基于GIS&RS的水库洪水预报模型研究与应用
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摘要
水库是重要的水利工程和水资源保障基地,起着保护下游人民生命财产安全、保障工农业生产和城镇人民生活用水的重要作用。为了在保证水库安全的前提下,使水库尽可能地多蓄水,达到充分利用洪水资源,保障供水的目的,需要为水库构建一套准确可靠的洪水预报模型,进行科学的洪水预报。遥感技术的快速发展为水库洪水预报模型提供了充足的数据源,本文以遥感数据在水库洪水预报模型中的应用为主线展开研究。运用人工免疫系统免疫学习的基本原理,研究了利用遥感影像提取流域下垫面信息的问题；研究了以ETM+数据为数据源提取流域下垫面信息的技术流程；研究了以下垫面信息和DEM为数据源,构建汇流网络的问题；根据分布式水文模型基础理论和前述研究成果,构建水库洪水预报模型；建立了水库洪水预报实验系统并在雪野水库进行了应用。研究结果对提高水库洪水预报水平具有重要的参考价值,本文的主要贡献有：
(1)发展了基于免疫学习的遥感影像分类算法。算法运用人工免疫系统免疫学习原理,首先构造了一个线型分类器用于学习类别的特征,对每个类别的抗原种群单独学习以减少算法的收敛时间；在提取过程中,采用多种方式进行判别并引入人工先验知识以提高提取精度和效率。实验表明：算法能够有效地提高分类精度。
(2)明确了流域下垫面信息提取技术流程。根据水库洪水预报模型的建模需要和Landsat-7 ETM+数据源特点,根据提取目标综合运用波段组合、计算特征指数、计算纹理特征等手段,合理组织特征空间,以有效地提取下垫面信息。
(3)发展了汇流网络构建算法。在充分理解水库汇流特点的基础上,以DEM和下垫面信息为数据源提取产流栅格,对提取的栅格及其流向关系进行拓扑处理,确定产流栅格计算次序,实现汇流网络的构建。
(4)构建了基于GIS和RS的水库洪水预报模型。根据分布式水文模型基础理论,模型以提取的下垫面信息为基础进行产流计算,利用汇流网络进行逐单元汇流演算。在雪野水库的实验结果表明：模型能够有效地提高洪水预报的精度。
(5)实现了基于GIS和RS的水库洪水预报实验系统,并在雪野水库进行了应用。
Reservoir is the important secure base of water conservancy project and water resource, which plays an important role in protecting the security of life and property of people situated downstream and ensuring water supply for industrial and agricultural production and urban people's life. To make the reservoir hold as much water as possible under the condition of its safety, aiming at making full use of flood resource and ensuring the need of water supply, a set of accurate and calculable flood forecasting model is needed to be built to forecast flood scientifically.The rapid development of remote sensing technology provides a sufficient data source for reservoir flood forecasting model. The application of remote sensing data in flood forecasting is the main line of this paper. We studied the problem of extracting the information of watershed underlying surface with remote sensing image using the basic principle of artificial immune system immunity learning; We studied the technological process of extracting the information of watershed underlying surface using the data source of ETM+ data; We also studied the problem of building flow networks using the data source of underlying surface information and DEM; According to the basic theory of distributed hydrological model and research findings mentioned above, we built a reservoir flood forecasting model. We built the experiment system of reservoir flood forecasting and applied it in Xueye Reservoir. The result of the reseach is of great reference value to improving the level of flood forecast, The main contribution of this paper:
(l)An algorithm of Classification of Remote Sensing Image based on immune learning was presented. The algorithm used immune learning theory of artificial immune system, which first constructed a linear classifier used for the learning of the characteristics of categories, and studied separately the antigen population of each category to reduce the algorithm's convergence time; In the process of extracting, it distinguished by a variety of different ways and introduced artificial priori knowledge to increase the precision and efficiency of extracting.The experiment showed that:the results of algorithm have high classification accuracy.
(2)This paper defined the technological process of extracting the information of watershed underlying surface. Based on the modeling needs of flood forecasting and the characteristics of Landsat-7 ETM+data source, by synthesizing means of band combination, calculating characteristic index and calculating the texture characteristics according to the extracting object, we organized feature space appropriately to extract underlying surface information effectively.
(3)The algorithm of building flow networks was developed in this paper. Based on understanding the characteristics of reservoir confluence sufficiently, we extracted runoff grid by the data source of DEM and the information of underlying surface; we did topological processing to the extracted grid and the flow relationship, and determined the computing sequence of runoff grid; and also we carried out the building of flow networks.
(4)The reservoir flood forecasting model based on GIS and RS was constructed. According to the basic theory of distributed hydrological model, the model took the extracted information of land surface as the basis to calculate runoff and used the flow networks to compute unit by unit. The experiment results in Xueye Reservoir showed that:The model can effectively improve the forecasting precision.
(5)This thesis achieved the experiment system of reservoir flood forecasting based on GIS and RS and applied it in Xueye Reservoir.
(1)发展了基于免疫学习的遥感影像分类算法。算法运用人工免疫系统免疫学习原理,首先构造了一个线型分类器用于学习类别的特征,对每个类别的抗原种群单独学习以减少算法的收敛时间；在提取过程中,采用多种方式进行判别并引入人工先验知识以提高提取精度和效率。实验表明：算法能够有效地提高分类精度。
(2)明确了流域下垫面信息提取技术流程。根据水库洪水预报模型的建模需要和Landsat-7 ETM+数据源特点,根据提取目标综合运用波段组合、计算特征指数、计算纹理特征等手段,合理组织特征空间,以有效地提取下垫面信息。
(3)发展了汇流网络构建算法。在充分理解水库汇流特点的基础上,以DEM和下垫面信息为数据源提取产流栅格,对提取的栅格及其流向关系进行拓扑处理,确定产流栅格计算次序,实现汇流网络的构建。
(4)构建了基于GIS和RS的水库洪水预报模型。根据分布式水文模型基础理论,模型以提取的下垫面信息为基础进行产流计算,利用汇流网络进行逐单元汇流演算。在雪野水库的实验结果表明：模型能够有效地提高洪水预报的精度。
(5)实现了基于GIS和RS的水库洪水预报实验系统,并在雪野水库进行了应用。
Reservoir is the important secure base of water conservancy project and water resource, which plays an important role in protecting the security of life and property of people situated downstream and ensuring water supply for industrial and agricultural production and urban people's life. To make the reservoir hold as much water as possible under the condition of its safety, aiming at making full use of flood resource and ensuring the need of water supply, a set of accurate and calculable flood forecasting model is needed to be built to forecast flood scientifically.The rapid development of remote sensing technology provides a sufficient data source for reservoir flood forecasting model. The application of remote sensing data in flood forecasting is the main line of this paper. We studied the problem of extracting the information of watershed underlying surface with remote sensing image using the basic principle of artificial immune system immunity learning; We studied the technological process of extracting the information of watershed underlying surface using the data source of ETM+ data; We also studied the problem of building flow networks using the data source of underlying surface information and DEM; According to the basic theory of distributed hydrological model and research findings mentioned above, we built a reservoir flood forecasting model. We built the experiment system of reservoir flood forecasting and applied it in Xueye Reservoir. The result of the reseach is of great reference value to improving the level of flood forecast, The main contribution of this paper:
(l)An algorithm of Classification of Remote Sensing Image based on immune learning was presented. The algorithm used immune learning theory of artificial immune system, which first constructed a linear classifier used for the learning of the characteristics of categories, and studied separately the antigen population of each category to reduce the algorithm's convergence time; In the process of extracting, it distinguished by a variety of different ways and introduced artificial priori knowledge to increase the precision and efficiency of extracting.The experiment showed that:the results of algorithm have high classification accuracy.
(2)This paper defined the technological process of extracting the information of watershed underlying surface. Based on the modeling needs of flood forecasting and the characteristics of Landsat-7 ETM+data source, by synthesizing means of band combination, calculating characteristic index and calculating the texture characteristics according to the extracting object, we organized feature space appropriately to extract underlying surface information effectively.
(3)The algorithm of building flow networks was developed in this paper. Based on understanding the characteristics of reservoir confluence sufficiently, we extracted runoff grid by the data source of DEM and the information of underlying surface; we did topological processing to the extracted grid and the flow relationship, and determined the computing sequence of runoff grid; and also we carried out the building of flow networks.
(4)The reservoir flood forecasting model based on GIS and RS was constructed. According to the basic theory of distributed hydrological model, the model took the extracted information of land surface as the basis to calculate runoff and used the flow networks to compute unit by unit. The experiment results in Xueye Reservoir showed that:The model can effectively improve the forecasting precision.
(5)This thesis achieved the experiment system of reservoir flood forecasting based on GIS and RS and applied it in Xueye Reservoir.
引文
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