Thailand was hit by a great flood in 2011 resulting from irregular rainfall during the typhoon season that was estimated at 140% more than average. The flood began in the north and slowly moved to the central region, where it remained for more than 4 months. The flood caused great damage to the economy because it adversely affected industrial estates and agricultural areas. In the north, there are four main rivers in the region that combine into a river called Chao Phraya in the central region. The Yom River is one of the northern rivers where no large-scale dam has been constructed, resulting in frequent flood and drought. Sukhothai Province is located in the Yom Basin, where flood and drought occur on a regular basis, and the province was also severely damaged in the 2011 flood. In order to estimate flood damage cost in 2011, a simple regression curve is presented first to relate flood areas and damage cost based on past records. The 2011 flood in Sukhothai province was then simulated by using a Rainfall-Runoff-Inundation (RRI) model with satellite based rainfall (TRMM). After simulation results were compared with the observed stream flow water level, discharge and inundation extent, this study estimates damage cost for the 2011 flood based on the simulated flood area. The proposed approach could be a useful guideline in damage cost computation.
In many provinces of Mekong delta, excessive groundwater extraction has resulted in many serious groundwater-related problems. To solve problems relevant to increasing water demand as well as other negative influence of groundwater depletion, an exigent question was raised whether at what time in future is the limits to local groundwater use reached? Hence, there is a need to know groundwater use (GWU) pattern and distribution in the study area for future groundwater management.In this study, firstly, the study used socio-economic data of Tra Vinh Province to classify groups of gross domestic product (GDP) per capita, potential of water resources and population distributed in each district in order to design and conduct the socio-economic survey and to explore information relevant to GWU for each purpose. Secondly, the data set of 419 survey questionnaires per 9 surveyed communes were analysed by SPSS tool to estimate ratio of household using groundwater (RHHUG) for each purpose as well as average pumping rate (APR) per household for domestic use and per ha for agriculture use, respectively. Thirdly, the APRs were extended to propose the total GWU pattern and distribution during 2007-2016 by using socioeconomic data of the province and expand to spatial distribution by using correlation with land surface temperature (LST) which was estimated from Landsat 8 images. Besides, the groundwater flow model of the study area was developed to verify the estimated amount of groundwater pumping (pattern and distribution) in the period.The study found that the GWU of Tra Vinh Province in dry season of 2016 was 346,279 m 3 /d in which two coastal districts occupied more than 50 percentages, i.e., about 188,551 m 3 /d. RHHUG increased from 1.5 to 2 times during the period of 2007 to 2016 in this area. LST distribution performed a good correlation (adj-R 2 = 0.646) with GWU distribution in Tra Cu district. Results of groundwater modelling also showed that the discharge from aquifer (mainly pumping) was always higher than the recharge to aquifer.
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