Haihe River Basin evapotranspiration datasets

Irrigation is the greatest human interference with the terrestrial water cycle. Detailed knowledge on irrigation is required to better manage water resources and to increase water use efficiency. This data repository contains two sources of evapotranspiration estimations that can be used to quantify irrigation. The data covers the Haihe River Basin with an area of approximately 320,000 km2 and encompasses mountainous regions in the west and north and lowlands in the east and south. The lowlands refer to the North China Plain, which covers approximately 140,000 km2. The North Chin Plain is a global hotspot of prolonged groundwater depletion induced by irrigation agriculture. The hydrologic model (mHM_Fluxes_States) does not consider irrigation and therefore it estimates evapotranspiration under purely rainfed conditions. The remote sensing based estimation of evapotranspiration (ET_PTJPL) reflects the natural conditions, with rain as sources of water, as well the human interferences (irrigation). Therefore the hydrologic model will systematically underestimated evapotranspiration under irrigation and the systematic residuals can be utilized to quantify irrigation. The spatial resolution if the evapotranspiration estimates is 1 km2 and the temporal resolution is at monthly timescale. The study period is from January 2002 to December 2016.

Data and Resources

This dataset has no data

Cite this as

Koch, Julian (2020). Dataset: Haihe River Basin evapotranspiration datasets. https://doi.org/10.1594/PANGAEA.914113

DOI retrieved: 2020

Additional Info

Field Value
Imported on November 29, 2024
Last update November 29, 2024
License CC-BY-4.0
Source https://doi.org/10.1594/PANGAEA.914113
Author Koch, Julian
Given Name Julian
Family Name Koch
Source Creation 2020
Publication Year 2020
Resource Type text/tab-separated-values - filename: KochJ_2020
Subject Areas
Name: Ecology

Name: LakesRivers

Related Identifiers
Title: Estimating net irrigation across the North China Plain through dual modelling of evapotranspiration
Identifier: https://doi.org/10.1029/2020WR027413
Type: DOI
Relation: References
Year: 2020
Source: Water Resources Research
Authors: Koch Julian , Zhang Wenmin , Martinsen Grith , He Xin , Stisen Simon .