Risk Map Research Articles

Risk management in the heating industry

The heating industry plays a very important role in countries with a cold and temperate climate. Together with the power industry, it determines the energy security of these countries. That is why it is so important to study the risks that threaten the stability of heating companies. The article identifies risks divided into three groups – general economic, industry and specific risks. A risk map was drawn up and a qualitative analysis of their impact for the aforementioned companies was carried out. Such a map is a helpful tool in making decisions related to risk management and ensuring the stability of the functioning of business entities.ul information for both government and local authorities in the search for effective ways to drive the sector’s development.

A Drone-Driven Delivery Network Design for an On-Demand O2O Platform Considering Hazard Risks and Customer Heterogeneity

Nowadays, the online-to-offline (O2O) retailers provide on-demand delivery service for online orders by their own fleets and riders. An intelligent delivery network lays an important foundation to support cost-effective delivery service in the long run. Drones have great potential to revolutionize the instant delivery industry regarding cost and timeliness, while the hazard risks to humans and the environment should be seriously considered through sophisticated network design. In this paper, we propose a framework for a drone-driven intelligent delivery network design problem with the consideration of the multi-dimensional risk map, which needs to determine store location, drone fleet size and allocation, customer assignment, customer delivery mode selection, and delivery routing. A bi-objective non-linear programming model is formulated to maximize profit and minimize integrated risks as well. To tackle large instances, a modified NSGA-III algorithm is developed, which is incorporated with problem-specific search operators and Pareto local search to obtain Pareto solutions efficiently. Real-world data-based numerical experiments are conducted to verify the performance of the modified NSGA-III algorithm compared to the modified NSGA-II. A case study based on the geographical information in Shanghai is analyzed to validate the effectiveness of the proposed model. Moreover, sensitivity analysis is presented to evaluate the effects of multiple parameters on the drone delivery service network design. Some managerial insights are obtained for the O2O retailer who offers on-demand delivery service through online platform.

Soil CO2 flux maps as tools to reduce the risk on soil diffuse degassing areas

Carbon dioxide released permanently from soils in diffuse degassing areas may constitute a permanent hazard for the population. Several villages in the Azores archipelago (Portugal) are placed in areas with anomalous soil CO2 degassing and lethal indoor CO2 concentration (>10 vol%) has been already recorded in some buildings. The 2021-2022 dislodgements of population at Vulcano (Italy) and La Palma (Spain) volcanic islands due to high soil CO2 degassing highlight the importance of defining criteria to produce human CO2 exposure risk maps, which are useful to mitigate the risk and should constitute valuable tools for land-use planners. Risk is assessed in the current study by combining susceptibility, exposure, and vulnerability maps. The defined criteria were applied to two villages in Furnas Volcano (São Miguel Island, Azores), showing that 58% and 98% of the buildings, respectively, at Furnas and Ribeira Quente villages are at high risk of CO2 exposure.

Establishment and Validation of Lactate Metabolism-Related Genes as a Prognostic Model for Gastric Cancer.

Gastric Cancer (GC) has become one of the most important causes of cancer-related deaths worldwide due to its intractability. Studying the mechanisms of gastric carcinogenesis, recurrence, and metastasis, and searching for new therapeutic targets have become the main directions of today's gastric cancer research. Lactate is considered a metabolic by-product of tumor aerobic glycolysis, which can regulate tumor development through various mechanisms, including cell cycle regulation, immunosuppression, and energy metabolism. However, the effects of genes related to lactate metabolism on the prognosis and tumor microenvironmental characteristics of GC patients are unknown. <P> </P> Method: In this study, we have collected gene expression data of gastric cancer from The Cancer Genome Atlas (TCGA) and identified differentially expressed genes in gastric cancer using the "Limma" software package. <P> </P> Result: 76 differentially expressed lactate metabolism-related genes were screened, and then the Least Absolute Shrinkage and Selection Operator (LASSO) and Cox regression analysis were employed that identified 8 genes, constructed Lactate Metabolism-related gene signals (LMRs), and verified the reliability of the prognostic risk mapping by using TCGA training set and TCGA internal test set. Finally, the functional enrichment analysis was employed to identify the molecular mechanism. <P> </P> Conclusion: Eight lactate metabolism-related genes were constructed into a new predictive signal that better predicted the overall survival of gastric cancer patients and can guide clinical decisions for more precise and personalized treatment.

Geomorphic risk maps for river migration using probabilistic modeling – a framework

Abstract. Lateral migration of meandering rivers poses erosional risks to human settlements, roads, and infrastructure in alluvial floodplains. While there is a large body of scientific literature on the dominant mechanisms driving river migration, it is still not possible to accurately predict river meander evolution over multiple years. This is in part because we do not fully understand the relative contribution of each mechanism and because deterministic mathematical models are not equipped to account for stochasticity in the system. Besides, uncertainty due to model structure deficits and unknown parameter values remains. For a more reliable assessment of risks, we therefore need probabilistic forecasts. Here, we present a workflow to generate geomorphic risk maps for river migration using probabilistic modeling. We start with a simple geometric model for river migration, where nominal migration rates increase with local and upstream curvature. We then account for model structure deficits using smooth random functions. Probabilistic forecasts for river channel position over time are generated by Monte Carlo runs using a distribution of model parameter values inferred from satellite data. We provide a recipe for parameter inference within the Bayesian framework. We demonstrate that such risk maps are relatively more informative in avoiding false negatives, which can be both detrimental and costly, in the context of assessing erosional hazards due to river migration. Our results show that with longer prediction time horizons, the spatial uncertainty of erosional hazard within the entire channel belt increases – with more geographical area falling within 25 % &lt; probability &lt; 75 %. However, forecasts also become more confident about erosion for regions immediately in the vicinity of the river, especially on its cut-bank side. Probabilistic modeling thus allows us to quantify our degree of confidence – which is spatially and temporally variable – in river migration forecasts. We also note that to increase the reliability of these risk maps, we need to describe the first-order dynamics in our model to a reasonable degree of accuracy, and simple geometric models do not always possess such accuracy.

Influence of wildfires on the conflict (2006–2022) in eastern Ukraine using remote sensing techniques (MODIS and Sentinel-2 images)

Humans primarily alter fire regimes in three ways: changing the distribution and density of ignitions, shifting the seasonality of burning, or altering available fuels. Remote sensing techniques are a highly feasible and effective tool for monitoring wildfires, delineating burn perimeters, describing patterns of fire occurrence, characterizing the degree of intensity, or fire risk mapping. In this study MODIS and Sentinel-2 satellite images were used to analyze the burned areas in the Luhansk and Donetsk Regions of Ukraine (2006–2022), and specifically how the political and military hostilities in 2014 impacted fire activity. The burned areas detected by the MODIS sensor were selected using a size (32 ha) and temporal (May–October) filter. The Relativized Burn Ratio (RBR) index was used to identify burned areas, while the Normalized Difference Water Index (NDWI) was employed to discriminate the water bodies in Sentinel-2 images. We analyzed the burned area data over the 17-year period, eight of them during the years before the conflict and the other nine after the conflict. The results show that burned area has increased from the pre-conflict period (2008–2013) by 689,898 ha to the post-conflict period (2014–2022) around the contact line. In addition, the frequency of fires has increased in the post-war period, especially towards the south of Donetsk. Finally, Sentinel-2 imagery was used to map Large Wildfires (LAWF), which means fires with a burned area >500 ha. Our study concluded that MODIS MCD64A1 underestimates the burned area with a recorded difference of up to 40% of the area in one of the analyzed fires. In addition, an analysis of the burned areas classified according to the main land use has been performed for both sensors. The results obtained show a regression for the total area of R2 = 0,97 and both sensors show high correlation between them for each land use analyzed. Grasslands and agricultural land covers were most affected by LAWFs during the conflict period (2014–2022), noting that fires near urban entities were also more frequent in the war period.

Development of a heat load index and risk map for grazing sheep

ABSTRACT A total of 5500 measurements of the respiration rate of 123 sheep with and without access to shade were obtained on 40 days in the summers (January–April) of 2022(Year 1) and 2023(Year 2). Models to predict respiration rate (breaths per minute (BPM)) based on temperature, humidity, wind speed, and solar radiation were calibrated to the Year 1 unshaded dataset (R2 =0.35, RMSE=39 BPM) and validated with the Year 2 unshaded dataset (R2=0.58, RMSE=40 BPM). Respiration rate increased 6 BPM for each 1°C increase in temperature. The shade treatment decreased respiration rate by 24 BPM and the shaded model for respiration rate had a validation RMSE of 47 BPM. The between sheep variability in respiration rate was described by a standard deviation of 18.9 BPM. The probability of open mouth and tongue out behaviours both increased linearly from 200 BPM. We constructed a daily Heat Load Index based on the cumulative respiration rate greater than 200 BPM. Climate data and sheep density information were used to construct a heat stress risk map for New Zealand from October 2018 to March 2022. Heat stress risk was concentrated in January–February and was primarily located on the east coast of the North Island.

Incidence of the El Niño–Southern Oscillation Cycle on the Existing Fundamental Niche and Establishment Risk of Some Anastrepha Species (Diptera-Tephritidae) of Horticultural Importance in the Neotropics and Panama

To compare the environmental space of four Anastrepha species in different ENSO episodes (El Niño, El Neutro and La Niña), we built ecological niche models with NicheA software. We analysed the fundamental niche and the combined establishment risk maps of these species developed with the ArcGisPro combine geoprocess. A comparison of the ellipsoids that represent the fundamental niche existing for the species showed changes in the El Niño, El Neutro and La Niña episodes. For A. grandis in the El Niño vs. El Neutro episodes, there was a Jaccard index of 0.3841, while the comparison between the La Niña vs. El Neutro episodes presented a Jaccard index of 0.6192. A. serpentina in the El Niño vs. El Neutro and La Niña vs. El Neutro episodes presented Jaccard indices of 0.3281 and 0.6328, respectively. For A. obliqua, the comparison between the El Niño vs. El Neutro and La Niña vs. El Neutro episodes presented Jaccard indices of 0.3518 and 0.7472, respectively. For A. striata, comparisons between the episodes of El Niño vs. El Neutro and La Niña vs. El Neutro presented Jaccard indices of 0.3325 and 0.6022, respectively. When studying the comparison between Anastrepha species and the different ENSO climatic episodes, we found that in the El Niño episode, the comparisons with the best environmental similarity were A. obliqua vs. A. striata and A. obliqua vs. A. serpentina, with higher Jaccard indices (0.6064 and 0.6316, respectively). In the El Neutro episode, the comparisons with the best environmental similarity were A. serpentina vs. A. striata and A. obliqua vs. A. striata, which presented higher Jaccard indices (0.4616 and 0.6411, respectively). In the La Niña episode, the comparisons that presented the best environmental similarity were A. obliqua vs. A. serpentina and A. obliqua vs. A. striata, with higher Jaccard indices (0.5982 and 0.6228, respectively). Likewise, our results present the risk maps for the establishment of these species throughout the Neotropics, allowing us to predict the level of risk in order to develop integrated pest management plans.

FOREST FIRES RISK IN A SEMI ARID REGION: A CASE STUDY IN WESTERN ALGERIA

Purpose: The objective of this study was to measure the fire risk of forests and to compare areas with high sensitivity to forest fires.   Theoretical Framework: Many authors have demonstrated the fragility of Algerian forests in the face of fires (Belhadj, 2003; Souidi et al., 2010 and 2017). In this research paper, the researchers focused on identifying the factors responsible for the risk of forest fires in Algeria using a state-of-the-art tool, the Geographic Information System (GIS). The researchers explained a scientific process for exploring new indicators using GIS, and showed how to develop a forest fire risk map.   Design/Methodology/Approach: The elaboration of the fire risk map requires the application of a model set up, and tested on forest areas in the Mediterranean region. The applied model involves the three main factors of forest fire risk assessment: topomorphology, fuel, and human occupation.   Findings: According to the results obtained, our study area is dominated by a very high risk index. In addition, more than half of the surface area of our study zone is located in topomorphological conditions that are highly conducive to the multiplication of fires and can increase the risk of forest fires breaking out. This study will help us to better control the risk of fires and to manage fire-fighting operations in the field.   Research, Practical &amp; Social Implications: Mapping the risk of forest fires using GIS will help land managers and planners to identify sensitive areas for better preservation and intervention in the event of fire.   Originality/Value: The results show that the number of forest fires is increasing over time and that managing them is becoming increasingly difficult. The use of a GIS for all stakeholder and managers will make it possible to combat forest fires.

Coastal Flood Induced Salinity Intrusion Risk Assessment Using a Spatial Multi-criteria Approach in the South-Western Bangladesh

AbstractBangladesh is extremely vulnerable to sea-level rise and other climate-induced extreme events, such as flooding, storm surge, and salinity intrusion. The south-western coastal region of Bangladesh is particularly vulnerable to salinity intrusion caused by cyclone induced storm surges and coastal floods. Salinity intrusion endanger land productivity by increasing both soil and surface water salinity. Detailed risk assessment using spatial mapping approach can contribute to mitigating the effects of salinity intrusion on natural capital and the environment. In this study, we established and evaluated a spatial multi-criteria approach for mapping the risk levels of areas to salinity intrusion impacts using field data and geospatial techniques at the local scale. We evaluated the viability of the proposed approach using Khulna District, a major coastal city and saline prone area in the south-western Bangladesh. We considered three risk components (i.e. vulnerability, exposure and hazard) with 16 relevant criteria for the study. For each criterion, an Analytical Hierarchy Process (AHP) was used to build and weight spatial raster map layers. Individual maps for each risk component were generated using a weighted sum technique, and lastly, a risk map was created by combining those. Our generated maps correctly identified relevant spatial dimensions as well as risk levels (i.e. very-high to very-low). The outcomes of our study suggest that the southern (east and west) parts of the study area are mostly susceptible to salinity intrusion due to higher storm surge impacts, lower elevation, and land use patterns than other parts. We validate our findings using a qualitative and quantitative approach. We believe that this novel approach would be useful to create risk maps that policymakers and relevant stakeholders could potentially use to evaluate risks posed by flood induced salinity intrusion in coastal regions of Bangladesh and elsewhere with similar geo-climatic context.

Analysis of the current risk of Leishmania infantum transmission for domestic dogs in Spain and Portugal and its future projection in climate change scenarios

Canine leishmaniosis, caused by the protozoan parasite Leishmania infantum, is a cosmopolitan vector-borne zoonosis, transmitted principally by Phlebotomus perniciosus in Spain and Portugal, where it is considered an endemic disease. Ecoinformatics tools such as ecological niche models (ENM) have been successfully tested to model the distribution of the risk of infection of different parasitosis as they take into account environmental variables vital for their survival. The risk map proposed in this study combines the potential distribution of Ph. perniciosus in the Iberian Peninsula and the calculation of the infection rate of the parasite in the vector to model the risk of contracting the disease in a more realistic way. In fact, this weighting strategy improves the predictive power of the resulting model (R2 = 0.42, p = &amp;lt; 0.01) compared to the Ph. perniciosus ENM model alone (R2 = 0.13, p &amp;gt; 0.05). The places with the highest risk of transmission are the southwest and central peninsular area, as well as the Mediterranean coast, the Balearic Islands and the Ebro basin, places where the ideal habitat of Ph. perniciosus and the infection rate is also high. In the case of future projections under climate change scenarios, an increase in the risk of infection by L. infantum can be observed in most of the territory (4.5% in 2040, 71.6% in 2060 and 63% in 2080), mainly in the northern part of the peninsula. The use of ENMs and their weighting with the infection rate in Ph. perniciosus is a useful tool in predicting the risk of infection for L. infantum in dogs for a given area. In this way, a more complete model can be obtained to facilitate prevention and control.

EVALUATION OF DISASTER PERCEPTION LEVELS OF UNIVERSI-TY STUDENTS: A SAMPLE APPLICATION STUDY

Disasters are important events that are difficult to predict and occur in various ways, often with high destructive power. Earthquakes, floods, droughts, major industrial accidents, famine, technological accidents, epidemics, etc. are only a few of the major types of disas-ters that mankind has been exposed to from past to present. In recent years, natural and unnatural disaster events have been observed both in Turkey (Düzce-earthquake, 1999; Giresun-Dereli-flood-flood, 2020; Kahramanmaraş-Pazarcık-earthquake, 2023) and in many other parts of the world (Sumatra-tsunami, 2004; Ecuador-earthquake, 2016; USA-hurricane-storm, 2023). The impact of disasters is often not limited to one region but can spread over a wide area. As a matter of fact, the impact of this destruction can be reduced at some point thanks to various measures that can be taken before the disaster. For exam-ple, identification of regional risks, early warning systems, crisis management, emergency action plans, etc. can be considered within the scope of these measures. Another important issue is to increase the level of disaster awareness of the society. Especially in regions where disaster risk maps have been prepared, such awareness raising activities can be carried out to make the reaction of the society against disasters more controlled and conscious. The aforementioned issues constitute the main objective of this study. This study was conducted to evaluate the disaster awareness levels of Gümüşhane Univer-sity central campus students. The data obtained in the study were analyzed using SPPS 25 statistical program. In the study, a 5-point Likert scale was used to measure disaster risk perception. In the study, frequency analysis test, Kruskal Wallis test and Mann Whitney U test were performed. As a result of the analysis, it was analyzed at 5% level of significance (p

Flood risk evaluation of the coastal city by the EWM-TOPSIS and machine learning hybrid method

The frequent occurrence of floods and waterlogging has significantly impacted coastal cities. Effective mapping of flood risk can enhance the precision of disaster risk reduction strategies. However, there is room for improvement in fields such as flood inundation data, evaluation objectivity, and classification refinement. This study, using Xiamen as a case study, advanced flood inundation data accuracy by generating a frequency-based flood inundation map from multi-year remote sensing imagery. This study integrated the EWM-TOPSIS model with a neural network model to evaluate the flood risk. The EWM-TOPSIS model was employed to assess the flood vulnerability and flood exposure, while the multi-class neural network model to simulate the flood hazard. This combined approach reduced subjectivity in the flood risk assessment of Xiamen and achieved a finer level of risk classification compared to traditional binary neural networks. The results indicated that the flood vulnerable areas of Xiamen are concentrated along waterways distant from roads, with high flood exposure in Tong'an and Xiang'an districts. The flood-prone areas in Xiamen are primarily located along the coastal areas characterized by extensive impermeable surfaces. High flood risk areas are mainly distributed in Tong'an and Xiang'an subdistricts, particularly in Xiangping and Xindian. The method developed offers support for accurate flood risk identification and decision-making in cities with limited data resources.

Evaluation of Radioactivity and Radiological Parameters in Soil Samples in Isparta, Türkiye

In the city centre of Isparta, located in the southwestern part of Türkiye, indoor radon concentrations and gamma dose rate levels were observed above the world and country averages. For this reason, the determination of the natural radioactivity levels in soil samples of Isparta province is of great interest. In the present study, the activity concentrations of radionuclides (namely 226Ra,232Th, 40K and 137Cs) were investigated in the soil samples collected from 72 different points including the city centre and 12 towns of Isparta by using a gamma spectrometer with a high-purity germanium (HPGe) detector. The activity concentrations of 226Ra,232Th, 40K and 137Cs radionuclides in the samples were found in the range of 4.08±0.39 - 69.84±1.43 Bqkg-1, 2.63±0.28 - 65.66±1.41 Bqkg-1, 44.48±3.17 - 452.38±9.65 Bqkg-1 and 0.28±0.18 - 19.10±0.61 Bqkg-1 respectively. The averages of all the measurements were determined as 15.69±0.72 Bqkg-1 for 226Ra, 15.40±0.78 Bqkg-1 for 232Th, 210.60±6.22 Bqkg-1 for 40K and 3.44±0.31 Bqkg-1 for 137Cs. Although these values were below the country and world averages, it was revealed that the 226Ra and 232Th activity concentrations in the city centre exceeded the national and world averages. In addition, radiological risk maps of the analysed radionuclides were produced for the first time, covering all towns within the Isparta province. To evaluate the radiological hazards resulting from natural radionuclides, external hazard index (Hex), absorbed dose rate (D), annual effective dose equivalent (AEDE), male and female lifetime cancer risk (LCR) values were also calculated. The outcomes of this study revealed that all the radiological parameter averages for Isparta were lower than the world and country averages but the calculation results for the city centre displayed the opposite of this situation except for the external hazard index.

Spatial design of groundwater quality monitoring network using multicriteria analysis based on pollution risk map

Spatial design of groundwater quality monitoring network using multicriteria analysis based on pollution risk map

Analyzing the Vulnerability of Residential Buildings in the City of Chaitén: A Focus on an Extreme Event Scenario in a Disrupted River Corridor Following the Cataclysmic Volcanic Eruption of 2008

Pillared on the hydrodynamic simulation of an extreme flooding scenario, we subsequently evaluated the physical vulnerability of residential buildings utilizing an ad hoc developed indicator-based methodology. This method aimed to quantify the expected loss for each affected residential structure. The outcome of this assessment facilitated the creation of a detailed risk map, allowing for the identification of hotspots that require immediate prioritization in mitigation efforts. The results of our study revealed a concentrated impact of the flood, particularly in the northern sector of the city. Within this region, four high-risk areas were pinpointed, comprising 70 homes predominantly situated close to the active channel zones. Notably, our findings underscored that twelve residential buildings, located at shorter distances from the river, are particularly susceptible to the impacts of the flood, as indicated by the physical vulnerability index values. It is important to highlight that the developed methodology is specifically tailored for the analysis of lightweight, one or two-storey houses with exteriors constructed from wood and zinc plates, as opposed to structures built with concrete or stone masonry. This distinction is crucial, given the prevalence of such building types in the Chilean Patagonian region. We recommend extending the application of this methodology to other urban areas in the region, where analogous impacts are possible and similar architectural patterns are common.

Identifying therapeutic targets for cancer among 2074 circulating proteins and risk of nine cancers.

Circulating proteins can reveal key pathways to cancer and identify therapeutic targets for cancer prevention. We investigate 2,074 circulating proteins and risk of nine common cancers (bladder, breast, endometrium, head and neck, lung, ovary, pancreas, kidney, and malignant non-melanoma) using cis protein Mendelian randomisation and colocalization. We conduct additional analyses to identify adverse side-effects of altering risk proteins and map cancer risk proteins to drug targets. Here we find 40 proteins associated with common cancers, such as PLAUR and risk of breast cancer [odds ratio per standard deviation increment: 2.27, 1.88-2.74], and with high-mortality cancers, such as CTRB1 and pancreatic cancer [0.79, 0.73-0.85]. We also identify potential adverse effects of protein-altering interventions to reduce cancer risk, such as hypertension. Additionally, we report 18 proteins associated with cancer risk that map to existing drugs and 15 that are not currently under clinical investigation. In sum, we identify protein-cancer links that improve our understanding of cancer aetiology. We also demonstrate that the wider consequence of any protein-altering intervention on well-being and morbidity is required to interpret any utility of proteins as potential future targets for therapeutic prevention.

Safety of Cyclists in Poland in the Context of European Road Traffic

The growing interest in cycling as a means of urban transport has led to an increased focus on cyclist safety as a key aspect of urban planning and transport policy. Simulation studies conducted by the International Transport Forum have demonstrated that reductions in CO2 and other pollutants can be achieved in the context of urban transport, thus realising the goals of decarbonising road transport. The spread of modal transport in cities is a potential reality within the next decade. Bicycles play a significant role in this context. This article presents an analysis of data on accidents involving cyclists. National and international data were analysed to identify the main risk factors. The aim of the paper is to analyse the risk to cyclists with an attempt to identify and map the five biggest risks to cyclists in urban traffic. The aim of the research is to raise awareness of cyclist safety issues and to identify directions for further action to reduce accidents and improve overall road safety. The results of the conducted analyses indicate that the risk for cyclists in road traffic (including urban traffic) has been on a noticeable downward trend over the past five to ten years. This trend allows for the mapping of the most significant types/risks in cycling in urban environments, thereby enabling the implementation of risk management strategies based on the method of risk mapping.

The concept of estimating the risk of water losses in the water supply network

One of the methods of increasing the availability of drinking water is to reduce water losses in existing water supply systems (WSS). The need to manage water losses in WSS is highlighted in the new Directive (EU) 2020/2184 of the European Parliament and of the Council of 16 December 2020 on the Quality of Water Intended for Human Consumption. It was indicated that the main cause of water losses is underinvestment in the maintenance and renovation of network infrastructure. The new legal provisions require a risk assessment to be carried out in the water supply system, taking into account the risk of leaks. The paper presents the concept of estimating the risk of water losses in the water supply network using the three-parameter risk assessment method and risk maps. The framework of the water balance proposed by International Water Association (IWA) were also presented, including the Infrastructure Leakage Index (ILI) for assessment of the water supply system Leakage Performance Category (LPC). The analysis was carried out for a water supply system used by 200,000 inhabitants. The LPC of the system was determined based on the ILI index. Then the water supply network pipes that could potentially be a source of leaks were identified. The analysis of the risk of water losses for the examined pipes allowed to determine which pipes should be first chosen to reduce the risk of water losses, i.e. active search for leaks.

A geospatial analysis of flood risk zones in Cyprus: insights from statistical and multi-criteria decision analysis methods.

Over the past few decades, flood disasters have emerged as the predominant natural hazard in Cyprus, primarily driven by the escalating influence of climate change in the Mediterranean region. In view of this, the objective of this study is to develop a geospatial flood risk map for the island of Cyprus by considering 14 flood hazard factors and five flood vulnerability factors, utilizing geographic information systems (GIS) and remotely sensed datasets. A comparative assessment was conducted for hazard mapping, employing statistical methods of frequency ratio (FR) and FR Shannon's entropy (FR-SE), and multi-criteria decision analysis method of fuzzy analytic hierarchy process (F-AHP). The main findings indicated that the FR method exhibited the highest predictive capability, establishing it as the most suitable approach for flood hazard mapping. Additionally, vulnerability factors were aggregated using F-AHP to generate the vulnerability map. The resulting flood risk map, which is the product of flood hazard and flood vulnerability, revealed that 9% of the island was located within highly risky regions, while 13.2% was classified as moderate risk zones. Spatial analysis of these high-risk areas indicated their concentration in the primary city districts of the island. Therefore, to mitigate future risks within these cities, an analysis of potential expansion zones was conducted, identifying the best-suited zone exhibiting the lowest risk. The generated flood risk map can serve as a valuable resource for decision-makers on the island, facilitating the integration of flood risk analysis into urban management plans.