Water Modelling-Modelled Data-Without Development-Border Rivers

Name: Water Modelling-Modelled Data-Without Development-Border Rivers
Creator: NSW Government Open Data Portal
Published: 2026-06-15T12:01:29+08:00

NSW Government Open Data Portal2026-06-15 收录

水文模拟

跨境水资源管理

数据链接：

https://data.nsw.gov.au/data/dataset/water-modelling-modelled-data-without-development-border-valley?nsw_prev=aHR0cHM6Ly9kYXRhLm5zdy5nb3YuYXUvZGF0YS9kYXRhc2V0Lz9xPSZwYWdlPTEz%0A 数据链接链接失效反馈

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资源简介：

Water Modelling-Modelled Data-Without Development-Border Rivers

提供机构：

NSW Government Open Data Portal

1998-2017年中国印度河流域上游5公里水资源时空分布数据集

水文模拟

水资源时空分布

本数据是基于气象观测数据、水文站点数据，结合各种同化数据和遥感数据，通过耦合积雪、冰川和冻土物理过程的青藏高原多圈层水文模型系统WEB-DHM（基于水和能量平衡的分布式水文模型）制备生成，时间分辨率为月尺度，空间分辨率为5km，原始数据格式为ASCII文本格式，数据种类包括格网径流与蒸发（若蒸发小于0, 则表示凝华；若径流小于0，则表示当月降水小于蒸发）。若asc无法在arcmap中正常打开，请将

地球大数据科学工程2018-10-25 更新20

Dataset underlying chapter 6 of dissertation F. van Oorschot

根区储水容量表征

水文模拟

This dataset is used in chapter 6 of the PhD dissertation of F. van Oorschot (May 2024). The data is used to provide an analysis of global root zone storage capacity representation with: (1) predicted

Zenodo2024-05-21 更新10

Watershed Data Management (WDM) Database (WBDR13.WDM) for West Branch DuPage River Streamflow Simulation, DuPage County, Illinois, January 1, 2007, through September 30, 2013 (ver. 1.1, November 2024)

水文模拟

径流预测

The U.S. Geological Survey (USGS), in cooperation with DuPage County Stormwater Management Department, maintains a watershed data management (WDM) database of hourly...

data.gov00

Raw datasets for paper "Rapid Spatio-Temporal Flood Modelling via Hydraulics-Based Graph Neural Networks"

洪水预测

水文模拟

Raw datasets for paper "Rapid Spatio-Temporal Flood Modelling via Hydraulics-Based Graph Neural Networks". The zip folder comprises 4 subfolders (DEM, WD, VX, VY), containing the elevation, water dept

Zenodo2023-06-20 更新20

GR4J-REG: regional gridded runoff dataset for northwest Russia based on GR4J model and nearest-neighbor regionalization technique

水文模拟

网格化径流数据

GR4J-REG: regional gridded runoff dataset for northwest Russia. Model: GR4J. Regionalization technique: Nearest-neighbor. Geographical domain: 25–57°E; 55–70°N. Spatial resolution: 0.5°x0.5°. Temporal

Zenodo2020-12-11 更新00

Water Modelling-Modelled Data-Without Development-Border Rivers

资源简介：

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