Flood Hazard Zones Research Articles

A GIS-based assessment of the potential soil erosion and flood hazard zones in Ekiti State, Southwestern Nigeria using integrated RUSLE and HAND models

Soil loss estimation and flood hazard mapping cannot be overemphasized due to their environmental, economic and societal concern. Thus, the main objective of this study was to assess the potential soil erosion and flood hazards zones using Revised Universal Soil Loss Equation (RUSLE) and Hand Above Nearest Drainage (HAND) models, respectively for appropriate conservation and prevention measures in Ekiti State, Southwestern Nigeria. The result reveals annual soil erosion ranges from 0 to 889 t ha−1 year−1. The estimated total annual soil loss in the state was around 1.5 million tonnes, of this, 193223.3 tonnes which covers 7508 ha was lost at a rate much greater than the tolerable soil loss rate. Soil erosion vulnerability mapping was done using six (6) categories of soil loss severity from slight to very severe. Soil erosion rates varied from 0.21 t ha−1 year−1 in forests to 1.69 t ha−1 year−1 under bare soils. The very steep slope category had the highest soil erosion rate of 15.07 t ha−1 year−1 while the gentle slope regions had the least soil erosion rate of 0.39 t ha−1 year−1. About 23% of the area which covers 115847.58 ha was prone to high flood hazard whereas 15.69% (80932.30 ha) was moderately susceptible to flood risk. Approximately 15% of the area was susceptible to low flood hazard zone while 44.90% were vulnerable to very low flood occurrence. LULC has significant effect on the spatial pattern of soil loss in the study area. Potential soil loss risk zones were highly related to the degree and inclination of slope. The reported results can serve as preliminary information to determine erosion and flood hotspots in the study area and as input for policy decision for disasters prevention and conservation measures.

Flood exposure analysis of road infrastructure – Comparison of different methods at national level

Assessing the flood exposure of infrastructure is crucial for sustainable flood risk management. We propose to define road exposure to floods as “any road segment/element located within a flood hazard zone”. On the example of Switzerland, we develop and compare three methods to assess the flood exposure of the road infrastructure: absolute road area potentially flooded (method A), relative road area potentially flooded (method B), and a network-based approach using the edge betweenness centrality index (method C). The results are aggregated and ranked in grid cells of 2 km by 2 km for comparison. The ranks are directly proportional to exposure levels. The results present distinct spatial patterns; grid cells with higher values in method A indicate where more road surfaces are in a flood hazard zone (urban or high road density areas in flood plains), while method B highlights where most of the road surface is in flood hazard zones of predominantly mountainous areas of Switzerland. Higher values in method C present areas where the most-connected road links within a network are exposed to floods. Most of the grid cells that have higher values in method B than in method C indicate isolated mountain valleys that can be accessed only by a single road exposed to floods. The study demonstrates the importance of an appropriate choice of methods in flood exposure analysis. As exposure analysis is a key step in flood risk assessment, the presented results provide information essential for decision making in disaster risk reduction.

Flood Hazard and Risk Assessment Due to Land Use Changes in Purbalingga, Indonesia

Purbalingga Regency is one of the regencies in Central Java Province that has rapid growing in economic and tourism in accordance with comprehensive urban planning. Land use changes is an important aspect of urban planning. Therefore, spatial analysis is needed to highlight the problem of flooding in Purbalingga Regency. Spatial analysis performed for flood risk is a spatial analysis based on flood hazard zoning and flood vulnerability. Flood hazard zoning and flood vulnerability analysis were conducted using Analytical Hierarchy Process (AHP) and Geographic Information System (GIS) for existing condition, regarding current data and projection condition presented in Purbalingga Urban Planning 2011-2031. Result of flood hazard zoning analysis showed that for existing condition, Purbalingga Regency is mostly considered into the medium category of hazard category with an area of 62,652.077 ha. On the other hand, referring urban planning projection data 2031, there is a decrease in categories of low, medium, and high, but increase in very high and extreme category. Risk assessment shows that Purbalingga Regency currently has an extreme category with an area of 11,080.047 ha, including the proposed location of Wirasaba Airport.

Place-Based Assessment of Intersection of Biophysical and Social Vulnerability to Flooding in Accra, Ghana

The relationship between flood hazards and social vulnerability is firmly on the intellectual agenda of geographers in Ghana. In an attempt to theorize and empirically examine this relationship, scholars have commonly followed a one-sided methodological strand. In this article, a triple-helix approach that relies on the application of social vulnerability index; mapping potential flood hazard zones; and examining degree of coincidence between flood hazards and social vulnerability, is used. Situating the analysis within Hazards-of-Place Model of Vulnerability, the study identifies spatial disparities in biophysical and social vulnerability within the City. It emerged that communities in the Ashiedu Keteke sub-metro were the most vulnerable based on the hazards-of-place model. Significantly, while flood risk awareness was very high among community members, the perception of flood risk management was poor. The study argues that understanding place-based vulnerability is crucial in mitigating the effect of hazards and building resilient communities.

Flood Plain Mapping and Hazard Assessment of Muga River by Using ArcGIS and HEC-RAS Model Upper Blue Nile Ethiopia

Flood happens repeatedly and is a common phenomenon in Ethiopia causing a lot of losses to human lives as well as damage to property. The majority of flood disasters’ victims are people living in and nearby stretch of floodplains. It results direct or indirect loss of agricultural productivity, infrastructure, and disruption of transportation access and services. The objective of this study was to analyze flood inundation area mapping and Hazard Assessment of Muga River. Flood generating factors, i.e. slope, elevation, rainfall, drainage density, land use, and soil type were rated and combined to delineate flood hazard zones using a multi-criteria evaluation technique in an ArcGIS environment. The flooded areas along the Muga River have been mapped based on highest flows for different return periods using the HEC-RAS model, ArcGIS for spatial data processing and HEC-GeoRAS for interfacing between HEC-RAS and ArcGIS. The areas along the Muga River simulated to be inundated for 5, 10, 25, 50 and 100 years return periods. The flooded areas along the Muga River are 18 km2, 21 km², 26 km², 34 km² and 43 km² for 5, 10, 25, 50 and 100 year return periods, respectively. Proper land use management and afforestation, is significant to reduce the adverse effects of flooding particularly in the low-lying flood prone areas. The result of this study will helps the concerned bodies to formulate develop strategies according to the available flood plain mapping and hazard to the area.

The Impact of Distant Hurricanes on Perception of Flood Risk in Local Housing Markets

This study investigates whether the local housing markets can be affected by the occurrence of a large-scale but distant hurricane without direct impact. Using a dataset of residential transactions in Miami-Dade County, FL between 2005 and 2014, we find that the impact of a property’s flood risk exposure on its value varies over time, with a price penalty of 4% in hurricane striking period. By contrast, within a quiet hurricane period, properties within high flood hazard zones demand a price premium ranging roughly from 4% to 6%, which may represent the price impact of water-related amenities. The premium declined significantly upon Hurricane Sandy. Several possible explanations are provided and tested to explain the main findings. Our findings indicate that the occurrence of a disastrous hurricane which impacted faraway regions also raised local home buyers’ perception of flood risk, but for a short period of time (one quarter).

A novel per pixel and object-based ensemble approach for flood susceptibility mapping

Conducting flood susceptibility assessments is critical for the identification of flood hazard zones and the mitigation of the detrimental impacts of floods in the future through improved flood management measures. The significance of this study is that we create ensemble methods using the per-pixel approaches of frequency ratio (FR), analytical hierarchical process (AHP), and evidence belief function (EBF) used for weightings with the object-based ‘geons’ approach used for aggregation to create a flood susceptibility map for the East Rapti Basin in Nepal. We selected eight flood conditioning factors considered to be relevant in the study area. The flood inventory data for the East Rapti basin was derived from past flood inventory datasets held in the regional database system by the International Centre for Integrated Mountain Development (ICIMOD). The flood inventory was classified into training and validation datasets based on the widely used split ratio of 70/30. The Receiver Operating Characteristic (ROC) was used to determine the accuracy of the flood susceptibility maps. The AUC results indicated that the combined per-pixel and object-based geon approaches yielded better results than the per-pixel approaches alone. Our results showed that the object-based geon approach creates meaningful regional units that are beneficial for future planning.

Prediction of flood hazard map based on hybrid fuzzy geographic information system and its application for Ayamama watershed

This research aims to bring a new methodology to early flood management and warning. It proposes modelling one of Istanbul watersheds, the Ayamama watershed in Istanbul, Turkey for possible flood hazard using a new fuzzy-geographical information system hybrid approach. It expands the domain of flood hazard early warning and management that usually uses conventional hydraulic and hydrology approaches to a newly developing area of artificial intelligence in flood early warning and management. The research opted for a more technical study using both GIS and MATLAB software to model the flood hazard levels in Ayamama watershed. The methodology takes into account three factors to model the flood hazard map. Elevation, Euclidian distance from Ayamama creek and local urbanisation degree are the chosen factors. Results on how to identify flood hazard were demonstrated by providing a map of flood hazard zones with their respective negative levels of impacts.

Potential flood hazard zone mapping based on geomorphologic considerations and fuzzy analytical hierarchy model in a data scarce West African basin

Fuzzy analytical hierarchy process (FAHP) was employed to map and rank flood hazard zones within the Northwest Benin Owena River Basin (NWBORB). Topographic wetness index, elevation, altitude above channel, slope, drainage density, convergence index, and runoff contributing to water accumulation/stagnation were processed to generate the flood hazard map of the basin. Values for the relative importance of each factor for flood occurrence were obtained using FAHP; these factors were super-imposed using weighted overlay. Sensitivity analysis of the weights was conducted to determine their influence on the overall analysis. The resultant flood hazard map was classified into five zones very high, high, moderate, low, and very low. Sensitivity analysis of the result showed that runoff and slope were the most sensitive factors in the analysis with values of 1.163 and 1.132, respectively. A comparison between flood hazard map and historical floods within the basin established the reliability of the methodology.

Integrated framework for flood relief package (FRP) allocation in semiarid region: a case of Rel River flood, Gujarat, India

Flash flood is disastrous; it losses property and life. Its effect is intensified while it occurs in semiarid region because of less preparedness. The present case conferred about a flash flood in semiarid region in Gujarat which was affected by flood in 2015 and 2017. Massive loss of lives and properties has been observed after the event. Now, recuperating the region against flood losses, it was a prime requirement to distribute the flood relief packages to the flood-susceptible areas. To identify the flood hazards and flood risk and assess the flood vulnerability in Rel River catchment, the region is divided into 52 micro-watersheds using RS and GIS techniques. The morphology of the Rel River catchments has been explored using the morphometric analysis. The priority rank and category for each micro-watershed were assigned based on compound factor values, whereas compound factor was calculated using weighted sum analysis techniques. Flood hazard zone map was prepared, and flood vulnerability has been characterized from very low to very high. Furthermore, the multi-criteria analysis was used to calculate the risk factor for the basin and AHP-MCE method was used to find the normalized weights of each factor (LU/LC, CF, soil, slope, drainage density) that were significant to the flood disaster. The integration of flood hazard map along with these parameters helped to understand the sensitivity of flash floods at different locations within the study area. Flood risk map was further analyzed at village level, and it has been identified that 17 out of 39 villages were at high risk, 12 villages were at moderate risk and 10 villages were at low risk. The study helped to clearly identify villages vulnerable to flood risk where more relief and flood insurance packages need to be allotted. Thus, the present method and integrated approach would be a useful tool for the decision maker to distribute the flood relief package in flash flood-prone area.

Let the Rich Be Flooded: The Unequal Impact of Hurricane Harvey on Household Debt

Outside of flood hazard zones, households must decide whether to insure or rely on disaster assistance to manage flood risk. We use the quasi-random flooding generated by Hurricane Harvey, which hit Houston in August 2017, to understand the implications of flood losses for households with differing access to insurance and credit. Outside the floodplain, credit-constrained homeowners experience a 20% increase in bankruptcies and a 13% increase in the share of debt in severe delinquency in flooded blocks relative to non-flooded areas. Treatment effects are universally insignificant inside the floodplain, implying that flood insurance mitigates the financial impact of flooding across the credit distribution. Disaster assistance, on the other hand, does not appear to counteract the role of initial inequalities on post-disaster credit outcomes. We find SBA disaster loans and, more surprisingly, FEMA grants to both be regressive in allocation. Our results highlight that averages mask important heterogeneity after disasters, which challenges existing narratives of how effectively Federal disaster programs mitigate the financial burden of natural disasters.

Evaluating urban growth and its implication on flood hazard and vulnerability in Srinagar city, Kashmir Valley, using geoinformatics

The present study investigates the urban growth in the Srinagar city of Kashmir Valley during 1972–2014 and the effect of 2014 Kashmir flood on the urban environment. Srinagar is the capital city in Kashmir Valley which has been affected by the devastating flood in 2014. The built-up growth for the past 42 years was 1565% with concomitant population growth of 224% in the Srinagar city. The built-up development was more pronounced in the central part of the city and along the river Jhelum during 1972–1989 which later on spread largely in the southernmost part of Srinagar city during the period of 1996–2014. High-Resolution Satellite (HRS) data-based observations indicated that 2014 flood inundation occupied 108 sq. km area within the Srinagar municipal limits. The increase of built-up inundation was monitored from 1972 to 2014, which reveals that the built-up inundation was 3.7 sq. km and increased to 39.2 sq. km. The spatial analysis revealed that nine wards located in the topographically low regions and in the proximity to Jhelum river were completely (100%) inundated during the flood. The past built-up inundation spatial analysis with reference to 2014 flood inundation indicated decrease in the percentage built-up area inundation (72.4% in 1972 to 46% in 2014) which reveals that the new built-up growth in the Srinagar city mostly occurred in the relatively safer zones. It is also observed that very high flood hazard and vulnerability zones were located in the western, southern, and central parts of the city in only 10 wards which rendered these wards with very high flood risk. The study demonstrated that geoinformatics-based spatial analysis of flood inundation can be effectively used for flood risk and related strategic planning.

Determination of Flood Hazard Zones Using Geographical Information Systems and Remote Sensing Techniques: A Case Study in Part Yenagoa Metropolis

Flood has been a serious hazard for the past decades in Nigeria at large. The incidence of 2012 and 2018 flood disaster in Yenagoa, Amassoma and other parts of the state have not been recover till date and the government is not consigned about the well been of the people. The major causes of the flood are attributed to increased rainfall and lack of drainages including dredging of rivers and disobeying of environmental law and infrastructure failure. Coastal Towns or communities are one of the most affected areas of flood and their farms and fishing implements were washed away by the floodwater in 2012 and 2018 in Bayelsa State. Flood management is needed for provision of time information so quick response can be done as soon as possible. Using SRTM data to produce digital elevation model and IDW Contour, the 3D model from ground data of Yenagoa metropolis using ArcGIS 10.6 to generate and analyze them. As a result of field survey, flood level calculation was made to classified flood hazard zones for migration, Agricultural Educational, and construction purpose such as land suitability. This was used in ascertaining the extent of the flooded area. The result reveals that an area of over 5.9888882km2 and riverine and coastal area is flooded, affecting more than 15 coastal and riverine communities. The finding also concludes that remote sensing data like SRTM data and Geospatial techniques seems effective in mapping and identifying areas prone to flooding. Therefore Remote sensing and Geospatial database should be established for proper flood mapping and the government should constantly dredge the area from time to time.

River basin-scale flood hazard assessment using a modified multi-criteria decision analysis approach: A case study

Flood is a major natural hazard with extremely large impact on social-ecological systems. Therefore, developing reliable and efficient tools to identify areas vulnerable to potential flooding is vital for water managers, engineers and decision makers. Moreover, being able to accurately classify the level of hazard is a step forward towards more efficient flood hazard mapping. This study presents a multi-criteria index approach to classify potential flood hazards at the river basin scale. The presented methodology was implemented in the Mashhad Plain basin in North-east Iran, where flood has been a major issue in the last few decades. In the present study, seven factors, selected based on their greater influence towards flooding, were identified and extracted from the basic thematic layers to be used to generate a five-class Flood Hazard Index (FHI) map. The Soil and Water Assessment Tool (SWAT) was used to develop a runoff coefficient map, which was found to be the most influential factor. A sensitivity analysis was performed and the results incorporated to generate a modified Flood Hazard Index (mFHI) map. The accuracy of the proposed method was evaluated against the well-documented flood records in the last 42 years at the study area. The results showed that, for both FHI and mFHI maps, more than 97% of historical flood events have occurred in moderate to very high flood hazard areas. This demonstrates that incorporating hydrological model (such as SWAT) and multi-criteria analysis introduces a robust methodology to generate comprehensive potential flood hazard maps. Moreover, the proposed modified methodology can be used to identify high potential flood hazard zones and work towards more efficient flood management and mitigation strategies.

Land subsidence in Houston correlated with flooding from Hurricane Harvey

Hurricane Harvey caused unprecedented flooding and socioeconomic devastation in Eastern Texas with high winds, elevated storm tide, and record rainfall. The flooded area is mapped using the radar backscattering difference between Sentinel-1A/B satellite acquisitions spanning the event, which provides a snapshot of standing water at the time of image acquisition. We find vast areas outside of designated flood hazard zones are overwhelmed. Furthermore, we map pre-cyclone land subsidence using multitemporal interferometric processing of large SAR datasets acquired by Advanced Land Observation Satellite (ALOS) and Sentinel-1A/B satellites. We find that subsidence of up to 49 mm/yr and 34 mm/yr during the ALOS (Jul-2007–Jan-2011) and Sentinel-1A/B (Dec-2015 to Aug-2017) acquisition periods affect various parts of Houston-Galveston area. We conclude that 85% of the flooded area subsided at a rate > 5 mm/yr. We suggest that subsidence affected flood severity by modifying base flood elevations and topographic gradients, supported by the Chi-square test of independence. This work highlights the importance of incorporating InSAR measurements of land subsidence in flood resilience strategies.

GIS digital mapping of flood hazard in Jeddah–Makkah region from morphometric analysis

Floods are considered to be one of the natural disasters that seriously affect people’s lives and property every year. Although, delineation and determination of hydrologic basins and their morphometric parameters are difficult morphological tasks, GIS-based approach simplifies the investigation of various morphometric factors and helps to explore the correlation between the drainage morphometry and landform properties. The present study is aimed to investigate the spatial distribution of drainage basins around Jeddah–Makkah region and its surrounding areas (nearly 40,247 km2) using GIS spatial analysis. The morphometric parameters of these drainage basins and their channel systems were estimated and calculated. The computed morphometric parameters are categorized into the following three main groups: linear, aerial, and relief features. The documentation of these parameters was, then, used to evaluate and construct flood hazard map of the region. Flood hazard map assesses five classes with varying degrees (very low, low, moderate, high, and very high) of flood hazard zones. Such hydrological hazard is mostly due to the basin’s area and its highest relief ratio, relative relief, and ruggedness factor. The flood hazard map shows that the city of Jeddah is in a moderate to high flood hazard zone, but most of the areas surrounding it are in moderate flood hazard zone. This indicates that during heavy rainfalls, flash flood could be generated in these areas which can be severely affecting the city. In addition, this study shows a remarkable correlation between theoretical concepts, data sets, and field observations, predominantly highlighting the role of geology and geomorphology in influencing the basin morphometry and identity.

PRIORITY SELECTION OF RESIDENTIAL DEVELOPMENT AREAS WITH FLOOD HAZARD IN LIMAPULUH KOTA DISTRICT, WEST SUMATRA

The flood disaster has caused much harm to human life. The Effort to reduce the disadvantages caused by the flood is to develop settlement area priority based natural disaster. The purpose of research to determine the priority zone of settlement development using geography information system method (GIS) with regards to hazard risk. The indicator used in determining of area suitability for the settlement are a slope, flood, drainage, gravel, texture, and effective depth. Meanwhile, the Indicators used to determine of flood hazard zone are kinds of soil, slope, landform, rainfall, elevation, land use, and geology. The result shows that the level of area suitability and flood hazard of Limapuluh Kota district were 46% and 50.6%, respectively, these results are categorized as prone to moderate. The analysis result for priority of settlement area development for Limapuluh Kota district shows that it was suitable for S2 (fourth level priority) and flood hazard to medium. Therefore, in the use of area needs more cost and environmental conservation as disaster mitigation efforts for the future.

Flood hazard mapping using geospatial techniques and satellite images-a case study of coastal district of Tamil Nadu.

In recent years, extreme rainfall events have resulted in several devastating floods especially in the east coast of Tamil Nadu, India. The main aim of this study is to identify the flood hazard zones in Cuddalore district by integrating spatial distribution of extreme rainfall events, slope, drainage density, soil, and geomorphology. Moderate Resolution Imaging Spectroradiometer satellite data was used to delineate the flood inundation area for the flood event which occurred in 2010 to validate the derived flood hazard zones by using geographical information system (GIS) and satellite images. The ground truth points were collected from the field to validate flood hazard zones, and it was identified that 92% of results were matched with hazard zones. Highly vulnerable blocks including Cuddalore, Kattumannarkoil, Keerapalayam, Kumaratchi, Kurinjipadi, Melbhunagiri, and Parangipettai were identified in Cuddalore district. From this study, it was also identified that nearly 45% of the total area of 3678km2 were inundated during the flood time. This present study will be a very useful tool and a resource for the policy planners and coastal planners to make effective decisions towards mitigation measures in flood-prone areas in the coastal districts.

Analysis of extreme flow uncertainty impact on size of flood hazard zones for the Wronki gauge station in the Warta river

In this paper, the impact of maximum flow uncertainty on flood hazard zone is analyzed. Two factors are taken into account: (1) the method for determination of maximum flows and (2) the limited length of the data series available for calculations. The importance of this problem is a consequence of the implementation of the EU Flood Directive in all EU member states. The factors mentioned seem to be among the most important elements responsible for potential uncertainty and inaccuracy of the developed flood hazard maps. Two methods are analyzed, namely the quantiles method and the maximum likelihood method. The maximum flows are estimated for the Wronki gauge station located in the reach of the Warta river. This simple river system is located in the central part of Poland. The length of the available data is 44 years. Hence, the series of the lengths 40, 30 and 20 years are tested and compared with reference calculations for 44 years. The hydrodynamic model HEC-RAS is used to calculate water surface profiles in steady state flow. The Python scripting language is applied for automation of HEC-RAS calculations and processing of final results in the form of inundation maps. The number of trials for each factor is not huge to keep the presented methodology useful in practice. The chosen measure of uncertainty is the range of variability for maximum flow values as well as inundation areas. The estimated values stressed the great importance of the factors analyzed for the uncertainty of the maximum flows as well as inundation areas. The impact of the data series length on the maximum flows is straightforward; a shorter data series gives a wider range of variability. However, the dependencies between other factors are more complex. Hence, the application of methodology based on the simulation and GIS data processing for assessment of this problem seems to be quite a good approach.

Brief Communication: Analysis of the Fatalities and Socio-Economic Impacts Caused by Hurricane Florence

Florence made landfall on the southeastern coast of North Carolina (NC) generating torrential rainfall and severe flooding that led to 53 fatalities in three states (NC, SC, and VA) and $16–$40 billion in damage. Seventy-seven percent (77%) of the fatalities occurred in the rural flood plains of NC with Duplin county reporting a high of eight deaths. Approximately 50% of the total number of hurricane-related fatalities across the three states were vehicle-related. The predominant demographic at risk were males over the age of 50 years. The type of property damage was in line with other major hurricanes and predominantly affected residential structures (93% of the total number of damaged buildings). Florence is among the top 10 costliest hurricanes in U.S. history with approximately 50% of the damage projected as uninsured losses due to residential flooding. The cumulative 5-day rainfall resulted in major flooding along the Cape Fear, Lumberton, and Neuse rivers where many industrial waste sites (hog manure lagoons and coal ash pits) are located. Several of these waste sites located in the flood plain were breached and have likely cross-contaminated the waterways and water treatment operations. The observed extent of the flooding, environmental contamination, and impact to public health caused by Florence will add to the long-term disaster related mortality and morbidity rates and suggests an expansion of the 100-yr flood hazard zone to communicate the expanded risk to the public.