Model Uncertainty Analysis Methods for Semi-Arid Watersheds with Different Characteristics: A Comparative SWAT Case Study

Simulating the land use change effects on non-point source pollution in the Duliujian River Basin

The uncertainty in the generation and formation of non-point source pollution makes it challenging to monitor and control this type of pollution. The SWAT model is frequently used to simulate non-point source pollution in watersheds and is mainly applied to natural watersheds that are less affected by human activities. This study focuses on the Duliujian River Basin (Xiqing section), which is characterized by a dense population and rapid urbanization. Based on the calibrated SWAT model, this study analyzed the effects of land use change on non-point source pollution both temporally and spatially. It was found that nitrogen and phosphorus non-point source pollution load losses were closely related to land use type, with agricultural land and high-density urban land (including rural settlements) being the main contributors to riverine nitrogen and phosphorus pollution. This indicates the necessity of analyzing the impact of land use changes on non-point source pollution loads by identifying critical source areas and altering the land use types that contribute heavily to pollution in these areas. The simulation results of land use type changes in these critical source areas showed that the reduction effect on non-point source pollution load is in the order of forest land > grassland > low-density residential area. To effectively curb surface source pollution in the study area, strategies such as modifying urban land use types, increasing vegetation cover and ground infiltration rate, and strictly controlling the discharge of domestic waste and sewage from urban areas can be implemented.

Assessment of Surface Irrigation Potential of the Dhidhessa River Basin, Ethiopia

Assessing available water resources and their potential for irrigation water use is vital for sustainable agricultural development and planning. This is particularly of interest in developing countries like Ethiopia, where a small portion of largely accessible land for surface irrigation applications has been utilized, despite the majority of the population relying on agricultural productivity. This study utilized the Dhidhessa River Basin (Ethiopia) as a case study and analyzed the main challenges to balance the sustainable water resources utilization and enhance agricultural productivity of the basin. The study mainly focused on estimating the available water resources and their potential for surface irrigation water use in the basin. This was achieved by utilizing Geographic Information System (GIS)-based tools, a hydrological Soil and Water Assessment Tool (SWAT) model, and a Crop Water and Irrigation Requirements Program of FAO (CROPWAT) model. While the SWAT estimated the water availability in the basin, GIS-tools such as Model Builder were used to map the irrigation potential of the basin. For irrigation water potential assessment, we selected six crops (cabbage, maize, tomato, pepper, groundnut and sugarcane) and estimated their irrigation water requirements using the CROPWAT model. We developed the SWAT model for the period from 1986 to 2012 using the available hydro-meteorological and geo-spatial data. Due to many parameters used in the model, we first performed a parameter sensitivity analysis and identified the most essential/sensitivity parameters via Sequential Uncertainty Fitting-II (SUFI-2). The identified sensitive parameters were subsequently used for model calibration (1989–2000) and validation (2001–2012) procedures achieved via SUFI-2. SWAT was able to reproduce the observed monthly streamflow values with a coefficient of determination (R2) and Nash-Sutcliffe Coefficient (NSE) of 0.85 and 0.87 for the calibration period and 0.91 and 0.89 for the validation period, respectively. The findings generally indicated a “good” performance of the model in simulating the hydrology. The annual available water of the basin is 9.26 billion cubic meters (BCM) whereas the 70% and 80% dependable flow is 7.56 and 6.97 BCM, respectively. Based on the Model Builder of ArcGIS, the SWAT estimated available water can potentially irrigate an area of 259,028 ha for slope less than 8%, 643,162 ha for slopes less than 15% and 1,023,581 ha for slopes less than 30%. Moreover, the irrigation water requirements were calculated by the CROPWAT model for the six selected crops indicated that although the need for irrigation water varies depending on the season, the potential irrigation area of the Dhidhessa River Basin is greater than its irrigated land. Therefore, it is concluded that the basin’s surface irrigation systems need to be expanded to enhance the agricultural productivity and improve the livelihood of the basin’s communities and similar basins elsewhere.