雅鲁藏布江流域天然径流及其组分模拟数据集（1982-2023）

数据集包含雅鲁藏布江流域干流五大水文站（拉孜站、奴各沙站、羊村站、奴下站、希让站）的月尺度天然径流及其各组分的模拟数据。数据基于SPHY（Spatial Processes in Hydrology）水文模型模拟获得，模型率定期与验证期的纳什效率系数均大于0.75，决定系数均大于0.85，模拟结果与观测值具有良好一致性，能够有效再现历史径流过程及其变化特征。该数据集可作为雅鲁藏布江流域天然径流过程的综合再现，为流域水文循环认知、水资源管理与生态环境保护等研究提供重要数据支持。This dataset provides simulated monthly-scale natural runoff and its constituent components from five key hydrological stations (Lazi, Nugesa, Yangcun, Nuxia, and Xirang) located on the main stream of the Yarlung Zangbo River Basin. All data were generated using the SPHY (Spatial Processes in Hydrology) hydrological model. For both the model calibration and validation periods, the Nash-Sutcliffe Efficiency Coefficients exceed 0.75, while the coefficients of determination are all greater than 0.85. The simulated outputs exhibit strong consistency with observed data, and can effectively replicate historical runoff processes and their evolutionary characteristics. This dataset serves as a comprehensive representation of natural runoff dynamics in the Yarlung Zangbo River Basin, offering critical data support for studies related to watershed hydrological cycle understanding, water resources management, and ecological environmental protection.

搜集汇总

背景与挑战

背景概述

该数据集包含雅鲁藏布江流域五大水文站的月尺度天然径流及其组分模拟数据，基于SPHY水文模型模拟，模拟结果与观测值具有良好一致性。数据集覆盖1982-2023年，为流域水文循环认知和水资源管理研究提供重要数据支持。