Soil erodibility mapping of hilly watershed using analytical hierarchy process and geographical information system: A case of Chittagong hill tract, Bangladesh

Soil erosion across watersheds and river basins is an alarming environmental deterioration process that poses severe risks to hydrological systems, hydrogeochemical processes, agricultural productivity, and the global natural ecosystem. The use of the Analytical Hierarchy Process (AHP) and Geographical Information System (GIS) to assess soil erosivity for the watershed is widely known. This study applied the AHP and GIS to understand the degree of erosivity of the hilly Karnaphuli watershed in Chattogram, Bangladesh. The study used topographical maps, soil maps, and satellite imagery datasets. It implemented the GIS-based AHP and weighted overlay technique to derive eight factors (slope, elevation, Stream Power Index (SPI), Land Use and Land Cover (LULC), curvature, soil, Topographic Wetness Index (TWI), and rainfall. The geological stage of erosion potential was also identified using Digital Elevation Model (DEM) data through GIS-based hypsometric analysis. The findings demonstrated that the eastern and north-western parts are particularly vulnerable to erosion compared to other parts of the study area. The most dominant variables identified to influence the process of soil erosion are slope, LULC, elevation, and SPI. According to the AHP analysis, slope was the most influential factor (26%), followed by LULC (23.8%), elevation (20.3%), and SPI (13.9%) in the soil erosion process, and the geological stage of erosion potential was determined from the hypsometric curve (S-shaped) and hypsometric integral (0.49), which revealed that moderately eroded areas characterized the whole research region. The findings are significant as they provide valuable information for researchers and planners to address soil erosion and develop measures to control it effectively.

Coastal Flood risk assessment using ensemble multi-criteria decision-making with machine learning approaches

Coastal areas are at a higher risk of flooding, and novel changes in the climate are induced to raise the sea level. Flood acceleration and frequency have increased recently because of unplanned infrastructural conveniences and anthropogenic activities. Therefore, the assessment of flood susceptibility mapping is considered the most significant flood management model. In this paper, flood susceptibility identification is performed by applying the innovative Multi-criteria decision-making model (MCDM) called Analytical Hierarchy Process (AHP) by ensembles with Support vector machine (AHP-SVM) and Decision Tree (AHP-DT). This model combines two Representation concentration pathway (RCP) scenarios such as RCP 2.6 & RCP 8.5. The factors influencing the coastal flooding in Bandar Abbas, Iran, identified through Flood susceptibility mapping. Multi-criteria decision-making (MCDM) has been applied to evaluate the Coastal flood conditioning factors, and ensemble machine learning (ML) approaches are employed for Coastal risk factor (CRF) prediction and classification. The statistical variances are measured through Friedman and Wilcoxon signed rank tests and statistical metrics such as Accuracy, sensitivity, and specificity. Among the models, AHP-DT obtained an improved AUC value of ROC as 0.95. After applying the ML models, the northern and western park of Raidak Basin River recognises very low and low flood susceptibility because of their topographic characteristics. The eastern part of the middle section fell very high and high CFSM. Observed from this result analysis, the people living nearer to the coastline are distributed by the low to medium exposure in the region of the west and middle of the considered study area. The results of this study can help decision-makers take necessary risk reduction approaches in the high-risk flooding zones of the coastal system.

Application of geographical information system-based analytical hierarchy process modeling for flood susceptibility mapping of Krishna District in Andhra Pradesh

Flooding is one of the most catastrophic natural disasters in terms of provoking socio-economic losses. The current study is to foster a flood susceptibility map of Krishna District in Andhra Pradesh (AP) through integrating remote sensing data, geographical information system (GIS), and the analytical hierarchy process (AHP). Eleven factors, including elevation, slope, aspect, land use/land cover (LULC), drainage density, topographic wetness index, stream power index, lithology, soil, precipitation, and distance from the streams, are considered for identifying and evaluating the spatial distribution of critical flood-susceptible regions. Thematic maps of different factors were derived in GIS using remote sensing data obtained from Sentinel-2A (satellite sensor), shuttle radar topography mission digital elevation model (SRTM DEM v3), and other scientific data products. An analytical hierarchy process is a mathematical approach for decision support, primarily based on the weight and rank of different causative factors. AHP technique is implemented for flood hazard modeling and ascertaining the Flood Hazard Index (FHI) to produce a flood susceptibility map. Different thematic maps weighed with the AHP framework are combined using overlay analysis to produce the flood susceptibility map of the study region. The outcomes of the study demonstrate the potential of GIS and AHP in providing a premise to recognize the vulnerable areas that are susceptible to flood. According to the findings, the Flood Hazard Index is 42% and the study region is classified into very high, high, moderate, low, and very low susceptible, respectively. Following that, historical flood data was used to validate the accuracy of the generated flood susceptibility map. This shows that a maximum of 90% of the data points are within floodplain.

Selection of the final solid waste disposal site in the Bolgatanga municipality of Ghana using analytical hierarchy process (AHP) and multi-criteria evaluation (MCE)

The various components of Municipal Solid Waste (MSW) such as collection, sorting, transportation, and disposal have their peculiarities and challenges. However, final disposal sites, generally referred to as landfill sites, present a complex difficulty. The aggregation of the problems of other components has consequences on the microenvironment, public health, and groundwater. Final disposal of MSW, site selection, and management presents an enormous burden for most Metropolitan, Municipal, and District Assembly (s) in Ghana. The case of Bolgatanga Municipality is similar to many others in the Upper East region in particular and Ghana as a whole. The existing landfill site is improperly sited and poses a great danger to adjoining communities. In this work, we used the Analytical Hierarchy Process (AHP) in a G.I.S. suite and Multi-Criteria Evaluation to assess the current location and select a possible new site within the municipality. The criteria used are generally environmental and socio-economic parameters, including; distance from major roads, rivers, settlements, and the selection of an appropriate slope and soil type that suits the guidelines for the siting of a landfill. The outcome of this multi-criteria assessment is the selection of a new site far from the current disposal site indicating the inappropriate location of the current site. A combination of all weighted criteria through a model builder process produced a suitability index map for candidate landfill sites. The selected site at Sherigu is about 16 km by road from the proposed site, which is much bigger than the threshold of 500 sq. meters. The separation distance and size between the current and the proposed site are indications of how economically and environmentally inappropriate the Sherigu site is and the need for a better site that is better situated for socio-economic and environmental considerations.

Mapping and identification of potential groundwater development zones of an alluvial aquifer in parts of Ghaggar and Upper Yamuna basins in India

Using an integrated analytical hierarchy process, remote sensing and geographic information system techniques, the current study aims to map and identify the potential groundwater zones of Kurukshetra District of Haryana, which is located in the Ghaggar and Upper Yamuna Basins in India. This is done in the context of a significant change in the use of groundwater pattern, with respect to its continuously increasing demand due to the growing population, expansion of area under irrigation and related economic factors. The amount and quality of groundwater are anticipated to be impacted by anthropogenic activities as well as natural factors such as geomorphology, soil type, lithology and rainfall variance owing to a changing climatic scenario. The potential index of groundwater for this study was calculated by using nine important factors, including geomorphology, rainfall, soil type, depth to groundwater level, lithology, land use land cover, normalized difference vegetation index, cumulative sand thickness and elevation. The integration of multiple thematic layers was accomplished using the overlay weighted method to generate a potential groundwater zonation map and the accuracy of the resulting map was validated against a groundwater resource potential map. Statistical measures demonstrate an 82% agreement between the two maps, indicating a high level of concurrence. Accordingly, three groundwater zones of good, average and bad potential have been identified in the study area. In the current study, a process that combines weighted ranking with spatial data transformation and harmonization has been developed to obtain information for accurate decision-making. The results accruing from this research have significant ramifications for creating regional sustainable groundwater management plans.

The impact of various geological factors on the real estate valuation using AHP analysis: case studies from Turkey

Turkey's diverse geology causes natural disasters that kill and damage towns every year. Population growth in unstable areas without geological variables in value studies endangers people and real estate. This study examines how geological factors affect house values, which are often overlooked in applications. The analytical hierarchy process (AHP) was used to analyze conventional parameters, geological factors, and priorities for three provinces in Turkey with unique geological properties in surface water, groundwater, active faults, and karstic collapse. The AHP analysis was performed in the Ankara-Cankaya district (Ilkbahar quarter), Bolu-Gerede district, and Konya-Karapinar district, test locations with unique geological properties in terms of surface water, groundwater, active faults, and karstic collapse in various regions of Turkey. Statistical software analyzed the test location survey data. The results show that surface water, groundwater, active faults, and karstic collapse all affect real estate value. The findings suggest that house valuation requires multidisciplinary building site investigations with appropriate methods. This reduces the risk of making unreliable decisions and eliminates uncertainties, resulting in reliable results. The geological factors that determine a house's value are crucial to reducing disaster-related deaths and property damage.

Spatial accessibility modeling to healthcare facilities in the case of health shocks of Midnapore municipality, India

This research aims to identify the accessibility of the entire population, especially the slum population to existing healthcare facilities (HCF) as well as the slum neighborhoods having low geographic accessibility, and finally, to provide an analytical model for the people living in areas that are outside the coverage range of existing healthcare facilities (HCF) across the study area. Spatial data has been collected and used based on the road network, elevation, location of HCF, municipal boundary, slum point, and satellite images from various sources. Also, non-spatial data such as socioeconomic variables are collected from questionnaires survey within a particular period. The spatial analysis tool like as near, network analysis, and predictive analysis in the ArcGIS platform was used to examine geographic accessibility. The results of the spatial analysis show that the distribution of public healthcare facility centers in the study area has not been uniformly distributed. Across 84% of areas in the study area have sound spatial accessibility with traveling time coverage is about 12 min. However, 16% of areas have a traveling time of 12 to 30 min under low accessibility with existing slum neighborhoods. Therefore, the low spatial accessibility areas are demanding new healthcare facilities in the study area. The Analytical Hierarchy Process (AHP) is employed to find the most optimal and efficient locational suitability for building new healthcare facility centers. The finding of AHP analysis for site suitability of healthcare facilities revealed five major classes as most suitable (2%), suitable (5%), moderate (35%), poor (54%), and very poor (4%) in the study area. Moreover, the realistic framework of this study helps to measure geographic accessibility and suitability in any geographical area.

Mapping potential groundwater accumulation zones for Karachi city using GIS and AHP techniques

Karachi is the largest industrial metropolitan of Pakistan facing an acute water shortage which is leading to an overdraft of groundwater resources in the city. Groundwater is an important freshwater resource for the city as millions of people depend for sustenance. However, over-exploitation of groundwater has led to decreased groundwater levels within the city leading to environmental issues of depleting aquifers, deteriorating groundwater quality, land subsidence, and harm to groundwater-dependent ecosystems. The objective of the study was to assess the potential groundwater accumulation zones by integrating hydrogeological aspects of the city through nine thematic layers using the Geographic Information System (GIS) based multi-criteria decision analysis (MCDA) technique. The potential groundwater accumulation map reveals that 20% of the area has a low potential, 70% has moderate potential, and around 10% of the area in the city is composed of a high potential accumulation zone. The upstream regions of the city have the highest recharge potential because of sandy soil and barren land use, which promote high infiltration rates. The urbanized downstream areas have the lowest recharge potential due to impervious fabric. The findings reveal that the MCDA technique can be used with confidence in data-scarce regions for groundwater resource assessment and management. The recharge potential map can help better manage groundwater resources in the city by helping explore groundwater extraction opportunities and could hint at areas suitable for artificial recharge wells/ponds.

Analytical hierarchy process for sustainable agriculture: An overview

United nation sustainable development goal two (UNSDG-2) aims to achieve the eradication of hunger along with the assurance of food security for all by 2030. This cannot be achieved without combining all forms of sciences including mathematics and statistics with agriculture practice to make agriculture sustainable. Agriculture has been considered the backbone of the economic systems of developing and developed countries. However, while practicing the activities, various conflicting issues incorporate and make the situation challenging for the agriculture industry in the decision-making process. Multi-criteria decision-making (MCDM) techniques can provide the optimal solution and they have proved to be viable in various complex decision-making problems of the real world like agriculture-related decision-making problems. They can help to find a suitable alternative for a particular complex situation.  The analytical hierarchy process (AHP); a globally accepted method; has been a winning arc of the MCDM techniques. This article specifically reviews the application of AHP in various agriculture-related problems, the models used, the data sources used, and the overall precision attained using the different performance criteria of the past few years.

Suitability evaluation of potential arable land in the Mediterranean region

The existing cultivated land in the Mediterranean region faces great pressure from various sources. A suitability evaluation of potential arable land is urgent for helping adaptation measures to mitigate the impacts of climate change and human pressure on agricultural production in the Mediterranean region. We integrated 15 biophysical and socio-economic factors from GIS and remote sensing data to perform a suitability evaluation of potential arable land in the Mediterranean region using analytical hierarchy process and radial basis function artificial neural network methods. Moreover, we analyzed the gap between potential arable land and existing cultivated land and compared the evaluation results between the analytical hierarchy process and artificial neural network methods. The results show that the suitability index of potential arable land based on artificial neural network with 6 neurons has the best correlation with average yield and average harvested area. The land area with a suitability grade over medium level accounts for 62.95% of the potential arable land area, of which 45.71% is uncultivated land. Cyprus, France, Greece, Italy, Lebanon, Portugal, Spain and Turkey have great opportunities for agricultural development. Radial basis function artificial neural network outperforms analytical hierarchy process, has better verification results, and requires less input. This study provides an initial insight into the agricultural land suitability of 16 countries around the Mediterranean Sea and introduces a research idea for agricultural land suitability evaluation.

Multi-criteria decision making and Dempster-Shafer model-based delineation of groundwater prospect zones from a semi-arid environment

The present study illustrates the delineation of the groundwater potential zones in one of the most critical and drought-affected areas under Bundelkhand region of Uttar Pradesh (India). Hydrological evaluations were carried out using GIS tools and remote sensing data which ultimately yielded several thematic maps, such as lineament density, land use/land cover, drainage density, lithology, slope, geomorphology, topographic wetness index (TWI), DEM, and soil. Thematic layers were assigned relative weightages as per their groundwater potential prospects under multi-criteria decision making (MCDM) method through analytical hierarchy process (AHP). To recognize the groundwater potential zone, weighted overlay analysis was also performed. Additionally, for testing of the Dempster-Shafer model, 16 wells in the study area have been selected. Based on the probability of the groundwater occurrence, the belief factor was equated to delineate groundwater potential zones which illustrate five different potential zones. According to the AHP model, the northwest side of the study area is characterized with very high potential zones whereas the northeast and southeast regions constitute medium and low groundwater potential zones respectively. According to the DS model, very high groundwater potential zones constitute 17% and the remaining area falls under low potential. Overall accuracy of the DS model is higher than AHP model.

A site selection model proposal for sustainable urban regeneration: case study of Karşıyaka, İzmir, Turkey

Cities that have become the most crowded living spaces in all over the world are facing numerous problems and challenges such as environmental pollution, heavy traffic, urban dilapidation, lack of facility provision, and economic decline. Urban regeneration, which is an important agenda for both academia and politicians, aims to address these urban problems which are mostly caused by overpopulation. As the urban regeneration is a complex issue that requires to consider numerous components, regeneration initiatives cannot always achieve sustainable urban applications, which are causing new urban and social problems. Previous research have mainly focused on one aspect of urban renewal, in which a comprehensive perspective is lacking by just considering the physical aspects of the regeneration areas while lacking the social aspects and current global issues such as climate change and urban adaptation. A multi-criteria decision-making process for site selection and sustainable regeneration plan would contribute to better regeneration outcomes. Therefore, this study proposes a multi-criteria decision-making process which combines the analytical hierarchy process (AHP) and geographical ınformation system (GIS) at site selection phase of urban regeneration on a case study that includes all the physical and social components of the study area as well as focusing on sustaining ecological, economic, and social features.

A modified approach to quantify aquifer vulnerability to pollution towards sustainable groundwater management in Irrigated Indus Basin

The quality of groundwater in the study watershed has worsened because of industrial effluents and residential wastes from the urbanized cities; therefore, there is an important need to explore the aquifer vulnerability to pollution for sustainable groundwater management in the Irrigated Indus Basin (IIB). This study proposed a novel methodology to quantify groundwater vulnerability using two fully independent methodologies: the first by reintroducing an improved recharge factor (R) map and the second by incorporating three different weight and rating schemes into a traditional DRASTIC framework to improve the performance of the DRASTIC approach. In the current study, we composed a recharge map from Soil and Water Assessment Tool (SWAT) output (namely SWAT recharge map) with a drainage density map to retrieve an improved composite recharge map (SWAT-CRM). SWAT-CRM along with other thematic layers was combined using weightage overlay analysis to prepare the maps of groundwater vulnerability index (VI). The weight scale (w) and rating scale (r) were assigned based on a survey of available literature, and we then amended them using the analytical hierarchy process (AHP) and a probability frequency ratio (PFR) technique. Results depicted that the region under high groundwater vulnerability was found to be 5-22% using traditional recharge maps, while those are 9-23% using improved SWAT-CRM. The area under the curve (AUC) revealed that groundwater vulnerability zones predicted with SWAT-CRM outperformed the DRASTIC model applied with the traditional recharge map. Groundwater electrical conductivity (EC) was>2500 mS/cm in the high groundwater vulnerability zones, while it was <1000 mS/cm in the low groundwater vulnerability zones. The outcomes of this study can be used to improve the sustainability of the groundwater resources in IIB through proper land-use management practices.

Analytical hierarchy process tool in Google Earth Engine platform: a case study of a tropical landfill site suitability

Kolkata being a metropolitan city in India has its main municipal solid waste dumpsite situated at Dhapa just adjacent to the East Kolkata Wetlands (Ramsar site). The current prevalent situation at Dhapa is open dumping leading to various contaminations and hazards putting forth the need to look for alternative sites where the landfiilling operation can be shifted to using scientific methods. A user interface (UI)-based analytical hierarchy process (AHP) tool has been developed within the Google Earth Engine (GEE) cloud platform to find out the alternative dumping sites using geospatial layers. AHP function is not available as a native algorithm or developed by any researcher in GEE. The tool has three major functionalities, of which the first one handles the UI elements. The AHP procedure is within another function, and the last function integrates the AHP coefficients to the layers generating the final suitability layer. Users can also upload comparison matrix as GEE asset in the form of CSV file which gets automatically integrated into the AHP to calculate the coefficients and consistency ratio to generate the spatial suitability layers. This approach showcases a generalized AHP function within the GEE environment, which has been done for the first time. The tool is designed in the cloud platform which is dynamic, robust and suitable for use in various AHP-based suitability analysis in environmental monitoring and assessment.

Assessing groundwater status and human perception in drought-prone areas: a case of Bankura-I and Bankura-II blocks, West Bengal (India)

Ground water is a precious natural resource in every aspect of human life from natural to artificial environment. Ground water is an indicator of regional development by improving the economic domain through intensive agricultural practices, and aesthetic value through sufficient ground water supply as drinking water, fertile soil, and healthy vegetation. However, ground water availability and associated human perceptions were the main themes of the present study. In this study, both primary and secondary data were incorporated to understand the human adaptation behaviour in drought-prone areas of the fringe of Chhotanagpur plateau region (Bankura-I and II blocks) to ground water storage. GWPZ mapping is a very important exposure to knowing the ground reality. So, the MCDM-AHP method has been developed based on the eight dominant conditioning factors viz. geomorphology, lithology, lineament density, soil, drainage density, LULC, average slope, and slope aspect using GIS analytics with field expertise. The output result was validated with comparing 105 inventory stations where 0.850 AUC value was good for accepting the GWPZ model. As a result, a major portion of the study area is dominated by poor to moderate possibilities of ground water level (ground water level drops 1-2 m during the pre-monsoon) due to Proterozoic granite gneiss formation over the study area. With comparing demographic status, it was not favourable for a healthy lifestyle. Agriculture dominated rural environment of Bankura-I and II blocks is far away from the modern digital environment that is why ground water has played a very crucial role in the field of development. Moreover, to build up a good level of ground water recharge zone through rainfall harvesting, and sustainable land use planning will be the best management practices. So, availability of ground water should be a positive sign of development in the field of the economic sector and sustainable human society.

Assessing ecological health of mangrove ecosystems along South China Coast by the pressure-state-response (PSR) model

The pressure-state-response (PSR) model was applied to establish a mangrove ecosystem health evaluation system combined with analytical hierarchy process (AHP) in this paper. The mangrove wetlands are divided into five ecological levels: excellent health, good health, health, sub-health and morbidity, which is based on the comprehensive health index (CHI) value. Twelve representative sites were selected for sampling to assess the ecological health condition of mangroves. As a result, the ecological health level of Gaoqiao mangrove area is excellent health; the ecological health level of Taiping mangrove area is good health; the ecological health level of Huguang and Qi'ao mangrove area is health; the ecological health level of Techeng and He'an mangrove area is sub-health; the ecological health level of Huidong mangrove area is morbidity. These results will give some advises for ecological protection and biological resource sustainable development of mangrove ecosystem in China.

Identification of potential strategic sites for city planning based on water quality through GIS-AHP-integrated model

Freshwater is one of the most important resources for the ecosystem's sustenance and any nation's development. However, clean water bodies are exploited to cater to urban societies' growing demands and economic expansion. This has led to the scarcity of clean water on the planet since the last decade, which is a crucial environmental concern in the present time. Therefore, proper water quality assessment and better management plan integrated with city planning have become an essential need of the hour to combat the clean water stress problem. This study aims to frame a model to identify the potential sites suitable for water use and document an effective development plan for a highly industrialized, populated, planned, and critically polluted city. The potential strategic sites were identified based on the impact of water quality on factors such as human health and economy, which are directly linked to drinking, irrigation, fisheries, as well as industrial production. The relative importance of each criterion (weightage) was estimated using the analytical hierarchy process (AHP). The physico-chemical parameters of groundwater and surface water of the strategic locations were analyzed to calculate multi-purpose water quality index (WQI) and Ryznar suitability index (RSI). These indices were interpolated through a geospatial tool and reclassified using a scoring system to a uniform scale. These thematic maps were weighted overlaid through the GIS model builder tool in GIS interface to develop suitability maps through developed potential site index (PSI) of the ground as well as surface water. The final suitability maps were used to identify the potential strategic sites for various uses such as drinking, fishery, irrigation, and industries, which can be considered by the planners for improvising the city planning. Various management practices were also drawn through these maps, which will safeguard human health as well as the environment.

Now is the time to press the reset button: Helping India's companies to become more resilient and effective in overcoming the impacts of COVID-19, climate changes and other crises

COVID-19 is the pandemic caused by one of the coronaviruses. This virus was not known before the outbreak in Wuhan, China, in December 2019. By January of 2020 it was declared to be a global human health crisis. The deaths and illnesses caused by the virus caused extensive fear and anxiety among people in all societies. The pandemic slowed economic activities nearly to a halt. The challenges of how companies should respond to the disruptions in their supply chains and how they can build more resilient systems, must be systematically addressed. The authors of this paper highlighted essential factors which can help companies to overcome this crisis and other types of crises, by learning from the approaches taken in India, which has a unique and diverse economic system. The Analytical Hierarchy Process (AHP) technique was used to identify the essential factors which can help companies to improve their resilience so they can recover during and after the COVID-19 pandemic era and potentially in other similar complex crises. The results of the AHP evaluation were prioritized by performing a sensitivity analysis to prioritise the essential factors. The "Role of governance" was found to be the most important factor that can be used to help in rebuilding industries and societies and in helping them to become more resilient to future severe shocks. The results of this research were used to develop recommendations for company managers, practitioners and policy-makers. The authors hope that this advice will help India to become a stronger nation with more resilient companies, which are better prepared to anticipate and to respond to future crises. We hope people in other nations will also benefit from the finding presented in this paper.

A multi-criteria decision support framework for municipal solid waste landfill siting: a case study of New South Wales (Australia)

Sanitary waste disposal and site selection for establishing landfills are challenging problems for environmental planners. This paper aims to take environmental, socio-economic, geological, geomorphological, hydrological and ecological factors into consideration to provide a decision support framework for landfill siting. Analytical hierarchy process (AHP) and Decision Making Trial and Evaluation Laboratory (DEMATEL) are coupled to develop an efficient multi-criteria decision-making method to be utilized in a Geographic Information System (GIS) environment for evaluating the suitability for landfill siting. As the first attempt to employ DEMATEL effectively in a landfill site selection problem, the proposed method is tested with landfill siting scenarios in New South Wales (NSW), Australia. Regional analysis is also performed to identify the potentially most suitable statistical divisions for landfill siting in NSW. The top two ranked zones covering 0.7% and 22% of the study area, respectively, are considered as the optimal areas for establishing landfills, while the bottom two ranked zones are not recommended for further consideration. Further detailed analysis is also conducted on the existing landfills, which shows that 1.0% and 37.0% of them are ranks 1 and 2, respectively. The scenario-based analysis implies that, among the contributing factors; geological and economic factors are highly important.

A robust approach for comparing conventional and sustainable flood mitigation measures in urban basins

An integrated methodological framework for assessing different flood mitigation measures in urban catchments is presented. The framework comprises hydrologic, hydraulic and economic indices aiming at quantifying the effect of different alternatives regarding flood hazard mitigation. The alternatives evaluated include both conventional drainage solutions and low impact development measures. The conventional drainage solutions were: (i) off-line detention tanks; and (ii) sewer enlargement. The low impact development measures included: (i) green roofs (GR); and (ii) permeable surfaces (PS). Each solution was modeled using SWMM5 with respect to flood reduction effectiveness, and the results were compared to those of the existing condition (i.e., no flood mitigation measures). All the examined solutions were also compared based on their construction and operation and maintenance costs for a typical lifespan (i.e., 30 years). The results of the simulation revealed that both low impact development measures and conventional drainage solutions were highly effective even for storm events with low probability of occurrence. However, sewer enlargement was found to be the best alternative from an economic perspective. Nevertheless, peak at the sewer exit increased and time to peak remained unchanged; as a result, local flooding problems are resolved but downstream flooding problems may be introduced. If other criteria are considered, i.e., traffic obstruction, noise, construction easiness, co-benefits and downstream impacts, low impact development measures become more attractive compared to conventional drainage solutions.

Selecting a suitable model for collecting, transferring, and recycling drilling wastes produced in the operational areas of the Iranian offshore oil company (IOOC) using analytical hierarchy process (AHP)

Waste from drilling operations of oil and gas wells in the event of poor management, in addition to imposing costs, can lead to environmental problems. This research was aimed at providing a suitable model for collecting, transferring, and recycling the drilling wastes produced in the operational areas of the Iranian offshore oil company. Data analysis was performed using the Expert Choice and template selection using the analytical hierarchy process method. Based on the results of this study, the method of collecting waste in a cutting skip (weight = 0.576) was identified as a suitable option in the waste-collecting sector. In the waste transfer sector, the waste shipments from the west of the Persian Gulf to Kharg Island (weight 0.623) and the transfer of waste from the Eastern areas to Lavan island (weight 0.625) were selected as suitable options. Among the waste recycling options, the thermal method with of 0.433 was chosen as a top priority.

Global mapping of eco-environmental vulnerability from human and nature disturbances

Global environments are threatened by intensively natural variation and continuously increased human-made disturbances. Assessment of the global eco-environment vulnerability (global EV or GEV) caused by both natural and human-induced disturbances plays a key role in providing valuable information about ecological and environmental background for designing suitable policy measures to improve and restore environment. We present the first global-scale map of quantified eco-environmental vulnerability by integrating remote sensing, GIS modelling, and global census datasets, employing 16 influential factors across five domains: socioeconomics, land resources, natural hazards, hydrometeorology, and topography. The GEV is classified into six levels, namely very low vulnerability, low vulnerability, medium vulnerability, medium high vulnerability, high vulnerability, and very high vulnerability. At global scale, a small fraction of the globe (10.1%) is strongly (high and very high vulnerability) affected by influential factors. Among continents, the largest fraction of very high vulnerability level is attributed to Asia (74.6%) followed by Africa (19.6%). National-scale analysis shows that China and India are the most vulnerable in Asia and in the world. Our study provides accumulative impacts of manmade and natural disturbances, which are vital for decision makers to set improvement targets on specific areas over local, regional, and global scales, and design and adopt new practices to lessen natural and manmade disturbances on environment, while keeping track of evolution of the other environmental aspects.

Environmental impact assessment studies for mining area in Goa, India, using the new approach

The mining industry is a fundamental source for building infrastructures and an enabler for a country's growth. Over the last decade, the act of mining has been among the top in the list of human activities which has the most disturbing and catastrophic impacts on environment, therein extensively affecting the ecological, economic, and social elements in the vicinity. There is an exigency for a pragmatic balance to exist between the global demand satisfaction of metal and environmental sustenance. In this paper, a comprehensive case study on Environmental Impact Assessment (EIA) of a mining site has been presented using the new approach. This new approach is an improved version of the traditional matrix method, incorporating a modified version of Rapid Impact Assessment Matrix (RIAM) integrated with analytical hierarchy process (AHP), thereby knocking out the limitations in the existing EIA techniques. The data used in this study is an outcome of a broad survey conducted among the people associated in both direct and indirect ways to the project actions related to the mining industry and, hence, minimizing issues such as assessors' reproducibility, subjectivity, and non-inclusivity of all stakeholders' opinion, which can contribute to misleading outcomes. This new approach delivers more precise and practical results for the assessment of environmental impact data.

Transshipment hub selection from a shipper's and freight forwarder's perspective

Transshipment hub selection becomes increasingly important to the global logistics community. From the perspectives of shippers and freight forwarders, a selection must align with cost control strategy and sustain service reliability across cooperative service providers. This paper assesses the selection with the options of both sea and air transports, and from the influence of country of origin of the company. Critical factors of transshipment hub selection, both qualitative and quantitative, are identified through focus group discussions. Relative importance of these factors is determined based on collective views of logistics stakeholders. The competitiveness of transshipment hubs is then assessed using an AHP approach. Our analysis is based on the historical implementation of direct transportation link policy between Mainland China and Taiwan. With this empirical work, the finding suggests that even the spawn of other nearby ports with shorter transport distance and closer proximity to cargo sources, there remain overriding factors such as customs regulations & government policies and connectivity that a transshipment hub is preferred.

Zoonotic cutaneous leishmaniasis in northeastern Iran: a GIS-based spatio-temporal multi-criteria decision-making approach

Zoonotic cutaneous leishmaniasis (ZCL) constitutes a serious public health problem in many parts of the world including Iran. This study was carried out to assess the risk of the disease in an endemic province by developing spatial environmentally based models in yearly intervals. To fill the gap of underestimated true burden of ZCL and short study period, analytical hierarchy process (AHP) and fuzzy AHP decision-making methods were used to determine the ZCL risk zones in a Geographic Information System platform. Generated risk maps showed that high-risk areas were predominantly located at the northern and northeastern parts in each of the three study years. Comparison of the generated risk maps with geocoded ZCL cases at the village level demonstrated that in both methods more than 90%, 70% and 80% of the cases occurred in high and very high risk areas for the years 2010, 2011, and 2012, respectively. Moreover, comparison of the risk categories with spatially averaged normalized difference vegetation index (NDVI) images and a digital elevation model of the study region indicated persistent strong negative relationships between these environmental variables and ZCL risk degrees. These findings identified more susceptible areas of ZCL and will help the monitoring of this zoonosis to be more targeted.