The increasing demands of the population and the need for development obliged the optimal use and adaptive management of the watershed resources. Accordingly, it is necessary to adopt comprehensive measures to reach sustainable development goals. This objective can be achieved by the application of interdisciplinary and professional approaches through establishing dynamic and optimal balance in supply and demand resources. However, such important optimization approaches have been rarely practiced at the watershed scale. The present study has been therefore formulated to apply a linear water-energy-food nexus optimization for the Shazand watershed, Markazi Province, Iran. This approach was applied for planning 14 crops planted in orchard, irrigated farms, and rain-fed farms, between 2006 and 2014, and targeting water-energy-food nexus index (WEFNI) maximization. The connections among the water, energy, and food were then evaluated through determining the amount of consumption, mass productivity, and economic productivity of water and energy. The results of WEFNIs revealed that almond has the highest WEFNI with values of 0.92, 0.76, 0.76, 0.83, 0.86, 0.86, 0.87, 0.87, and 0.88. Whilst, potato with WEFNI of 0.05, 0.05, 0.05, 0.06, 0.09, 0.10 and 0.11, sugar cane with WEFNI of 0.10 and cucumber with WEFNI of 0.13 had the lowest scores and the corresponding lowest performance among the study crops. The outcomes of optimization study explained that the current situation of land use in the Shazand Watershed is unsuitable to minimize water and energy consumption and maximize benefit. The results can be used as an effective tool for designating proper soil and water resource management strategies in the region.

Groundwater pollution with nitrate of agricultural origin is a major problem in many countries. A great deal of effort is focused on finding ways to reduce leaching from agricultural land. In this study, different land management scenarios were evaluated with the SWAT model in order to determine which are the most effective in reducing nitrate leaching on specific soil types in the Krška kotlina alluvial plain (Slovenia). The area is very important both for agriculture production and drinking water resources. The model was calibrated for three soil moisture field trial sites, each representing one major soil type of the area. Simulated soil moisture values were in good agreement with the observed values (PBIAS (percent bias) ±25%). Of the nine land management scenarios that were evaluated, vegetable rotation caused the most nitrate leaching on all soil types, but it fared better on Cambisol than on Fluvisol. Orchards on the other hand leached the least amount of nitrate, but also fared better on Cambisol. Presented studies should be considered as a preliminary stage in the study of nitrate pollution in the investigated area. Results show that nitrate leaching varies for different land management scenarios on different soil types. Further work should concentrate on field trials to evaluate the impacts of reduced fertilization on nitrate leaching and both crop yield and quality on different soil types.