Geospatial Hydrological Modelling and Linear-Programming Based Optimisation of Water and Land Allocation in a Canal Command Area of Purna Irrigation Project, Maharashtra, India

Sustainable management of surface water resources in large canal command areas requires an integrated understanding of catchment hydrology, crop water demand, canal delivery performance and land-water allocation economics. This study presents an integrated assessment of the Purna Irrigation Project (PIP), a major canal irrigation scheme of the Marathwada region of Maharashtra, India, combining the Soil and Water Assessment Tool (SWAT) with hydraulic performance evaluation and a linear-programming (LP) optimisation framework. The catchment (7784 km²) draining to the Siddheswar reservoir was delineated into four sub-basins and fourteen hydrological response units using a 90 m Shuttle Radar Topography Mission (SRTM) digital elevation model, land-use/land-cover classification and soil textural data prepared in ArcGIS. The model was calibrated (1992–2004) and validated (2005–2013) against observed monthly streamflow using the SWAT-CUP SUFI-2 algorithm, achieving a coefficient of determination (R²) of 0.98 and Nash–Sutcliffe efficiency (NSE) of 0.98 during calibration, and R² of 0.95 with NSE of 0.56 during validation, indicating good-to-very-good model performance as per established rating criteria. Average annual water availability in the reservoir over the 1992–2013 simulation period was 927.72 Mm³, of which 540.92 Mm³ (58.3%) was utilised for irrigation, drinking and lift-irrigation purposes. Crop water requirements were estimated for eleven major crops using the FAO-56 Penman–Monteith approach with stage-wise crop coefficients, and canal delivery performance for the Basmat branch canal was evaluated using adequacy, efficiency, equity, dependability, deficiency and wastage indicators, revealing poor-to-fair system performance (mean adequacy = 0.19; mean efficiency = 0.84; mean equity coefficient of variation = 0.89). A linear-programming model with land and water availability constraints was developed to maximise net benefit across seven cropping-intensity scenarios (10–100%). Results indicate that the existing cropping pattern, operating at 53% cropping intensity and consuming approximately 70% of available reservoir water, generated a net benefit of Rs. 210.67 crores from 30,734 ha, whereas full utilisation of the 57,988 ha command area under the optimised scenario (100% cropping intensity) could nearly double net returns to Rs. 416.00 crores. The study demonstrates that an integrated SWAT–performance-indicator–LP framework provides a transferable, data-efficient decision-support tool for water allocation planning in data-scarce semi-arid canal command areas, and recommends reallocation of area under high-water-consuming, low-return perennial crops (sugarcane, banana) toward higher water-productivity field crops (wheat, gram, cotton, turmeric).