Floods are phenomenon with significant socio-economic implications mainly for human loss, agriculture, livestock, soil loss and land degradation, for which many researchers try to identify the most appropriate methodo...Floods are phenomenon with significant socio-economic implications mainly for human loss, agriculture, livestock, soil loss and land degradation, for which many researchers try to identify the most appropriate methodologies by analyzing their temporal and spatial development. This study therefore attempts to employ the GIS-based multi-criteria decision analysis and analytical hierarchy process techniques to derive the flood risks management on rice productivity in the Gishari Agricultural Marshland in Rwamagana district, Rwanda. Here, six influencing potential factors to flooding, including river slope, soil texture, Land Use Land Cover through Land Sat 8, rainfall, river distance and Digital Elevation Model are considered for the delineation of flood risk zones. Data acquisition like Landsat 8 images, DEM, land use land cover, slope, and soil class in the study area were considered. Results showed that if the DEM is outdated or inaccurate due to changes in the terrain, such as construction, excavation, or erosion, the predicted flood patterns might not reflect the actual water flow. This could result unexpected flood extents and depths, potentially inundating rice fields that were not previously at risk and this, expectedly explained that the increase 1 m in elevation would reduce the rice productivity by 0.17% due to unplanned flood risks in marshland. It was found that the change in rainfall distribution in Gishari agricultural marshland would also decrease the rice productivity by 0.0018%, which is a sign that rainfall is a major factor of flooding in rice scheme. Rainfall distribution plays a crucial role in flooding analysis and can directly impact rice productivity. Oppositely, another causal factor was Land Use Land Cover (LULC), where the Multivariate Logistic Regression Model Analysis findings showed that the increase of one unit in Land Use Land Cover would increase rice productivity by 0.17% of the total rice productivity from the Gishari Agricultural Marshland. Based on findings from these techniques, the Gishari Agricultural Marshlands having steeped land with grassland is classified into five classes of flooding namely very low, low, moderate, high, and very high which include 430%, 361%, 292%, 223%, and 154%. Government of Rwanda and other implementing agencies and major key actors have to contribute on soil and water conservation strategies to reduce the runoff and soil erosion as major contributors of flooding.展开更多
A municipal solid waste(MSW)management system needs solid waste management(SWM)techniques where the presence of a sanitary landfill is vital.One of the most important issues of sanitary landfilling is to locate the f...A municipal solid waste(MSW)management system needs solid waste management(SWM)techniques where the presence of a sanitary landfill is vital.One of the most important issues of sanitary landfilling is to locate the facility to an optimal location.Despite the versatility and case-dependent nature of conventional expert-based site selection procedures,the number of sites to be chosen increases with increased population forcing a number of constraints.Consequently,constraints and environmental regulations mechanically mask unsuitable areas,leaving very little areas to be assessed.This turns the situation into a challenging issue for a geographical information system(GIS)used with multicriteria decision analysis(MCDA),to select optimal site.The study aims to apply MCDA integrated with GIS to select possible sites of a MSW landfill with the same expert and same cognitive parameters while compared with the already present one.Results of this study revealed that conventional expert-based methods could not always evaluate all constraints at the same time and map reproduction is limited when parameter maps are changing rapidly in time.In order to produce cognitive and reproducible analyses,GIS with MCDA integration offers a good solution for site selection issue and forms a good alternative for conventional methods.展开更多
文摘Floods are phenomenon with significant socio-economic implications mainly for human loss, agriculture, livestock, soil loss and land degradation, for which many researchers try to identify the most appropriate methodologies by analyzing their temporal and spatial development. This study therefore attempts to employ the GIS-based multi-criteria decision analysis and analytical hierarchy process techniques to derive the flood risks management on rice productivity in the Gishari Agricultural Marshland in Rwamagana district, Rwanda. Here, six influencing potential factors to flooding, including river slope, soil texture, Land Use Land Cover through Land Sat 8, rainfall, river distance and Digital Elevation Model are considered for the delineation of flood risk zones. Data acquisition like Landsat 8 images, DEM, land use land cover, slope, and soil class in the study area were considered. Results showed that if the DEM is outdated or inaccurate due to changes in the terrain, such as construction, excavation, or erosion, the predicted flood patterns might not reflect the actual water flow. This could result unexpected flood extents and depths, potentially inundating rice fields that were not previously at risk and this, expectedly explained that the increase 1 m in elevation would reduce the rice productivity by 0.17% due to unplanned flood risks in marshland. It was found that the change in rainfall distribution in Gishari agricultural marshland would also decrease the rice productivity by 0.0018%, which is a sign that rainfall is a major factor of flooding in rice scheme. Rainfall distribution plays a crucial role in flooding analysis and can directly impact rice productivity. Oppositely, another causal factor was Land Use Land Cover (LULC), where the Multivariate Logistic Regression Model Analysis findings showed that the increase of one unit in Land Use Land Cover would increase rice productivity by 0.17% of the total rice productivity from the Gishari Agricultural Marshland. Based on findings from these techniques, the Gishari Agricultural Marshlands having steeped land with grassland is classified into five classes of flooding namely very low, low, moderate, high, and very high which include 430%, 361%, 292%, 223%, and 154%. Government of Rwanda and other implementing agencies and major key actors have to contribute on soil and water conservation strategies to reduce the runoff and soil erosion as major contributors of flooding.
基金Scientific&Technological Research Council of Turkey(TUBI˙TAK)for providing financial support of this work under Grant No:106Y305.
文摘A municipal solid waste(MSW)management system needs solid waste management(SWM)techniques where the presence of a sanitary landfill is vital.One of the most important issues of sanitary landfilling is to locate the facility to an optimal location.Despite the versatility and case-dependent nature of conventional expert-based site selection procedures,the number of sites to be chosen increases with increased population forcing a number of constraints.Consequently,constraints and environmental regulations mechanically mask unsuitable areas,leaving very little areas to be assessed.This turns the situation into a challenging issue for a geographical information system(GIS)used with multicriteria decision analysis(MCDA),to select optimal site.The study aims to apply MCDA integrated with GIS to select possible sites of a MSW landfill with the same expert and same cognitive parameters while compared with the already present one.Results of this study revealed that conventional expert-based methods could not always evaluate all constraints at the same time and map reproduction is limited when parameter maps are changing rapidly in time.In order to produce cognitive and reproducible analyses,GIS with MCDA integration offers a good solution for site selection issue and forms a good alternative for conventional methods.
