摘要
山区春季融雪洪水模拟及预报是寒区水文研究的难点,目前的预报模型主要采用复杂的积雪消融能量平衡模型,并考虑了冻土、植被等下垫面和产汇流过程,导致模型结构复杂,并且这种方法在预报中需要大量的数据支撑,在业务预报中应用困难,同时预测结果也具有很多不确定性。本文利用西营河流域冬季气象站点雪深观测资料与多种积雪遥感数据,结合其控制断面九条岭水文站洪水观测资料,利用统计学方法建立简单有效的春季融雪洪水预报方法。研究表明,利用3—4月MODIS积雪遥感产品以及融合微波遥感雪深产品的流域雪水当量信息能够很好地反映西营河九条岭水文站春季融雪洪水大小。这种预报方法可为其他稳定积雪区的融雪洪水预报提供有益的借鉴。
Spring snowmelt flood simulation and forecasting in the mountainous region has been a difficulty of cold region hydrological study.Current forecasting studies mainly use complex snow melt energy balance models,and take into account underlying surfaces such as frozen soil,vegetation,and runoff processes,resulting in complex model structures.This method needs a lot of data support and has a great uncertainty in prediction,which leads to difficulties in application in operational forecasting.In this paper,a simple and ef⁃fective spring snowmelt flood forecasting method is established by using statistical methods and the snow depth observation data in win⁃ter of meteorological stations as well as a variety of snow remote sensing data in the Xiying River Basin,combined with the flood obser⁃vation data of Jiutiaoling Hydrology Station on its control section.The study shows that the snow water equivalent information of the ba⁃sin from MODIS snow cover products in March and April and the integration of microwave remote sensing snow depth products can well reflect the magnitude of spring snowmelt flood at Jiutiaoling Hydrological Station in the Xiying River Basin.This method provides a use⁃ful reference for snowmelt flood forecasting in other stable snow cover areas.
作者
赵成先
罗建华
王学良
党志英
祁进贤
刘俊峰
韩春坛
ZHAO Chenxian;LUO Jianhua;WANG Xueliang;DANG Zhiying;QI Jinxian;LIU Junfeng;HAN Chuntan(Xinjiang Water Conservancy Development Investment(Group)Co.LTD,Urumqi 830009,China;Gansu Hydrological Stations,Lanzhou 730000,China;Qilian Forestry and Grassland Administration/Qilian Management Branch of Qilian Mountain National Park,Qilian 810400,Qinghai,China;Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands,Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Lanzhou 730000,China)
出处
《干旱气象》
2024年第5期776-783,共8页
Journal of Arid Meteorology
基金
国家重点研发计划项目(2019YFC1510500)
甘肃省自然科学基金项目(21JR7RA043、23JRRA664)
新疆额河建管局技术服务项目(KKYG08/2021)共同资助。
