Spatial Seasonal Distribution of Climatological Precipitation over the Middle of the Indochina Peninsula

Rainfall intensity and frequency are important parameters in agricultural development and water resource management. The middle of the Indochina peninsula climate is characterized by rainfall variability associated with complex terrains. The present study focuses on spatial seasonal extreme precipitation trends over the middle of the Indochina Peninsula for the 30 year period from 1978-2007. Daily gridded precipitation data obtained at 0.5° horizontal grid resolution from APHRODITE (Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of Water Resources) was used to detect the spatial trends with the use of the Man-Kendall and Theil-Sen approach. Extreme precipitation indices were selected from the WMO–CCL/CLIVAR list of extreme precipitation indices focusing on intensity and frequency. The study shows a consistently increasing upward trend at 10.04 d from the WDAY index. In seasonal analysis, the pre-monsoon trend shows a significant upward trend in the PRCTOT index, while the WDAY index for pre-monsoon season has the highest correlation coefficient in downward trend. Spatial analysis of extreme precipitation indices shows that the PRCTOT index of the pre-monsoon season has the largest percentage change in significant upward trend over the northern Basins that are consistent with MAX and Mean but not for WDAY. In addition, the inter-annual relationship between the Oceanic Nino Index and PRCTOT is shown in relation with the La Niña phase for both April and May

Radar Quality Index for a Mosaic of Radar Reflectivity over Chao Phraya River Basin, Thailand

The weather radar is one of the tools that can provide spatio-temporal information for nowcast which is useful for hydro-meteorological disasters warning and mitigation system. The ground-based weather radar can provide spatial and temporal information to monitor severe storm over the risky area. However, the usage of multiple radars can provide more effective information over large study area where single radar beam may be blocked by surrounding terrain Even though, the investigation of the sever storm physical characteristics needs the information from multiple radars, the mosaicked radar product has not been available for Thai researcher yet. In this study, algorithm of mosaicked radar reflectivity has been developed by using data from ground-based radar of Thai Meteorological Department over the Chao Phraya river basin in the middle of Thailand. The Python script associated with OpenCV and Wradlib libraries (Heistermann et al., 2013) are used in our investigations of the mosaicking processes. The radar quality index (RQI) field has been developed by implementing an equation of a quality radar index to identify the reliability of each mosaicked radar reflectivity pixels. First, the percentage of beam blockage is computed to understand the radar beam propagation obstructed by surrounding topography in order to clarify the limitations of the observed beam on producing radar reflectivity maps. Second, the elevation of beam propagation associated with distance field has been computed. Then, these two parameters and the obtained percentage of beam blockage are utilized as the parameters in the equation of RQI. Finally, the detected radar flare, non-precipitating radar area, has been included to the RQI field. Then, the RQI field has been applied to the extracted radar reflectivity to evaluate the quality of mosaicked radar reflectivity to inform end user in any application fields over the Chao Phraya river basin

Land Cover Classification Based on UAV Photogrammetry and Deep Learning for Supporting Mine Reclamation: A Case Study of Mae Moh Mine in Lampang Province, Thailand

Detailed, accurate, and frequent mapping of land cover are the prerequisite regarding areas of reclaimed mines and the development of sustainable project-level for goals. Mine reclamation is essential as the extractive organizations are bounded by-laws that have been established by stakeholders to ensure that the mined areas are properly restored. As databases at the mines area become outdated, an automated process of upgrading is needed. Currently, there are only few studies regarding mine reclamation which has less potential of land cover classification using Unmanned Aerial Vehicle (UAV) photogrammetry with Deep learning (DL). This paper aims to employ the classification of land cover for monitoring mine reclamation using DL from the UAV photogrammetric results. The land cover was classified into five classes, comprising: 1) trees, 2) shadow, 3) grassland, 4) barren land, and 5) others (as undefined). To perform the classification using DL, the UAV photogrammetric results, orthophoto and Digital Surface Model (DSM) were used. The effectiveness of both results was examined to verify the potential of land cover classification. The experimental findings showed that effective results for land cover classification over test area were obtained by DL through the combination of orthophoto and DSM with an Overall Accuracy of 0.904, Average Accuracy of 0.681, and Kappa index of 0.937. Our experiments showed that land cover classification from combination orthophoto with DSM was more precise than using orthophoto only. This research provides framework for conducting an analytical process, a UAV approach with DL based evaluation of mine reclamation with safety, also providing a time series information for future efforts to evaluate reclamation. The procedure resulting from this research constitutes approach that is intended to be adopted by government organizations and private corporations so that it will provide accurate evaluation of reclamation in timely manner with reasonable budget

A Fuzzy AHP Approach to Assess Flood Hazard for Area of Bang Rakam Model 60 Project in Yom River Basin, Northern Thailand

The Thai government developed the “Bang Rakam Model 60” to solve flood issues in low-lying areas (Phitsanulok and Sukhothai Provinces). In the project, farmers will have to start planting in early April and harvest in July. This research proposes a methodology for assessing flood hazard using a fuzzy analytic hierarchy process (fuzzy AHP) relied on Chang’s extent analysis. It was employed to derive the weight for factor ranking and create a flood hazard map. Eight hazard factors are considered in the methodology: average annual rainfall, drainage density, distance from drainage network, soil water infiltration, land use, elevation, slope, and flow accumulation. The generated flood hazard maps were validated using the repeated flood area from Geo-Informatics and Space Technology Development Agency (GISTDA). Due to the difference of rated opinion on the drainage density factor, the eight experts were divided into two groups of four each. The results of both expert groups indicated that the most pivotal influencing factor to flood hazard is the average annual rainfall. From the first group, it is stated that the highest flood hazard areas are in Phrom Phiram, Mueang Phitsanulok, and Bang Rakam Districts. Whereas, the second group stated that very high flood hazards level occurring mostly in Phrom Phiram District. The flood hazard area was divided into five levels of very low, low, moderate, high, and very high which the first group found that they covered 75.59 km2, 184.44 km2, 211.94 km2, 165.78 km2, and 57.81 km2, respectively, while the second group found that they covered 38.93 km2, 100.22 km2, 175.58 km2, 218.90 km2, and 161.91 km2, respectively. The obtained flood hazard assessment provides crucial information for future flood preparation, response, prevention, mitigation, and recovery initiatives. Moreover, it will guide the government agencies in supplying water and save the compensation budget to victims’ flood-affected farms

雨量計補正した地上レーダデータ作成による夏季モンスーン期インドシナ半島中央部における降雨の研究

京都大学0048新制・課程博士博士(理学)甲第19168号理博第4108号新制||理||1591(附属図書館)32160京都大学大学院理学研究科地球惑星科学専攻(主査)准教授 重 尚一, 准教授 林 泰一, 教授 余田 成男学位規則第4条第1項該当Doctor of ScienceKyoto UniversityDGA

Radar rainfall analysis in the middle of Indochina peninsular

The method of measurement a radar rainfall is studied using both a standard Z-R, B=200 and β=1.6, and a calculated Z-R. A temporal average of radar rainfall shows a good statistics between the radar rainfall (RR) and the gauge rainfall (RG). The calculated Z-R parameters in September 2009 are 18.51 and 1.96 for B and β respectively. Using a calculated conversion factor (C.F) from the calculated Z-R shows a good result of validation of RR and RG. Rainfall pattern shows a high rain rate and high standard deviation of daily mean of rainfall near the Annam range

Dual-Polarimetric Radar Applications for Investigating Severe Thunderstorms in Northern Thailand during the Pre-Monsoon Season

Understanding the physical characteristics of severe pre-monsoon thunderstorms is crucial for mitigating the adverse impacts of natural disasters on people in tropical regions. On April 23, 2020, a severe storm affected the Chiang Khong District of the Chiang Rai Province in Northern Thailand, causing devastation to more than 500 houses with hail and strong winds. This study investigated the storm's physical characteristics using dual-polarimetric radar data from the Thai Meteo-rological Department (TMD). Using a combination of polarimetric radar variables, such as reflectivity (ZH), specific differential phase (KDP), differential reflectivity (ZDR), and copolar correlation coefficient (ρhv), fuzzy logic was utilized to classify the hydrometeor types. During the severe storm that affected the Chiang Khong District, hail and large raindrops were mixed in with the rain, according to the analysis. Two severe storms were observed in the unorganized mesoscale convective systems that were analyzed, with the second storm producing more intense effects due to the radar reflectivity shape of a bow echo that generated strong wind gusts. The Doppler radar data retrieved the wind field, indicating the convergence of intense local winds during the storm, which was consistent with the analysis results of synoptic-scale weather systems from ECMWF Reanalysis v5 (ERA5). In addition, a Hovmöller diagram revealed orographic enhancement of the convective cloud as the storm passed through mountainous regions prior to approaching the Chiang Khong District. The findings of this study can provide valuable information for TMD's near-real-time warning operation in order to minimize loss of life and property from future severe storms