| Accurate simulation and prediction of snowmelt runoff play an essential role in managing spring water resources and preventing drought and flood disasters in the cold region of Northeast China.However,too many meteorological factors influencing snowmelt runoff and complex physical processes of snowmelt runoff result in low simulation and prediction accuracy.To improve the simulation and prediction accuracy of snowmelt runoff,firstly,this paper selected the mountainous snowmelt runoff area"Baishan Basin"and the hilly snowmelt runoff area"Xinlicheng Basin"as the research area to analyze the characteristics of snowmelt runoff and its meteorological influencing factors by using trend analysis method and mutation point test method.Secondly,this paper analyzed the influence of meteorological factors on snowmelt runoff employing geostatistical analysis and global sensitivity analysis.And then,based on the analysis results of the influence of meteorological factors on snowmelt runoff,this paper established a set of methods for improving the SWAT model snowmelt module for the cold regions in Northeast China.Finally,the improved SWAT model(SWAT-SNOW)was applied to predict the snowmelt runoff in the Baishan Basin and Xinlicheng Basin in the next seven days and the next 30 years using data of weather forecast data and climate model data from the 6th International Coupled Model Comparison Program(CMIP6).Moreover,the research results are as follows:(1)Snowmelt runoff’s variation trend,mutation characteristics,and meteorological influencing factors were revealed.Based on the historical meteorological and hydrological data,the Mann-Kendall method,cumulative anomaly method,and sliding T-test were used to explore the variation trend and mutation characteristics of snowmelt runoff and its meteorological influencing factors in Baishan Basin and Xinlicheng Basin.The results show that the snowmelt runoff in the Baishan basin(mountain area)and Xincheng basin(hilly area)showed a significant upward trend.Among them,there was a sudden change in the snowmelt runoff in the Xinlicheng basin,and the abrupt change was in 2013.Among the meteorological influencing factors,only the relative humidity in the Baishan Basin and the wind speed in the Xinlicheng Basin tended to decrease significantly.There were differences in the abrupt time of meteorological influencing factors in different types of snowmelt runoff areas,including sudden changes in the temperature of the Baishan Basin in 1998 and solar radiation and temperature in the Xinlicheng Basin in 2013 and2005,respectively.(2)The contribution rate of critical meteorological influence factors to snowmelt runoff was evaluated.The correlation between snowmelt runoff and meteorological factors was explored by geostatistical analysis,and the time lag and critical meteorological influence factors were identified by global sensitivity analysis.An empirical equation was further established based on the correlation and time delay analysis results to evaluate the contribution rate of critical meteorological factors to the influence of snowmelt runoff.The results show that snowmelt runoff positively correlates with precipitation and relative humidity and negatively correlates with solar radiation,temperature,and wind speed.In addition,the time lag effect of aerodynamic factors(wind speed)on snowmelt runoff is more significant than that of thermal factors(temperature and solar radiation)and moisture factors(precipitation and relative humidity).Solar radiation and temperature were the critical meteorological influencing factors of snowmelt runoff in the cold region of Northeast China.Furthermore,the annual solar radiation and temperature contribution rates to the snowmelt runoff in the Baishan Basin are 56%and44%,respectively.The contribution rates of solar radiation and temperature on snowmelt runoff at the annual scale of the Xinlicheng Basin are 67%and 33%,respectively.(3)A set of methods improving the SWAT model snowmelt module suitable for the cold regions in Northeast China was constructed.The improved methods of the snowmelt module of the SWAT model include the calculation method of the snowmelt volume with two factors of radiation and temperature,the method of identifying the snowmelt temperature threshold based on physical analysis,the identification method of the maximum and minimum snowmelt factors time and seasonal variation formula of the snowmelt factor in the cold regions of Northeast China.Compared with the SWAT model,the snowmelt runoff simulation performance of the modified SWAT model in the cold regions of Northeast China is significantly improved,especially when the snowmelt runoff is small.During the validation period,MAE and RMSE decreased by 3.23～23.34m~3/s,RE decreased by4.90～31.31%,and NSE and R~2 increased by 0.16～0.42 and 0.07～0.47.(4)The snowmelt runoff forecast in the cold regions of Northeast China was carried out based on the SWAT-SNOW model.The SWAT-SNOW model was applied to forecast snowmelt runoff in the next seven days based on meteorological forecast data and snowmelt runoff in the next 30years(2025～2054)based on SSP1-2.6,SSP2-4.5,and SSP5-8.5 climate scenario data.The results show that the qualified rates of snowmelt runoff forecast with a forecast period of 7 days in Baishan Basin and Xinlicheng Basin are 75.0%and 62.5%,respectively,which meet the requirements of forecast accuracy.Under the three climate scenarios in the future,the precipitation in the snowmelt runoff period of Baishan Basin will be higher than that in the historical period.In contrast,Xinlicheng Basin will be the opposite.The temperature of the two basins will show an increasing trend,and the snowmelt runoff will show a decreasing trend. |
