the daily actual ET (ET a ) across the Lower Chenab Canal (LCC) irrigation system using the MODIS data for clouds-free days. Land cover classification was used to study the temporal changes in ET for different crops. There is no flux tower in the study area for direct measurement of latent heat flux and sensible heat flux; SEBS model-derived ET a values were evaluated against reference crop ET (ET o ) that were calculated using FAO-56 Penman-Monteith method. SEBS-based ET a values were found to be lower compared to the referenced ET (ET o ). Higher ET o values were observed for a hypothetical reference crop that is well-watered and disease-free, unlike actual field conditions. Results showed ET a values are much closer to ET o in the winter season with the mean difference of 0.36 mm/day, while in the summer season, the mean difference was 1.5 mm/day. This study shows the potential of remote sensing–based derived ET a at high spatial and temporal resolution over heterogeneous crops instead of the point-based estimation methods. Mapping ET is also helpful for better understanding of hydrological processes because it is a major loss and its spatial and temporal quantification can help in water regulation and equitable distribution.