Assessing Climate-Smart Land Suitability for Cotton Cultivation in South Punjab: A GIS-Based Perspective

Cotton plays a vital role in Pakistan's textile industry and is becoming vulnerable to heat, aridity, soil degradation and water scarcity. In this study, a climate responsive land suitability model was developed in the Dera Ghazi Khan, Multan and Bahawalpur divisions in South Punjab using a GIS-based Analytic Hierarchy Process (AHP) for land suitability analysis. The following criteria were considered: aridity index, soil organic carbon (SOC), precipitation in the sowing period, May air temperature, and soil pH. Raster layers were projected to WGS 84/UTM Zone 43N using a 30 m analysis grid, were standardized to dimensionless suitability scores, and then summed using a weighted linear combination. The geometric mean was used to combine the judgments of eight experts in the fields of agronomy, soil science, climatology and GIS. Aridity (0.30), SOC (0.20), precipitation (0.18), temperature (0.17) and pH (0.15) were the final weights, with a reported consistency ratio of 0.09. Four analytical classes were developed. Dera Ghazi Khan (38%) had maximum percentage of highly suitable land followed by Multan (32%) and Bahawalpur (24%). The changes in divisional class shares between the baseline and a ±10% one at a time perturbation of the criterion weights by no more than 5 percentage points were considered reasonable for rank stability. The findings include Priority Adaptation Measures such as restoring soil carbon, efficient irrigation, and managing at the site level. The framework offers a clear screening tool during the provincial planning process and should be supported with irrigation, groundwater, farm-management, socioeconomic and field-validation data prior to making plot-level investment decisions.