[关键词]
[摘要]
气候变化会导致水文序列的非稳态性,从而给水文预报带来新的挑战。以疏勒河上游为例,提出了一种适于非稳态条件下的新的中长期径流预报方法。根据疏勒河径流的补给来源及其受气候变化的影响,按照时间序列模型的思路,依次提取趋势项和周期项,对剩余的随机项采用基于水文-气象遥相关模型,构建了时间序列与水文-气象遥相关的耦合模型。对比分析时间序列法、水文-气象遥相关法和耦合预报法对昌马堡站径流预报的结果,发现耦合预报方法不仅精度最高、模型可信度最高,而且可以描述非稳态的趋势性变化。
[Key word]
[Abstract]
Climate change can cause non-stationarity in hydrological series, bringing more challenges to hydrological prediction. Taking Shule rive as a case, this paper explores a new long-term runoff prediction model under non-stationarity. Based on runoff recharge sources and climate change in upper reaches of the river, this paper first analyzes the trend term and periodic term of the runoff series, and then builds a multiple regression model based on hydro-climatic teleconnection analysis to predict the stochastic term. The issued model couples auto-correlation model and hydro-climatic teleconnection model by merging the three terms together, and yields ultimate prediction runoff values. Prediction results of the teleconnection based model, the time series model, and the coupling model, are compared. It is shown that the coupling model has the highest precision and provides the most efficient results. Meanwhile, it can capture the nonstationary trend of streamflow.
[中图分类号]
[基金项目]
国家自然科学基金面上项目(51579129)