Simulation Of Streamflow And Sediment Transportation In The Xun River Basin Using SWAT Model

Streamflow and sediment transportation are important components of the eco-hydrological cycle in a river system,which is mainly affected by climate and human activities.The Xun River is a major branch of the Han River in the upstream of the danjiangkou reservoir,the water source of the middle route of the South-to-North Water Diversion Project.The variations of its streamflow and sediment exportation could have important impacts on the water input,water quality and ecological function of the Danjiangkou Reservoir.Streamflow is an important indicator for the water resource feature of a watershed.Climatic factors affect the runoff process of the basin through precipitation and temperature.Nowadays,significant climate change is occurring mainly due to the increase of global greenhouse gas emissions.The occurrence frequency of extreme climate events(such as:extreme precipitation and extreme drought)has increased in some parts of China,which seriously threaten the economic development and security of residents.Therefore,it is necessary to conduct a systematic study to quantitatively explore the response of streamflow to future climate change scenarios.With increasing development and management of natural environment by human activities,the characteristic of land use transformation in basins and the spatial distribution pattern of landscape have been dramatically changed,which had strongly influence on soil erosion.The relationship between landscape pattern and soil erosion can be partly explained by the landscape pattern indices.Thus,the responding mechanism of soil erosion process to landscape pattern change can provide a scientific basis for soil erosion control and mitigation in the Xun River area.In this study,we assessed the applicability of the SWAT hydrological model in the Xun River basin using the ArcGIS platform.We used the future climate data in 2036-2055 predicted by the UK Hadley climate center in the SWAT model to explore the response of watershed runoff to climate change.Twelve typical watersheds in the upper,middle and lower reaches of the Xunhe River were selected to simulate and analyze the sediment transportation in each tributary.We also interpreted remote sensing images from 1995 and 2015 to obtain land cover and calculate landscape indices.The relationship between landscape pattern change and sediment transportation were then examined.The main findings are as follows:1?In the simulation of runoff and sediment transportation in SWAT model,the modelling showed that the correlation coefficients(R²)in the calibration period were 0.85 and 0.75,respectively,the Nash-Sutcliffe efficiency coefficients(Ens)were 0.85 and 0.74,respectively,and the PBIAS were 9.5%and-4.8%,respectively.All of the R² in validation period were greater than 0.86,and all of the Ens were greater than 0.75,and all of the absolute values of PBIAS were less than 15%.These showed that the simulation results of SWAT model were accurate and applicable in the hydrological simulation process of the Xun River Basin.2?Simulation results indicated that under historical climate scenarios,the third-quarter precipitation contributed the most to the annual streamflow.The streamflow of the fourth season showed a lag after the precipitation of the third season under historical climate conditions.The annual average temperature was negatively correlated with the runoff.There was a positive correlation between annual precipitation and runoff,with a correlation coefficient of 0.88.Under the scenario of RCP2.6,the correlation between average runoff and average annual runoff in the third quarter was the highest with a correlation coefficient of 0.82,followed by the second quarter.The RCP8.5 showed an earlier and longer rainy season.3?According to remote sensing image of the 2015a,forest and agricultural land were the two major land cover types in the Xun River watershed.Due to forestation and the conversion of agricultural lands into forest and grassland,forest area increased significantly.In all the four quarters of the year,the simulated value of sediment transport in the upper reaches of the river was significantly lower than that in the lower reaches.LPI and CONTAG of the upstream area were relatively large.It indicates that the dominanation and aggregation degree of patch type(forest land)are high,which is conducive to water and sand conservation.However,the underlying surface in the downstream area was frequently interfered by human activities,so the shapes of various types of patches in the landscape tend to be complicated and the spatial distribution was more fragmented,causing more serious soil erosion.4?the landscape in 2015 had a significantly higher dominant degree,a stronger connection among landscape classes,a more concentrated distribution of patches than that in 1995.As a result,the landscape pattern is evolved to be more simplified,with a significant reduction in river sediment transportation.At the level of class,landscape indexes such as PD₅,PLAND₃,PD₁ and LSI₁ are strongly correlated with sediment transport.At the landscape level,there was a significant positive correlation between LSI and sediment transport,with a correlation coefficient of 0.78.The DIVISION of the landscape level and the PD₅ of the class level for water were the two indices that contributed the most to sediment transportation.In addition,the class level indices performed better in explaining sediment transportation than the landscape level indices.In summary,streamflow and sediment transportation are strongly influenced by climate(precipitation,temperature)and landscape pattern.Climate is the dominant factor influencing streamflow.Watershed landscape configuration is closed related to river sediment transportation,with higher soil erosion as landscape becoming more fragmentated.Incorporating the factors affecting hydrological cycle(vegetation type and growth trend,etc.)into hydrological models is an effective way to further reveal the temporal and spatial dynamics of streamflow and sediment transportation.