This study assessed the climate resilience and characterized the existing farming systems in steep terrain in the hilly regions in South Asia. The farming systems considered were at an elevation ≥300 m in the mountain regions of two sites from Sri Lanka (Hatton and Welimada) and one site each from Bangladesh (Chittagong) and Nepal (Jhikhu Khola). A Climate Resilience Index (CRIi) score, varying from 0 (negligible resilience) and 1 (very high resilience), was calculated for each household using 31 parameters under Adaptive Capacity (ADC), Absorptive Capacity (ABC) and Transformative Capacity (TC). To spatially represent the CRIi, the four study locations were mapped using Inverse Distance Weighted (IDW) interpolation technique of GIS. All 424 households in the study sites scored a CRIi between 0.36 and 0.76, while the average CRI was the highest in Hatton (0.67), followed by Welimada (0.60), Jhikhu Khola (0.59) and Chittagong (0.48). Different demographic, socioeconomic and environmental parameters have contributed to the level of climate resilience of farming system units. Identification of good management practices of the climate-resilient farming systems and implementing those practices in vulnerable systems would increase the resilience and well-being of farming communities in steep terrain of mountain regions in South Asia.

Actual Evapotranspiration (AET) is a major component of the river basin hydrological cycle over land surface and energy balances. More than 60% of input water on land is returned to the atmosphere through evapotranspiration and it greatly influences the water availability on the land surface. Estimation of AET is an essential part in various fields. Thus, this study mainly aims at assessing the impact of urbanization-associated land use changes on actual evapotranspiration and water balance in the Kelani River Basin, Sri Lanka. Thronthwaite equation and land use conditions are mainly considered in this study to estimate AET. Average monthly temperature data has been obtained from NASA MOD1C3 and data has been validated using observed temperature data processed by the Meteorological Department in Sri Lanka. Potential Evapotranspiration (PET) was calculated using monthly average temperature and fractional vegetation cover was calculated using Landsat images (TM, ETM and OLI) to identify the land use and land cover changes from year 2000 to 2018. Both potential evapotranspiration and fractional vegetation cover are used to estimate AET. TRRM data was used to get Digital Elevation Model (DEM) and Landsat images were used to calculate Normalized Differential Vegetation Index (NDVI), Normalized Differential Building Index (NDBI). All the analysis used in this study have been carried out using raster calculator, zonal statistics and pivot tools in ArcGIS 10.1 software. The study revealed that land use and land cover is a major fact to determine AET. Upper catchment of Kelani River has obtained high AET values due to the vegetation cover and the elevation. Lower part of the catchment is associated with the low values due to build - up areas. AET has decreased by 2018 and urbanization is the main reason for it. Rainy seasons reduce the AET since high humidity and reducing AET can be highlighted when considering the temporal changes of AET in Kelani river basin. Evapotranspiration as a major component of water cycle should be considered because it can be a significant fact to reduce precipitation. Keywords Evapotranspiration; AET; PET; NDVI; NDBI DOI: https://doi.org/10.23953/cloud.ijarsg.440

The agricultural sector faces increasing vulnerability to climate change, necessitating effective adaptation measures to maintain productivity and enhance system resilience. Despite this critical need, limited studies explore the factors influencing farmers’ adaptive responses within specific climatic zones. This study aimed to identify adaptation measures essential for agricultural sustainability in the three purposively selected Grama Niladari divisions (GNDs) known for their diverse crop varieties in the Maho Agrarian Zone, a region characterised by the Maha (Northeast Monsoon) and Yala (Southwest Monsoon) agricultural seasons. A mixed-methods descriptive research design, integrating quantitative surveys and qualitative focus group data, was employed. The findings reveal a highly experienced farming community: 34.9% of farmers have over 30 years of farming experience. A total of 96.7% of farmers reported noticing changes, including a shift in seasons (over 80%) and unpredictable rainfall patterns (53%). A vast majority (62.8%) of farmers lack access to agricultural insurance, leaving them financially exposed to crop losses. Furthermore, while younger and middle-aged groups demonstrated the highest awareness of climate-smart agriculture (CSA), there is a strong, consistent perception across all age groups that government and associated institutions are not providing sufficient support for adaptation efforts. The results offer actionable recommendations for empowering local planning authorities, optimising climate communication strategies, and prioritising the development of practical CSA training modules, ultimately synthesising local knowledge with expert insight to support global resilience-building initiatives.