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[EN] Floods greatly impact human settlements in flood risk areas, such as floodplains and coastal lowlands, following heavy rainfall. The Alto Guadalentin valley, an orogenic tectonic depression, experiences extreme flash floods and land subsidence due to groundwater withdrawal, rendering it one of Europe's fastest subsiding regions. In this study, we compared two 2D flood event models representing different land subsidence scenarios for 1992 and 2016. To determine the flooded area and water depth variations due to land subsidence, the Hydrologic Engineering Centre River Analysis System 2D (HEC-RAS 2D) model was used to simulate flood inundation by the Alto Guadalentin River and its tributaries. Synthetic aperture radar (SAR) satellite (ERS, ENVISAT, and Cosmo-SkyMED) images were employed, along with the interferometric SAR (InSAR) technique, to calculate the magnitude and spatial distribution of land subsidence. By analysing the accumulated subsidence distributions obtained from InSAR, the original topography of the valley in 1992 and 2016 was reconstructed. These digital surface models (DSMs) were then used to generate 2D hydraulic models, simulating flood scenarios in the unsteady mode. The results demonstrated significant changes in the water surface elevation over the 14-year period, with a 2.04 km2 increase in areas with water depths exceeding 0.7 m. These findings were utilized to create a flood risk map and assess the economic flood risk. The data highlight the crucial role of land subsidence in determining the inundation risk in the Alto Guadalentin valley, providing valuable insights for emergency management and civil protection against future potential flooding events.

Delineating a flood map is critical to perceive the potential risks of the event at diverse communities living both in urban and rural settings in Bangladesh A timely generated flood map can help determine the losses of properties calculate payment options from insurances and set up mitigation measures when required Application of satellite remote sensing RS and geographic information systems GIS are common these days to determine inundated areas and to calculate possible losses of economies at scale However challenges remain while considering the available options for collecting satellite imageries obtained during the monsoon season with more than 70 cloud coverages found in the data As a result active synthetic aperture radar SAR sensors are a better choice to utilize the data in delineating the inundated areas In doing so this scientific paper sets up a few objectives to 1 prepare a flood map of Bangladesh using SAR remote sensing data available from Sentinel 1 satellite and 2 generate the inundated maps using cloud based product i e Google Earth Engine GEE in categorizing flood affected districts of Bangladesh in 2020 Results have demonstrated that approximately 11 area of Bangladesh has been affected by the 2020 flood mainly located in the north central and north eastern part of the country Moreover the old Brahmaputra floodplain Tista floodplain lower Ganges River floodplain and Karataya Bangali floodplain have been severely affected by the flood Note that the GEE based automated processing systems adopted in this study have enhanced the computational time while obtaining freely available satellite data to generate mitigation strategies for the betterment of the communities suffered by the flood event 2022 King Abdulaziz University and Springer Nature Switzerland AG

Delineating a flood map is critical to perceive the potential risks of the event at diverse communities living both in urban and rural settings in Bangladesh A timely generated flood map can help determine the losses of properties calculate payment options from insurances and set up mitigation measures when required Application of satellite remote sensing RS and geographic information systems GIS are common these days to determine inundated areas and to calculate possible losses of economies at scale However challenges remain while considering the available options for collecting satellite imageries obtained during the monsoon season with more than 70 cloud coverages found in the data As a result active synthetic aperture radar SAR sensors are a better choice to utilize the data in delineating the inundated areas In doing so this scientific paper sets up a few objectives to 1 prepare a flood map of Bangladesh using SAR remote sensing data available from Sentinel 1 satellite and 2 generate the inundated maps using cloud based product i e Google Earth Engine GEE in categorizing flood affected districts of Bangladesh in 2020 Results have demonstrated that approximately 11 area of Bangladesh has been affected by the 2020 flood mainly located in the north central and north eastern part of the country Moreover the old Brahmaputra floodplain Tista floodplain lower Ganges River floodplain and Karataya Bangali floodplain have been severely affected by the flood Note that the GEE based automated processing systems adopted in this study have enhanced the computational time while obtaining freely available satellite data to generate mitigation strategies for the betterment of the communities suffered by the flood event 2022 King Abdulaziz University and Springer Nature Switzerland AG

Delineating a flood map is critical to perceive the potential risks of the event at diverse communities living both in urban and rural settings in Bangladesh A timely generated flood map can help determine the losses of properties calculate payment options from insurances and set up mitigation measures when required Application of satellite remote sensing RS and geographic information systems GIS are common these days to determine inundated areas and to calculate possible losses of economies at scale However challenges remain while considering the available options for collecting satellite imageries obtained during the monsoon season with more than 70 cloud coverages found in the data As a result active synthetic aperture radar SAR sensors are a better choice to utilize the data in delineating the inundated areas In doing so this scientific paper sets up a few objectives to 1 prepare a flood map of Bangladesh using SAR remote sensing data available from Sentinel 1 satellite and 2 generate the inundated maps using cloud based product i e Google Earth Engine GEE in categorizing flood affected districts of Bangladesh in 2020 Results have demonstrated that approximately 11 area of Bangladesh has been affected by the 2020 flood mainly located in the north central and north eastern part of the country Moreover the old Brahmaputra floodplain Tista floodplain lower Ganges River floodplain and Karataya Bangali floodplain have been severely affected by the flood Note that the GEE based automated processing systems adopted in this study have enhanced the computational time while obtaining freely available satellite data to generate mitigation strategies for the betterment of the communities suffered by the flood event 2022 King Abdulaziz University and Springer Nature Switzerland AG

Reservoirs can be viewed as sentinels of their catchments and a detailed monitoring of reservoir systems informs about biogeochemical and hydrological processes at the catchment scale. We developed a comprehensive online monitoring system at Rappbode reservoir, the largest drinking water reservoir in Germany, and its inflows. The Rappbode Reservoir Observatory comprises of a set of online-sensors for the measurement of physical, chemical, and biological variables and is complemented by a biweekly limnological sampling schedule. Measurement stations are deployed at the four major inflows into the system, at the outlets of all pre-reservoirs, as well as in the main reservoir. The newly installed monitoring system serves both scientific monitoring and process studies, as well as reservoir management. Particular emphasis is paid to the monitoring of short-term dynamics and many variables are measured at high temporal resolution. As an example, we quantitatively documented a flood event which mobilised high loads of dissolved organic carbon and changed the characteristics of the receiving reservoir from eutrophic to dystrophic within a few days. This event could have been completely missed by conventional biweekly sampling programs, but is relevant for biogeochemical fluxes at the catchment scale. We also show that the high frequency data provide a deeper insight into ecosystem dynamics and lake metabolism. The Rappbode Reservoir Observatory; moreover, offers a unique study site to apply, validate, and develop state of the art lake models to improve their predictive capabilities.

Purpose The presented study investigated on contamination of suspended particulate matter (SPM) in rivers that was sampled long-term and with higher frequency during a flood event at the river Rhine. It was conducted to determine in vitro biological effects as well as to identify and quantify compound classes and effective contaminants. Research was part of investigation on hazards of contaminants bound to SPM to inundated sites and retention areas that are inundated during flood events. Material and methods SPM was sampled in 2006 and more frequently in a flood event (August, 2007) at the river Rhine barrage of Iffezheim, Germany. SPM was GC-MS analyzed for hexachlorobenzene (HCB), several polychlorinated biphenyls (PCBs) as well as for polycyclic aromatic hydrocarbons (PAHs). Flood samples were fractionated applying a recently developed automated fractionation method to receive further insight into contaminant loads in flood SPM. Impacts on biological scale were assessed using in vitro biotests for xenometabolic 7-ethoxyresorufin-o-deethylase (EROD) assay as well as for mutagenic activity (Ames fluctuation assay). EROD induction was calculated as biological equivalent concentrations (bio-TEQs) and mutagenic potentials were shown as NOECs and maximum induction factors. Results and discussion Chemical analysis gave low concentrations of PCBs (2006 and 2007) and HCB (2006). HCB concentrations increased during the flood in 2007 (maximum, 110 µg/kg SPM). Concentrations of PCBs were only initially elevated in the flood (maximum, 67 µg/kg SPM). EROD induction bio-TEQs ranged from 1,160 to 6,640 pg/g SPM in 2006 and showed maximum bio-TEQ at the peak discharge in 2007. There was no mutagenic activity with SPM of both years. Fractionation indicated highest EROD induction in PAH fractions with prioritized (EPA-) PAHs contributing to less than 1% to the fractions total bio-TEQ but also fractions containing more polar-to-polar substances were shown to contribute minor. Furthe

Diversification of flood risk management strategies can be seen as a necessary but not sufficient precondition for enhancing societal resilience to floods. This chapter identifies three relevant capacities of resilience: the capacity to resist flooding, the capacity to absorb/recover when a flood event occurs and the capacity to adapt to future risks and transform deliberately. These are to be seen as different views on desired outcomes for flood risk governance and have been found to be to some extent mutually exclusive. Resilience is closely linked to the notion of appropriateness: desired outcomes in terms of resilience should be considered in the light of physical circumstances and existing institutional and social contexts. The presence of links between strategies is crucial for countries’ achievements in all three capacities. The chapter goes on to review two other evaluation criteria for flood risk governance: efficiency and legitimacy. Efforts to improve resource efficiency by increased application of (societal) Cost Benefit Analyses are underway in different countries, albeit to a different extent. These CBAs were found to contribute to resource efficiency, but in some countries were perceived as rather technocratic. In terms of legitimacy, the researched countries are doing well on access to information and transparency; procedural justice and accountability. The most potential for improvement lies with the criteria of social equity; public participation and acceptability.

The importance of heterotrophic bacteria relative to phytoplankton in the uptake of ammonium and nitrate was studied in Mediterranean coastal waters (Thau Lagoon) during autumn, when the Mediterranean Sea received the greatest allochthonous nutrient loads. Specific inhibitors and size-fractionation methods were used in combination with isotopic N-15 tracers. NO3 (-) and NH4 (+) uptake was dominated by phytoplankton (60 % on average) during the study period, which included a flood event. Despite lower biomass specific NH4 (+) and NO3 uptake rates, free-living heterotrophic bacteria contributed significantly (> 30 %) to total microbial NH4 (+) and NO3 (-) uptake rates in low chlorophyll waters. Under these conditions, heterotrophic bacteria may be responsible for more than 50 % of primary production, using very little freshly produced phytoplankton exudates. In low chlorophyll coastal waters as reported during the present 3-month study, the heterotrophic bacteria seemed to depend to a greater extent on allochthonous N and C substrates than on autochthonous substrates derived from phytoplankton.

The importance of heterotrophic bacteria relative to phytoplankton in the uptake of ammonium and nitrate was studied in Mediterranean coastal waters (Thau Lagoon) during autumn, when the Mediterranean Sea received the greatest allochthonous nutrient loads. Specific inhibitors and size-fractionation methods were used in combination with isotopic N-15 tracers. NO3 (-) and NH4 (+) uptake was dominated by phytoplankton (60 % on average) during the study period, which included a flood event. Despite lower biomass specific NH4 (+) and NO3 uptake rates, free-living heterotrophic bacteria contributed significantly (> 30 %) to total microbial NH4 (+) and NO3 (-) uptake rates in low chlorophyll waters. Under these conditions, heterotrophic bacteria may be responsible for more than 50 % of primary production, using very little freshly produced phytoplankton exudates. In low chlorophyll coastal waters as reported during the present 3-month study, the heterotrophic bacteria seemed to depend to a greater extent on allochthonous N and C substrates than on autochthonous substrates derived from phytoplankton.

The importance of heterotrophic bacteria relative to phytoplankton in the uptake of ammonium and nitrate was studied in Mediterranean coastal waters (Thau Lagoon) during autumn, when the Mediterranean Sea received the greatest allochthonous nutrient loads. Specific inhibitors and size-fractionation methods were used in combination with isotopic N-15 tracers. NO3 (-) and NH4 (+) uptake was dominated by phytoplankton (60 % on average) during the study period, which included a flood event. Despite lower biomass specific NH4 (+) and NO3 uptake rates, free-living heterotrophic bacteria contributed significantly (> 30 %) to total microbial NH4 (+) and NO3 (-) uptake rates in low chlorophyll waters. Under these conditions, heterotrophic bacteria may be responsible for more than 50 % of primary production, using very little freshly produced phytoplankton exudates. In low chlorophyll coastal waters as reported during the present 3-month study, the heterotrophic bacteria seemed to depend to a greater extent on allochthonous N and C substrates than on autochthonous substrates derived from phytoplankton.

Land use and land cover (LULC) change results in increased of flood frequency and severity. The increase of annual runoff which is caused by urban development, heavy deforestation, or other anthropogenic activities occurs within the catchment areas. Therefore, accurate and continuous LULC change information is vital in quantifying flood hydrograph for any given time. Many studies showed the effect of land use change on flood based on hydrological response (i.e., peak discharge and runoff volume). In this study, a distributed hydrological modeling and GIS approach were applied for the assessment of land use impact in the Kelantan Basin. The assessment focuses on the runoff contributions from different land use classes and the potential impact of land use changes on runoff generation. The results showed that the direct runoff from developmental area, agricultural area, and grassland region is dominant for a flood event compared with runoff from other land-covered areas in the study area. The urban areas or lower planting density areas tend to increase for runoff and for the monsoon season floods, whereas the inter-flow from forested and secondary jungle areas contributes to the normal flow.

On November 25, 2009, heavy amount of rainfall precipitated in the city of Jeddah that led to floods causing unexpected loss of life (113 person died), and damaged public and private properties (10,000 cars were damaged/destroyed, and many houses, roads, highways, and industrial properties were also affected). The city of Jeddah is located within an independent mega drainage basin with a surface area of 1,760 km2. This mega basin is divided into three major sub-basins (northern, middle, and southern). Wadi Qus is located in the southern sub-basin with an area of ~63 km2. It passes through many of the neighborhoods such as Al-Harazat, Al-Sawaid, Queza, Al-Mesaid, Al-Haramin Highway, and the King Abdel Aziz University. These areas were severely damaged during the flash flood event in 2009. The current study deals with the determination of the best sites for the construction of flood control dams, followed by a number of detailed studies to ensure that these selected sites are appropriate. Geological, geotechnical, geophysical, and hydrological investigations were conducted to identify the types of rocks, the subsurface conditions, and the geotechnical properties of abutment and subsurface of soil and rock in the dam sites. The study found that there are three locations that can be appropriate for the construction of the flood control dams at Wadi Qus. Hydrological studies indicated that the runoff volumes for sub-basins B1, B2, and B3 are 2,102,709, 1,023,156, and 4,868,304 m3, respectively, for 500-year return period and 2,356,081, 1,149,687, and 5,451,123 m3, respectively, for 1,000-year return period. Comparing these values with the reservoir volumes calculated from the detailed ground survey with different dam’s height, it was found that dam’s heights of 15.5, 11.5, and 13.5 m for dams Q01, Q02, and Q03, respectively, are adequate for different basin volumes for 1,000-year return periods. Finally, the conceptual designs have been prepared and recommended for these

On November 25, 2009, heavy amount of rainfall precipitated in the city of Jeddah that led to floods causing unexpected loss of life (113 person died), and damaged public and private properties (10,000 cars were damaged/destroyed, and many houses, roads, highways, and industrial properties were also affected). The city of Jeddah is located within an independent mega drainage basin with a surface area of 1,760 km2. This mega basin is divided into three major sub-basins (northern, middle, and southern). Wadi Qus is located in the southern sub-basin with an area of ~63 km2. It passes through many of the neighborhoods such as Al-Harazat, Al-Sawaid, Queza, Al-Mesaid, Al-Haramin Highway, and the King Abdel Aziz University. These areas were severely damaged during the flash flood event in 2009. The current study deals with the determination of the best sites for the construction of flood control dams, followed by a number of detailed studies to ensure that these selected sites are appropriate. Geological, geotechnical, geophysical, and hydrological investigations were conducted to identify the types of rocks, the subsurface conditions, and the geotechnical properties of abutment and subsurface of soil and rock in the dam sites. The study found that there are three locations that can be appropriate for the construction of the flood control dams at Wadi Qus. Hydrological studies indicated that the runoff volumes for sub-basins B1, B2, and B3 are 2,102,709, 1,023,156, and 4,868,304 m3, respectively, for 500-year return period and 2,356,081, 1,149,687, and 5,451,123 m3, respectively, for 1,000-year return period. Comparing these values with the reservoir volumes calculated from the detailed ground survey with different dam’s height, it was found that dam’s heights of 15.5, 11.5, and 13.5 m for dams Q01, Q02, and Q03, respectively, are adequate for different basin volumes for 1,000-year return periods. Finally, the conceptual designs have been prepared and recommended for these

Land use and land cover (LULC) change results in increased of flood frequency and severity. The increase of annual runoff which is caused by urban development, heavy deforestation, or other anthropogenic activities occurs within the catchment areas. Therefore, accurate and continuous LULC change information is vital in quantifying flood hydrograph for any given time. Many studies showed the effect of land use change on flood based on hydrological response (i.e., peak discharge and runoff volume). In this study, a distributed hydrological modeling and GIS approach were applied for the assessment of land use impact in the Kelantan Basin. The assessment focuses on the runoff contributions from different land use classes and the potential impact of land use changes on runoff generation. The results showed that the direct runoff from developmental area, agricultural area, and grassland region is dominant for a flood event compared with runoff from other land-covered areas in the study area. The urban areas or lower planting density areas tend to increase for runoff and for the monsoon season floods, whereas the inter-flow from forested and secondary jungle areas contributes to the normal flow.

The purpose of the present study was to assess the hazard potentials of contaminated suspended particulate matter (SPM) sampled during a flood event for floodplain soils using in vitro bioassays and chemical analysis. Sediment-contact tests were performed to evaluate the direct exposure of organisms to native soils and SPM at two different trophic levels. For comparison, acetonic extracts were tested using both contact tests and additionally two cell-based biotests for cytotoxicity and Ah receptor-mediated activity (EROD-Assay). The sediment-contact tests were carried out with the dehydrogenase assay with Arthrobacter globiformis and the fish embryo assay with Danio rerio. The results of this study clearly document that native samples may well be significantly more effective than corresponding extracts in the bacteria contact assay or the fish embryo test. These results question the commonly accepted concept that acetonic extracts are likely to overestimate the toxicity of soil and SPM samples. Likewise, the priority organic compounds analyzed failed to fully explain the toxic potential of the samples. The outcomes of this study revealed the insufficient knowledge regarding the relationship between the different exposure pathways. Finally, there is concern about adverse effects by settling suspended particulate matter and remobilized sediments in frequently inundated floodplain soils due to an increase of the hazard potential, if compared with infrequently inundated floodplain soils. We showed that the settling of SPM and sediments revealed a significant impact on the dioxin-like potencies of riparian soils.

Flood hazard is expected to increase in the context of global warming. However, long time-series of climate and gauge data at high-elevation are too sparse to assess reliably the rate of recurrence of such events in mountain areas. Here paleolimnological techniques were used to assess the evolution of frequency and magnitude of flash flood events in the North-western European Alps since the Little Ice Age (LIA). The aim was to document a possible effect of the post-19(th) century global warming on torrential floods frequency and magnitude. Altogether 56 flood deposits were detected from grain size and geochemical measurements performed on gravity cores taken in the proglacial Lake Blanc (2170 m a.s.l., Belledonne Massif, NW French Alps). The age model relies on radiometric dating (Cs-137 and Am-241), historic lead contamination and the correlation of major flood- and earthquake-triggered deposits, with recognized occurrences in historical written archives. The resulting flood calendar spans the last ca 270 years (AD 1740-AD 2007). The magnitude of flood events was inferred from the accumulated sediment mass per flood event and compared with reconstructed or homogenized datasets of precipitation, temperature and glacier variations. Whereas the decennial flood frequency seems to be independent of seasonal precipitation, a relationship with summer temperature fluctuations can be observed at decadal timescales. Most of the extreme flood events took place since the beginning of the 20(th) century with the strongest occurring in 2005. Our record thus suggests climate warming is favouring the occurrence of high magnitude torrential flood events in high-altitude catchments.

Flood hazard is expected to increase in the context of global warming. However, long time-series of climate and gauge data at high-elevation are too sparse to assess reliably the rate of recurrence of such events in mountain areas. Here paleolimnological techniques were used to assess the evolution of frequency and magnitude of flash flood events in the North-western European Alps since the Little Ice Age (LIA). The aim was to document a possible effect of the post-19(th) century global warming on torrential floods frequency and magnitude. Altogether 56 flood deposits were detected from grain size and geochemical measurements performed on gravity cores taken in the proglacial Lake Blanc (2170 m a.s.l., Belledonne Massif, NW French Alps). The age model relies on radiometric dating (Cs-137 and Am-241), historic lead contamination and the correlation of major flood- and earthquake-triggered deposits, with recognized occurrences in historical written archives. The resulting flood calendar spans the last ca 270 years (AD 1740-AD 2007). The magnitude of flood events was inferred from the accumulated sediment mass per flood event and compared with reconstructed or homogenized datasets of precipitation, temperature and glacier variations. Whereas the decennial flood frequency seems to be independent of seasonal precipitation, a relationship with summer temperature fluctuations can be observed at decadal timescales. Most of the extreme flood events took place since the beginning of the 20(th) century with the strongest occurring in 2005. Our record thus suggests climate warming is favouring the occurrence of high magnitude torrential flood events in high-altitude catchments.

Flood hazard is expected to increase in the context of global warming. However, long time-series of climate and gauge data at high-elevation are too sparse to assess reliably the rate of recurrence of such events in mountain areas. Here paleolimnological techniques were used to assess the evolution of frequency and magnitude of flash flood events in the North-western European Alps since the Little Ice Age (LIA). The aim was to document a possible effect of the post-19(th) century global warming on torrential floods frequency and magnitude. Altogether 56 flood deposits were detected from grain size and geochemical measurements performed on gravity cores taken in the proglacial Lake Blanc (2170 m a.s.l., Belledonne Massif, NW French Alps). The age model relies on radiometric dating (Cs-137 and Am-241), historic lead contamination and the correlation of major flood- and earthquake-triggered deposits, with recognized occurrences in historical written archives. The resulting flood calendar spans the last ca 270 years (AD 1740-AD 2007). The magnitude of flood events was inferred from the accumulated sediment mass per flood event and compared with reconstructed or homogenized datasets of precipitation, temperature and glacier variations. Whereas the decennial flood frequency seems to be independent of seasonal precipitation, a relationship with summer temperature fluctuations can be observed at decadal timescales. Most of the extreme flood events took place since the beginning of the 20(th) century with the strongest occurring in 2005. Our record thus suggests climate warming is favouring the occurrence of high magnitude torrential flood events in high-altitude catchments.

Spring snowmelt in the arctic and boreal regions represents the most significant event in the hydrological year. We measured concentrations and fluxes of different carbon species in 2 small contrasting (control v drained) forested peatland catchments in E. Finland between April and June 2008 and compared these to long-term annual fluxes. Measurements were made using a combination of continuous sensors (CO2, temperature, pH, discharge) and routine spot sampling (DOC, POC, DIC, CO2, CH4, N2O). The highest concentrations of CO2 and CH4 in streamwater were observed under low flow conditions before the spring flood event,reflecting accumulation and downstream release of gaseous C at the end of the winter period. Over the length of the study mean CH4 concentrations were 10x higher in the drained site. The snowmelt event was associated with a dilution of DOC and CO2, with the drained catchment showing a much flashier hydrological response compared to the control site, and post-event, a slower recovery in DOC and CO2 concentrations. Fluxes of all carbon species during the snowmelt event were significant and represented 37–45% of the annual flux. This highlights the challenge of quantifying aquatic C fluxes in areas with large temporal variability and suggests that inability to ‘‘capture’’ the spring snowmelt event may lead to under-estimation of C fluxes in northern regions.

Spring snowmelt in the arctic and boreal regions represents the most significant event in the hydrological year. We measured concentrations and fluxes of different carbon species in 2 small contrasting (control v drained) forested peatland catchments in E. Finland between April and June 2008 and compared these to long-term annual fluxes. Measurements were made using a combination of continuous sensors (CO2, temperature, pH, discharge) and routine spot sampling (DOC, POC, DIC, CO2, CH4, N2O). The highest concentrations of CO2 and CH4 in streamwater were observed under low flow conditions before the spring flood event,reflecting accumulation and downstream release of gaseous C at the end of the winter period. Over the length of the study mean CH4 concentrations were 10x higher in the drained site. The snowmelt event was associated with a dilution of DOC and CO2, with the drained catchment showing a much flashier hydrological response compared to the control site, and post-event, a slower recovery in DOC and CO2 concentrations. Fluxes of all carbon species during the snowmelt event were significant and represented 37–45% of the annual flux. This highlights the challenge of quantifying aquatic C fluxes in areas with large temporal variability and suggests that inability to ‘‘capture’’ the spring snowmelt event may lead to under-estimation of C fluxes in northern regions.

Floods are a common feature in rapidly urbanizing Dhaka and its adjoining areas. Though Greater Dhaka experiences flood almost in every year, flood management policies are mostly based on structural options including flood walls, dykes, embankments etc. Many shortcomings of the existing flood management systems are reported in numerous literatures. The objective of this paper is to assess flood hazard in Greater Dhaka for the historical flood event of 1998 using Synthetic Aperture Radar (SAR) data with GIS data. Flood-affected frequency and flood depth calculated from the multi-date SAR imageries were used as hydrologic parameters. Elevation heights, land cover classification,geomorphic division and drainage network data generated from optical remote sensing and analogue maps were used through GIS approach. Using a ranking matrix in three dimensional multiplication mode, flood hazard was assessed.All possible combination of flood hazard maps was prepared using land-cover, geomorphology and elevation heights for flood-affected frequency and floodwater depth. Using two hazard maps which produced the highest congruence for flood frequency and flood depth, a new flood hazard map was developed by considering the interactive effect of flood-affected frequency and floodwater depth, simultaneously. This new hazard map can provide more safety for flood countermeasures because pixels belonging to higher hazard degrees were increased due to the consideration of higher degrees of ranks. The estimation of flood hazard areas revealed that a major portion of Greater Dhaka comprised moderate to very high hazard zone. Only a little portion (8.04%) was found to be the least vulnerable to potential flood hazard. Conversely, 28.70% of Greater Dhaka was found within very high hazard zone. Based on this study, comprehensive flood hazard management strategies for land use planning decision were proposed for the efficient management of future flood disasters.

Flood events cause substantial damage to urban and rural areas. Monitoring water extent during large-scale flooding is crucial in order to identify the area affected and to evaluate damage. During such events, spatial assessments of floodwater may be derived from satellite or airborne sensing platforms. Meanwhile, an increasing availability of smartphones is leading to documentation of flood events directly by individuals, with information shared in real-time using social media. Topographic data, which can be used to determine where floodwater can accumulate, are now often available from national mapping or governmental repositories. In this work, we present and evaluate a method for rapidly estimating flood inundation extent based on a model that fuses remote sensing, social media and topographic data sources. Using geotagged photographs sourced from social media, optical remote sensing and high-resolution terrain mapping, we develop a Bayesian statistical model to estimate the probability of flood inundation through weights-of-evidence analysis. Our experiments were conducted using data collected during the 2014 UK flood event and focus on the Oxford city and surrounding areas. Using the proposed technique, predictions of inundation were evaluated against ground-truth flood extent. The results report on the quantitative accuracy of the multisource mapping process, which obtained area under receiver operating curve values of 0.95 and 0.93 for model fitting and testing, respectively.

Flood events cause substantial damage to urban and rural areas. Monitoring water extent during large-scale flooding is crucial in order to identify the area affected and to evaluate damage. During such events, spatial assessments of floodwater may be derived from satellite or airborne sensing platforms. Meanwhile, an increasing availability of smartphones is leading to documentation of flood events directly by individuals, with information shared in real-time using social media. Topographic data, which can be used to determine where floodwater can accumulate, are now often available from national mapping or governmental repositories. In this work, we present and evaluate a method for rapidly estimating flood inundation extent based on a model that fuses remote sensing, social media and topographic data sources. Using geotagged photographs sourced from social media, optical remote sensing and high-resolution terrain mapping, we develop a Bayesian statistical model to estimate the probability of flood inundation through weights-of-evidence analysis. Our experiments were conducted using data collected during the 2014 UK flood event and focus on the Oxford city and surrounding areas. Using the proposed technique, predictions of inundation were evaluated against ground-truth flood extent. The results report on the quantitative accuracy of the multisource mapping process, which obtained area under receiver operating curve values of 0.95 and 0.93 for model fitting and testing, respectively.

An episode of extreme monsoonal flood event has severely affected the East and West coast of Peninsular Malaysia from 16th to 18th December 2021. The extreme rainfall was documented to be associated to Tropical Depression 29 and Typhoon Rai. In addition, biomass burning aerosols were suspected to be capable of intensifying the precipitation. Thus, the main causes of this extreme event are studied with model evaluation being carried out with biomass burning as one of the possible reasons and variables. From the sensitivity analysis on the PBL scheme for the model physics, QNSE scheme is tested to be the best scheme to simulate the episode compared with MYJ and ACM2 and used in the model assessment. The performances of ARW (WRF-ARW), BB (WRF-Chem with biomass burning), and NOBB (WRF-Chem without biomass burning) have been assessed in the reproduction of the precipitation pattern and tropical depression. Simulation results indicate that ARW shows an overall better performance for most meteorological variables with better performance in reproducing the surface-level pressure and wind speed. Model scenarios of ARW and BB produced similar tropical depression spatial distributions but differ in magnitude, where the tropical depression in ARW is stronger during the study period over East coastline. All models overestimate the precipitation intensity, but ARW is much better correlated with observation data followed by NOBB and BB. The findings show that biomass burning aerosols have only a minor impact on intensifying or delaying the rainfall event. Therefore, tropical depression over Peninsular Malaysia is shown to be the main causation to this extreme event in 2021. The model could be applied for the future flood risk management in Malaysia to provide information on decision making.

This paper presents a first estimate of the exposure of the world’s large port cities (population exceeding one million inhabitants in 2005) to coastal flooding due to sea-level rise and storm surge now and in the 2070s, taking into account scenarios of socio-economic and climate changes. The analysis suggests that about 40 million people (0.6% of the global population or roughly 1 in 10 of the total port city population in the cities considered) are currently exposed to a 1 in 100 year coastal flood event. For assets, the total value exposed in 2005 across all cities considered is estimated to be US$3,000 billion; corresponding to around 5% of global GDP in 2005 (both measured in international USD) with USA, Japan and the Netherlands being the countries with the highest values. By the 2070s, total population exposed could grow more than threefold due to the combined effects of sea-level rise, subsidence, population growth and urbanisation with asset exposure increasing to more than ten times current levels or approximately 9% of projected global GDP in this period. On the global-scale, population growth, socio-economic growth and urbanization are the most important drivers of the overall increase in exposure particularly in developing countries, as low-lying areas are urbanized. Climate change and subsidence can significantly exacerbate this increase in exposure. Exposure is concentrated in a few cities: collectively Asia dominates population exposure now and in the future and also dominates asset exposure by the 2070s. Importantly, even if the environmental or socio-economic changes were smaller than assumed here the underlying trends would remain. This research shows the high potential benefits from risk-reduction planning and policies at the city scale to address the issues raised by the possible growth in exposure.

Managing risks from extreme events will be a crucial component of climate change adaptation. In this study, we demonstrate an approach to assess future risks and quantify the benefits of adaptation options at a city-scale, with application to flood risk in Mumbai. In 2005, Mumbai experienced unprecedented flooding, causing direct economic damages estimated at almost two billion USD and 500 fatalities. Our findings suggest that by the 2080s, in a SRES A2 scenario, an 'upper bound' climate scenario could see the likelihood of a 2005-like event more than double. We estimate that total losses (direct plus indirect) associated with a 1-in-100 year event could triple compared with current situation (to $690-$1,890 million USD), due to climate change alone. Continued rapid urbanisation could further increase the risk level. The analysis also demonstrates that adaptation could significantly reduce future losses; for example, estimates suggest that by improving the drainage system in Mumbai, losses associated with a 1-in-100 year flood event today could be reduced by as much as 70%.,We show that assessing the indirect costs of extreme events is an important component of an adaptation assessment, both in ensuring the analysis captures the full economic benefits of adaptation and also identifying options that can help to manage indirect risks of disasters. For example, we show that by extending insurance to 100% penetration, the indirect effects of flooding could be almost halved. We conclude that, while this study explores only the upper-bound climate scenario, the risk-assessment core demonstrated in this study could form an important quantitative tool in developing city-scale adaptation strategies. We provide a discussion of sources of uncertainty and risk-based tools could be linked with decision-making approaches to inform adaptation plans that are robust to climate change.

Flood events cause substantial damage to urban and rural areas. Monitoring water extent during large-scale flooding is crucial in order to identify the area affected and to evaluate damage. During such events, spatial assessments of floodwater may be derived from satellite or airborne sensing platforms. Meanwhile, an increasing availability of smartphones is leading to documentation of flood events directly by individuals, with information shared in real-time using social media. Topographic data, which can be used to determine where floodwater can accumulate, are now often available from national mapping or governmental repositories. In this work, we present and evaluate a method for rapidly estimating flood inundation extent based on a model that fuses remote sensing, social media and topographic data sources. Using geotagged photographs sourced from social media, optical remote sensing and high-resolution terrain mapping, we develop a Bayesian statistical model to estimate the probability of flood inundation through weights-of-evidence analysis. Our experiments were conducted using data collected during the 2014 UK flood event and focus on the Oxford city and surrounding areas. Using the proposed technique, predictions of inundation were evaluated against ground-truth flood extent. The results report on the quantitative accuracy of the multisource mapping process, which obtained area under receiver operating curve values of 0.95 and 0.93 for model fitting and testing, respectively.

Flood events cause substantial damage to urban and rural areas. Monitoring water extent during large-scale flooding is crucial in order to identify the area affected and to evaluate damage. During such events, spatial assessments of floodwater may be derived from satellite or airborne sensing platforms. Meanwhile, an increasing availability of smartphones is leading to documentation of flood events directly by individuals, with information shared in real-time using social media. Topographic data, which can be used to determine where floodwater can accumulate, are now often available from national mapping or governmental repositories. In this work, we present and evaluate a method for rapidly estimating flood inundation extent based on a model that fuses remote sensing, social media and topographic data sources. Using geotagged photographs sourced from social media, optical remote sensing and high-resolution terrain mapping, we develop a Bayesian statistical model to estimate the probability of flood inundation through weights-of-evidence analysis. Our experiments were conducted using data collected during the 2014 UK flood event and focus on the Oxford city and surrounding areas. Using the proposed technique, predictions of inundation were evaluated against ground-truth flood extent. The results report on the quantitative accuracy of the multisource mapping process, which obtained area under receiver operating curve values of 0.95 and 0.93 for model fitting and testing, respectively.

Flood events cause substantial damage to urban and rural areas. Monitoring water extent during large-scale flooding is crucial in order to identify the area affected and to evaluate damage. During such events, spatial assessments of floodwater may be derived from satellite or airborne sensing platforms. Meanwhile, an increasing availability of smartphones is leading to documentation of flood events directly by individuals, with information shared in real-time using social media. Topographic data, which can be used to determine where floodwater can accumulate, are now often available from national mapping or governmental repositories. In this work, we present and evaluate a method for rapidly estimating flood inundation extent based on a model that fuses remote sensing, social media and topographic data sources. Using geotagged photographs sourced from social media, optical remote sensing and high-resolution terrain mapping, we develop a Bayesian statistical model to estimate the probability of flood inundation through weights-of-evidence analysis. Our experiments were conducted using data collected during the 2014 UK flood event and focus on the Oxford city and surrounding areas. Using the proposed technique, predictions of inundation were evaluated against ground-truth flood extent. The results report on the quantitative accuracy of the multisource mapping process, which obtained area under receiver operating curve values of 0.95 and 0.93 for model fitting and testing, respectively.