Floodplain Mapping Research Articles

An exploration of exposure to river flood risk in Spain using the National Floodplain Mapping System

In Spain, human exposure to flooding continues to increase driven by changes in land use and population growth in urban and coastal areas. This study explores the geography of flood exposure in Spain in relation to human population, economic activities and points of special significance. The analysis is based on public flood hazard and risk mapping generated by water management administrators at the river basin district level. The data are published and accessible through the Spanish National Floodplain Mapping System (NFMS). The results show for first time, the spatial distribution of human population exposure, which amounts to at least 3,263,000 inhabitants nationwide (6.9% of the total Spanish population), the potential economic loss, totalling at least 122,132 million euros across Spain, and points of special significance classified into eleven different categories that have been analysed for all Spanish river basin districts. The results also indicate a higher exposure concentration along the Mediterranean coast.

A blueprint for coupling a hydrological model with fine- and coarse-scale atmospheric regional climate change models for probabilistic streamflow projections

In cold regions, climate change, including warming and changes in snowmelt dynamics, have profound impacts on streamflow patterns, often leading to flooding events. Understanding the projected changes in hydrometeorological factors contributing to streamflow, such as snowmelt runoff and rain-on-snowmelt, is crucial for effective adaptation and mitigation strategies. It is also essential to consider uncertainty in streamflow projections and incorporate this uncertainty into flood predictions. This study presents a blueprint for calculating probabilistic future streamflow and flow duration curves in a mountainous cold region. The methodology integrated forcings from an atmospheric model (WRF) with a hydrological model (MESH) at fine spatial (4 km) and temporal (3-hourly) resolutions. To account for uncertainty, an ensemble of 15 CanRCM4 regional climate simulations with varying boundary conditions for the RCP 8.5 scenario was utilized. A novel method was developed to perturb the CanRCM4 simulations’ precipitation using a WRF Pseudo Global Warming run to incorporate uncertainty. This comprehensive approach revealed significant uncertainty in streamflow driven by internal variability. WRF-driven simulations without uncertainty showed a decrease in future high streamflows, while the perturbed simulations demonstrated the potential for substantially higher streamflows under climate change. Moreover, the study derived probabilistic flow duration curves from the streamflow projections, aiding in estimating flood frequency for floodplain mapping when driving local hydraulic models. The methodology developed in this work can be extended to other river basins in Canada and elsewhere where gridded downscaled climate model outputs are available.

A Low-Impact Development-Based Modeling Framework for Flood Mitigation in a Coastal Community

Urbanization is known to increase the volume of stormwater runoff and peak flow rates, which leads to changes in the natural flow regime and increases the likelihood of flooding. Low-impact development (LID) practices seek to reduce runoff volume and peak flow and are generally considered to be a more sustainable solution for urban stormwater management. In this study, we present a systematic approach to address nuisance flooding issues in small cities and communities. As an application, the effectiveness of two LID practices, rain barrels and permeable pavements, were explored in mitigating the urban flooding problem of a highly urbanized small coastal watershed in Alabama, USA. The EPA Stormwater Management Model (SWMM) was first calibrated for water depth using data collected at multiple sites within the watershed during the 2014–2015 period. The calibrated model was then used to first identify the areas prone to flooding using design storms with 1, 2, 5-, 10-, 50-, and 100-year return periods. Floodplain maps were generated for those design storms with HEC-RAS. Next, LID options upstream of those flood-prone areas were assessed to potentially minimize the flooding risks. The results indicate that LID controls can have considerable benefits for stormwater management by reducing runoff volume (1–24%), peak flow rates (18–25%), and water depth (5–15%), potentially returning watersheds to their natural flow regimes, thereby minimizing the flooding risk in urbanized areas. However, the effectiveness of LIDs, especially for the runoff volume, quickly diminishes as the return periods of the storms increase. Rain barrels were identified as the most economical and effective LID within the drainage system.

SHIFT: a spatial-heterogeneity improvement in DEM-based mapping of global geomorphic floodplains

Abstract. Floodplains are a vital part of the global riverine system. Among all the global floodplain delineation strategies empowered by remote sensing, digital elevation model (DEM)-based delineation is considered to be computationally efficient with relatively low uncertainties, but the parsimonious model struggles with incorporating the basin-level spatial heterogeneity of the hydrological and geomorphic influences into the map. In this study, we propose a globally applicable thresholding scheme for DEM-based floodplain delineation to improve the representation of spatial heterogeneity. Specifically, we develop a stepwise approach to estimate the floodplain hydraulic geometry (FHG) scaling parameters for river basins worldwide at the scale of the level-3 HydroBASINS to best respect the scaling law while approximating the spatial extent of two publicly available global flood maps derived from hydrodynamic modeling. The estimated FHG exponent exhibits a significant positive relationship with the basins' hydroclimatic conditions, particularly in 33 of the world's major river basins, indicating the ability of the approach to capture fingerprints from heterogeneous hydrological and geomorphic influences. Based on the spatially varying FHG parameters, a ∼ 90 m resolution global floodplain map named the Spatial Heterogeneity Improved Floodplain by Terrain analysis (SHIFT) is delineated, which takes the hydrologically corrected MERIT Hydro dataset as the DEM inputs and the height above nearest drainage (HAND) as the terrain attribute. Our results demonstrate that SHIFT validates better with reference maps than both hydrodynamic-modeling- and DEM-based approaches with universal parameters. The improved delineation mainly includes better differentiation between main streams and tributaries in major basins and a more comprehensive representation of stream networks in aggregated river basins. SHIFT estimates the global floodplain area to be 9.91×106 km2, representing 6.6 % of the world's total land area. SHIFT data layers are available at two spatial resolutions (90 m and 1 km), along with the updated parameters, at https://doi.org/10.5281/zenodo.11835133 (Zheng et al., 2024). We anticipate that SHIFT will be used to support applications requiring boundary delineations of the global geomorphic floodplains.

Can geomorphic flood descriptors coupled with machine learning models enhance in quantifying flood risks over data-scarce catchments? Development of a hybrid framework for Ganga basin (India).

Quantifying flood risks through a cascade of hydraulic-cum-hydrodynamic modelling is data-intensive and computationally demanding- a major constraint for economically struggling and data-scarce low and middle-income nations. Under such circumstances, geomorphic flood descriptors (GFDs), that encompass the hidden characteristics of flood propensity may assist in developing a nuanced understanding of flood risk management. In line with this, the present study proposes a novel framework for estimating flood hazard and population exposure by leveraging GFDs and Machine Learning (ML) models over severely flood-prone Ganga basin. The study incorporates SHapley Additive exPlanations (SHAP) values in flood hazard modeling to justify the degree of influence of each GFD on the simulated floodplain maps. A set of 15 relevant GFDs derived from high-resolution CartoDEM are forced to five state-of-the-art ML models; AdaBoost, Random Forest, GBDT, XGBoost, and CatBoost, for predicting flood extents and depths. To enumerate the performance of ML models, a set of twelve statistical metrics are considered. Our result indicates a superior performance of XGBoost (κ = 0.72 and KGE = 82%) over other ML models in flood extent and flood depth prediction, resulting in about 47% of the population exposure to high-flood risks. The SHAP summary plots reveal a pre-dominance of Height Above Nearest Drainage during flood depth prediction. The study contributes significantly in comprehending our understanding of catchment characteristics and its influence in the process of sustainable disaster risk reduction. The results obtained from the study provide valuable recommendations for efficient flood management and mitigation strategies, especially over global data-scarce flood-prone basins.

Advanced floodplain mapping: HEC-RAS and ArcGIS pro application on Swat River

AbstractFloods stand out as one of the most devastating environmental threats worldwide resulting in the tragic loss of human lives and significant damage to our essential infrastructure. This study focuses on creating floodplain maps for the two important reaches of Swat River in the Khyber Pakhtunkhwa Province of Pakistan, namely, Kalam–Khwazakhela and Khwazakhela–Chakdara reaches. The Advanced Land Observing Satellite Phased Array Type L-band Synthetic Aperture Radar (ALOS PALSAR) 12.5 m Digital Elevation Model (DEM) data has been used for this purpose. Furthermore, the sensitivity of the flood model was assessed for the Flood 2022 event, considering simulated flood depth, extent, and velocity in relation to various terrains derived from the 12.5-m ALOS PALSAR data. To estimate extreme flows for different return periods (2, 5, 10, 25, 50, and 100 years), the Log Normal (LN), Log Pearson III (LP3), and Generalized Extreme Value (GEV) distributions were employed for the frequency analysis. The GEV distribution turned out to be the best fit for modeling the Swat River for both the Chakdara and Khwazakhela gauge stations. To predict flood levels for the peak floods identified through frequency analysis and for the specific return periods the Hydrologic Engineering Center's River Analysis System (HEC-RAS) 2D simulations were performed. Subsequently the outcomes of this model were used to create floodplain maps using Geographic Information System Professional (ArcGIS Pro) software customized for various return periods. The analysis revealed a linear increase in flood inundation area with longer return periods. The floodplain maps developed hold significant importance for the governing authorities of the Swat region. These maps serve as essential tools for implementing proactive measures against potential infrastructure damage, thereby protecting against economic losses and enhancing public safety. This research effectively combines hydrological modeling and geospatial technology offering practical solutions for managing flood risks. It serves as a valuable guide for making well-informed decisions and promoting sustainable development in flood-prone areas.

LiDAR topo‐bathymetry for riverbed elevation assessment: A review of approaches and performance for hydrodynamic modelling of flood plains

AbstractTopo‐bathymetric LiDAR (TBL) can provide a continuous digital elevation model (DEM) for terrestrial and submerged portions of rivers. This very high horizontal spatial resolution and high vertical accuracy data can be promising for flood plain mapping using hydrodynamic models. Despite the increasing number of papers regarding the use of TBL in fluvial environments, its usefulness for flood mapping remains to be demonstrated. This review of real‐world experiments focusses on three research questions related to the relevance of TBL in hydrodynamic modelling for flood mapping at local and regional scales: (i) Is the accuracy of TBL sufficient? (ii) What environmental and technical conditions can optimise the quality of acquisition? (iii) Is it possible to predict which rivers would be good candidates for TBL acquisition? With a root mean square error (RMSE) of 0.16 m, results from real‐world experiments confirm that TBL provides the required vertical accuracy for hydrodynamic modelling. Our review highlighted that environmental conditions, such as turbidity, overhanging vegetation or riverbed morphology, may prove to be limiting factors in the signal's capacity to reach the riverbed. A few avenues have been identified for considering whether TBL acquisition would be appropriate for a specific river. Thresholds should be determined using geometric or morphological criteria, such as rivers with steep slopes, steep riverbanks, and rivers too narrow or with complex morphologies, to avoid compromising the quality or the extent of the coverage. Based on this review, it appears that TBL acquisition conditions for hydrodynamic modelling for flood mapping should optimise the signal's ability to reach the riverbed. However, further research is needed to determine the percentage of coverage required for the use of TBL as a source of bathymetry in a hydrodynamic model, and whether specific river sections must be covered to ensure model performance for flood mapping.

Simulation of the Hydraulic Model HEC-RAS Coupled with GIS and Remote Sensing to Study the Effect of River Cross-section Width in Detecting Flood-prone Areas

Abstract Flooding is one of the extreme hydrological phenomena. It is a recurring natural disaster that causes loss of life and property in many parts of the world, particularly during the monsoon season. It is important to address such issues for local government and policymakers to manage the flood properly. One such flood management activity is to develop a flood-prone area that depicts the spatial and temporal extent of flood accurately. The integration of the Hydrologic Engineering Centre - River Analysis System (HEC-RAS) model and geospatial tools have emerged as a crucial approach for identifying and mapping flood-prone areas. The successful application of the HEC-RAS model generally depends on the topographical data, which represents the channel and floodplain geometry. In floodplain geometry, discrete cross-sections play a vital role to develop the floodplain map, particularly in the flat topographical region. To extract these data it needs a high-quality digital elevation model (DEM), such as light detection and ranging (LiDAR). However, due to a lack of high-resolution topographical data, flood hazard mapping in developing countries is rare. In common practice, the centerline of the river is considered the flow path for the channel. The orientation of the cross-sections is perpendicular to this line and extends to reach the limits of the floodplain. But, it is difficult to define the limits and it may depend on the magnitude of the flood. Hence, in this study, the HEC RAS model coupled with ArcGIS has been applied to the Ganga River, which traverses through the Bihar state of India to study the effect of cross-sectional width to define the floodplain. The Bihar state is facing substantial hardships from annual flooding events with approximately 16.5% of India’s flood-prone area. The extreme flood values for 5, 10, and 25 years of return period have been determined and the influence of the three different cross-sectional widths to mapping the floodplain has been investigated. This novel perspective adds dimension to the understanding of flood dynamics and its implications for flood risk assessment. In this analysis, it has been observed that, with an increase in the width of the cross-section, the floodplain area also getting increased. In this topographical region, keeping a fixed flow path will underestimate the flood-prone area. The width of the flow path depends on the topography of the region and the river flow. The outcomes of this analysis provide valuable insights into the flood-inundated areas for the specified return periods, enabling the identification and prioritization of flood-prone zones.

Floodplain mapping of an ungauged river: A case study on Seti River in Pokhara, Nepal

Settlements and infrastructures along the banks of Seti River in Pokhara, Nepal are at high risk of flood. Floodplain mapping for ungauged Seti River is not straightforward like the one for gauged rivers. Main goal of this study was to prepare floodplain maps along the ungauged Seti River in Pokhara, as a case study, using one-dimensional HEC-RAS model. First, catchment area ratio (CAR) method was applied to find annual flow in ungauged Seti River based on flow data of gauged Mardi station. Once the annual maximum flow was estimated for sufficient time length (i.e., 42 years), peak flood was predicted using Gumbel method for various reaches of Seti River within Pokhara. Thus, estimated peak floods were also compared with the peak floods predicted using Gumbel method based on the annual flow data of Tanahu station. As the specific discharge observed to be comparable with each other (difference ≤ 2.68%), CAR method found be a reliable one that is useful for ungauged river. Then, Cowan’s approach was applied to estimate Manning’s roughness coefficient (n) and used it for calibration of HEC-RAS model. Cowan approach found to be a best alternative for ungauged river as the comparison of modelled flow depth with measured flow depth yielded only 3.82% difference. Finally, 1D hydraulic modelling was performed using calibrated HEC-RAS model with available 12.5 m resolution DEM terrain data. Floodplain maps were prepared based on the HEC-RAS simulation results coupled with Google Earth map. The flood inundation area within Pokhara was found to be 2.76, 3.05, and 3.59 Km2 for the peak flood of 20, 50, and 100 years return periods, respectively. Moreover, Laltin Bazar and Gaighat areas were identified to be at high risk of flood such that these areas found to be inundated with 20 or greater years return period floods, compared to Ramghat area which was observed to be flooded with the peak flood of 50 or more years return period. Floodplain maps of this study could be used for preparing flood hazard maps, planning infrastructures, and flood management.

Potential Dam Breach Flood Assessment with the 2D Diffusion and Full Dynamic Wave Equations Using a Hydrologic Engineering Center-River Analysis System

Dam breaches have catastrophic consequences, causing severe property damage, life loss, and environmental impact. The potential dam breach downstream flooding of the Kulekhani reservoir, Nepal, was studied using a 2D Diffusion Wave Equation (DWE) and Full Dynamic Wave Equation (FDWE) through an open-source solver, Hydrologic Engineering Center-River Analysis System (HEC-RAS). The suitable dam breach model was identified based on the dam geometry and sixteen historical dam failure cases. The simulated downstream peak was tested with an empirical relation, considering reservoir volume and duration of failure. Model comparisons through the flood plain mapping of water depth, flow velocity, flood intensity as per guidelines of the American Society of Civil Engineers (ASCE), and arrival time were carried out for flood hazard assessment. FDWE was able to capture the physical flow phenomena in the river bend resulting in higher flow velocity at the outer bend, lower velocity at the inner bend, and formation of eddies due to the application of the turbulence model, considering possible momentum losses, whereas DWE was unable to capture these effects due to a simplified momentum equation. The total area of flood extension was found to be increased by 30% using FDWE than the DWE due to higher water surface elevation. Most of the towns along the Kulekhani River were classified as “Very High” intensity flood regions according to ASCE, due to the V-shape valley. The peak time difference at the Bagmati River confluence was evaluated between the models. This plays an important role in decision-making for the selection of the flood model to make a safe evacuation plan. The application of FDWE was found to be suitable for the rapidly varying unsteady flow in the steep meandering river.

Flood Risk Mapping of Kankai Basin: A Case Study of Shivasatakshi Municipality and Kankai Municipality

Floods are probably the most frequent, widespread, and disastrous hazards in the world. It causes loss of life, casualties, financial loss, and displacement. Heavy monsoons, fragile geography, and constructions along the embankments cause the river to flood. The increase of population and squatter settlement of landless people living at the bank of the river has tremendous pressure on encroachment of flood plain making them vulnerable to flood damage. This study aims to develop HEC-RAS models for the Kankai River basin for preparation of 1D flood plain maps, vulnerability, risk assessment of RCC building in Shivasatakshi Municipality ward 10, and Kankai Municipality ward 4. Flood frequency analysis for 2, 10, 25, 50, 100, 200 and 1000 years return was carried out by Log Pearson III, Gumbel and Log Normal method based on maximum instantaneous flow recorded at Mainachuli station. The result of flood frequency analyzed by Log Normal method for 2, 10, 25, 50, 100, 200 and 1000 years return period floods shows higher among the results obtained using different methods. The flooding impact of the Kankai River being a large catchment with braided river form inundates vast downstream flood plain regions during high flood levels. With numerous people living along the river and downstream plains, flood risk is predominately high in the Kankai River catchment. With increasing flood intensity, higher flood depth increases and lower flood depth decreases. The inundation of a large area of Shivasatakshi Municipality ward 10 and Kanaki Municipality ward 4 at the bank of the Kankai river indicates that human lives and the physical infrastructure will be more vulnerable to flood disasters in the future. According to a study, the largest areas affected by floods with return periods of 2, 10, 25, 50, 100, 200, 1000 years, respectively, are 1843.24 ha, 1967.96 ha, 2016.32 ha, 2049.48 ha, 2079.64 ha, 2109.4 ha and 2176.08 ha of the whole basin. As a result, the study may help in future disaster planning and management.

An Investigation of the Current Situation of Floodplain Mapping in British Columbia: A Fuzzy Rule-Based Approach

An Investigation of the Current Situation of Floodplain Mapping in British Columbia: A Fuzzy Rule-Based Approach

Deriving synthetic rating curves from a digital elevation model to delineate the inundated areas of small watersheds

Study regionTwo southern Quebec (Canada) watersheds were used to validate the proposed method for delineating inundated areas of small watersheds: the 554-km2 St.Charles and the 133 km2 À la Raquette watersheds. Observed data from six-gauge stations were used to validate the Synthetic Rating Curves (SRC) developed in the study. Study focusThis research focuses on the application of the Height Above the Nearest Drainage (HAND) method to derive SRCs and support floodplain mapping in small watersheds.Accurate floodplain delineation is crucial of flood management, particularly in datascarce regions. This study presents a novel approach using (HAND) approach to precisely identify flood-prone areas. It involves generating (SRCs) connecting discharge and terrain derived hydraulic characteristics, integrated into PHYSITEL; a Geographic Information System (GIS) for distributed hydrological modeling. The Froude number established a consistent relationship between mean discharge and water depth across various discharge levels, defining unique hydraulic regimes. A Global Sensitivity Analysis quantified the uncertainty associated with SRC parameters, guiding calibration efforts to achieve biases below 20%. For both watersheds, postcalibration results showed SRCs with NRMSE values between 0.03 and 0.62. HANDSRC-based inundated areas corroborated the Quebec City flood risk zones well, with over 70% recall and 90% precision, validating its efficacy. These results contribute significantly to the region by providing SRCs for ungauged river sections and delineating first-hand floodplain maps.

Modelling flood hazards impacted by ungauged river in urbanised area using HEC-RAS and GIS

Ilorin City is located downstream of Asa, Oyun and Awun River Basins. The Asa River is a major river that traverses the city and divides the metropolitan area into east and west, almost equally. The river often overflows its banks to inundate adjacent communities, influencing severe economic damage and impact on human lives. However, efforts to mitigate this have majorly been focused on dredging the Asa River channel which has not solved the problem. For an accurate spatial and temporal understanding of the risks of floods and their potential hazards, it is important to estimate floods using river hydrology. The objective of this study is to model steady flow of the rivers using flow data and to map flood-prone areas in Ilorin using HEC-RAS integrated with GIS. Using the HEC-GeoRAS extension in the GIS environment, the geometric data of the rivers were obtained from the 30 m resolution digital elevation model (DEM) and input into HEC-RAS applying Manning Co-efficient values of 0.04, 0.045, and 0.04. For each river, flow data (Q) was given as the upstream boundary condition while a normal depth of 0.001 was assigned for the downstream condition to model a steady flow and inundation extents. The result of the HEC-RAS model has shown the flood-prone areas along the river channels delineated. The floodplain map produced reveals the spatial distribution and extent of the high flood-risk areas in the Ilorin metropolis. The total flooded area covers approximately 60.95 km2 (18%) majorly along the river channels. This study has demonstrated that integration of hydraulic modelling using HEC-RAS and GIS process is capable of producing an inundation flood map with good accuracy that will aid in suggesting effective measures to mitigate the impact of flooding.

Geomorphic floodplain mapping in small Mediterranean catchments using LiDAR data

Recent advances in remote sensing technologies along with the increased availability of topographic data have lately encouraged the development of automatic DEM (Digital Elevation Model)-based procedures for floodplain delineation. Geomorphic methods, establishing relationships between flood descriptors and morphologic catchment characteristics, appear particularly suitable to be implemented within a GIS algorithm. In the present work, four simplified geomorphic approaches based on “flow-depth scaling laws” (FD) or “flow-cross-sectional area scaling laws” (FA) with contributing area and two methods employing two different flood descriptors (Hydro-Geomorphic Method, HGM and Geomorphic Flood Index method, GFIM) have been applied for the preliminary evaluation of floodplain extent using high resolution DEMs (i.e. LiDAR at 1 and 2 m resolution) as the main input. Taking as a case study six of the largest basins located in southern Italy, the performances of these methods were evaluated and critically compared using government agency derived flood hazard maps as benchmarks. Results show that the adoption of FD especially when combined with morphology to formulate the GFIM, allows to efficiently predict the flood-prone areas with low computational costs. At the same time, performances of the flood mapping procedures based on “flow-area scaling laws”, although in principle more appealing, seem to be slightly lower. Overall, the proposed approaches can be applied for rough mapping of floodplains in ungauged basins or in data-scarce regions where standard flood hazard maps are unavailable.

Flood modelling at Bandar Batu Pahat, Johor using HEC-RAS software

Flood catastrophe continuously hit Malaysia through monsoonal flood and flash flood as well posing threat towards people, infrastructure and environment. Batu Pahat is among the district in Johor affected by flood disaster for almost every year. This study conducted to determine the hydraulic and hydrological characteristic and the ability of drainage system in Parit Besar and Jalan Pontian-Batu Pahat catchment area at Batu Pahat using HEC-RAS software. Through HEC-RAS, floodplain map was also produced to access the overview of potential floodplain areas. Survey data, geometric data and flow data were computed in HEC-RAS to produce drainage flow and cross-sectional area along the catchment area. Four (4) flow rates of 0.05284, 0.05894, 0.06910 and 0.07113 (m3/s) were utilized to identify the drainage ability to accommodate additional water. Several stations in Parit Besar catchment cannot accommodate the runoff with the minimum flow rate of 0.05284 (m3/s). Meanwhile, Jalan Pontian-Batu Pahat catchment cannot accommodate flow rates of 0.06910 and 0.07113 (m3/s). This is due to the catchment area has low elevation and insufficient drainage system. From the results, floodplain areas were identified. Modification of drainage cross-section was proposed to reduce the floodplain areas. This study is vital for better understanding of flooding and help the authorities to produce better flood management plan.

Validating the Quality of Volunteered Geographic Information (VGI) for Flood Modeling of Hurricane Harvey in Houston, Texas

The primary objective of this study was to examine the quality of volunteered geographic information (VGI) data for flood mapping of Hurricane Harvey. As a crowdsourcing platform, the U-Flood project mapped flooded streets in the Houston metro area. This research examines the following: (1) If there are any significant differences in water depth (WD) among the hydraulic and hydrologic (H&H) model, the Federal Emergency Management Agency (FEMA) reference floodplain map, and the VGI? (2) Are there any significant differences in the inundated areas between the floodplain modeled by the VGI and hydraulic simulation? This study used HEC-RAS to simulate flood inundation maps and validated the results with high water marks (HWM) and the FEMA-modeled floodplain after Hurricane Harvey. The statistical results showed that there were significant differences in the WD, the inundated road count, and the length inside/outside of HEC-RAS-modeled floodplain. The results also showed that a less consistent decreasing trend between the U-Flood data and the modeled floodplain over time and space. This study empirically evaluated the data quality of the VGI based on observed and modeled data in flood monitoring. The findings from this study fill the gaps in the literature by assessing the uncertainty and data quality of VGI, providing insights into using supplementary data in flood mapping research.

Evaluating Dry and Wet Season Precipitation from Remotely Sensed Data Using Artificial Neural Networks for Floodplain Mapping in an Ungauged Watershed

This research creates a framework for modelling the rainfall-runoff process using satellite precipitation data and a floodplain map in ungauged urban watersheds. The combined effects of urbanisation and climate change over the past few decades have increased the number of flooding incidents. Accurate prediction of the flood-prone zone is crucial for policymakers and system managers to build the watershed's resilience during catastrophic flooding events. Precipitation and runoff data are crucial for hydraulic and hydrologic analysis and for identifying flood-prone areas. However, it is difficult to obtain precipitation and discharge data for hydrologic analysis in data-scarce regions. In this context, this research employs satellite precipitation products for rainfall-runoff analysis, which is subsequently utilised in a hydraulic model to delineate a flood-prone zone in an ungauged watershed. The Hydrologic Engineering Centre-River Analysis System (HEC-RAS) and Hydrologic Modelling System (HEC-HMS) models were utilised in the study region to simulate and analyse interactions between rainfall, runoff, and the extent of the flood zone. Setting up and calibrating the HEC-HMS model using a satellite precipitation product is required for the dry and wet seasons. For the wet and dry seasons, HEC-HMS gets validated with an R-square value of 0.72 and 0.85, respectively. Three types of simulations were conducted in the calibrated HEC-HMS model to create the hydrograph with 25-, 50-, and 100-year of rainfall return periods. Finally, the one dimensional HEC-RAS model generates a flood inundation map for the pertinent flooding occurrences from the acquired peak hydrograph. By comparing the values of the specified return periods, the produced flood map depicts the affected area during various return periods of flooding events and provides a quantifiable display of inundation extent percentage (IE%).

Flood inundation mapping of upper Krishna basin using hydrodynamic model

Floodplain management and mapping are new and applied methods in river engineering and for the prediction of flood hazards. Krishna river basin is the second largest river basin in Peninsular India. This basin is one of the flood prone basins in India. The purpose of this study is to focus on the analysis of HEC-RAS to assess and predict the flood depth and spatial extent of flood in the upper Krishna River basin which is drained by Krishna River. To determine extent of inundation, the hydrodynamic model HEC-RAS with ArcGIS was used. For this, discharge data of two months from August and September 2012 has been processed in the study. A methodology was applied to combine hydraulic simulation model, HEC-RAS and GIS analysis for delineation of flood extents and depths for upper Krishna basin in India. Results obtained by using HEC-RAS Model were used by integrating with Arc-GIS to floodplain maps. Through this floodplain maps, the areas that are vulnerable to hazards, have been identified. The results of this research will benefit in future of flood forecasts on a regional scale, also they will be beneficial for water resources management and planning.

Evaluating topography-based approaches for fast floodplain mapping in data-scarce complex-terrain regions: Findings from a Himalayan basin

Despite a proven record of accurate floodplain mapping, complex hydrodynamic models lack efficiency due to their data-intensive approach and high computation time. As fast-computing low-complexity alternatives, topography-based hydrogeomorphic approaches are being increasingly used in recent times. Yet, there is little evidence to suggest whether and to what extent such topography-based approaches, simply relying on Digital Elevation Models (DEMs), can effectively delineate floodplains/flood hazard zones in data-scarce, highly complex mountainous terrains. We fill this knowledge-gap by conducting a floodplain mapping comparative assessment with three topography-based approaches along a 56-km river reach in the North West Himalayas (Beas River, India). Specifically, we generated floodplain extent using Height Above the Nearest Drainage (HAND), Topographic Wetness Index (TWI), and Slope Position (SP), and estimated their relative differences compared to a reference inundation extent simulated by MIKE11 hydrodynamic model. The unique feature of our study was an extensive field survey to collect longitudinal and cross-sectional elevation data across 223 locations, which allowed us to verify vertical accuracy across multiple alternative DEMs and subsequently improve the selected DEM via bathymetry integration. Statistical measures estimating the degree of consistency across three topography-based approaches suggested that HAND and TWI produce more reasonable floodplain maps than SP. HAND-based floodplain demonstrated greater agreement with the model-simulated reference map. TWI showed moderate predictability with a tendency of underestimating floodplains. SP was largely inconsistent, demarcating floodplains in areas where the hydrodynamic model found uplands and vice versa. Our study can offer critical insights to support floodplain hydrological, biological, and habitat studies across the world’s developing countries where locally relevant delineation of floodplains remains challenging due to data scarcity.