# Predicting Runoff from the Weigan River under Climate Change
## 4 Discussion
### Shortcomings of This Study  
As we all know, the Xinjiang region has perennial drought and little rain, most of the rivers in this region are glacial snow-melt recharge-type rivers, and many glaciers in southern Xinjiang are widely distributed, such as the Kanas Glacier, Moustagh Glacier and Ouyitak Glacier. The glacier flow rate is not only affected by the melting and evaporation of ice, but also by solar radiation, glacier size, ice surface nature and so on, which are closely related. The Weigan River is a typical arid inland glacier snow-melt recharge river. According to existing research results, the proportion of glacier runoff in the outflow of Weigan River reaches 32.40% [21], which is not small, and the glacier-produced flow in the context of global warming has a certain impact on the outflow of the Weigan River. However, although the SWAT model constructed in this study was validated for its applicability in the study area, it cannot fully and accurately reproduce the hydrological processes of the watershed. And when predicting the future runoff from the Weigan River,due to the immaturity of current research techniques and tools, we failed to complete the separation and prediction of the proportion of glacier runoff in future runoff. Therefore, the primary task of the next study is to separate glacier runoff from future runoff, and to clarify the proportion of future runoff due to the increases in precipitation and temperature caused by an increase in the incoming water from the perspective of the physical model, which can provide a reference for the allocation and management of water resources in the surrounding areas.  
Although substantial work was performed in this study to correct the downscaling bias of the GCM data, and the simulation ability of the results is relatively consistent, it cannot be denied that the GCM data themselves have systematic errors and high levels of uncertainty. These uncertainties are related to factors such as the structure of the GCMs, spatial resolution, initial conditions and parameterisation scheme settings [50]. There is a certain variability in the simulation effects for different regions and elements [51], which also demonstrates the fact that different choices of climate models lead to certain differences in the simulation results. In the face of the large differences between models, and with the uncertainties in the simulation results of each model, the current solution is to target better-performing climate models. As for the many general common deviations and uncertainties in the simulation results of each model, these uncertainties can only be eliminated by using weighted ensemble averaging or other methods to reduce the deviations as much as possible so that the simulation and prediction results are more accurate. These problems are important obstacles to overcome in the use of numerical model simulation to predict climate change, which seriously affect the credibility of the model prediction method used [52]. Therefore, research in this area should be strengthened in the next phase of research work to solve such problems.