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We explore future changes of temperature, precipitation, and drought characteristics in the Indochina Region (ICR) based on the optimal ensemble subset of global climate models (GCMs) of the Couple Model Intercomparison Project Phase 5 (CMIP5). The optimal ensemble subset is selected from 34 GCMs using an ensemble selection method by focusing on precipitation over ICR. Bias correction procedures for the optimal ensemble subset are examined for drought analysis in ICR. Based on the bias-corrected optimal ensemble subset, mean temperature in ICR is projected to increase around 1.1 °C (0.99 °C) in near future (2011–2040), 2.5 °C (1.8 °C) in mid future (2041–2070), and 4.3 °C (2.2 °C) in far future (2071–2100) time frames under representative concentration pathway 8.5 (RCP8.5) (RCP4.5) scenario. Mean precipitation decreases in the dry season and increases in the wet season. The 3-month Standardized Precipitation Evapotranspiration Index (SPEI-3) projects larger changes of drought characteristics than those of the 3-month Standardized Precipitation Index (SPI-3), especially quite large increases of drought duration, severity, and peak. Based on SPEI-3, the potential increase of severe drought hazard is expected in ICR in the far future period under both scenarios. The most drought-prone areas are detected over Thailand and Cambodia in which the drought characteristics are projected to expand to cover most parts of ICR in the mid and far future. The potentially dry condition over ICR is clearly depicted based on SPEI-3 with more reliable estimation after selecting the optimal ensemble subset and bias correction procedure.

The original article has been corrected. Figure 3 in the original article has been replaced by this figure.

The consequences of climate change are arising in the form of many types of natural disasters, such as flooding, drought, and tropical cyclones. Responding to climate change is a long horizontal run action that requires adaptation and mitigation strategies. Hence, future climate information is essential for developing effective strategies. This study explored the applicability of a statistical downscaling method, Bias-Corrected Spatial Disaggregation (BCSD), in downscaling climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and then applied the downscaled data to project the future condition of precipitation pattern and extreme events in Cambodia. We calculated four climate change indicators, namely mean precipitation changes, consecutive dry days (CDD), consecutive wet days (CWD), and maximum one-day precipitation (rx1day) under two shared socioeconomic pathways (SSPs) scenarios, which are SSP245 and SSP585. The results indicated the satisfactory performance of the BCSD method in capturing the spatial feature of orographic precipitation in Cambodia. The analysis of downscaled CMIP6 models shows that the mean precipitation in Cambodia increases during the wet season and slightly decreases in the dry season, and thus, there is a slight increase in annual rainfall. The projection of extreme climate indices shows that the CDD would likely increase under both climate change scenarios, indicating the potential threat of dry spells or drought events in Cambodia. In addition, CWD would likely increase under the SSP245 scenario and strongly decrease in the eastern part of the country under the SSP585 scenario, which inferred that the wet spell would have happened under the moderate scenario of climate change, but it would be the opposite under the SSP585 scenario. Moreover, rx1day would likely increase over most parts of Cambodia, especially under the SSP585 scenario at the end of the century. This can be inferred as a potential threat to extreme rainfall triggering flood events in the country due to climate change.

Basic wind speed is a very essential parameter used for conversion into wind loads on building structures. In Cambodia, the information on basic wind speed remains uncertain due to insufficient fundamental studies on the wind characteristics associated with regional climatic conditions. The aim of this paper is to assess and discuss the basic wind speeds for structural wind-resistant design in Cambodia by using statistical and probabilistic approaches. The datasets have been collected from National Centers for Environmental Information datasets, National Oceanic and Atmospheric Administration under World Meteorological Organization, and Mekong River Commission in forms of hourly wind speeds. The hourly wind speeds were then statically converted to 3-second gusts speeds using Gaussian Distribution Transformation. The extreme value distributions namely, Gumbel and Gringorten were used to analyze the extreme speed in accordance with a return period. The results showed that with a return period of 10 to 1000 years, the basic wind speed varies from a minimum of 22m/s to a maximum of 53m/s, respectively. These results provided a new aspect over traditionally uncertain basic wind speed selection and can be an alternative for the estimation of wind loads for the design of building structures in Cambodia.

The floating houses in Tonle Sap Lake might be one of the main factors for degradation of water quality since the people in floating houses discharge sewage and waste from their households into the lake. Therefore, the government of Cambodia has decided to move the floating houses in Chhnok Tru to the upland regions, and more than 90% of the floating houses in Chhnok Tru have already been moved in accordance with the government’s plan. However, the scientific information on water quality before and after moving the floating houses in Tonle Sap Lake is limited. Thus, this paper aimed to evaluate differences in basic water quality such as temperature, pH, dissolved oxygen (DO), oxidation–reduction potential (ORP), conductivity (Cond), and nitrate (NO3−) before and after the floating houses were moved and to reveal the relationships between the floating houses and basic water quality. The water quality parameters were measured at 18 sampling sites in Chhnok Tru using an EXO sensor and NO3− was analyzed by ion chromatography (IC). Statistical analyses such as t-tests, correlation analysis, principal component analysis (PCA), and structural equation modeling (SEM) were used. The results show that the water quality was better after moving the floating houses; however, some parts of the study area were still polluted. In addition, the percentage of floating house distribution was significantly correlated with the temperature and ORP in the study area during dry and wet seasons. The obtained results are useful for making management decisions to sustainably manage the water quality in the area.

Indochina Peninsula is located in between Bay of Bengal (BoB) and South-China Sea (SCS). This region is affected frequently from Tropical Cyclones (TCs) formed in North Indian Ocean (NIO), South-China Sea (SCS), and North West Pacific Ocean (NWP). This research analyzed the structure of the rainfall over Indochina Peninsula and its relationships with TCs from the aforementioned sources. Principle Component Analysis (PCA) was performed to investigate the dominant rainfall area produced from those TCs. Spatial and Temporal structures of rainfall from the TCs is analyzed to understand their propagation. The results show that the dominant TC rainfall area covers Central Vietnam which contributed around 25% to total rainfall in the region. However, the contribution of this TC rainfall over LMB is likely less than 20% where Laos's territory receives highest contribution (20%). Furthermore, from the three source areas, TCs formed in SCS produce the highest rain rate when they develop into typhoon intensity stage of Joint Typhoon Warning Center (JTWC)'s scale. The average duration of TC rainfall over Indochina Peninsula is 81.28 hours, and over LMB is 66.22 hours. Thus, same as other regions in the Indochina Peninsula, LMB is affected by TC rainfall with considerable scales both spatially and temporally that may lead to significant hydrometeorological hazards.