Validating the accuracy of remotely sensed soil moisture indicators for Thailand river basins using semi-distributed rainfall-runoff models

Name: Ekkarin Maekan

LCSH: Kasetsart University -- Dissertations. Ph.D. (Water Resources Engineering) 2023.

Classification :.LCCS: GB790

LCSH: Kasetsart University. -- Department of Water Resources Engineeringy -- Dissertations.

LCSH: Soil moisture -- Measurement -- Thailand.

LCSH: Hydrological modeling -- Thailand.

LCSH: Remote sensing -- Thailand.

Abstract: Soil moisture is a crucial element in the hydrologic cycle, affecting weather patterns, plant growth, and the groundwater storage. It significantly influences the Earth’s climate on a global scale. Assessing soil moisture at both catchment and sub-catchment levels poses a challenging task, requiring reliable accuracy to support effective water management. In this study, a combination of hydrological models and remote sensing technology was employed to identify soil moisture at the sub-catchment scale for six river basins in Thailand including the Lower Ping, Wang, Yom, Upper Nan, Lower Nan and Mun River Basins. The semi-distributed rainfall-runoff models, KU-FLEX-SD and KU-FLEX-SD-NDII, were employed for runoff estimation in these river basins. Additionally, FLEXL, a lumped rainfall-runoff model, was used as the baseline model. In the process of model calibration and validation, it was observed that FLEXL, calibrated at all gauging stations, demonstrated higher accuracy compared to the semi-distributed models, which were calibrated only at the most downstream stations. However, an exception was noted for stations affected by large-scale reservoir, where the semidistributed models performed substantially more accurately than the FLEXL. This was because outflows from the reservoirs can be included as the input data, enhancing the modeling precision. Nevertheless, the KU-FLEX-SD and KU-FLEX-SD-NDII models can provide flow estimates along with the root zone soil reservoir (Su) for all sub-catchments upstream of the calibrated gauging station. The time series of Su for all sub-catchments were found to correlate well with the average Normalized Difference Infrared Index (NDII) values during the dry season but much less during the wet season. In contrast, Soil Water Index (SWI) with optimal time windows demonstrated strong correlations with Su for both the wet season and the dry season. This study also found that NDII-SWI relationships can indicate moisture stress within sub-catchment scales, which are highly correlated with different land use categories. These findings can be applied to define soil moisture content within the sub-catchment scales as well as at the pixel scale. Such information would be valuable for hydrological studies and catchment water management

Kasetsart University. Office of the University Library

Address: Bangkok

Email: tdckulib@ku.ac.th

Name: Nutchanart Sriwongsitanon

Role: Thesis Advisor

Name: Punpim Puttaraksa Mapiam

Role: Thesis Co-Advisor

Created: 2023

Modified: 2026-07-08

Issued: 2026-07-08

วิทยานิพนธ์/Thesis

วิทยานิพนธ์/Thesis

application/pdf

URL: https://www.lib.ku.ac.th/KUthesis/2566/ekkarin-maek-all.pdf

CallNumber: GB790 .E44

eng

Spatial: Thailand.

Spatial: Thailand.

Spatial: Thailand.

DegreeName: Doctor of Philosophy

Level: Doctoral Degree

Descipline: Water Resources Engineering

Grantor: Kasetsart University

©copyrights Kasetsart University

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