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Soil Moisture Fluctuation during Severe Flooding Events in Chiang Mai, Thailand Using SMAP Satellite Data
Organization(s):Chonprathan Wittaya
Country:Thailand
Student(s):Bunyaorn Orachorn, Haruitchaya Anurathapan, Kantapong payakkachai, Ketsarin Darathavat, Krittawan jarutasroj, Natthakan Saprom, Nirattichai Suksang, Paphatchaya Charattham, Phatchaya Chaichuaypakdee, Ravisara Sornkeaw, Sorawit boontam, Teethat Thosumralt.
Grade Level:Secondary School (grades 9-12, ages 14-18)
GLOBE Educator(s):Kaset Bubphapasom
Contributors:Assoc.Prof.Dr.Krisanadej Jaorensutasinee, Assoc.Prof.Dr. Mullica Jaroensutasinee, Dr.Watcharapong Srisaeng.
Report Type(s):International Virtual Science Symposium Report
Protocols:Soil Moisture - Gravimetric, Soil Moisture - SMAP Block Pattern
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Language(s):English
Date Submitted:12/24/2024
This study investigates the potential of Soil Moisture Active Passive (SMAP) satellite data for monitoring soil moisture changes during severe flooding events in Chiang Mai, Thailand, by exploring the relationship between soil moisture, river water levels, and flood extent. Data were collected from two study sites: a Chiang Mai hydrological measurement station and a Saraburi cornfield for validation. The research integrates field data from the GLOBE Soil Moisture Protocol, GLOBE Data Archive, SMAP satellite data, and water level data from the Upper Northern Region Irrigation Hydrology Center. Data analysis includes time series graphs, box-whisker plots, and linear regression to identify correlations between soil moisture and water levels during flooding. The study analyzed soil moisture data from GLOBE field measurements, GLOBE Retrieved Data (GLOBE-ADAT), and SMAP satellite data. The sample sizes were 5 for GLOBE field measurements, 415 for GLOBE-ADAT, and 324 for SMAP, with no missing data in any dataset. The mean ± standard deviation soil moisture values were 19.6 ± 7.37% g/g for GLOBE field measurements, 9.91 ± 7.19% g/g for GLOBE-ADAT, and 27.4 ± 3.26% m³/m³ for SMAP. The results demonstrate significant relationships between soil moisture in the root zone and surface layer and water levels. A linear relationship was observed between the water level in the Ping River and the soil moisture in the root zone, with the equation: Soil Moisture Rootzone = 0.01 × Water Level + 0.21. An ANOVA test confirmed the statistical significance of this relationship. These findings highlight SMAP's potential as a reliable flood monitoring and management tool, suggesting that SMAP data can improve flood prediction and contribute to effective flood management strategies in Thailand.