Hydrological Modeling and Forecasting of Semi-arid Watersheds Based on Similarity Cluster Analysis
Due to the complex rainfall characteristics and variable subsurface characteristics of small and medium-sized watersheds in arid and semi-arid regions,the accuracy of hydrological simulation is low.In order to improve the simulation and forecasting accuracy of distributed hydrophysical model in arid areas,based on the water and sand data of Huangjiahe in the semi-arid region of southern Ningxia from 1981 to 2017,considering the influence of the pre-rainfall and maximum rainfall on the over-permeable surface runoff,this paper carried out the clustering analysis to categorize flooding by taking the characteristic values of the pre-accumulated rainfall in multiple time periods,the characteristic val-ues of the maximum rainfall,and the different flood recurrence periods as the variables.The CASC2D-SED model was used to simulate water-sand.The forecasting field was simulated by directly transplanting the sensitive parameters of each category model.The results show that the water-sand simulation accuracy of Huangjiahe by CASC2D-SED model is bet-ter,with the average Nash-Sutcliffe efficiency coefficient flood value of 0.74 and the average Nash-Sutcliffe efficiency co-efficient sand value of 0.67;The model runoff producing simulation accuracy is higher than the sand-producing simulation accuracy.Based on the clustering analysis,the forecast field directly transplanted the model parameters of each category has better forecast results,and the average Nash-Sutcliffe efficiency coefficient flood volume value and sand volume value accuracy distribution improved by 0.07 and 0.01,respectively.
万方数据
维普
