Several related pre-event environment indices coupled with a 200-year event of Typhoon Morakot were used in this study to analyse landslide risk/scale for mapping and verifying the danger grade of watershed landslides. Risk analysis was modelled using maximum daily rainfall of the tested event as the hazard factor, and a complex indicator derived from indices of return period, road development and green deterioration as the vulnerability factor. The vulnerability factor was then modified using the slope to adjust the weight for excluding the flat areas and increasing impact of steep areas. A comprehensive indicator integrated from indices of river concave, headward erosion and dip slope was provided as the hotspot of potential large-scale landslides which were modified by vegetation index to correct sediment yield due to antecedent effects. Finally, sites with high potential large-scale landslide could be interpreted by the danger grade calculated from collapse risk/scale analysis. The results show that the higher the danger grade, the greater the collapse ratio; and the coefficient of determination for the relationship is greater than 0.9. The model developed in this study for accurately estimating the risk/scale of rainfall-induced landslide can be fulfilled.

Meteorological conditions change substantially during rainstorms, potentially affecting ambient concentrations of fungal spores. Exposure to ambient fungal spores during rainstorm periods may result in adverse health outcome such as thunderstorm asthma and allergic symptoms. This study investigated the ambient concentrations of culturable fungi during rainstorms period in Bangkok, Thailand. Using a single-stage impactor, air samples were collected between October and November 2017, when Thailand was struck by three major tropical cyclones: Typhoon Khanun, Typhoon Damrey, and Typhoon Kirogi. Fungal colonies were counted and identified according to their morphology. Meteorological data were obtained from the Thai Meteorological Department. Multiple regression analysis, performed to determine the associations between fungal concentrations and meteorological parameters, revealed a mean fungal concentration of 1,230 ± 1,136 CFU/m³ (n = 60). Fungal concentrations increased before the rainstorm arrival and decreased during the downpour rain. The fungal genera Cladosporium sp., Penicillium sp., and Aspergillus sp. were commonly observed but less than nonsporulating fungi, which accounted for more than 68% of all colonies. Fungal concentrations were positively associated with meteorological parameters, namely temperature, relative humidity, and maximum wind speed (R² = 0.58, p < 0.05). Considerable changes in daily weather conditions during rainstorm periods strongly affected the fungal concentrations. Future studies should collect relevant hospital admission and more fungal monitoring data to determine the associations between fungal exposure during rainstorm periods and adverse outcomes.

Low-cost capacitive soil moisture sensors have potential application in precision irrigation in Thailand. However, these sensors require proper calibration and are affected by soil temperature fluctuations that reduce their measurement accuracy. This study developed and validated a combined calibration and temperature compensation approach for the commercially available soil stick sensor. The calibration was performed using soil samples ranging from sandy clay loam to silty clay. A temperature compensation equation was developed by measuring the sensor responses under varying soil temperatures and moisture content levels in outdoor conditions. The sensor performance was assessed against a reference Time-Domain Reflectometry (TDR) sensor (TRIME-PICO64) and evaluated based on continuous field measurements for 14 days. The temperature compensation equation reduced the diurnal temperature effects through a linear correction model. The calibration showed a piecewise linear relationship between the Relative Voltage (VR) and volumetric water content (qV) with a strong correlation. The performance of the calibrated soil stick sensor was comparable to the TDR sensor, with the Confidence Index values exceeding 0.8. These findings indicated that the calibrated and temperature-compensated low-cost capacitive sensors could provide accurate soil moisture measurements for precise irrigation scheduling.

This study aims to assess a spillway’s capacity to manage the highest possible fluctuations in water levels, the probable maximum flood (PMF). The PMF values have experienced alterations throughout the last six decades since the initial design and construction of the Kaeng Krachan Dam, one of Thailand’s major dams. The study also conducted an assessment of the greatest levels of rainfall for different timeframes, known as probable maximum precipitation (PMP). This was achieved by simulating the movement of rainstorms into the reservoir area near the dam. Afterwards, a thorough examination was carried out on several time periods related to anticipated flood volumes, PMF, and the spillway’s capability. The research entailed a comprehensive analysis of rainfall occurrences spanning 65 years, encompassing a total of 190 storm events, to present the top 10 highest recorded levels of rainfall in the southern and western regions of Thailand. This information is of utmost significance in assessing the potential maximum rainfall in the study area. The results reveal that the highest PMP observed over a three-day period was 429.20–726.40 mm, which is slightly different from the results obtained using storm transposition method (513.90–869.76 mm). Results of PMF and base flow were 4677.00 and 86.80 cms, respectively. The results of the examination of the estimated maximum flood volumes and their comparison with previous studies show that the maximum flow rates per unit area are within reasonable and consistent boundaries. The current spillway has the capability to manage flood flows with a frequency of up to 10,000 years. Nevertheless, while examining the potential PMF, it has been concluded that the existing spillway’s capacity is insufficient to adequately handle the highest water level in the reservoir, therefore preventing it from exceeding the designated maximum water level.