Abstract
The soil moisture level effectively estimates the extremity of irrigation demand, and thus acts as a significant indicator of irrigation water management. In recent time due to increase in population, demand for freshwater in all competing sectors is being a constraint for irrigation that raises the need to optimise utilisation of irrigation water with its high efficiency. Therefore, an accurate and precise assessment of soil moisture content (SMC) is required for optimal allocation and management of water in agriculture. Owing to this, the current study aims to simulate SMC from water balance–based macro-scale Variable Infiltration Capacity (VIC) hydrological model for various applications in irrigation water management. The current study was carried out in the Bundelkhand region of Uttar Pradesh, India, for a period of 5years (2010–14). The simulated SMC was validated with ESA Climate Change Initiative soil moisture (CCI-SM) indicated high R2 value ranging from 0.73 to 0.90 and low RMSE value ranging from 0.03 to 0.05 m3m−3. The dataset of simulated and CCI-SM content values was close to the 1:1 scale line for approximately all the periods. Additionally, the Soil Moisture Deficit Index (SMDI), a dryness index, was computed for estimating irrigation demand from VIC-derived SMC for Kharif season (July–October) from 2010 to 2014; this shows more irrigation water demand in 2014 and sowing period of 2010 and 2012.
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