【作者】 冯小冲；

【导师】 王银堂；

【作者基本信息】 南京水利科学研究院 ， 水文学及水资源， 2010， 硕士

【摘要】 中长期降雨径流预报作为水文预报的重要组成部分,对水库洪水调控和兴利调度均具有重要意义。由于中长期预报预见期较长,又受客观认知能力和技术水平的限制,以及众多不确定因素的影响,中长期水文预报的精度尚不能满足生产部门的需要。大量研究发现,在中长期水文预报中,关键预报因子的选择是提高预报精度的关键。因此,从形成径流的气象背景和物理机制入手识别预报因子,建立具有一定物理成因的预报模型,是现今中长期水文预报领域的主要研究方向。论文在综述国内外中长期水文预报的理论研究和科学实践的基础上,以南水北调中线工程水源地——丹江口水库为研究对象,从中期降雨预报、长期径流预报、贝叶斯概率预报以及概念性月径流模型等方面开展研究。论文首先分析影响我国汛期降雨的主要天气因素,阐明了丹江口水库控制流域降雨的大气环流系统和海温因素,为掌握流域降雨和径流的关键影响因子奠定基础。其次,利用物理分析与统计分析相结合的方法,遴选出具有物理成因背景的中长期预报因子,采用多元回归、逐步回归、神经网络等多种方法,建立中期降雨及长期径流预报模型,同时融合多种预报信息的基础上,构建了组合预测模型。为检验本文所建模型适用性,利用1980~2000年丹江口水库控制流域逐旬面平均雨量及1968~2000年的逐月入库径流量进行模拟,2001~2006年流域逐旬面平均雨量及逐月入库径流量进行试报。结果表明,上述模型均可达到较高精度,其中组合预报模型效果最好,作为推荐预报模型。为了进一步分析降雨径流中长期预报结果中的不确定性,论文建立了贝叶斯概率预报模型,给出了一定置信度下的降雨径流预报区间。最后,基于水热平衡方程和流域蓄泄关系,概化径流、降雨、蒸发和流域蓄水量之间的关系,建立了丹江口水库控制流域三参数月水量平衡模型。结果表明,该模型具有较强的适用性,可以较好的模拟丹江口水库控制流域各分区及全流域的月径流过程。更多还原

【Abstract】 Mid-long term precipitation and runoff forecast is a significant part of hydrological forecast which is vital to flood regulation and effective water resources utilization. However,with long forecast period, the accuracy of mid-long term forecast failed to satisfy the need of production department, restricted by objective cognitive ability, technology development and many uncertain factors. Large numbers of studies have verified that the rational selection of predictors is the key to improve prediction precision of mid-long term precipitation and runoff forecast.Therefore, the mid-long term hydrological forecast research should focus on establishing forecast model by identifying predictors according to the synoptic background and physical mechanism controlling precipitation and runoff.A review of theoretic researches and practice on mid-long term hydrological forecast both domestically and abroad was drawn in this paper. Then, some key problems of mid-long term hydrological forecast, such as mid-term rainfall prediction, long-term runoff prediction, Bayesian probabilistic forecast and monthly water balance runoff model were investigated. The Danjiangkou Reservoir basin,which is the waterhead area of middle of South-to-North Transfer Project, is selected as the study object.The atmospheric circulation systems and sea surface temperature influencing the rainfall in China and the Danjiangkou Reservoir basin were firstly analyzed in this paper, in order to select the key factors of rainfall and runoff forecast. Subsequently, forecast models were established with multiple regression, stepwise regression and artificial neural network respectively.At the same time, the combination prediction model was built by integration of the result of all the models aforementioned. In order to test the applicability of these models, ten-day rainfall and monthly runoff both from 2001 to 2006 in Danjiangkou Reservoir basin were predicted by simulation based on the data of ten-day areal rainfall from 1980 to 2000 and monthly runoff from 1968 to 2000 in the basin. Results showed that all of these models can attain a promising accuracy, in which the combination prediction model is recommended as forecast model with the highest accuracy.To further investigate the uncertainty of mid-long term forecast, a Bayesian probabilistic forecast model was established. The predicated value range with a confidence level is provided.Finally, a three-parameter monthly water balance model for the Danjiangkou Reservoir basin was proposed. This model was based on the hydrothermal equilibrium equation and the relationship among water storage, runoff, rainfall and evaporation. Results showed that the three-parameter monthly balance model is feasible for simulating the runoff processes of the whole basin and different sub-basin.更多还原