Vulnerability Map Research Articles

PEMETAAN KERAWANAN BANJIR DI KOTA SURAKARTA

<p class="Keywords"><em><span lang="EN-GB">Floods have become one of the problems occurring in the city of Surakarta. The floods are caused by the overflow of the tributaries of the Bengawan Solo River, located within the Surakarta City area. One of the strategies for flood disaster management is through flood zone mapping. In flood vulnerability mapping, hydrological analysis is conducted to determine the magnitude of the flood discharge for different return periods (Q<sub>2</sub>, Q<sub>5</sub>, Q<sub>10</sub>, Q<sub>25</sub>, and Q<sub>50</sub>) using the HSS SCS method, which will serve as input for the HEC-RAS program to simulate floods, used as determining variables in flood vulnerability mapping. The results of the flood simulation analysis indicate that the level of vulnerability in non-vulnerable areas has a flood area limit ranging from 1.05 ha to 8.93 ha, a maximum flood depth limit ranging from 0.24 m to 0.57 m, and a maximum flood velocity limit ranging from 0.06 m/sec to 0.21 m/sec. For areas with low vulnerability, the flood area limit ranges from 8.93 ha to 16.80 ha, the maximum flood depth limit ranges from 0.57 m to 0.90 m, and the maximum flood velocity limit ranges from 0.21 m/sec to 0.35 m/sec. For areas with moderate vulnerability, the flood area limit ranges from 16.80 ha to 24.68 ha, the maximum flood depth limit ranges from 0.90 m to 1.23 m, and the maximum flood velocity limit ranges from 0.35 m/sec to 0.50 m/sec. For areas with high vulnerability, the flood area limit ranges from 24.68 ha to 32.55 ha, the maximum flood depth limit ranges from 1.23 m to 1.55 m, and the maximum flood velocity limit ranges from 0.50 m/sec to 0.64 m/sec.</span></em></p>

GIS-based Social Vulnerability Integration for Robust Flood Response, Disease Prevention and Community Resilience in Chennai Metropolitan Area post-Cyclone Michaung

The present study outlines a comprehensive strategy for flood response, disease prevention and long-term community resilience in the aftermath of a recent Cyclone Michaung, with the proximity of landfall near Chennai and the increased likelihood of flooding in the CMA. Drawing insights from an existing social vulnerability map, the study addresses the unique challenges posed by flooding and aims to mitigate the heightened risk of waterborne and vector-borne diseases. Objectives encompass assessing social vulnerability, formulating a targeted flood response strategy, implementing healthcare interventions for disease prevention, strengthening information dissemination and advocating for long-term resilience planning. The methodology involves reviewing the existing vulnerability map, identifying vulnerable communities, integrating flood impact data and developing a comprehensive response plan. The study utilizes GIS and Remote Sensing technologies for monitoring and assessing the results. Key findings from the social vulnerability assessment inform prioritized intervention areas for both flood response and disease prevention. The discussion interprets results in the context of strategy effectiveness, emphasizing the significance of a nuanced and inclusive approach. This manuscript serves as a guide for stakeholders in implementing a holistic strategy that addresses immediate concerns, prevents disease outbreaks and fosters long-term community resilience.

An integrated risk assessment method for urban areas due to chemical leakage accidents

Chemical parks which hold large inventories of hazardous materials have become one important type of urban critical infrastructure. The hazardous chemical leakage such as toxic gas leakage has emerged in recent years, resulting in not only serious environmental pollution but also catastrophic consequences to certain urban areas. It is critical to make scientific risk assessment for such events to reduce negative effects. To address this issue, an integrated urban risk assessment (IURA) method coupling consequences of chemical leakage accidents and the vulnerability of local population is proposed in this work. The threat zones and hazard maps of toxic gas dispersion are present by using the ALOHA software. The population vulnerability is decided by three indicators including exposure, sensitivity, and adaptive capacity of residents in affected areas, the Grey Correlation-TOPSIS (GC-TOPSIS) method is used to rank the vulnerability of different regions. The ArcGIS software is applied to generate an integrated risk map through superimposing the hazard map and the population vulnerability map. The original risk matrix evaluation results were subdivided using the Borda count method. A case about an industrial city in Hubei, China is analyzed to test the method. Result shows the new integrated risk assessment method is more accurate and effective, which is beneficial for the government to develop emergency plans and enhance the safety of people.

GROUNDWATER VULNERABILITY MAP OF BASARA BASIN, SULAIMANI GOVERNORATE, IRAQI KURDISTAN REGION

The Basara basin which is one of the most promising hydrogeological basin in Iraqi Kurdistan Region, located in north east of Iraq, 25 km west of Sulaimani city, between the 496652 - 537752 East and 3911038 - 3951906 North in Universal Transverse Mercator (UTM) and lie in Zone 38N. The basin has a rectangular shape and covering an area of 571 km². The present hydrogeological investigations have revealed three inhomogeneous and anisotropic water bearing formations: Eocene Karstic Fissured Aquifer (EKFA), Intergranular Aquifer represented by Alluvium and Pliocene (AIA) & (PIA), as well as Miocene Complex Aquifer (MCA).For the first time, not only in Kurdistan but also in Iraq, Groundwater Vulnerability Map has been constructed in this study, using DRASTIC method with the assistance of Geographic Information System (GIS) to show zonation area of high and low groundwater susceptibility to pollution. Accordingly, vulnerability classes of the study area were classified into four classes. Most of the basin shows the highest extension of the zones with very low and low vulnerability zones, in contrast the zones with high vulnerability are distributed mainly in the mountain areas, solely in the eastern Uloblagh and Kuwaik mountains, in addition to that small zones in the farthest northern corner and south western corner of the area have less or no human activity.

Using VES and GIS-Based DRASTIC Analysis to Evaluate Groundwater Aquifer Contamination Vulnerability in Owerri, Southeastern Nigeria

This study assesses groundwater vulnerability in Owerri, Nigeria, using Vertical Electrical Sounding (VES) and Geographic Information System (GIS)-based DRASTIC modeling. The research methodology includes literature review, field survey, geological feature mapping, hydrogeological assessment, geo-electrical sounding, and data interpretation. Owerri, a rapidly developing city with flat topography and a growing population, uses the DRASTIC model to construct a groundwater vulnerability map. The model evaluates the risk of groundwater contamination using seven critical criteria, including depth to water table, net recharge, aquifer media, soil media, topography, vadose zone impact, and hydraulic conductivity. Each parameter was given a weight and rating, and the DRASTIC Index (DI) was calculated by summing the products of the weights and ratings for each factor. The results of the vulnerability assessment indicated that approximately 49% of the study area falls into the high vulnerability category, around 45% is classified as moderate vulnerability, and the remaining 6% is labeled as low vulnerability. The study reveals moderate to high vulnerability zones in Owerri, Nigeria, due to factors like lower slope terrain, permeable aquifer media, and vadose zone impact. The use of VES and GIS-based DRASTIC mapping techniques provides insights into groundwater vulnerability, aiding in sustainable resource management and environmental protection. The findings emphasize the importance of understanding potential risks and the need for effective management strategies to safeguard clean water supplies. Further research and mitigation efforts should focus on highly vulnerable areas.

Mapping seabird vulnerability to offshore wind farms in Norwegian waters

IntroductionOffshore wind energy development (OWED) has been identified as a major contributor to the aspired growth in Norwegian renewable energy production. Spatially explicit vulnerability assessments are necessary to select sites that minimize the harm to biodiversity, including seabird populations. Distributional data of seabirds in remote areas are scarce, and to identify vulnerable areas, species, and seasons it is necessary to combine data sets and knowledge from different sources.MethodsIn this study, we combined seabird tracking data, data from dedicated coastal and seabird at-sea surveys, and presence-only data from citizen science databases to develop habitat suitability maps for 55 seabird species in four seasons throughout the Norwegian exclusive economic zone; in total 1 million km2 in the Northeast Atlantic. The habitat suitability maps were combined with species-specific vulnerability indicators to yield maps of seabird vulnerability to offshore wind farms (OWFs). The resulting map product can be used to identify the relative vulnerability of areas prospected for OWED with respect to seabird collision and habitat displacement. More detailed assessments can be done by splitting the spatial indicators into seasonal and species-specific components.Results and discussionAssociated with higher diversity of seabirds near the coast, the cumulative vulnerability indicator showed a strong declining gradient from the coast to offshore waters while the differences in vulnerability between ocean areas and seasons were negligible. Although the present map product represents the best currently available knowledge, the indicators are associated with complex uncertainties related to known and unknown sampling biases. The indicators should therefore be used cautiously, they should be updated regularly as more data become available, and we recommend that more detailed environmental impact assessments based on dedicated seabird surveys, tracking of birds from potentially affected populations and population viability analyses are conducted in areas ultimately selected for OWED.

Comparative study for coastal aquifer vulnerability assessment using deep learning and metaheuristic algorithms.

Coastal aquifer vulnerability assessment (CAVA) studies are essential for mitigating the effects of seawater intrusion (SWI) worldwide. In this research, the vulnerability of the coastal aquifer in the Lahijan region of northwest Iran was investigated. A vulnerability map (VM) was created applying hydrogeological parameters derived from the original GALDIT model (OGM). The significance of OGM parameters was assessed using the mean decrease accuracy (MDA)method, with the current state of SWI emerging as the most crucial factor for evaluating vulnerability. To optimize GALDIT weights, we introduced the biogeography-based optimization (BBO) and gray wolf optimization (GWO) techniques to obtain to hybrid OGM-BBO and OGM-GWO models, respectively. Despite considerable research focused on enhancing CAVA models, efforts to modify the weights and rates of OGM parameters by incorporating deep learning algorithms remain scarce. Hence, a convolutional neural network (CNN) algorithm was applied to produce the VM. The area under the receiver-operating characteristic curves for OGM-BBO, OGM-GWO, and VMCNN were 0.794, 0.835, and 0.982, respectively. According to the CNN-based VM, 41% of the aquifer displayed very high and high vulnerability to SWI, concentrated primarily along the coastline. Additionally, 32% of the aquifer exhibited very low and low vulnerability to SWI, predominantly in the southern and southwestern regions. The proposed model can be extended to evaluate the vulnerability of various coastal aquifers to SWI, thereby assisting land use planers and policymakers in identifying at-risk areas. Moreover, deep-learning-based approaches can help clarify the associations between aquifer vulnerability and contamination resulting from SWI.

Advancing groundwater vulnerability assessment in Bangladesh: a comprehensive machine learning approach

In response to Bangladesh's severe water shortages, this research delves into the intricate dynamics of groundwater vulnerability. Integrating often-overlooked factors such as topography, meteorology, socio-economic conditions, and land use & geology, the study employs advanced Random Forest (RF) modeling. Rigorously analyzing 200 strategically chosen sample points, the research uncovers critical areas like Rajshahi, Nawabganj, Naogaon, and Dhaka, constituting 21% of the land, as highly vulnerable. In contrast, regions like Rangpur, Mymensingh, and Barisal, encompassing 31% of the area, exhibit lower vulnerability. Topographic factors, accounting for 45% of the vulnerability, including aspect, drainage density, and slope, significantly influence susceptibility. Socio-economic elements contribute 22%, particularly population density and industrial activities. The RF model achieves exceptional accuracy (over 90%), emphasizing the complexity of groundwater dynamics. By integrating geological, social, and economic aspects, the study provides actionable insights for nuanced and sustainable management strategies. This research not only unveils a highly accurate groundwater vulnerability map, enriching scientific understanding, but also offers a unique approach by incorporating often-overlooked variables and leveraging machine learning. These insights empower policymakers and urban planners to craft targeted and sustainable groundwater management strategies, ensuring a resilient water supply system for Bangladesh's growing population. Through this work, the aim is to significantly contribute to the scientific community while providing data-driven solutions for the nation's pressing water challenges.

Flood vulnerability assessment trough overlay-scoring data method based on Geographical Information System (GIS) in Giriwoyo, Wonogiri, Indonesia

The Sub-District of Giriwoyo, located on the southern edge of Wonogiri District, is classified as an agricultural land. This subdistrict is located in the Keduang sub-watershed. This geographical condition makes this subdistrict extremely vulnerable to flooding. This research seeks to determine the distribution of flood-prone areas and categorize the level of flood vulnerability in the Wonogiri Regency, with Giriwoyo as a research site. Quantitative descriptive research employs a scoring procedure based on environmental conditions-related scoring parameters. These variables include slope, soil type, rainfall, altitude, land use, and buffers for river flow. The measured parameters are then layered in a geographic information system (GIS) application to generate a flood vulnerability map. The data analysis procedure employed a descriptive approach. The results indicate that the dispersed, areas of Giriwoyo are classified into 4 vulnerability catogeries such as not vulnerable, vulnerable enough, vulnerable and very vulnerable. Areas with vulnerable categories are scattered throughout the giriwoyo area which is dominated by rice fields and settlements with a flat slope. The very vulnerable area dominates the western part of the giriwoyo which has a lower elevation and flat slope. The parts of giriwoyo that are not prone to flooding are in Selomarto, Tukulrejo, and Girikikis.

Assessing Social Vulnerability to Coastal Hazards: A Case Study of Bandar Lampung City Coastal Area

Bandar Lampung City’s coastal area is highly susceptible to coastal hazards due to its location within the subduction zone of the Indo-Australian and Eurasian tectonic plates. Additionally, the presence of the Anak Krakatau volcano in the Sunda Strait further increases the vulnerability of the city’s coast to natural disasters. This study analyses the current social vulnerability in the coastal area of Bandar Lampung City. The aim is to provide a starting point for disaster management and policy planning in the city. To determine the level of social vulnerability in the coastal area of Bandar Lampung City, social vulnerability mapping is conducted by overlaying four indices: population, population density, sex ratio, and dependency ratio. The data indicates that there is significant variation in the level of social vulnerability among the coastal areas of Bandar Lampung City. Specifically, 8 out of 25 villages in the coastal area of Bandar Lampung City exhibit high levels of social vulnerability. The villages of Bumi Waras, Pesawahan, and Keteguhan have the highest levels of social vulnerability in the coastal area of Bandar Lampung City. As revealed by this study, the indicators of population size and dependency ratio have the most significant impact on the level of social vulnerability. These findings are expected to provide valuable input to stakeholders in their efforts to reduce social vulnerability in coastal areas.

An Empirical Social Vulnerability Map for Flood Risk Assessment at Global Scale (“GlobE‐SoVI”)

AbstractFatalities caused by natural hazards are driven not only by population exposure, but also by their vulnerability to these events, determined by intersecting characteristics such as education, age and income. Empirical evidence of the drivers of social vulnerability, however, is limited due to a lack of relevant data, in particular on a global scale. Consequently, existing global‐scale risk assessments rarely account for social vulnerability. To address this gap, we estimate regression models that predict fatalities caused by past flooding events (n = 913) based on potential social vulnerability drivers. Analyzing 47 variables calculated from publicly available spatial data sets, we establish five statistically significant vulnerability variables: mean years of schooling; share of elderly; gender income gap; rural settlements; and walking time to nearest healthcare facility. We use the regression coefficients as weights to calculate the “Global‐Empirical Social Vulnerability Index (GlobE‐SoVI)” at a spatial resolution of ∼1 km. We find distinct spatial patterns of vulnerability within and across countries, with low GlobE‐SoVI scores (i.e., 1–2) in for example, Northern America, northern Europe, and Australia; and high scores (i.e., 9–10) in for example, northern Africa, the Middle East, and southern Asia. Globally, education has the highest relative contribution to vulnerability (roughly 58%), acting as a driver that reduces vulnerability; all other drivers increase vulnerability, with the gender income gap contributing ∼24% and the elderly another 11%. Due to its empirical foundation, the GlobE‐SoVI advances our understanding of social vulnerability drivers at global scale and can be used for global (flood) risk assessments.

Landslide potential mapping in Pituruh District of Purworejo by using geographic information system

Located in Purworejo Regency, Pituruh is an area that prone to a landslide. Disaster mapping was a strategy that has been done so far by the government institutions and academia. According to its topography, Purworejo has been dominated by slope with more than 30 degree. The creation of landslide vulnerability map was carried out through several stages, namely, calculating rainfall at 6 stations located in Pituruh district, then producing average rainfall data to be used as a reference to create a rainfall map, then overlay process. Referring to the 4 parameters used, slope became an important parameter to determine the level of landslide vulnerability in Pituruh. The development of Geographic Information Systems can provide various types of spatial data related to the earth’s surface, and has the ability to perform accurate spatial analysis. Mitigation aims to reduce risks that have the potential to become disasters or reduce the effects of disasters. This study represents the level of vulnerability in Pituruh district by classifying the existing level. The results of this study have 5 classifications with different areas, namely highly vulnerable that covers 240.27 ha, moderately vulnerable for about 2237.81 ha, moderate with 3322.68 ha, vulnerable by 3040.14 ha, and not vulnerable area of 24.72 ha.

Flood Susceptibility Assessment of Chandpur Sadar Upazila using Analytical Hierarchy Process and Frequency Ratio Model

Flood susceptibility is a critical aspect of natural hazard assessment and disaster risk reduction. The objective of this study find out flood risk zone of chandpur sadar upazila using the Flood frequency ratio (FFR) and Analytical hierarchy process (AHP). The article explore the complex idea of flood susceptibility, focusing on analytical techniques used. The integration of twelve spatial data layers, such as Sediment Transport Index (STI), elevation, Topographic Wetness Index (TWI), slope, aspect, Land Use Land Cover (LULC), soil type, rainfall patterns, Normalize Difference Vegetation Index (NDVI), drainage density and distance from the river, is required for the assessment of flood vulnerability. A flood inventory map was buildup and using these methods, two vulnerability map was created, it was discovered that 60% & 48% of Chandpur's territory is categorized by very high to high risk zone. Flood has dangerous effect on livelihood. I was hoped that it will be a helpful study for researcher and people of this upazila will be benefited.

MANAGEMENT OF DISASTER THROUGH KNOWLEDGE MANAGEMENT SYSTEM: A CASE STUDY ON SAMBALPUR DISTRICT, ODISHA

Odisha is one of the hazard-prone state and suffers both natural and man-made hazards extensively threatening millions of lives and causing large-scale losses. Disaster management in India also saw a paradigm shift after 2002 from-the humanitarian relief and rehabilitation of victims to the holistic management of disasters viewpoint. The present research addressed this absence of information related to hazards and disasters affecting the district-level Sambalpur. This research aimed to find out some aid in the management of disasters at the district level by collecting and synthesizing all related information about disasters that occur in Sambalpur using an integrated approach. The research used publicly available tools as well as data from credible sources (e.g., government reports). To full-fill the aim, the research compiled information about disasters in the Sambalpur district and prepares a spatial database. Based on socio-economic factors-population density and working population, exposure of the blocks was calculated. Risk and exposure to it assisted in making a vulnerability map of the district at the block level. Based on vulnerability, blocks were prioritized for the policy-makers to ease their management in pre-during and post-disaster situations. The result of this paper would assist policy makers to take proper and quick decisions for the management of the blocks making their management efficient and effective and it could be replicated for other districts of Odisha and India.

DRR pioneer interview with Thea Hilhorst

PurposeThe transcript takes you on a journey of the book mapping vulnerability and the developments thereafter.Design/methodology/approachThe transcript and video was developed in the context of a United Nations Office for Disaster Risk Reduction (UNDRR) project on the History of DRR.FindingsThis interview highlights how DRR is central to conflict settings as well.Originality/valueThe interview provides reflections on DRR in conflict settings.

Delineation of Potential Groundwater Zones and Assessment of Their Vulnerability to Pollution from Cemeteries Using GIS and AHP Approaches Based on the DRASTIC Index and Specific DRASTIC

The risk of aquifer contamination is determined by the interaction between the pollutant load and the vulnerability of an aquifer. Owing to the decomposition of bodies and degradation of artefacts, cemeteries may have a negative impact on groundwater quality and suitability for use due to the leaching of organic compounds (e.g., biodegradable organics, pharmaceuticals, and formaldehyde), inorganic compounds (e.g., nitrate and heavy metals), pathogenic bacteria, and viruses. Factors such as burial and soil type, rainfall amount, and groundwater depth may increase aquifer vulnerability to pollutants generated in cemeteries. The potential for groundwater contamination was investigated in two cemeteries of the Soure region in Portugal (Samuel–UC9 and Vinha da Rainha–UC10), using the classic DRASTIC model, followed by some adjustments, depending on the particularities of the locations, resulting in a Final Classification considered as Specific DRASTIC. By combining Remote Sensing (RS), Geographic Information System (GIS), and Analytical Hierarchy Process (AHP), groundwater potential zones (GWPZs) were identified, and aquifer vulnerability was assessed, which included the elaboration of thematic maps using GIS operation tools. The maps allowed for the identification of areas with different susceptibilities to contamination: from “Low” to “Very high” for the DRASTIC index and from “Very Low” to “Very high” for the Specific DRASTIC index. Although the difference between the UC9 and UC10 cemeteries is negligible, UC10 is more vulnerable because of its proximity to the community and critically important mineral water resources (such as Bicanho Medical Spa). The Specific model seems better-suited for describing vulnerability to cemeteries. Although there is limited groundwater quality data for the area, the development of vulnerability maps can identify areas that can be sensitive spots for groundwater contamination and establish procedures for pollution prevention.

Enhancing groundwater vulnerability assessment for improved environmental management: addressing a critical environmental concern

Groundwater serves as a primary water source for various purposes. Therefore, aquifer pollution poses a critical threat to human health and the environment. Identifying the aquifer’s highly vulnerable areas to pollution is necessary to implement appropriate remedial measures, thus ensuring groundwater sustainability. This paper aims to enhance groundwater vulnerability assessment (GWVA) to manage aquifer quality effectively. The study focuses on the El Orjane Aquifer in the Moulouya basin, Morocco, which is facing significant degradation due to olive mill wastewater. Groundwater vulnerability maps (GVMs) were generated using the DRASTIC, Pesticide DRASTIC, SINTACS, and SI methods. To assess the effectiveness of the proposed improvements, 24 piezometers were installed to measure nitrate concentrations, a common indicator of groundwater contamination. This study aimed to enhance GWVA by incorporating new layers, such as land use, and adjusting parameter rates based on a comprehensive sensitivity analysis. The results demonstrate a significant increase in Pearson correlation values (PCV) between the produced GVMs and measured nitrate concentrations. For instance, the PCV for the DRASTIC method improved from 0.42 to 0.75 after adding the land use layer and adjusting parameter rates using the Wilcoxon method. These findings offer valuable insights for accurately assessing groundwater vulnerability in areas with similar hazards and hydrological conditions, particularly in semi-arid and arid regions. They contribute to improving groundwater and environmental management practices, ensuring the long-term sustainability of aquifers.

Assessment of the Vulnerability of Paddy Cultivation to Impacts of Climate Change in Anuradhapura District in North Central Province, Sri Lanka

Anuradhapura District in Sri Lanka heavily relies on paddy cultivation and plays a significant role in the country's paddy production. Given the grave threat posed by climate change to paddy cultivation in this region, it is crucial to assess its vulnerability. This study aims to fill the gap in sub-national vulnerability assessments by determining the degree of vulnerability and mapping it in the district. A combination of secondary and primary data was employed in this study. Secondary data encompassed the analysis of average annual and monthly rainfall and temperature variations in Anuradhapura District from 2010 to 2020, as well as the occurrence of droughts and floods in the same period. Additionally, the study examined the variations in average annual paddy yield in Anuradhapura District from 2010 to 2020. For primary data collection, Climate Change Vulnerability Indices (CCVI) were employed, which included indicators, exposure, sensitivity, and adaptive capacity. Under the exposure indicator, climate exposure, biophysical exposure, and biological exposure were considered. Sensitivity was assessed through social, financial, and farm sensitivity sub-indicators, while adaptive capacity was evaluated using socio-economic, agricultural, and institutional capacity sub-indicators. The field sampling focused on divisions with significant paddy lands that depend on minor irrigation and rainfed cultivation, such as Thirappane and Kahatagasdigiliya. Nuwaragam Palatha Central which had fewer paddy lands and a population engaged in non-paddy-related activities, was used as a control. Two Grama Niladhari (GN) divisions from each selected Divisional Secretariat (DS) division were randomly chosen for detailed sampling. In each GN division, 50 families were randomly selected to participate in semi- structured questionnaire surveys supplemented with focus group discussions and key informant surveys. The collected data were used to create a vulnerability map for Anuradhapura District through GIS analysis. The study results revealed that the annual rainfall showed a decrease from 2010 to 2020. Other parameters did not show significant variation. In terms of vulnerability, Kahatagasdigiliya DSD exhibited the highest vulnerability followed by Thirappane DSD. The lowest vulnerability was observed in Nuwara Gampalatha Centre DSD.
  
 Keywords: Climate change, Paddy cultivation, Adaptation measures, Vulnerability assessment, Anuradhapura
  

Assessing Groundwater Resources Vulnerability with the New DRASTIC-LP: A Case Study in Chiang Mai Province, Thailand

Groundwater vulnerability has gained widespread attention, particularly in Chiang Mai Province, one of Thailand’s fastest-growing cities, which is experiencing rapid development in both economic and social sectors. The expansion of urban communities and the industrial, tourism, and agriculture sectors has resulted in the overutilization of available resources, notably water resources. This overuse, coupled with the adoption of modern technology to boost productivity and meet market demands, has led to an increased reliance on groundwater to supplement surface water sources, providing benefits across all sectors. However, the economic and social growth plays a pivotal role in shaping the diversity of land use, encompassing residential, commercial, industrial, and agricultural activities. These activities, in turn, directly contribute to environmental pollution, particularly in terms of the risk of groundwater contamination in Chiang Mai Province. This study aims to predict the future vulnerabilities of groundwater resources under an ensemble of climate change scenarios and changes in land-use patterns. Chiang Mai Province in northern Thailand is one of the fastest-growing cities and therefore is experiencing rapid urbanization, as well as land-use pattern changes, which was important for the case study. The new DRASTIC model, namely the DRASTIC-LP model, combined with GIS-based techniques and overlay techniques, was used to generate the map of groundwater resource vulnerabilities. A point pollution source (P)-related land-use pattern (L) that represents contamination impacts was considered an additional new DRASTIC parameter. The study’s findings reveal the high reliability and maximum effectiveness of the new DRASTIC-LP model in assessing groundwater vulnerability and contamination-risk areas under a climate change scenario (by MIROC-ESM-CHEM model under RCP.8.5 scenario) and land-use pattern changes (by CA_Markov Chian Model) for both the current year (2020) and the next 50-year period (2021–2070). Furthermore, the new DRASTIC-LP model is employed to trace the movement of pollutants from high- to very high-risk areas based on the groundwater vulnerability and contamination-risk maps. The results highlight that waste disposal dumping sites pose a more critical distribution and movement of pollutants when compared to industrial sites. Additionally, unconsolidated aquifers and cracked consolidated rock aquifers show a potentially higher occurrence of pollutant distribution and movement when compared to consolidated aquifers. Consequently, the study’s outcomes are applied to formulate guidelines for the management and control of groundwater resource contamination. These guidelines serve as valuable tools for decision makers, aiding in pollution prevention and the effective management of contamination risks in groundwater resources.

Enhancing Landslide Vulnerability Mapping Through Automated Fuzzy Logic Algorithm-Based Methodology

Enhancing Landslide Vulnerability Mapping Through Automated Fuzzy Logic Algorithm-Based Methodology