Hydrological modeling for streamflow and sediment yield simulation using the SWAT model in a forest-dominated watershed of north-eastern Himalayas of Kashmir Valley, India

In this study, the Soil and Water Assessment Tool (SWAT) model was used to examine the spatial variability of sediment yield, quantify runoff, and soil loss at the sub-basin level and prioritize sub-basins in the Sindh watershed due to its computational efficiency in complex watersheds. The Sequential Uncertainty Fitting-2 approach was used to determine the sensitivity and uncertainty of model parameters. The parameter sensitivity analysis showed that Soil Conservation Services Curve Number II is the most sensitive model parameter for streamflow simulation, whereas linear parameters for sediment re-entrainment is the most significant parameter for sediment yield simulation. This study used daily runoff and sediment event data from 2003 to 2013; data from 2003 to 2008 were utilized for calibration and data from 2009 to 2013 were used for validation. In general, the model performance statistics showed good agreement between observed and simulated values of streamflow and sediment yield for both calibration and validation periods. The noticed insights of this research show the ability of the SWAT model in simulating the hydrology of the Sindh watershed and its reliability to be utilized as a decision-making tool by decision-makers and researchers to influence strategies in the management of watershed processes.

Response of Variation of Water and Sediment to Landscape Pattern in the Dapoling Watershed

The relationship between water-sediment processes and landscape pattern changes has currently become a research hotspot in low-carbon water and land resource optimization research. The SWAT-VRR model is a distributed hydrological model which better shows the effect of land use landscape change on hydrological processes in the watershed. In this paper, the hydrological models of the Dapoling watershed were built, the runoff and sediment yield from 2006 to 2011 were simulated, and the relationship between landscape patterns and water-sediment yield was analyzed. The results show that the SWAT-VRR model is more accurate and reasonable in describing runoff and sediment yield than the SWAT model. The sub-basins whose soil erosion is relatively light are mostly concentrated in the middle reaches with a slope mainly between 0–5°. The NP, PD, ED, SPIIT, SHEI, and SHDI of the watershed increased slightly, and the COHESION, AI, CONTAG, and LPI showed a certain decrease. The landscape pattern is further fragmented, with the degree of landscape heterogeneity increasing and the connection reducing. The runoff, sediment yield and surface runoff are all extremely significantly negatively correlated with forest, which implies that for more complicated patch shapes of forest which have longer boundaries connecting with the patches of other landscape types, the water and sediment processes are regulated more effectively. Therefore, it can be more productive to carry out research on the optimization of water and soil resources under the constraint of carbon emission based on the SWAT-VRR model.

Predicting the Hydrological Impacts of Future Climate Change in a Humid-Subtropical Watershed

Future climate change is expected to impact the natural systems. This study used future climate data of general circulation models (GCMs) to investigate the impacts of climate change during the future period (2062–2095) relative to the historical period (1981–2014) on the hydrological system of the Minjiang river watershed, China. A previously calibrated soil and water assessment tool (SWAT) was employed to simulate the future hydrology under the impacts of changes in temperature, precipitation, and atmospheric CO2 concentration for four shared socioeconomic pathways (SSP 1, 2, 3, and 5) of the CMIP6. The study revealed that the impacts of increase in future temperature, i.e., increase in ET, and decrease in surface runoff, water, and sediment yield will be countered by increased atmospheric [CO2], and changes in the hydrological parameters in the future will be mostly associated to changes in precipitation. Data of the GCMs for all the SSPs predicts increase in precipitation of the watershed, which will cause increase in surface runoff, water yield, and sediment yield. Surface runoff will increase more in SSP 5 (47%), while sediment and water yield will increase more in SSP 1, by 33% and 23%, respectively. At the seasonal scale, water yield and surface runoff will increase more in autumn and winter in SSP 1, while in other scenarios, these parameters will increase more in the spring and summer seasons. Sediment yield will increase more in autumn in all scenarios. Similarly, the future climate change is predicted to impact the important parameters related to the flow regime of the Minjiang river, i.e., the frequency and peak of large floods (flows > 14,000 m3/s) will increase along the gradient of scenarios, i.e., more in SSP 5 followed by 3, 2, and 1, while duration will increase in SSP 5 and decrease in the other SSPs. The frequency and duration of extreme low flows will increase in SSP 5 while decrease in SSP 1. Moreover, peak of extreme low flows will decrease in all scenarios except SSP 1, in which it will increase. The study will improve the general understanding about the possible impacts of future climate change in the region and provide support for improving the management and protection of the watershed’s water and soil resources.