Towards a soil moisture drought monitoring system for South Korea SCIE SCOPUS

Cited 23 time in WEB OF SCIENCE Cited 28 time in Scopus
Title
Towards a soil moisture drought monitoring system for South Korea
Author(s)
Jung H.C.; Kang D.-H.; Kim E.; Getirana A.; Yoon Y.; Kumar S.; Peters-lidard C.D.; Hwang E.
Alternative Author(s)
정한철
Publication Year
2020-10
Abstract
The Korea Land Data Assimilation System (KLDAS) has been established for agricultural drought (i.e. soil moisture deficit) monitoring in South Korea, running the Noah-MP land surface model within the NASA Land Information System (LIS) framework with the added value of local precipitation forcing dataset and soil texture maps. KLDAS soil moisture is benchmarked against three global products: the Global Land Data Assimilation System (GLDAS), the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), and the European Space Agency Climate Change Initiative (ESA CCI) satellite product. The evaluation is performed using in situ measurements for 2013-2015 and one month standardized precipitation index (SPI-1) for 1982-2016, focusing on four major river basins in South Korea. The KLDAS outperforms all benchmark products in capturing soil moisture states and variability at a basin scale. Compared to GLDAS and FLDAS products, the EAS CCI product is not feasible for long term agricultural monitoring due to lower data quality for early periods (1979-1991) of soil moisture estimates. KLDAS shows that the most recent 2015 drought event leads to highest drought areas in the Han and Geum River basins in the past 35 years. This work supports KLDAS as an effective agricultural drought monitoring system to provide continuous regional high-resolution soil moisture estimates in South Korea.
ISSN
0022-1694
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/38573
DOI
10.1016/j.jhydrol.2020.125176
Bibliographic Citation
JOURNAL OF HYDROLOGY, v.589, 2020
Publisher
ELSEVIER
Subject
SURFACE; PRECIPITATION; MODEL; ASSIMILATION; INDEXES; RETRIEVALS
Keywords
Agricultural drought; Soil moisture; Precipitation; Land surface model
Type
Article
Language
English
Document Type
Article
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