A 500 m high-fidelity soil hydraulic properties dataset over China's drylands

This dataset provides high-resolution (500 m × 500 m) gridded maps of soil hydraulic properties (SHPs) across China’s drylands, derived from field-measured data and machine learning-based pedo-transfer functions (PTFs). The dataset includes spatially explicit predictions of five primary SHPs—saturated hydraulic conductivity (cm/min), saturated water content (cm³/cm³), residual water content (cm³/cm³), and the van Genuchten parameters α (1/cm) and n (-)—at six standard soil depths (0–5, 5–10, 25–30, 55–60, 95–100, and 195–200 cm), covering the full 0–200 cm soil profile. Additionally, four derived SHPs—field capacity (cm³/cm³), wilting point (cm³/cm³), plant available water (cm³/cm³), and soil macroporosity—were calculated from the primary SHPs and provided at the same resolution and depths. The gridded dataset captures the spatial variability and vertical heterogeneity of SHPs across diverse soil types, land uses, and climatic zones in China’s drylands. This dataset supports improved parameterization in land surface and earth system models and facilitates more accurate simulations of hydrological and ecological processes in arid and semi-arid regions. Data are provided in NetCDF format, organized by soil variable, and are suitable for direct integration into regional to continental-scale modeling frameworks.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-01-01
DOI
https://doi.org/10.5281/zenodo.16936713
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A 500 m high-fidelity soil hydraulic properties dataset over China's drylands

Zenodo (CERN European Organization for Nuclear Research)
Geochemistry and Geologic Mapping
article

A 500 m high-fidelity soil hydraulic properties dataset over China's drylands

article en

Abstract

This dataset provides high-resolution (500 m × 500 m) gridded maps of soil hydraulic properties (SHPs) across China’s drylands, derived from field-measured data and machine learning-based pedo-transfer functions (PTFs). The dataset includes spatially explicit predictions of five primary SHPs—saturated hydraulic conductivity (cm/min), saturated water content (cm³/cm³), residual water content (cm³/cm³), and the van Genuchten parameters α (1/cm) and n (-)—at six standard soil depths (0–5, 5–10, 25–30, 55–60, 95–100, and 195–200 cm), covering the full 0–200 cm soil profile. Additionally, four derived SHPs—field capacity (cm³/cm³), wilting point (cm³/cm³), plant available water (cm³/cm³), and soil macroporosity—were calculated from the primary SHPs and provided at the same resolution and depths. The gridded dataset captures the spatial variability and vertical heterogeneity of SHPs across diverse soil types, land uses, and climatic zones in China’s drylands. This dataset supports improved parameterization in land surface and earth system models and facilitates more accurate simulations of hydrological and ecological processes in arid and semi-arid regions. Data are provided in NetCDF format, organized by soil variable, and are suitable for direct integration into regional to continental-scale modeling frameworks.

Zenodo (CERN European Organization for Nuclear Research)
Chinese Academy of Sciences (CN), Institute of Geographic Sciences and Natural Resources Research (CN)
Life in Land
Openalex Percentile: Top 66%
Geochemistry and Geologic Mapping
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.