荒漠化地区土壤-水文-植被参数多尺度时空变异与耦合转换函数研究

合理确定土壤-水文-植被参数是研究流域水循环、生态水文模拟等问题的关键环节，本研究以荒漠化的科尔沁沙地为研究区，将土壤传递函数PTFs、地统计学与联合多重分形、神经网络、随机理论、谱分析、不确定性分析、数据处理与分类、逐步/树形回归分析等技术方法相结合，采用野外试验-变异分析-函数构建-可适性评估的技术路线，针对饱和渗透系数、地下水位、植被指数等参变量，水分特性曲线、非饱和导水率、下渗曲线等系数模型，分析其多尺度时空变异、耦合效应与协同结构特征，建立它们与易获主相关变量和其它时空分布信息间的多尺度耦合传递函数，并将构建的PTFs函数用于GSPAC系统水-热-盐耦合运移分析、生态水文过程模拟与水资源系统动态评价，进而评估耦合传递函数的有效性、适用性、不确定性和可靠性。这不仅可丰富完善土壤-水文-植被参数的时空变异及其传递函数理论，也为水资源保护、生态系统健康维持等方面提供技术支持和理论保证。

Reasonable assurance of soil-hydrology-vegetation parameters is the key issue to study water cycle, eco-hydrological modeling. Taking the desertified Horqin Sandy Land as the study area, by following the technology roadmap of field experiments, variance analysis, functions building, adaptive assessment, this study will: 1) combined the methods of pedo-transfer function, geostatistics, joint multifractal, neural networks, stochastic theory, spectral analysis, uncertainty analysis, data processing and classification, and gradually/tree regression analysis; 2) analyze multi-scale spatiotemporal variations, coupling effects and collaborative structural features of the parameters of saturated hydraulic conductivity, groundwater level, vegetation index as well as the coefficient models of moisture characteristic curve, unsaturated hydraulic conductivity, infiltration curve; 3) establish the multi-scale coupled transfer functions by related the parameters, coefficient models to the easy-accessed main correlation variable and other spatiotemporal information; 4) applied the coupled transfer functions to the water-heat-salt coupled transfer analyzing of GSPAC system, eco-hydrological processes simulation and water system dynamic evaluation; 5) evaluated the validity, applicability, uncertainty and reliability of coupled transfer functions. This project will play an important role in enriching and advancing the theory of multi-scale spatiotemporal variations and coupled transfer functions of soil-hydrology-vegetation parameters, and will provide technical information for water resources protection and ecosystem health maintenance.