As an important part of the terrestrial hydrological system,natural lakes and manmade reservoirs have an important influence and significance on the extraction of hydrological characteristics,the construction of hydrological connectivity,and the simulation of hydrological processes in the basin.Many researchers have carried out exploration and practice related to considering the impact of lakes/reservoirs for multiple scales and different watershed applications.However,the current method of catchment network extraction considering lakes/reservoirs still has difficulty in describing the upstream and downstream boundaries between lakes/reservoirs and the surrounding area,and the constructed watershed dataset has not yet reasonably considered the influence of lakes/reservoirs on the catchment relationship.The development of spatial observation techniques,geographic information system(GIS)methods,and high-performance computing frameworks provide new opportunities for extracting basin hydrological information from increasingly refined spatial data.Through the detailed description of the influence of lakes/reservoirs on the catchment relationship,the concept of multi-scale nesting to construct the basin dataset can provide a strong data support for the basin hydrology study.On this basis,oriented to the characteristics of the watershed dataset considering lake/reservoir impact,the ondemand service of the watershed dataset can provide a more convenient way of data application for researchers across fields.Thus,this study considers lakes/reservoirs as independent characteristics in the basin,explores the method of differentiation and extraction of related hydrological characteristics,implements and optimizes the method of nested dataset construction,and proposes an auxiliary scheme for basin catchment network data application in combination with application requirements,aiming to provide finer data resources and easy-to-use data views for basin hydrology-related studies.The main contents and results of this paper are as follows:(1)A method for constructing watershed catchment networks considering lakes/reservoirs.By distinguishing and extracting the following five hydrological characteristics: lake/reservoir,river,sub-basin that flow into river systems,slope that flow into lakes/reservoirs and the slope flow path between the lake/reservoir and the downstream water body,the confluence process in the basin considering the influence of the lake/reservoir is expressed explicitly,and the algorithm implementation is given based on the relevant basic data and digital terrain analysis methods.(2)A method for constructing nested watershed datasets considering lakes/reservoirs.Implemented and optimized a nested basin dataset generation method with the Pfafstetter coding system as the core,and combined with the aforementioned method of dividing and extracting the hydrological characteristics of the basin,and incorporated the lake/reservoir and related characteristics into the nested dataset for representation with the help of the current base data optimized for the hydrological field.(3)An auxiliary scheme for watershed catchment network data applications.Based on the intuitive and convenient application requirements of the nested watershed dataset,the practical application scenarios of this dataset are sorted out,and a web service based application scheme for the watershed catchment network dataset is designed,and then a highly concurrent geographic data engine is used to realize the efficient service of the watershed catchment network dataset to assist the rapid development of basin hydrology related research.The feasibility and rationality of this research method is verified through experiments and typical cases.Based on the construction of a hydrological characteristics extraction method considering lakes/reservoirs and the generation of nested watershed datasets,a prototype system is built with data serviceability as the driving force,and the practicality of this research method and results for watershed hydrology-related studies is verified by using Jiao Gang Lake and its pollution into the lake as an application case and comparing the datasets. |