Big Data Applications in Hydrology

Title
Big Data Applications in Hydrology
Author(s)
Jung, Hahn Chul
KIOST Author(s)
Jung, Hahn Chul(정한철)
Alternative Author(s)
정한철
Publication Year
2021-05-26
Abstract
The satellite and model data have complementary advantages and disadvantages and they can be merged to produce an optimally merged hydrological product. First, 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. This study compares KLDAS products with two benchmark LDAS products and one remote sensing product (ESA CCI) and examines the performance of KLDAS agricultural drought area percentages in the four major river. Second, total water storage (TWS) estimates from the Gravity Recovery and Climate Experiment (GRACE) mission were assimilated into the Catchment Land Surface Model (CLSM) and its impacts on surface soil moisture (SSM) simulations were evaluated for the years, 2002–2017. This study analyzes the impact of GRACE DA on modeled SSM and presents the qualitative comparisons of seasonality and annual trend of these SSM estimates in West Africa.
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/41451
Bibliographic Citation
International Symposium on Remote Sensing 2021, 2021
Publisher
The Korean Society of Remote Sensing
Type
Conference
Language
English
Publisher
The Korean Society of Remote Sensing
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