Drought Vulnerability Assessment and Cluster Analysis of Island Areas Taking Korean Island Areas at Eup (Town) and Myeon (Subcounty) Levels as Study Targets

The purpose of this study is to conduct drought vulnerability assessment and cluster analysis of Korean island areas at eup (town) myeon (subcounty) level. Drought vulnerability assessment was conducted using factor analysis and entropy method, and cluster analysis was analyzed using K-means, a nonhierarchical cluster analysis method. Vulnerability consisted of climate exposure, sensitivity, and adaptive capacity. Twenty-two indicators were used to evaluate and analyze vulnerability of drought in small island areas. The results of entropy method showed that winter rainfall, no rainfall days, agricultural population rate, cultivation area rate, water supply rate and groundwater capacity have a substantial impact on drought assessment. The overall assessment of vulnerability indicated that Seodo-myeon Ganghwa-gun, Seolcheon-myeon Namhae-gun, and Samsan-myeon Ganghwa-gun were most vulnerable to drought. The cluster analysis was evaluated by categorizing the regions into three clusters, and policy support and planning are needed to suit the characteristics of each cluster was observed.

Future Projection of Drought Vulnerability over Northeast Provinces of Iran during 2021–2100

Future projection of drought vulnerability is vital for northern provinces of Iran, including North Khorasan, Khorasan-Razavi, and South Khorasan, due to the highly dependent of their economy on agriculture. The study is motivated by the fact that no research has been conducted to project the future Drought Vulnerability Index (DVI). DVI consist of three components of exposure, sensitivity, and adaptation capacity. More exposure levels of drought, higher sensitivity value, and lower adaptation capacity lead to a higher amount of vulnerability. Combined ERA-Interim-observation meteorological data, CMIP5 models under RCP4.5 and RCP8.5 scenarios, and national census data are used to estimate DVI in the past and future periods. CanESM2, GFDL-ESM2M, and CNRM-CM5 General Circulation Model (GCM) are selected from CMIP5 based on Taylor diagram results. The delta-change technique was selected for statistical downscaling of GCM outputs because it is most widely used. The study period is regarded as 1986–2005 as observation and four future 20-years periods during 2021–2100. Results indicated that the dissipation of the class of “very low” vulnerability is eminent in the near future period of 2021–2040 under the RCP4.5 scenario, and all provinces would experience a new worse class of “very high” vulnerability at 2081–2100, both under RCP4.5 and RCP8.5 scenarios.

Drought Hazard Modelling of Klaten Regency Central Java Using AHP and TOPSIS Method

According to information of areas at high risk of drought provided by Central Java disaster risk assessment in 2016 - 2020, Klaten Regency is in the top ten at high risk of drought in Central Java. Drought is an annual disaster in this region, which usually occurs during the dry season. The impact of the drought has caused some areas to experience a lack of clean water. For the purpose of disaster mitigation in anticipating and minimizing drought disasters losses, it is necessary to analyze the level of drought with a decision-making system by comparing two methods, namely the AHP with TOPSIS. Both methods are decision-making methods that are composed of various criteria to obtain an alternative sequence of choices. Both the AHP and TOPSIS methods produces weight values and a positive ideal solution value, respectively. These are used as input data in the mapping of drought vulnerability analysis with Geographical Information Systems (GIS). The results of the analysis are visualized with a map that shows the level of drought vulnerability. AHP and TOPSIS method decision making generates the order of the drought classes in predicting the distribution of areas experiencing drought. To validate the model, the authors compare the results of the analysis of drought vulnerability of the two methods with drought data from BPBD (Local Agency for Disaster Prevention) and DPUPR (Public Works and Public Housing Department). The results show that AHP provides better results than TOPSIS based on results validation with BPBD and DPUPR data. By comparing the two models with BPBD data, the results show that the percentage of AHP suitability is higher than TOPSIS at 47,619% and 19,048% respectively.

Remote sensing and GIS application for monitoring drought vulnerability in Indonesia: a review

Agricultural drought is one of the hydrometeorological disasters that cause significant losses because it affects food stocks. In addition, agricultural droughts, impact the physical and socio-economic development of the community. Remote sensing technology is used to monitor agricultural droughts spatially and temporally for minimizing losses. This study reviewed the literatures related to remote sensing and GIS for monitoring drought vulnerability in Indonesia. The study was conducted on an island-scale on Java Island, a provincial-scale in East Java and Bali, and a district-scale in Indramayu and Kebumen. The dominant method was the drought index, which involves variable land surface temperature (LST), vegetation index, land cover, wetness index, and rainfall. Each study has a strong point and a weak point. Low-resolution satellite imagery has been used to assess drought vulnerability. At the island scale, it provides an overview of drought conditions, while at the provincial scale, it focuses on paddy fields and has little detailed information. In-situ measurements at the district scale detect meteorological drought accurately, but there were limitations in the mapping unit's detailed information. Drought mapping using GIS and remote sensing at the district scale has detailed spatial information on climate and physiographic aspects, but it needs temporal data monitoring.

Assessing the Vulnerability of Agricultural Systems to Drought in Kyrgyzstan

As climate change worsens, the frequent occurrence of extreme drought events will further threaten the agricultural systems of all countries in the world. Kyrgyzstan is a country with agriculture and animal husbandry as its main industries, with a weak industrial base, and agriculture plays an important role in the national economy. Kyrgyzstan is located in Central Asia and suffers from a dry climate and frequent droughts. Thus, an integral analysis of the vulnerability of Kyrgyzstan’s agricultural system is of great significance for this country’s socio-economic stability. In this study, we comprehensively analyze the agricultural system drought vulnerability of Kyrgyzstan from three dimensions of sensitivity, adaptability and exposure. The results show that the areas of higher vulnerability in Kyrgyzstan’s agricultural system are distributed in the eastern mountainous, northwest and southwest areas. In addition, regions with low vulnerability are mainly concentrated in the central area. Kyrgyzstan has abundant water resources, but the supporting infrastructure construction is relatively backward. The imperfect irrigation facilities have greatly restricted the development of agriculture and have also increased the vulnerability of the agricultural systems. In the face of climate change, the region may face more severe drought disasters, so increasing infrastructure investment and building a complete irrigation system and water use plan are the keys to reducing the vulnerability of Kyrgyzstan’s agricultural system.