Water scarcity has emerged as a major environmental challenge in rain shadow regions of mountainous areas worldwide. The Hindu Kush–Karakorum–Himalaya, although recognized as one of the world’s major “water towers”, is experiencing increasing water scarcity due to climate change and rapid population growth, threatening ecosystems, economies, and livelihoods. The Chitral River basin in northwestern Pakistan is a snow-dominated watershed where meltwater and seasonal precipitation generate substantial runoff during spring, followed by prolonged periods of acute water scarcity. Water harvesting represents a potential strategy for sustainable water resource management in this region. This study employed a hybrid approach combining Multi-Criteria Decision Analysis (MCDA), based on Analytical Hierarchy Process (AHP), with geospatial techniques to identify potentially suitable locations for rainwater and snowmelt harvesting (RSH). The results indicate that Chitral can be divided into four RSH suitability classes: very highly suitable (19.1%), highly suitable (43.8%), moderately suitable (22.1%), and less/non-suitable (15.0%). Evaluation of the suitability map using existing water-harvesting structures, satellite imagery, field observations, and expert and local resident interviews demonstrated the robustness of the methodology. The findings provide a spatial framework to support stakeholders in identifying suitable sites for RSH and contribute to the scientific basis for sustainable water management and climate change adaptation. The approach can also be adapted to other mountainous basins with similar hydroclimatic and geomorphological characteristics.
Soil erosion is one of the most serious environmental concerns of our time, leading to land degradation, agricultural inefficiency, reservoir siltation, and ecological imbalance. Thus, a thorough assessment of soil erosion is crucial whilst developing and implementing any conservation strategies and measures. In this context, the present research aims to estimate Soil Loss (SL) and Sediment Yield (SY) in the Chami Qeshan Watershed (CQW) between Iraq and Iran using the integrated application of the Revised Universal Soil Loss Equation (RUSLE) and Sediment Delivery Ratio (SDR) techniques. In addition to rain gauge observations, three satellite-derived precipitation datasets were applied for calculating the rainfall–runoff erosivity (R) variable of RUSLE, namely the Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS), the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), and the Tropical Rainfall Measuring Mission (TRMM). We also considered four other key factors for predicting soil erosion: soil erodibility (K), slope length and steepness (LS), cover management (C), and conservation practice (P). Ultimately, we used the Pearson correlation to statistically evaluate relationships between input variables and soil erosion outcomes. Results revealed substantial differences among the implemented products, where CHIRPS provided the best reproduction of annual precipitation. Likewise, the CHIRPS-based RUSLE-SDR model reproduced the closest mean soil loss of 12.18 t·ha−1·yr−1 and total outlet sediment yield of 51,826 t·yr−1 to the corresponding gauge-driven model estimates. The correlation analysis found moderate associations between modeled soil loss estimates and LS (r = 0.56–0.57), C (r = 0.50–0.61), and P (r = 0.48–0.63) variables. Given the direct influence of precipitation products on rainfall erosivity and RUSLE–SDR estimates, native-resolution sensitivity analyses and alternative interpolation schemes are recommended to assess result robustness.
Urban agriculture (UA) is increasingly recognized as a strategic approach to enhance food security and urban resilience, particularly in arid regions like the United Arab Emirates (UAE). This mixed-methods study investigates how public perceptions shape the acceptance and promotion of UA in the Abu Dhabi Emirate, addressing a critical gap in the social dimensions of UA implementation. The research employed a concurrent triangulation design, integrating a quantitative survey of 255 residents with qualitative insights from a focus group of 15 urban planning and sustainability experts. Quantitative data were analyzed using confirmatory factor analysis to validate constructs of public perception and policy support, while qualitative data were thematically analyzed. The findings reveal a significant, positive correlation (r = 0.64, p < 0.001) between public awareness of UA’s benefits and support for policy integration. While residents expressed strong enthusiasm for UA, their willingness to participate was contingent upon tangible government incentives. Concurrently, experts highlighted critical technical and regulatory barriers, including water scarcity and outdated zoning codes, that must be addressed. The study concludes that advancing UA in Abu Dhabi requires a synergistic policy approach that aligns robust public support with targeted institutional mechanisms, such as subsidies for water-efficient technologies and the formal integration of UA into urban planning frameworks. This research contributes valuable empirical evidence for developing socially accepted and context-specific UA policies in arid urban environments. Given the cross-sectional design and non-probability sampling approach, the findings should be interpreted as exploratory and should not be generalized to the entire Abu Dhabi population.
The village of Hogsback is in an Afromontane region in the Eastern Cape province and caters to nature-based, winter, and cultural tourism markets. This research used mixed methods to explore the trends and variability of the microclimate of Hogsback and linked them to an investigation of the resilience of the local economy. Local temperature, rainfall, and snowfall data were utilized for the climatic analysis. Climatic data revealed an increase in total annual hot days, total annual rainfall, and rainfall days. Interannual variability in total annual rainfall was shown to be increasing. Total annual snow days declined but displayed high levels of interannual variability. Semi-structured interviews with local tourism businesses found that this climate variation could pose a threat to many local tourism activities and events. Although some resilience was already fostered, greater collaboration, cooperation, and partnerships were identified as areas for building future resilience.
This study evaluated the planning relevance of biophysical land suitability for rubber plantation in a hilly landscape of Central Vietnam. A GIS-based square-root parametric method calculated a land suitability index (LSI) using elevation, slope, annual rainfall, soil depth, soil texture, and soil type. LSI values ranged from 0 to 77.67. Highly and moderately suitable land covered 38.79 ha (0.31%) and 3986.01 ha (31.83%), respectively, with soil depth and texture as important constraints. Overlay with the 2023 land-use map showed that biophysical suitability did not directly indicate practical land availability. Planted forest occupied 38.16 ha, or 98.38%, of the highly suitable class, and no existing rubber plantations occurred in this class. In contrast, 49.27% of existing rubber plantations occurred in the moderately suitable class. After excluding planted forest, paddy rice land, and existing rubber plantations from the 4024.80 ha classified as highly or moderately suitable, only 251.46 ha remained in unused land and annual cropland for further assessment. Data from 45 PB260 plantations showed a positive association between LSI and fresh latex yield after adjustment for the other variables in the multiple regression model, with an adjusted partial regression coefficient of 2.09 kg ha−1 year−1 per LSI unit (p = 0.016). Thus, suitability maps should not be used as expansion maps without considering current land use, practical land availability, and plantation performance.
