The hydrological conditions upstream of the Ciliwung watershed are changing due to climate and land-use changes. Any changes in this area may increase the flood frequencies which may have countless consequences downstream of the watershed where the Jakarta city is located. We simulated the effects of land-use and climate changes on flooding (e.g., peak flow and river discharge) in the upper Ciliwung River basin in Greater Jakarta, Indonesia. Hydrologic Modeling System (HEC-HMS), a rainfall-runoff simulation model, was used to simulate peak river discharge values for current and future conditions. The model was calibrated and validated based on the observed river discharge data from February 2007 and January 1996, respectively. The statistical analysis showed that the performance of the model is satisfactory, with Nash–Sutcliffe efficiency 0.64 and 0.58 for calibration and validation, respectively. The coefficients of determination values are 0.86 and 0.82, respectively. The effect of the projected land-use changes alone in 2030 increased the peak flow by approximately 20%. When considering the land-use changes in conjunction with the future climate scenario, the peak flow based on the precipitation corresponding to a 50-year return period in 2030 increased by 130%. Based on the results of this study, it is urgent that a flood management plan be implemented in the target area to reduce flooding in the near future.

The A-Luoi district in Thua Thien Hue province of Vietnam is under extreme pressure from natural and anthropogenic factors. The area is ungauged and suffering from data scarcity. To evaluate the water resources availability and water management, we used Soil and Water Assessment Tools (SWAT). A multi-approach technique was used to calibrate the hydrological model. The model was calibrated in three time scales: daily, monthly and yearly by river discharge, actual evapotranspiration (ETa) and crop yield, respectively. The model was calibrated with Nash-Sutcliffe and R² coefficients greater than 0.7, in daily and monthly scales, respectively. In the yearly scale, the crop yield inside the model was calibrated and validated with Root Mean Square Error (RMSE) less than 2.4 ton/ha. The water resource components were mapped temporally and spatially. The outcomes showed that the highest mean monthly surface runoff, 323 to 369 mm, between September and November, resulted in extreme soil erosion and sedimentation. The monthly average of actual evapotranspiration was the highest in May and lowest in December. Furthermore, installing “Best Management Practices” (BMPs) reduced surface runoff in agricultural lands. However, using event-based hydrological and hydraulic models in the prediction and simulation of flooding events is recommended in further studies.

The semi-arid regions of Iran have experienced severe water resources stress due to natural (e.g., drought) and anthropogenic (e.g., depletion of water in various sectors) factors. Assessing the impact of climate change on water resources and crop production could significantly help toward better water management and hence prevention of land degradation in this area. A hydrological model of the Razan–Ghahavand basin was used as a representative case study of a semi-arid region of Iran. Future climate scenarios in the mid-21st century were generated from four global circulation models (GCMs) with three scenarios under the fourth assessment report of Intergovernmental Panel on Climate Change emission projections. The GCMs have been downscaled based on observed data at 10 climate stations across the basin. The results showed that for the basin as a whole, the mean annual precipitation is likely to decrease while the maximum temperature increases. The changes in these two climate variables resulted in substantial reduction in groundwater recharge as the main source of water supply in this area. Furthermore, soil water content was decreased which resulted in the reduction of crop yield in rain-fed areas. Indeed, the risk of drought in the south and flooding in the north was high.