Groundwater plays an important role for socioeconomic development of Comoro watershed in Timor Leste. Despite the significance of groundwater for sustainable development, it has not always been properly managed in the watershed. Therefore, this study seeks to identify groundwater potential zones in the Comoro watershed, using geographical information systems and remote sensing and analytic hierarchy process technique. The groundwater potential zones thus obtained were divided into five classes and validated with the recorded bore well yield data. It was found that the alluvial plain in the northwest along the Comoro River has very high groundwater potential zone which covers about 5.4 % (13.5 km 2 ) area of the watershed. The high groundwater potential zone was found in the eastern part and along the foothills and covers about 4.8 % (12 km 2 ) of the area; moderate zone covers about 2.0 % (5 km 2 ) of the area and found in the higher elevation of the alluvial plain. The poor and very poor groundwater potential zone covers about 87.8 % (219.5 km 2 ) of the watershed. The hilly terrain located in the southern and central parts of the study area has a poor groundwater potential zone due to higher degree of slope and low permeability of conglomerate soil type. The demarcation of groundwater potential zones in the Comoro watershed will be helpful for future planning, development and management of the groundwater resources.
Hand, Foot and Mouth Disease (HFMD) is an emerging viral disease, and at present, there are no antiviral drugs or vaccines available to control it. Outbreaks have persisted for the past 10 years, particularly in northern Thailand. This study aimed to elucidate the phenomenon of HFMD outbreaks from 2003 to 2012 using general statistics and spatial-temporal analysis employing a GIS-based method. The spatial analysis examined data at the village level to create a map representing the distribution pattern, mean center, standard deviation ellipse and hotspots for each outbreak. A temporal analysis was used to analyze the correlation between monthly case data and meteorological factors. The results indicate that the disease can occur at any time of the year, but appears to peak in the rainy and cold seasons. The distribution of outbreaks exhibited a clustered pattern. Most mean centers and standard deviation ellipses occurred in similar areas. The linear directional mean values of the outbreaks were oriented toward the south. When separated by season, it was found that there was a significant correlation with the direction of the southwest monsoon at the same time. An autocorrelation analysis revealed that hotspots tended to increase even when patient cases subsided. In particular, a new hotspot was found in the recent year in Mae Hong Son province.
Urban expansion is considered as one of the most important problems in several developing countries. Bangkok Metropolitan Region (BMR) is the urbanized and agglomerated area of Bangkok Metropolis (BM) and its vicinity, which confronts the expansion problem from the center of the city. Landsat images of 1988Landsat images of , 1993Landsat images of , 1998Landsat images of , 2003Landsat images of , 2008, and 2011 were used to detect the land use and land cover (LULC) changes. The demographic and economic data together with corresponding maps were used to determine the driving factors for land conversions. This study applied Cellular Automata-Markov Chain (CA-MC) and Multi-Layer Perceptron-Markov Chain (MLP-MC) to model LULC and urban expansions. The performance of the CA-MC and MLP-MC yielded more than 90% overall accuracy to predict the LULC, especially the MLP-MC method. Further, the annual population and economic growth rates were considered to produce the land demand for the LULC in 2014 and 2035 using the statistical extrapolation and system dynamics (SD). It was evident that the simulated map in 2014 resulting from the SD yielded the highest accuracy. Therefore, this study applied the SD method to generate the land demand for simulating LULC in 2035. The outcome showed that urban occupied the land around a half of the BMR.
Abstract:In recent years, research and development on liveable cities has gained much attention due to the complexity and diversity of liveability standards. Due to the already-existing grand-scale developments commonly found in most capitals, research on liveability is often conducted in smaller semi-urban cities. Using Khon Kaen District in Thailand as a case study, we have developed a Liveable City Index (LCI) based on residents' opinions and experts' recommendations with the integration of Geographic Information System (GIS) techniques. The first stage of the survey (out of three), identifies marked variations in attitudes towards the liveability of a city. The survey evaluates nine significant factors (Safety, Economy, Environment, Education, Health, Transportation, Recreation, Population Density, and Public Utility) through the Analytical Hierarchy Process (AHP) for LCI development. The LCI map reveals that only 3.49% of the Khon Kaen area corresponds to the highest and high liveable city levels. This contradicts the earlier ranking of the city as the most liveable city in 2010, which was only based on economic factors. Moreover, the proposed method was applied to another area-the Muang district of Suphanburi in western Thailand-in order to test its reliability, and the results were found to be similar. This clearly supports the integration of residents' participation in assessing the liveability of a city, and it is evident that this proposed approach can be adopted in other areas for LCI development.
Streamflow alteration is one of the most noticeable effects of climate change. This study explored the effects of climate change on streamflow in the Bheri River using the Soil and Water Assessment Tool (SWAT) model. Three General Circulation Models (GCMs) under two Representative Concentration Pathways (RCPs; 4.5 and 8.5) for the periods of 2020-2044, 2045-2069, and 2070-2099 were used to investigate the impact of climate change. Based on the ensemble of the three models, we observed an increasing trend in maximum and minimum temperatures at the rate of 0.025 • C/year and 0.033 • C/year, respectively, under RCP 4.5, and 0.065 • C/year and 0.071 • C/year under RCP 8.5 in the future. Similarly, annual rainfall will increase by 6.8-15.2% in the three future periods. The consequences of the increment in rainfall and temperature are reflected in the annual streamflow that is projected to increase by 6-12.5% when compared to the historical data of 1975-2005. However, on a monthly scale, runoff will decrease in July and August by up to 20% and increase in the dry period by up to 70%, which is favorable for water users.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.