Climate change poses a significant challenge to global food security and agricultural sustainability, making innovative solutions essential. Integrating geospatial technologies into agricultural planning and management provides better opportunities to advance Climate-Smart Agriculture (CSA). This review examines the role of geospatial technologies, such as Geographic Information Systems (GIS), Remote Sensing (RS), and Global Navigation Satellite System (GNSS), in enhancing decision-making, optimising resource use, and building resilience. Spatial Data Infrastructures (SDIs) facilitate the exchange of information and enhance preventive and emergency plans in agriculture. Farmers can engage in the process through Volunteered Geographic Information (VGI) applications. Case studies from South Asia demonstrate how geospatial data and tools facilitate climate risk assessment, crop modelling, and precision agriculture. Real-time data monitoring and Early Warning Systems (EWSs) manage extreme weather events and adapt to changing climatic conditions. Integrating geospatial technologies in CSA enhances productivity and profitability, contributing to sustainable and resilient agriculture in the face of a changing climate. This article underscores the need for continued research and investment in geospatial technologies to support CSA practices, ensuring food security in a warming world.

The monsoon season in Nepal brings calamitous events like riverbank erosion, toe cutting, and the structural failure of bridges due to floods. In July 2021, a motorable bridge in Bhadgaun, Tanahun district, Nepal, collapsed during a massive flood in Chhabdi Khola. The study aims to comprehensively document the aftermath, specifically focusing on the causal factors that led to the damage of the Chhabdi Khola Dovan Bridge. The study delves into an in-depth analysis of the stream's channel morphology, with the 5.85 kilometers Chhabdi Khola partitioned into 28 distinct segments, each spanning approximately 200 meters. These segments, sequentially labeled from Site 1 to Site 28, encompass the area extending from the upstream at Chhabdi Barah temple to the downstream at bridge’s location. Rigorous measurements of length, breadth, and depth at each site form the basis for volumetric assessments of the stream. The study revolves around contrasting paleo channel attributes with contemporary alterations within the Chhabdi Khola catchment. The analysis leverages precipitation data sourced from the Department of Hydrology and Meteorology (DHM) to discern precipitation trends within the Chhabdi Khola catchment area. The hydrographic data underwent trend analysis utilizing Mann-Kendall and Sen's slope method through R software (version 4.3.2). The collapse of the Chhabdi Khola Dovan Bridge resulted from intense water flow and debris due to heavy rainfall and a narrow outlet near the bridge, impacting the local population and land users facing the enduring aftermath of a catastrophic monsoon event. The study highlights the significance of understanding river dynamics in small streams and advocates for proactive disaster preparedness measures, even in seemingly small river channels.

Flood is one of the most common hazards in Nepal that have a severe socio-economic effect especially in Himalayan basins that are dominated by monsoons. In this study, we constructed the rainfall thresholds of flood early warning in the Babai River Basin (BRB) by using a calibrated and validated Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) rainfall-runoff model. The model showed good performance, with the calibration values of NSE = 0.84, R² = 0.87, and PBIAS = − 5.6%, and validation values of NSE = 0.78, R² = 0.81, and PBIAS = − 7.9%. The historical flood occurrences and rain data (1990–2018) were examined at Chepang (mid-basin) and Bhada Bridge (basin outlet). The findings indicate that cumulative rainfall and peak discharge have a significant positive association, and amplified downstream runoff is by virtue of integrated basin runoff. The rainfall thresholds were calculated to obtain bankfull, warning, and danger levels of the river for 1-day, 3-day, and 5-day accumulations. Chepang had 105–110 mm of bankfull, 135–140 mm of warning, and 200–205 mm of danger levels, and the Bhada Bridge needed higher thresholds of 140–145 mm, 185–190 mm, and 240–245 mm for bankfull, warning, and danger, respectively. These thresholds provide a practical advice on anticipatory flood management in addition to current stage-based monitoring. Although the downstream discharge information is not well known and there may be some land-use and climate shifts, the study provides a feasible model of improving early warning of floods in the Himalayan basins. Communities at floods risk are ensured safer and more resilient with real time monitoring combined with risk-based planning.