Flood Myth

Wadi Qena is one of the Nile Valley areas particularly at risk of severe flash flooding, located in Egypt. The study aims to verify TRMM rainfall data (TRMM 3B42), using eight stations across Egypt as well as relies on morphometric analysis to generate a flood risk map based on the ranking method. Three process could be recognized through the study, calibration, correction and verification processes. The results discuss the match daily rainfall trends of TRMM and observed data, producing a correction equation for TRMM data with root mean square error (RMSE) value of 0.837 mm d-1 and R2= 0.238 (calibration process). On the other hand, a verification process, using the developed correction equation, obtain RMSE value of 1.701 mm d-1 and R2= 0.601. The morphometric analysis shows 32 sub-basins with a hazard degree from moderate to high, amounting to 50.3% of the watershed area. Conclusively, this study confirms that the current monitoring system is not enough to cover the whole area, e...

Coastal aquifers in semi-arid zones are particularly exposed to environmental changes because of their low annual recharge and the increasing anthropogenic pressure. This is particularly the case in the Trarza phreatic aquifer (SW Mauritania), which is the uppermost northern part of the great Senegalese-Mauritanian sedimentary basin. The interactions between the Atlantic Ocean and the Tertiary-Quaternary aquifer have evolved considerably during the last millennia and these continuous changes concern the nature and location of processes at work, their intensity and their current consequences. In this vast region with a very flat topography, hydrodynamic and geochemical observations are still rare and currently allow only the main features of recent history to be reconstructed. The analysis of old and recent data reveals that eustatic variations and the annual flood of the Senegal River were in the past the most important factors of equilibrium between fresh water and sea water, even ...

Flood is a condition in which water cannot be accommodated in a drainage channel such as a river or river. An area is said to be flooded if the water in the area is inundated in large quantities so that it can cover all or most of a large area. Determining forecasting or prediction on a potential in the long or short term, especially changes in water content levels in an area, requires a method, model, or approach that must be well tested. The lower the error value in a model, the better the model for testing a forecast. One of the data that can be used for analysis of potential flood models is the use of remote sensing data with technology from Landsat 8. The advantage of sensing data from Landsat 8 is that it has data good history and allows to see changes in land cover from year to year in an area. The purpose of this study was to determine the best model for forecasting the potential for flooding in an area using the Holt Winters model and the Simple Moving Average. The result o...

A massive flood struck the Chao Phraya River Basin in Thailand from August to December in 2011. The total fl ood volume was estimated to be 15 billion m 3 , and the area of damaged agricultural land was as large as the Kanto Plain. To understand the planar and temporal characteristics of water quality of fl oodwater along with the fl ow, the authors conducted a fi eld survey of the fl ood from Chai Nat, Ayutthaya to Bangkok in November and December. The results show that some indices were higher in the southern area from Ayutthaya and that the effect of the fi rst fl ash was observed in an area where inundation had started a few days earlier in Bangkok. E. coli was detected in the Chao Phraya River in inundated Ayutthaya in November, suggesting that human excrement fl owed into fl oodwater. However, it was not detected in December there, suggesting that the infl ow of human excrement stopped owing to the extinction of the inundated area.

s The arts and science in determining the residential property value make property value has evolved due to the changing in external factors such as economy, environmental and social. This research is aim to determine the residential property value by taking into account the economic attributes that could affect the value of residential property in flood risk areas. The economic attributes consist of structural, locational and environmental attributes involved in residential property valuation in relations with flooding. This paper will discover the significance and effect of each economic attributes in determining residential property value in flood risk area. An extensive review of previous studies in economic valuation of property for different floods disaster studies. It is considered to be the main restrictive factor resulting in lack of empirical studies in this field. Practitioners and researchers will find this study useful in developing an improved understanding of the econ...

The art and science of determining residential property value has evolved due to the changing external factors, such as the economy, environmental (climate change) and social aspects. This research aims to identify the impact of climate change (floods) to determine residential economic attributes that could affect the value for residential property in flood risk areas. The case study covers all residential housing schemes in Langat River Basin area, which has been considered as the highest flood risk area in the State of Selangor, Malaysia. The methodology of this research is based on the conceptual analysis from previous studies from local and international scenarios. The systematic analysis of previous literature of real estate valuation theory consists of economic attributes such as structural, locational and environmental attributes involved in residential property valuation in relation to flooding. The findings reveal that the economic attributes' response to flood hazards ...

The purpose of this research is to develop the residential flood hazard information map using Geographical Information System (GIS) for residential community resilience. The review approach is based on related literature contributing to identifying themes such as “flood hazard information map” and “geographical information system”. Integration of data will be sourced from Department of Irrigation and Drainage (DID), National Property Information Centre (NAPIC) and Jabatan Ukur dan Pemetaan Malaysia (JUPEM) using Unique Parcel Identifier (UPI) for respective residential land parcels. An extensive review of previous studies of flood hazard information map of residential community resilience for different flood disaster studies is considered to be the main restrictive factor resulting in a lack of empirical studies in this field. The development of residential property needs to be imposed with the elements for building specifications and materials that have flood resistance and resilie...

L’évolution de la ville de Saint-Louis, au Sénégal, est marquée par une croissance démographique et un développement urbain dans un environnement sujet aux risques d'inondation fluviale et aux phénomènes d'érosion côtière. Dans ce contexte, la ville s’étend sur les rares ressources foncières disponibles et se développent est souvent caractérisée par une urbanisation informelle et un manque d'infrastructures.  Cette extension urbaine s'accompagne de problèmes de gestion liés à la stagnation des eaux de pluie et à une forte densité de population. Cette étude a pour objectifs de cartographier l'extension du tissu urbain de Saint-Louis entre 1980 et 2024, en utilisant des outils de cartographie diachronique comme l’algorithme du Random Forest pour analyser l'évolution de la ville et de caractériser les formes d'expansion. Les résultats montrent une évolution de l'occupation du sol à Saint-Louis, entre 1980, 2000 et 2024. A cet effet, on note une croissance significative des zones urbaines, avec une multiplication par cinq des surfaces occupées par les bâtis et infrastructures, passant de 374,38 ha en 1980 à 2006,35 ha en 2024. L'urbanisation a surtout progressé vers le faubourg de Sor et la périphérie, modifiant l’espace urbain de la ville. Les transformations sont marquées par une augmentation des surfaces bâties, mais aussi par des disparitions dues à l'érosion côtière et aux inondations, notamment dans les zones sensibles de la ville. Ainsi, la gestion de cette croissance urbaine nécessite une approche intégrée, tenant compte des défis environnementaux, des besoins en infrastructures et de la préservation des espaces naturels, pour garantir un développement durable et résilient de la ville de Saint-Louis.

The evolution of the city of Saint-Louis, Senegal, is marked by population growth and urban development in an environment prone to river flood risks and coastal erosion. Despite measures such as the opening of the drainage canal in 2003, which reduced the risk of flooding, the effects of climate change and erosion remain a challenge. In this context, the city extends into the scarce available land resources and is often characterized by informal urbanization and a lack of infrastructure. This urban expansion is accompanied by management issues related to stagnant rainwater and high population density. In light of these challenges, this study aims to map the urban expansion of Saint-Louis between 1980 and 2024, using diachronic mapping tools like the Random Forest algorithm to analyze the city's evolution and characterize the forms of expansion. The results show the evolution of land use in Saint-Louis, Senegal, between 1980, 2000, and 2024. There has been significant growth in urban areas, with the area occupied by housing and infrastructure increasing fivefold, from 374.38 ha in 1980 to 2006.35 ha in 2024. Urbanization has primarily progressed toward the Faubourg de Sor and the periphery, altering the urban space of the city. The transformations are marked by an increase in built-up areas, but also by disappearances due to coastal erosion and flooding, particularly in the city's vulnerable zones. Thus, managing this urban growth requires an integrated approach, taking into account environmental challenges, infrastructure needs, and the preservation of natural spaces to ensure sustainable and resilient development of the city of Saint-Louis.

Mapping regions prone to flooding constitutes a crucial step toward developing localized solutions for flood preparedness and mitigation. This study presents a geographic information system (GIS)-driven approach that combines the decision-making trial and evaluation laboratory (DEMATEL), criteria importance through intercriteria correlation (CRITIC), and simple additive weighting (SAW) methodologies to identify flood-prone areas in the Sekondi-Takoradi Metropolis (STM), Ghana. The study's originality lies in using the hybrid DEMATEL-CRITIC-SAW model for flood susceptibility assessment, a novel integration of decision-making methods and analytical techniques not previously applied together for this purpose. This novel framework provides a comprehensive approach to analyze relationships among 11 flood-inducing variables, determine variable importance, and integrate these findings to produce a more accurate and robust flood susceptibility map. The results reveal a constructed network structure that highlights the complex relationships and dependencies among the variables. Among the assessed criteria, stream power index was identified as the most significant factor due to its high total interaction with other criteria. The flood susceptibility zones within STM are classified into five levels: very low (15%), low (27%), moderate (21%), high (22%), and very high (14%). Notably, the coastal and central sections of STM were marked as areas with moderate to very high flood susceptibility. The results, measured using the area under the curve, indicate that the proposed approach achieved a score of 0.947, demonstrating its superior performance over other existing hybrid models in the literature. The method provides actionable recommendations to authorities in STM for developing flood prevention/mitigation measures.

This paper aims to contribute to the debate on the feasibility of the provision of micro flood insurance as an effective tool for spreading disaster risks in developing countries and examines the role of the institutional–organisational framework in assisting the design and implementation of such a micro flood insurance market. In Bangladesh, a private insurance market for property damage and livelihood risk due to natural disasters does not exist. Private insurance companies are reluctant to embark on an evidently unprofitable venture. Testing two different institutional–organisational models, this research reveals that the administration costs of micro‐insurance play an important part in determining the long‐term viability of micro flood insurance schemes. A government‐facilitated process to overcome the differences observed in this study between the nonprofit micro‐credit providers and profit‐oriented private insurance companies is needed, building on the particular competence ea...

RESUMEN Los sistemas torrenciales se caracterizan por corrientes efímeras pero súbitas, que alcanzan rápidamente su caudal punta e incorporan abundante carga sólida que depositan también de forma brusca al desvanecerse la crecida. Se manifiestan desde ...

Environmental degradation is creating serious challenges for the spring water security in the mountainous region of South Asia. The freshwater springs meeting the growing water demands of the numerous mountain communities are under a high strain due to changing climate and land degradation in the region. The current study aims to assess the spring distribution and vulnerability to land degradation in Khyber Pakhtunkhwa province of Pakistan using geospatial modeling techniques coupled with ground information. The study revealed a total of 2564 springs with a density of about 0.06 springs/km² in the study area. More than fifty percent of springs were observed in the 1000–1400 mm rainfall regime, pointing towards a high influence of precipitation in recharging the springs. The mean soil loss of over 48.8 tons/ha/yr was predicted in the area, the risk of which was found to be very high (>100 tons/ha/yr) over 12% and high (50–100 tons/ha/yr) over 8.1% of the area. Based on the land degradation analysis, over 20.4% of the springs appear to be highly vulnerable, 28.4% medium vulnerable, and 51.1% low vulnerable in the region. The restoration of the forest cover over mountain slopes and highland pastures can lessen overland flows and improve groundwater and spring resources. In-depth investigations of the hydrogeology and environmental implications could be helpful for sustainable management of the springs in the region. The study would provide a base for developing viable land and water conservation strategies to improve spring water security in the region in future.

Improper land management often causes flood, this is due to uncontrolled runoff. Runoff is affected by the management of the land cover. The phenomena also occurred in South East Sulawesi, Indonesia. This study aims to analyze the flow rate of water in watershed of Lalindu River in North Konawe, South East Sulawesi by using a Tank Model. The model determined the magnitude of the hydrologic runoff, infiltration capacity and soil water content several land uses were evaluated in the study area. The experimental and calculation results show that the runoff in the forest is 2,639.21 mm /year, in the reed is 2,517.05 mm/year, in the oil palm with a slope more than 45% is 2,715.36 mm/year, and in the oil palm with slopes less than 45% is 2,709.59 mm/year. Infiltration in the forest is 30.70 mm/year, in the reed is 7.51 mm/year, in the palm oil with a slope more than 45% is 24.13 mm/year and in the palm oil with slopes less than 45% is 29.67 mm/year. Runoff contributes to stream flow for water availability.

Improper land management often causes flood, this is due to uncontrolled runoff. Runoff is affected by the management of the land cover. The phenomena also occurred in South East Sulawesi, Indonesia. This study aims to analyze the flow rate of water in watershed of Lalindu River in North Konawe, South East Sulawesi by using a Tank Model. The model determined the magnitude of the hydrologic runoff, infiltration capacity and soil water content several land uses were evaluated in the study area. The experimental and calculation results show that the runoff in the forest is 2,639.21 mm /year, in the reed is 2,517.05 mm/year, in the oil palm with a slope more than 45% is 2,715.36 mm/year, and in the oil palm with slopes less than 45% is 2,709.59 mm/year. Infiltration in the forest is 30.70 mm/year, in the reed is 7.51 mm/year, in the palm oil with a slope more than 45% is 24.13 mm/year and in the palm oil with slopes less than 45% is 29.67 mm/year. Runoff contributes to stream flow for water availability.

This paper draws from a larger doctoral study, conducted between 2013 and 2016 in five flood-prone schools of the Budalang’i division of western Kenya. The mixed-methods study was based on empirical data drawn from twenty-three in-depth interviews from parents, senior school managers, and Sub County Education officers. Fifteen of these interviews were with males and eight with females. A questionnaire was completed by a total of 191 Standard Eight pupils, 49.2% boys and 50.8% girls across the five schools. Focus group discussions (FGDs) consisting of ten pupils from each of the five schools were also conducted. The study investigated the extent to which flood-prone schools can generate equitable epistemological access (EEA) and how they are committed to delivering a socially just educational experience. The research was embedded in the 'critical realism framework' as the overarching philosophy, premised on Sen's capability approach and Nancy Fraser's social justice f...

Sedimentary facies, short-lived isotopes 7 Be, 137 Cs, and 210 Pb, and magnetic properties of sediment cores in Hanalei Bay, Kaua`i, Hawai`i, were used to assess sediment sources and patterns of deposition associated with seasonal flooding of the Hanalei River. Sediment cores were collected from the seafloor in June and September of 2006 to supplement similar data collected during the summer of 2005. The youngest and thickest terrigenous sediment was observed on the east side of the bay: near the Hanalei River mouth and in a bathymetric depression, known locally as the Black Hole, that acts as a temporary sediment sink. Deposits from floods that occurred between February and April 2006 left flood deposits in the eastern bay that, by June of 2006, were on the order of 10 cm thick. A flood occurred on August 7, 2006, that was smaller than floods that occurred the previous winter but was a substantial discharge event for the summer season. Deposits from the winter 2006 floods continued to dominate the sedimentary record in the eastern bay through early fall, even after the addition of newer sediment during the August 7 flood; this is consistent with the much higher sediment input of the winter floods compared with the August 7 flood. Broad variations in magnetic grain size and relative magnetite-hematite abundance in several sediment cores indicate many sources of upland terrigenous sediment. As a group, recent flood deposits show much less variation in these properties compared with older deposits, implying either that the 2006 winter-spring flood sediment originated from one or more distinct upland settings, or that substantial mixing of sediment from multiple sources occurred during transport. Sediment is most readily remobilized and advected out of the bay during winter, when oceanic conditions are energetic. In summer, wave and current measurements made concurrently with this study showed weak currents and little wave energy, indicating that sediment delivered during summer floods most likely remains in the bay until winter storms can remove it. Increased turbidity and sedimentation on corals resulting from floods of the Hanalei River could affect the sustainability of coral reefs and their many associated species. This possibility is of particular concern during summer months when wave energy is low and sediment is not readily remobilized and transported out of the bay. The timing (seasonality) and magnitude of sediment input to the coastal ocean relative to seasonal variations in wave and current energy could have significant ecological consequences for coral-reef communities in the Hawaiian Islands.

Seasonal flood pulses drive important seasonal ecosystem changes, trigger ecological processes that control spatial and temporal distribution of organisms and their life-history strategies, and are considered a key ecological process shaping diversity in floodplains. We used generalized dissimilarity modelling (GDM) to analyse the relative importance of flooding as a driver of snake community composition in the Paraguay River Basin (PRB), which encompasses discontinuous seasonal flooded areas, including the Pantanal floodplain, one of the largest Neotropical wetland systems. We modelled the beta diversity of pairs of PRB snake communities (based on species occurrence and phylogenetic relationships) as a function of biogeographical and environmental dissimilarities between areas, considering predictors that represent distinct limitations of species' ability to use an area. Annual flooding directly drives snake diversity, mainly when ancient evolutionary relationships between species were considered to calculate the phylogenetic diversity of the communities. Floods recurrently produce major changes in the environment and probably limit the persistency of species extremely specialized in habitat use. Despite the confirmation of the effect of flooding, the most important predictor of beta diversity between snake communities in the PRB was forest cover where communities were placed. Forest cover seems to constrain the occurrence of some species in both gradient extremities through the absence of suitable conditions for either specialized habitat use or thermoregulatory behaviours. Geographical distance was also an important predictor of beta diversity, highlighting the importance of neutral process in the assembly of local communities in systems such as seasonally flooded areas, where annual disturbances of varying intensities continually disassemble and reassemble biological communities. For the first time, we quantified the relative importance of flooding affecting patterns of biological communities in the Pantanal floodplain, compared to multiple factors also acting on species turnover in the area.

Introduction

Flooding, one of the most common natural disasters, poses a serious threat to ecosystems and human safety, with factors such as heavy rainfall, rapid snowmelt, dam failures, and poor management of water, soil, and vegetation resources exacerbating its impacts. Over the past two decades, approximately 2.4 billion people have been affected by natural disasters, resulting in economic damages amounting to $2.97 trillion. Among these, human-related factors such as reduced permeability, construction near riverbanks, and altering water flow paths have played a greater role in intensifying flood damage than natural factors. Accurate monitoring of floods and assessing affected areas are of significant importance. Flood zoning is a practical tool that plays a crucial role in managerial planning. Today, the combined use of optical and radar imagery can provide more comprehensive information. This study aims to effectively utilize Sentinel-1 and Sentinel-2 satellite images in conjunction with the Google Earth Engine (GEE) platform for flood mapping and vegetation indices in the Germi and Ungut counties, which have been impacted by flood events in May and June 2023. This innovative approach enhances the accuracy and speed of flood detection and offers a scalable solution for managing flood risks in vulnerable areas. By leveraging the latest advancements in remote sensing and cloud computing, this research contributes to developing more resilient strategies against flooding and is essential for regions like Ardabil Province, which are prone to irregular and heavy rainfall.



Materials and Methods

In this study, various methods were employed to identify and analyze flood-affected areas using Sentinel-1 and Sentinel-2 satellite data. Initially, Synthetic Aperture Radar (SAR) images from Sentinel-1 in the form of GRD (Ground Range Detected) products were utilized, which can capture images in all weather conditions and at any time of day. These data were derived from the C-band and Interferometric Wide Swath (IW) mode for flood mapping. To reduce speckle noise, the Refined Lee filter was applied, which removed random noise while preserving structural details. A threshold of 1.25 was set for VV polarization (vertical transmit, vertical receive) to identify flood-prone areas, with pixels having VV values above this threshold considered as flooded regions. To avoid misinterpretation, areas with permanent water bodies were excluded using JRC Global Surface Water data. SAR images of Sentinel-1 taken before, during, and after the flood (between April 1 and August 20, 2023) were compared for change detection. Additionally, Sentinel-2 images were used to calculate the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) to assess the impact of vegetation variability from April 1, 2019, to August 20, 2023. These methods effectively identified flood-affected areas and flood impacts on the vegetation cover of the two study counties.



Results and Discussion

In May and June 2023, the Germi and Ungut counties witnessed unprecedented rainfall, which led to severe flooding. The results of the interpretation of Sentinel-1 SAR images showed that about 185.83 km2 were affected by flooding, which is equivalent to 9.01 % of the total study area. Before the flood (April-May 2023), the mean NDVI and EVI respectively, were 0.25 and 0.18, indicating a significant decrease in vegetation cover compared to the reference year (April-May 2019). This could be due to land use change, drought, gradual destruction of dense vegetation, or other environmental stresses before the flood. At the time of the flood (June 2023), the mean NDVI and EVI reached 0.22 and 0.15, respectively, which are the lowest levels recorded up to that time. Only seven percent of the area had healthy vegetation during this period. This decrease could be due to the inundation of plants, destruction due to the intensity of the flood flow, or the covering of the soil surface by sediments. After the flood (August 2023), a more severe decrease in vegetation status was observed. The mean NDVI decreased to 0.15 and EVI to 0.1, and only about 2% of the area remained with healthy vegetation. This decrease may be due to severe soil degradation, erosion of the fertile topsoil, reduced vegetation cover due to seasonal conditions in the area.





Conclusion

This study mapped the June 2023 flood and vegetation indices in two counties of Germi and Ungut, located in the northwest of Iran, using Sentinel-1 SAR and Sentinel-2 data. In adverse weather conditions, SAR technology is an effective tool for mapping and monitoring flood-prone areas. The combination of SAR data, the Refined Lee filter, and the GEE platform facilitates crisis management and mitigates flood impacts. SAR's ability to penetrate cloud cover and provide rapid data access plays a critical role in the swift detection of floods. Integrating this technology with early warning systems enables quicker responses to floods, reducing both human casualties and financial losses. Analysis of the June 2023 Flood occurred in the two counties of Germi and Ungut, with an area of 2064 km2, showed that about 185.83 km2 (equivalent to nine percent of the total area) were directly affected by the flood. From an environmental perspective, the analysis of NDVI and EVI indices in four time periods (one reference period in 2019 and three time periods related to before, during, and after the flood of 2023) indicates a sharp decrease in the density and extent of vegetation cover in the region. The amount of desirable vegetation cover decreased from approximately 269 km² in the pre-flood period to only 41 km² in the post-flood period, indicating the destructive impact of the flood on the region's ecological structure. These findings emphasize the need for integrated watershed management and strategic land-use planning. To enhance community resilience, it is recommended to prioritize and protect vulnerable areas through strategic policies. Utilizing these results can help reduce flood damage and save time and costs in foundational studies.

Introduction

The rapid growth of the population, the development of economic activities, and human needs for natural resources, including water resources, have caused an imbalance between supply and demand, and have ultimately caused the instability and lack of resilience of these resources in most regions of the world, especially arid and semi-arid regions such as our countries. Water is the foundation of life, the foundation of nature, and the axis of economic, social, and cultural development of societies. Providing safe and sufficient water has always been one of the most important challenges of the world community in the third millennium, especially in the arid belt countries of the world and the West Asian region. The United Nations World Water Development Report (2020) shows that global water consumption has increased six-fold over the past century and continues to grow by approximately 1% annually. Therefore, an increasing share of the population will face water shortage. Achieving sustainable development of water resources is widely linked to the concept of resilience.

In this research, an attempt has been made to address the various dimensions and indicators of resilience, which include social, economic, and environmental resilience, and which play an effective role in the resilience of water resources. Then we will focus on the resilience of water resources and the emergence of imaginable possibilities in case of occurrence in each scenario to prioritize environmental, economic, and social changes by considering different conditions to create a clear understanding of the change of each variable for researchers. The present study tries to apply the basic scenario planning approach with Futurology for future research by dealing with one of Iran's important central catchment areas, which is also facing various challenges.

Materials and Methods

The current research, with a future research approach, identifies the most important factors affecting the resilience of water resources in the Zayandeh Rood watershed. In this research, due to its exploratory nature, the environmental scanning technique was used, and due to the dominant approach of this research, which is future research, the Delphi technique was used. Because due to its specialized nature, this research cannot be done through conventional methods of surveying people. The Delphi method is a method that relies on wisdom, collective intelligence, and brainstorming to reach the consensus of experts on a specific topic so that the most appropriate answers can be obtained. The sample population of this research is a group of 50 experts, people active in the field of water, experts, who are experts in two fields: "future research approach" and "resilience of water resources". At the final stage, because the coefficient of agreement between the panel members regarding the questions of the questionnaire has increased significantly compared to the first round, the continuation of Delphi has been omitted and at this stage, the number of 33 factors has been called as the final index for structural analysis. The vision of questions and issues is designed for the next 25 years. At this stage, these 33 factors were distributed in the form of a semi-structured questionnaire among the statistical community (Delphi group consisting of experts) and they were asked to rate the variables in the framework of the cross-effects matrix based on influence and effectiveness with numbers in the range of 0 to 4. These points were entered in the cross matrix to measure the direct and indirect influence of each factor and according to the score of influence and influence of the factors, key factors are obtained.

Results and Discussion

In the analysis done, the dimensions of the matrix in the Mikmac software are 33 x 33 and the number of repetitions is considered 2 times. The index of filling the matrix is 91.99%, which indicates that about 92% of the cases have influenced each other. from a total of 1001 relationships; 88 relationships have cross effects, 392 relationships have cross effects 1, 497 relationships have cross effects 2, and 112 relationships have cross effects 3. These results indicate that the number of relationships with moderate impact is high compared to other relationships, and relationships with high intensity form a small percentage of the total relationships. In the following, the analysis of the direct and indirect effectiveness of the factors is discussed. What can be understood from the state of the scatter plot of variables affecting the resilience of Zayandeh Rood water resources is the state of instability of the system. After identifying the influential indicators and determining their role and importance in direct and indirect variables, the selected indicators are identified as the uncertainty of the scenarios, and the base scenario planning is formed. Therefore, 5 scenarios were prepared based on uncertainties

Conclusion

With the expansion of urbanization and the increase of population in metropolises, the conflict between development and the environment is gradually revealed. In the meantime, the ecological power of the regions is limited to each region. In the area of the central plateau of Iran, the amount of population settlement has never been as high as it is today. Therefore, urbanization in the central plateau of Iran has created many problems for natural resources. On the other hand, the distribution of the population in the area with natural resources, including water sources, is not consistent, because the rainfall occurs in the western area of the watershed, but the majority of the people and the population live in other parts. Therefore, the conflict of interests between citizens and villagers is observed in the use of water resources and the consumption pattern, and the need to use technology to manage and reuse water resources has become particularly important. Heterogeneous rainfall distribution within the catchment area has doubled the importance of the interaction of people groups with each other. The development of industrial and service jobs should be done with the approach of reducing jobs dependent on water resources to reduce water consumption

Bangladesh is crisscrossed by the branches and tributaries of three main river systems, the Ganges, Bramaputra and Meghna (GBM). The temporal variation of water availability of those rivers has an impact on the different water usages such as irrigation, urban water supply, hydropower generation, navigation etc. Thus, seasonal flow outlook can play important role in various aspects of water management. The Flood Forecasting and Warning Center (FFWC) in Bangladesh provides short term and medium term flood forecast, and there is a wide demand from end-users about seasonal flow outlook for agricultural purposes. The objective of this study is to develop a seasonal flow outlook model in Bangladesh based on rainfall forecast. It uses European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal precipitation, temperature forecast to simulate HYDROMAD hydrological model. Present study is limited for Ganges and Brahmaputra River Basins. ARIMA correction is applied to correct the model...

Recent advances in the field of flood forecasting have shown increased interests in probabilistic forecasting as it provides not only the point forecast but also the assessment of associated uncertainty. Here, an investigation of a hydrologic uncertainty processor (HUP) as a postprocessor of ensemble forecasts to generate probabilistic flood forecasts is presented. The main purpose is to quantify dominant uncertainties and enhance flood forecast reliability. HUP is based on Bayes's theorem and designed to capture hydrologic uncertainty. Ensemble forecasts are forced by ensemble weather forecasts from the Global Ensemble Prediction System (GEPS) that are inherently uncertain, and the input uncertainty propagates through the model chain and integrates with hydrologic uncertainty in HUP. The bias of GEPS was removed using multivariate bias correction, and several scenarios were developed by different combinations of GEPS with HUP. The performance of different forecast horizons for these scenarios was compared using multifaceted evaluation metrics. Results show that HUP is able to improve the performance for both short-and medium-range forecasts; the improvement is significant for short lead times and becomes less obvious with increasing lead time. Overall, the performances for short-range forecasts when using HUP are promising, and the most satisfactory result for the short range is obtained by applying bias correction to each ensemble member plus applying the HUP postprocessor.

Recent years have witnessed considerable developments in multiple fields with the potential to enhance our capability of forecasting pluvial flash floods, one of the most costly environmental hazards in terms of both property damage and loss of life. This work provides a summary and description of recent advances related to insights on atmospheric conditions that precede extreme rainfall events, to the development of monitoring systems of relevant hydrometeorological parameters, and to the operational adoption of weather and hydrological models towards the prediction of flash floods. With the exponential increase of available data and computational power, most of the efforts are being directed towards the improvement of multi-source data blending and assimilation techniques, as well as assembling approaches for uncertainty estimation. For urban environments, in which the need for high-resolution simulations demands computationally expensive systems, query-based approaches have been ...

This study investigates five hydrological models to identify adequate model(s) for operational flood forecasting at Waterford River watershed. These models included three lumped conceptual models (SAC-SMA: Sacramento Soil Moisture Accounting, GR4J: modèle du Génie Rural à 4 paramètres Journalier, and MAC-HBV: McMaster University Hydrologiska Byråns Vattenbalansavdelning), a semi-distributed model (HEC-HMS: Hydrologic Engineering Center's Hydrologic Modeling System) and a fully distributed physically-based model (WATFLOOD: University of Waterloo Flood Forecasting System). The best model(s) were chosen by comparison of performance criteria. To verify the potential of the best performing hydrological models for operational use, deterministic hydrologic forecasts were performed. New hydrological insights for the region: All five models are capable of simulating streamflow reasonably well in both calibration and validation periods. The SAC-SMA and GR4J models perform equally well and perform better than the other three models for all low, medium, and peak flows. The SAC-SMA and GR4J models generally perform better for peak flows, followed by HEC-HMS. Streamflow forecast experiment using deterministic weather prediction shows that SAC-SMA, GR4J, and HEC-HMS models perform well for up to 1-3 days ahead forecasts and are recommended for operational use. However, due to the good performance of all five models, an ensemble forecasting using continuous, multiple hydrological models is also recommended.

Emergency preparedness is essential for ensuring the safety and protection of the population in the event of a disaster. To develop effective emergency plans, it is imperative to prepare and assess appropriate response scenarios. An event (an accident or a climatic event) that occurred on a primary road artery could lead to partial or total closure of the artery to vehicular tra c for several hours or days, with negative consequences for vehicular circulation along the transport network including the structure itself. Therefore, in addition to reestablishing the functionality of the affected arterial road, reestablishing the functionality of the affected arterial road is highly important for determining possible alternative routes capable of providing an adaptive response to disruption. The aim of this paper is to improve the resilience of road infrastructures and to ensure reliable network availability under adverse conditions, such as extreme weather. The results of a study carried out in the city of Palermo to develop emergency response scenarios for heavy rainfall are presented. A dynamic microsimulation model was developed and implemented using Dynasim to model the main tra c corridors in the at-risk area. The impact of different emergency management strategies on mobility in response to natural disasters was assessed. The results can guide local public safety agencies in implementing effective tra c management strategies in the event of an actual emergency.

Geographically, Nepal is situated on the lap of the Himalayas occupying 0.3 percent area of Asia and 0.03 percent of the world. Recently, global climate change has invited enormous environmental hazards and disasters in the Hindu-Kush Himalayan region. Catastrophic floods originating from the outburst of glacial lakes have been recognized as one of the primary natural hazards in Nepal, making downstream areas vulnerable. Frequent severe floodscaused by glacier outburst in the Nepal Himalayas, occur once every three years. Nine potentially dangerous glaciers were identified in the Eastern and Central Himalayas during pre- and post-monsoon seasons. At national and international level, Glacial Lake Outburst Floods (GLOF) in Nepal, are receiving considerable attention. Such floods endanger thousands of people, hundreds of villages and basic infrastructure causing disasters. This paper incorporates a case of flash-flood caused by GLOF and torrential rain in India which can be taken as a ...

Flood disaster has incurred remarkable costs to human, social and economic aspects, affecting not only the local but national and world economy as well. Flood is the most significant natural hazard in Malaysia, particularly in terms of its frequency and duration, size of the affected areas and economic damages. This paper examines the impacts of flood disaster on gross domestic product (GDP) growth in the agricultural and manufacturing sectors in Malaysia for the period of 1960 to 2013 by applying the Autoregressive Distributed Lag (ARDL) bounds testing approach for cointegration and error correction model (ECM) for short-term relationship. Augmented Dickey-Fuller (ADF) test, Phillips-Perron (PP) test and Kwiatkowski-Phillips-Schmidt-Shin (KPSS) unit root test examines the stationarity of the series. Results show that the series are cointegrated. The findings suggest that size of affected areas affects agricultural growth in both the long run and short run. Meanwhile, total damage cost also appears to affect manufacturing growth in both the long run and short run. The results of the study have important implications on the country's agricultural and manufacturing sectors.

Flood disaster has become a natural concern to the land owners where it raised a critical issue in term of land value depreciation. Previous studies have discussed the issue of potential decline in the value of land which are located on the flood-liable area. However, in Malaysia, current studies on flood impact are considered limited and do not focus on the effects of flood on land property. With the Hedonic Pricing Model (HPM) approach, we investigate the effect of flood on agricultural and industrial land property values in the urban and rural areas in Malaysia. The analysis indicates that the agricultural and industrial land values in the urban and rural areas have significantly decreased due to flood events. This study will benefit the land owners to understand the flood impact on land value and also the factors that contribute to the loss in the land value. It becomes the responsibility of the land owner to put the asset and property to its best use, given the presence of the ...

High Arsenic (As) concentrations have been reported in superficial water in the Yamuna flood plains (YFP), Delhi, which is being extensively used for agriculture. The concentration of As in some common vegetables such as Solanum lycopersicum (tomato), Abelmoschus esculentus (lady's finger), Solanum melongena (brinjal), Lagenaria siceraria (bottle gourd), Raphanus sativus (radish), Zea mays (corn), and Luffa acutangula (ridge gourd) has been studied in this work. The range of As concentrations (dry weight) varies from 0.6 to 2.52 mg/kg with the highest accumulation of 2.52 mg/kg in radish followed by tomato (2.36 mg/kg). The order of As concentration in the decreasing order is R. sativus [ S. lycopersicum [ Z. mays [ L. acutangula [ L. siceraria [ S. melongena [ A. esculentus. Thus, As accumulation is the highest in roots and the lowest in least juicy fruits. The daily dietary intake of As through the consumption of various vegetables was also calculated. Though the mean As concentration was the highest in radish (2.52 mg/kg) but the highest amount of As is being consumed through tomato (0.383 mg/day), which is nearly three times the World Health Organization's provisional maximum tolerable daily intake limit of 0.126 mg/day for a 60 kg person. High concentration of As in vegetables grown in YFP, Delhi is being reported here. This high contamination is primarily due to the presence of As in irrigation water having its source from coal-based thermal power plants in the vicinity of the area. If not checked properly, it will pose a serious health risk to people living in these densely populated areas surrounding YFP.

We identify the mechanisms controlling fine deposits on the inner‐shelf in front of the Besòs River, in the northwestern Mediterranean Sea. This river is characterized by a flash flood regime discharging large amounts of water (more than 20 times the mean water discharge) and sediment in very short periods lasting from hours to few days. Numerical model output was compared with bottom sediment observations and used to characterize the multiple spatial and temporal scales involved in offshore sediment deposit formation. A high‐resolution (50 m grid size) coupled hydrodynamic‐wave‐sediment transport model was applied to the initial stages of the sediment dispersal after a storm‐related flood event. After the flood, sediment accumulation was predominantly confined to an area near the coastline as a result of preferential deposition during the final stage of the storm. Subsequent reworking occurred due to wave‐induced bottom shear stress that resuspended fine materials, with seaward flo...

Waterlogging is considered a severe environmental hazard in the Sylhet city corporation (SCC) area of northeast Bangladesh adversely affects the local socio-economic development. The integrated geospatial approach presents a worthy alternative to the conventional mapping of waterlogged surface areas. The remote sensing-based water index technique was used for delineating pre-monsoon and post-monsoon waterlogged areas of SCC in 2020 and 2021. Seasonal deviations of the waterlogging were determined by overlaying the waterlogged sites emanated from the pre-monsoon and post-monsoon periods under the GIS environment. Results show that waterlogged areas for pre-monsoon and post-monsoon seasons in 2020 are 2.25 sq. km and 4.12 sq. km, respectively, whereas 2.22 sq. km and 3.90 sq. km in 2021. Hence, the seasonal variations in waterlogged areas in 2020 and 2021 are 1.87 sq. km and 1.68 sq. km, respectively. This analysis also demonstrates that waterlogging in SCC is utterly driven by the hi...

Along the Upper Danube, almost all former floodplain areas have been lost due to river regulation, large-scale land-use changes, and terrestrialization processes. In the Lobau floodplain near the City of Vienna, ongoing terrestrialization leads to a dramatic loss of aquatic and semiaquatic habitats. Although the ecological values of the remaining floodplain area, such as high productivity and high biodiversity, are widely acknowledged, the implementation of restoration measures is difficult. In urban environments such as the Lobau, planning and decision-making for floodplain restoration inevitably involves trade-offs, uncertainties, and conflicting objectives and value judgments. Beyond ecological values, the main socioeconomic aspects are flood control, drinking water supply for Vienna, and recreation. The aim of this chapter is to present the current ecological situation and the major development tendencies of the Lobau floodplain and to show the effects of potential management measures on the ecological situation.

We used an information theoretic approach to assess the effects of an ecologically adjusted sediment management scheme on grayling (Thymallus thymallus L. 1758) populations. Additionally to reservoir operation, candidate models included a variety of parameters and processes that may influence grayling populations such as flow, temperature, density dependence, and bird predation. Population parameters analyzed included total densities, young of the year numbers, and larval densities. These analyses were supplemented by a characterization of sediments and sedimentation patterns in the reach. Investigations were carried out in six sites affected by flushing and in one control site. A total of thirteen flushing operations have been undertaken within the study period leading to considerable remobilization of fine sediments and gravel. Due to seasonal and hydrological restrictions, not every flood could be used for flushing. These limitations led to an interrupted management throughout the chain of reservoirs as well as to long time intervals between flushing events with possible effects on spawning habitat quality. None of the investigated population parameters was affected by flushing, and thus, the study generally supports the current reservoir management scheme. Our analyses revealed the magnitude and timing of high water events, temperature, and density-dependent effects, that is, population densities the year before, as the most influential variables for grayling population dynamics in the investigated stretch. The siltation of reservoirs is a significant problem for reservoir storage, flood protection, river deltas, and coastal zones. Its management-which is inevitable to safeguard river deltas and secure flood protection-poses also the challenge to safeguard riverine ecosystems below reservoirs. Based on our experience, we propose a periodic flushing regime in concordance with the hydrograph thereby mimicking the timing, magnitude, frequency, and duration of natural SSC pulses and gravel transport. This flushing regime minimizes adverse downstream environmental impacts and maximizes benefits.

Background Despite being in existence for hundreds of years, Streptococcus pyogenes remains a significant cause of global morbidity and mortality, with a particular impact in resource-limited settings like Ethiopia. Even though research on Streptococcus pyogenes skin infections in Ethiopia is growing, there's a gap in identifying the potential risk factors contributing to this infection with prevention and control measures. The primary objective of this case-control study design was to identify potential risk factors of Streptococcus pyogenes skin infections and outbreak investigation was also undertaken to control and prevent the spread of Streptococcus pyogenes. Methods A case-control study was conducted in the South Gondar Zone of Andabet and Dera districts from December 10, 2022, to January 10, 2023. An active case search was done with house-to-house by using epidemiologically linked case definitions, and a total of 914 residents were attacked by the outbreak. A face-to-face interview using a structured questionnaire was carried out to collect data. Epi Data version 4.6 and STATA version 17 software were used for data entry and analysis, respectively. Regression analysis was computed, and variables with a P-value of ≤ 0.05 were considered as statistically significant risk factors. Result Group A beta-hemolytic streptococcus pyogenes was identified during the outbreak investigation. The attack rate of the infection was 22.2 cases per 1,000 population. The logistic regression analysis revealed that contact with cases (OR = 5.98, 95% CI: 2.91-12.25), poor personal hygiene (OR = 0.37, 95% CI: 0.2-0.66), inadequate water access for hygiene (OR = 2.2, 95% CI: 1.27-3.76), inadequate clothing practices (OR = 0.41, 95% CI: 0.23-0.70), and presence of injury (OR = 9.8, 95% CI: 5.85-18.41) were statistically significant risk factors. Significant risk factors included contact with cases, poor personal hygiene, inadequate water access for hygiene and clothing practice, and injury. Improving personal hygiene, increasing water access, and injury prevention are recommended to reduce S. pyogenes transmission. S. pyogenes infection should be included in the national public health surveillance system. Longitudinal studies should be conducted to track the impacts of S. pyogenes infections over time in the same population.

This study aims to develop a methodology for generating a flood runoff susceptibility (FRS) map using a revised curve number (CN) method. The study area is in the Kuantan watershed (KW), Malaysia, which was seriously affected by floods in December 2013 and December 2014. A revised runoff CN map was developed for the study area and then compared with those available in the SCS standard tables. The CN obtained from the revised approach range between 18 and 100, which reveals a stretching effect on the CN, which initially ranged between 33 and 100. Subsequently, the FRS map was developed for the KW. Approximately 5 % of the study area was identified as a very high-risk zone and 13 % as high-risk zone. However, the spatial extent of a high-risk zone in the downstream end and lowland areas of the KW could be considered to be the main cause of flood damage in recent years. From practical point of view, the finding of this research provides a road map for government agencies to effectively implement flood mitigation projects in the study area.

Tropical Cyclone Seroja, which occurred between April 2 to 6, 2021, is one of the strongest storms ever in East Nusa Tenggara. The track results of the cyclone showed that Seroja, formed at coordinates 10.5° S and 123° E, moved towards west longitude to Sumba Island and continued towards Australia. Moreover, the Global Precipitation Measurement (GPM) output was used to analyze the rainfall conditions at the center of the Seroja cyclone through the Kambaniru watershed in East Sumba, and the results showed that the precipitation continued to increase during Seroja's development to reach 225 mm. Therefore, this study aimed to analyze the effect of the rainfall during the storm on the maximum runoff experienced in the Kambaniru watershed through the application of quantitative analysis on the rainfall data from GPM data. The process involved analyzing the flood discharge using the HSS-SCS Curve Number method and GPM data, which were initially used to evaluate the rainfall during the...

Introduction

The expansion of cities in the margins of rivers, alluvial cones, low-altitude coasts, deltas and downstream areas of storage dams has led to an increase in the vulnerability of watersheds to the risk of flooding. This study was carried out with the aim of flood risk zoning and prioritization of flood-prone areas using multi-criteria decision making techniques and remote sensing indicators using Fuzzy AHP and VIKOR model in Rakat Khuzestan watershed. One of the solutions used to identify flood risk and prepare maps of its sensitivity is the use of bivariate and multivariate statistical models, data mining and machine learning. But since many of these models require a lot of data and their calibration is complex, therefore, in recent years, many models have been tested to prepare a flood susceptibility map, among which, the combination of statistical models And decision-making with remote sensing techniques and geographic information system has been of great interest to researchers due to increasing the ability of the model in forecasting. The difference between this study and the studies carried out so far is that in this study, for the first time, multi-criteria decision making techniques and remote sensing indicators are used in the zoning of flood risk in the watershed simultaneously in the watershed. Mountainous and flowing rakat will be used in Khuzestan province and its efficiency will be measured.

Materials and Methods

After making the necessary corrections on the Sentinel 2 satellite images of the region, vegetation indices (EVI, NDVI and SAVI), vegetation density and land use of the region were extracted. Then, by using two multi-criteria decision making techniques (FAHP and VIKOR), weighting of indicators and prioritization of sub-basin flooding were carried out. Finally, after extracting the topography, elevation, soil and geological maps and producing 15 morphometric indicators effective in the flooding situation of the basin, using two multi-criteria decision making techniques FAHP and VIKOR, the weighting of the indicators and the prioritization of the flood proneness of the basin were carried out. became In order to validate and evaluate the multi-criteria decision making models, in the future, with field survey, the use of remote sensing indicators such as NDVI and MNDVI, twenty-five points, flood-prone areas of the basin were randomly selected and placed, and the output of the multi-criteria decision-making models FAHP and VIKOR were validated with these points.



Results and Discussion

It was concluded that among all the indicators, the runoff curve number index, vegetation cover and land use and distance from the waterway account for about 50% of the total flood share of the basin and have The greatest impact on the flood phenomenon is in mountain basins, including the Barkat basin in Dehdez County. Also, the direction of the slope range and the rainfall index (due to the uniformity of the index at the basin level) were found to have the least effect (total less than 5%) among the investigated parameters. It can be said that due to the combination of land use and soil maps, vegetation and rainfall of the basin, as well as the simultaneous effect of land use and soil hydrological group on the flood potential of the basin, it can be a more effective indicator in determining the flood benefit of the basin. The results obtained in this study are consistent with the results of Nouri et al., (2019). Another influential parameter in the flooding of the Rakat basin area (19 percent) is vegetation and land use. The vegetation cover of the area includes agricultural lands, medium pastures, oak forest, and high quality pastures, which respectively had the highest and lowest values in the occurrence of floods, belonging to agricultural lands and high quality pastures. The distance from the waterway is the next influential parameter with a weighted value (about 15 percent), the smaller the distance from the waterway, the higher the value in the occurrence of floods, and the greatest flood potential of the region is in this area. The results of EVI, NDVI and SAVI spectral indices in the two methods of Fuzzy AHP and VIKOR showed that the EVI index has an overestimate and vice versa the SAVI index has an underestimation, but the NDVI index has shown more accurate results of locating the flood prone areas of Rakat Basin.

Conclusion

The results of the study showed that out of the 15 indicators used in the flood zoning of Rakat basin, the vegetation cover indicators are 19%, the runoff curve number is 15% and the distance from the waterway is 15%. The effect was among the investigated parameters. The maps extracted from the two fuzzy AHP and VIKOR methods were determined by using the EVI, NDVI and SAVI spectral indices. On the contrary, the SAVI index has shown the percentage of flooding in high-risk areas with a low estimate, but the NDVI index has shown more accurate results of locating the flood-prone areas of the basin. By summarizing the obtained results, it can be stated that the evaluation of the flood risk maps of the Rakat watershed based on the Vikor model and fuzzy AHP shows the highest agreement with an accuracy of about 68% compared to the Vikor model map with an accuracy of about 40%. with the basic information of the region compared to other models and it is suggested as the optimal model in this region. Finally, the final flood risk map of the basin was located using the fuzzy AHP method, the high risk flood prone areas exactly according to the hydrographic network of the basin, it can be considered the reason for the superiority of this method over the VIKOR method.

Floods is one of the common unavoidable problems which have been causing problems and threatning to the people of Digaru and its adjoining areas from time to time. Flood hazards are one of the alarming phenomena in the region. During every rainy season the river overtops its bank and inundates the adjoining areas. Though Digaru and its catchment experiences flood almost every year, flood management policies are not adequate or mostly based on structural options including flood walls, dykes, embankments etc. Natural disasters have their greatest impact at local level especially on the lives of ordinary people. Current disasters are becoming more complex and the damages caused by the natural disaster at community level in Digaru catchment has increased exponentially in the past 20 years, despite the great efforts that the Government, NGO's and Local Communities have put into many disaster prevention programes. The objective of this paper is to assess flood hazard in Digaru and its catchment areas for the historical flood events using GIS approach and comprehend flood hazard management strategies for landuse planning. The database & methodology are Base mapping, topographic mapping and post-disaster verification of mapped floodplain extents and depths by DEM model using analogue maps through GIS approach. All possible combination of flood hazard maps are prepared using landcover, geomorphology and elevation heights for flood affected frequency and flood water depth of different flood seasons. The study related to natural hazards is a very new research in Arunachal Pradesh context that's too in the district of Lohit. The study area falls under a very strategic location i.e. Tidding thrust in the northern side and Mishmi thrust in the south-eastern side that makes the region geologically very fragile. This research work is a humble beginning where as researcher i will try to comprehend flood hazard management strategies for landuse planning decision proposed for the efficient management of future flood disasters.

Haulage trucks and cross border traders cross through Beitbridge border post from landlocked countries such as Zimbabwe and Zambia for the sake of trading. Because of global warming, South Africa has lately been experiencing extreme weather patterns in the form of very high temperatures and heavy rainfall. Evidently, in 2013 traffic could not cross the Limpopo River because water was flowing above the bridge. For planning, its important to predict the likelihood of such events occurring in future. Extreme value models offer one way in which this can be achieved. This study identifies suitable distributions to model the annual maximum heights of Limpopo river at Beitbridge border post. Maximum likelihood method and the Bayesian approach are used for parameter estimation. The r -largest order statistics was also used in this dissertation. For goodness of fit, the probability and quantile-quantile plots are used. Finally return levels are calculated from these distributions. The dissertation has revealed that the 100 year return level is 6.759 metres using the maximum likelihood and Bayesian approaches to estimate parameters. Empirical results show that the Fréchet class of distributions fits well the flood heights data at Beitbridge border post. The dissertation contributes positively by informing stakeholders about the socioeconomic impacts that are brought by extreme flood heights for Limpopo river at Beitbridge border post.

Haulage trucks and cross border traders cross through Beitbridge border post from landlocked countries such as Zimbabwe and Zambia for the sake of trading. Because of global warming, South Africa has lately been experiencing extreme weather patterns in the form of very high temperatures and heavy rainfall. Evidently, in 2013 traffic could not cross the Limpopo River because water was flowing above the bridge. For planning, its important to predict the likelihood of such events occurring in future. Extreme value models offer one way in which this can be achieved. This study identifies suitable distributions to model the annual maximum heights of Limpopo river at Beitbridge border post. Maximum likelihood method and the Bayesian approach are used for parameter estimation. The r -largest order statistics was also used in this dissertation. For goodness of fit, the probability and quantile-quantile plots are used. Finally return levels are calculated from these distributions. The dissertation has revealed that the 100 year return level is 6.759 metres using the maximum likelihood and Bayesian approaches to estimate parameters. Empirical results show that the Fréchet class of distributions fits well the flood heights data at Beitbridge border post. The dissertation contributes positively by informing stakeholders about the socioeconomic impacts that are brought by extreme flood heights for Limpopo river at Beitbridge border post.

Natural disasters destroy valuable resources and are necessary to recognize so that appropriate strategies may be designed. In recent past, social networks are very good source to gather event specific information. This working notes paper is based on the task of Disaster Image Retrieval from Social Media dataset (DRISM), as a part of MediaEval, 2017. The Dataset of images and their relevant metadata is taken from various social networks including Twitter and Flicker. An ensemble approach is adopted in this paper where different visual and metadata features are integrated. Kernel Discriminant analysis using spectral regression is then used as dimensionality reduction technique. Mean Average Precision (MAP) at various cutoffs are reported in this paper.

Introduction

As the population continues to grow, the significance of boosting food production becomes increasingly evident. Consequently, it is imperative to find solutions to address water limitations and enhance food production in regions facing water scarcity. In this context, it is proposed to implement strategies that involve expanding cultivated areas and optimizing the utilization of available water resources, particularly in scenarios where irrigation is restricted. Successful water engineering projects necessitate precise estimation of plants' water requirements across various regions. The goal is to maximize the efficiency of water usage per unit volume to ensure optimal agricultural output. This study aims to explore fluctuations in the water requirements and hydromodule of crops within different cultivation patterns in selected regions of northwest Iran, in response to climatic variables.



Materials and Methods

The objective of this study is to evaluate the variations in plant water needs in cultivation patterns across different regions in northwest Iran, taking into account climatic parameters. Initially, meteorological data from stations in Tabriz, Kalibar, Parsabad, Germi, and Bukan were collected from the national meteorological organization.

Cultivation pattern of agricultural plants in the investigated stations was extracted from the Jihad Agricultural Organization of the respective province. Considering the vastness of the studied areas and the impossibility of detailed soil investigation, the soil of the areas was considered medium. According to Ministry of Energy researches, the irrigation efficiency for all the studied areas averagely was considered to 60%.

Subsequently, utilizing CROPWAT 8.0 software based on the FAO56 equation, factors such as evapotranspiration of grass (used as a reference plant), solar radiation, and effective rainfall were determined for the selected stations. The hydromodule, representing water requirements, was then calculated monthly for the desired cultivation patterns in the respective areas. Finally, employing the Weibull transformation coefficient, the irrigation hydromodule with various return periods was derived for the study region.



Results and Discussion

The results indicated that the average potential evapotranspiration of grass, serving as the reference plant, was calculated as 4.12, 3.03, 2.86, 3.32, and 3.86 mm per day for the Tabriz, Kalibar, Parsabad, Germi, and Bukan stations, respectively. Furthermore, the average irrigation hydromodule for these stations was determined as 0.73, 0.35, 0.6, 0.7, and 0.62 liters per second per hectare, respectively. Utilizing the linear variation function, the average irrigation hydromodule for return periods of 2, 5, 10, 25, 50, 100, and 200 years for the aforementioned stations were obtained as 0.813, 0.552, 0.707, and 0.721 liters per second per hectare, respectively. Similarly, using the exponential function, the corresponding values were extracted as 0.818, 0.632, 0.719, 1, and 0.73 liters per second per hectare, respectively. Specifically, for the Tabriz, Kalibar, Parsabad, Germi, and Bukan stations, the irrigation hydromodule values with a return period of 2 years, employing the linear function, were calculated as 0.742, 0.439, 0.622, 0.821, and 0.67 liters per second per hectare, and with the exponential function, they were determined as 0.74, 0.444, 0.618, 0.829, and 0.672 liters per second per hectare, respectively. Additionally, for these stations, with a return period of 200 years, using the linear function, the calculated irrigation hydromodule values were 0.851, 0.613, 0.754, 1.015, and 0.748 liters per second per hectare, while employing the exponential function, they were determined as 0.862, 0.749, 0.777, 1.1, and 0.762 liters per second per hectare, respectively.



Conclusion

The irrigation hydromodule values in the Tabriz station increased by 0.851 liters per second per hectare, which is equivalent to a 10.88 percent increase compared to the average. Similarly, in the Kalibar, Parsabad, Germi, and Bukan stations, the increases were 0.613, 0.754, 1.01, and 0.748 liters per second per hectare, respectively, representing increments of 8.44, 13.17, 38, 19.7, and 7.78 percent compared to the average. Utilizing the exponential changes function, when the return period was adjusted from 2 years to 200 years and the probability of occurrence was reduced, the irrigation hydromodule increased by 0.862 liters per second per hectare in the Tabriz station, which corresponds to a 12.23 percent increase relative to the average. Similarly, in the Kalibar, Parsabad, Germi, and Bukan stations, the increases were 0.749, 0.777, 1.1, and 0.762 liters per second per hectare, respectively, representing rises of 30.5, 15.82, 09, 27.04, and 9.04 percent compared to the average. Given the water scarcity in various regions of the country, it is recommended to use the minimum values of functions (linear or exponential) to estimate the irrigation hydromodule for different return periods. With respect to linear function changes, and considering that the irrigation hydromodule does not decrease significantly (around 20% on average) with an increase in the return period (up to 200 years), it is advisable to design and implement storage facilities, transfer systems, and water distribution networks in the studied plains with a low probability of occurrence (high return period). This approach minimizes the increase in costs and reduces risks during water transfer and distribution operations.

The study develops an integrated geospatial data-driven framework to map groundwater  potential in semi-arid Agra, addressing urbanization-induced stress on aquifers and the  limitations of ground-based assessments for regional planning. Using multicollinearityscreened factors—rainfall, elevation, slope, drainage, geology, LULC, and soil—the workflow  combines AHP-based multi-criteria weighting with machine learning techniques, converting  inputs into raster layers and validating outputs with groundwater well locations and waterlevel data. Rainfall emerged as the dominant predictor, contributing up to 75.17% in  Random Forest and 75% in Boosted Regression Tress feature importance, underscoring  monsoonal control on recharge. Model performance assessed via ROC-AUC showed RF  (81.6% pre-monsoon, 79.9% post-monsoon) and BRT (81.4%, 80.7%) substantially  outperform AHP (70.1%, 70.0%), indicating stronger discrimination from data-driven  learning. Spatially, high groundwater potential concentrates in the middle-eastern Agra  corridor between the Yamuna and Chambal rivers, reaching 32.93% areal extent in postmonsoon RF results, while southwestern and western tracts consistently remain very low to  low across all models. Seasonal groundwater-level analysis reveals post-monsoon depth  reduction—most pronounced in recharge-favorable zones—with observed ranges of 4.78–  50.7 m bgl (pre-monsoon) and 3.8–50.5 m bgl (post-monsoon). The hybrid MCDA–ML  framework offers a robust, scalable basis for groundwater zoning, guiding sustainable  extraction, recharge targeting, and urban-peri-urban water management.

Flood disaster is the most common disaster in Indonesia, flood events continue to increase and occur almost every year during the rainy season, on average caused by extreme rainfall above 100 mm, with the number of losses increasing every years, there are many factors that affect One of the causes of flooding is human activities resulting in changes in land use in the form of settlements and agricultural land. This paper aims to present a conceptual reference from the implementation results using software assistance, to determine the level of influence and dependent variables. The method used to assess the most influential factors on flood events, especially in the Ciliwung watershed, is by using Cross-Impact Matric Multiplication Applied to Classification (MICMAC). From the 11 contributing factors analyzed based on the Matrix of Direct Influence (MDI) and Matrix of Indirect Influence (MII) it is known that rainfall and distance from the river are the variables that have the most in...

Human impact on land use and land cover (LULC) significantly affects the local and global environment. Accelerating urbanization affects developing nations more than developed nations. Multispectral satellite imagery of 2001, 2011, and 2021 was utilized for urban area transformations due to anthropogenic activities in Assam's Goalpara district. LANDSAT datasets were categorized into four classes: urban areas, vegetation, water bodies, and vacant land. The classification's accuracy was validated using the Semi-Automatic Classification (SCP) tool, which analyzed urban growth in Goalpara District by examining proximity-based factors that influenced its development pattern. A hybrid simulation model, Artificial Neural Network (ANN), was utilized to predict the future urban sprawl for 2031 and 2041 the model validation involved comparing simulated results with the actual data. Predictions reveal 61.6 percent accuracy for the ANN algorithm and 41.8 percent for the Markov Chain algorithm. Urban areas will expand from 91.2sqkm in 2001 to approximately 333.52 sqkm by 2041. These findings highlight integrating remote sensing, GIS, and AI models for urban planning, providing highly accurate insights for effective decision-making.

Flood hazard mapping in the United States (US) is deeply tied to the National Flood Insurance Program (NFIP). Consequently, publicly available flood maps provide essential information for insurance purposes, but they do not necessarily provide relevant information for non-insurance aspects of flood risk management (FRM) such as public education and emergency planning. Recent calls for flood hazard maps that support a wider variety of FRM tasks highlight the need to deepen our understanding about the factors that make flood maps useful and understandable for local end users. In this study, social scientists and engineers explore opportunities for improving the utility and relevance of flood hazard maps through the co-production of maps responsive to end users' FRM needs. Specifically, two-dimensional flood modeling produced a set of baseline hazard maps for stakeholders of the Tijuana River valley, US, and Los Laureles Canyon in Tijuana, Mexico. Focus groups with natural resource managers, city planners, emergency managers, academia, nonprofit, and community leaders refined the baseline hazard maps by triggering additional modeling scenarios and map revisions. Several important end user preferences emerged, such as (1) legends that frame flood intensity both qualitatively and quantitatively, and (2) flood scenario descriptions that report flood magnitude in terms of rainfall, streamflow, and its relation to an historic event. Regarding desired hazard map content, end users' requests revealed general consistency with mapping needs reported in European studies and guidelines published in Australia. However, requested map content that is not commonly produced included (1) standing water depths following the flood, (2) the erosive potential of flowing water, and (3) pluvial flood hazards, or flooding caused directly by rainfall. We conclude that the relevance and utility of commonly produced flood hazard maps can be most improved by illustrating pluvial flood hazards and by using concrete reference points to describe flooding scenarios rather than exceedance probabilities or frequencies.

Nonstationary extreme value analysis (NEVA) can improve the statistical representation of observed flood peak distributions compared to stationary (ST) analysis, but management of flood risk relies on predictions of out-of-sample distributions for which NEVA has not been comprehensively evaluated. In this study, we apply split-sample testing to 1250 annual maximum discharge records in the United States and compare the predictive capabilities of NEVA relative to ST extreme value analysis using a log-Pearson Type III (LPIII) distribution. The parameters of the LPIII distribution in the ST and nonstationary (NS) models are estimated from the first half of each record using Bayesian inference. The second half of each record is reserved to evaluate the predictions under the ST and NS models. The NS model is applied for prediction by (1) extrapolating the trend of the NS model parameters throughout the evaluation period and (2) using the NS model parameter values at the end of the fitting period to predict with an updated ST model (uST). Our analysis shows that the ST predictions are preferred, overall. NS model parameter extrapolation is rarely preferred. However, if fitting period discharges are influenced by physical changes in the watershed, for example from anthropogenic activity, the uST model is strongly preferred relative to ST and NS predictions. The uST model is therefore recommended for evaluation of current flood risk in watersheds that have undergone physical changes. Supporting information includes a MATLAB V R program that estimates the (ST/NS/uST) LPIII parameters from annual peak discharge data through Bayesian inference.