nasa-gesdisc/es-publications-researchareas huggingface dataset:
Daily GRACE gravity field solutions track major flood events in the GangesBrahmaputra Delta (2018)

Abstract. Two daily gravity field solutions based on observations from the Gravity Recovery and Climate Experiment (GRACE) satellite mission are evaluated against daily river runoff data for major flood events in the GangesBrahmaputra Delta (GBD) in 2004 and 2007. The trends over periods of a few days of the daily GRACE data reflect temporal variations in daily river runoff during major flood events. This is especially true for the larger flood in 2007, which featured two distinct periods of critical flood level exceedance in the Brahmaputra River. This first hydrological evaluation of daily GRACE gravity field solutions based on a Kalman filter approach confirms their potential for gravity-based large-scale flood monitoring. This particularly applies to short-lived, high-volume floods, as they occur in the GBD with a 45-year return period. The release of daily GRACE gravity field solutions in near-real time may enable flood monitoring for large events.

Research areas: Floods
Flood impact on Mainland Southeast Asia between 1985 and 2018—The role of tropical cyclones (2020)

Floods are disastrous natural hazards accused of human live losses. As a flood‑prone area, Mainland Southeast Asia (MSEA) has often been hit by floods, resulting in the highest fatality in the world. Despite the destructive flood impacts, how has flood occurrence changed over the past decades, and to what extent did floods affect the MSEA are not yet clear. Using the Dartmouth Flood Observatory large flood data archive, we aim to assess the trend of flood occurrence in the MSEA in 1985–2018, and quantify the associated impacts on humans. Particularly, the contribution of tropical cyclone (TC) landfall induced floods (TCFloods) is quantified, because of the frequent TC landfalls. Results show that (a) occurrence and maximum magnitude of floods by all causes (ALLFloods) significantly increased (p &lt; .01), but not for TCFloods; (b) On average, TCFloods accounted for 24.6% occurrence of ALLFloods; (c) TCFloods caused higher mortality and displacement rate than ALLFloods did. As low flood protection standards in Cambodia and Myanmar is considered a reason for high flood‑induced mortalities, building higher flood protection standards should be taken as a priority for mitigating potential flood impacts. With quantifying flood occurrence and impacts, this study offers scientific understandings for better flood risk management.

Research areas: Floods
Low cost, multiscale and multi-sensor application for flooded area mapping (2018)

Abstract. Flood mapping and estimation of the maximum water depth are essential elements for the first damage evaluation, civil protection intervention planning and detection of areas where remediation is needed. In this work, we present and discuss a methodology for mapping and quantifying flood severity over floodplains. The proposed methodology considers a multiscale and multi-sensor approach using free or low-cost data and sensors. We applied this method to the November 2016 Piedmont (northwestern Italy) flood. We first mapped the flooded areas at the basin scale using free satellite data from low- to medium-high-resolution from both the SAR (Sentinel-1, COSMO-Skymed) and multispectral sensors (MODIS, Sentinel-2). Using very- and ultra-high-resolution images from the low-cost aerial platform and remotely piloted aerial system, we refined the flooded zone and detected the most damaged sector. The presented method considers both urbanised and non-urbanised areas. Nadiral images have several limitations, in particular in urbanised areas, where the use of terrestrial images solved this limitation. Very- and ultra-high-resolution images were processed with structure from motion (SfM) for the realisation of 3-D models. These data, combined with an available digital terrain model, allowed us to obtain maps of the flooded area, maximum high water area and damaged infrastructures.

Research areas: Floods
Defining the degree of flood hazard using a hydrodynamic approach, a case study: Wind turbines field at west of Suez Gulf (2020)

There is a big shortage of drinking water in the western Suez Gulf in Egypt. Fortunately, wind energy is available to cope with the required power for desalination. In previous works the area was subjected to Multi-Criteria Analysis process using a DEM implemented into a GIS environment. For each watershed, a Weighted Standardized Risk Factor (WSRF) was deduced based on the correlation factor for all the main morphological parameters which were obtained from the HEC-HMS model results. Former thought of defining the safe and unsafe watersheds based on global scale and dependent only on (WSRF), is nowadays criticized as a watershed with high value for (WSRF) could have safe specific areas for the wind turbines establishment. A 2D hydrodynamic model was applied on a Macro Scale to deduce inundation maps then were overlaid with wind speeds maps to define the most appropriate locations for wind turbines.

Research areas: Floods
Recent hydrological evolutions of the Senegal River flood (West Africa) (2021)

The flood of the Senegal River is a resource for the populations of the Senegal valley, who practise agriculture, fishing and livestock farming in the annually flooded areas. The objective of this paper is to investigate the hydrological evolution of the Senegal River flood since the drought of the 1970s and the construction and management of the Manantali Dam. To this purpose, the paper analyses the evolution of several parameters of the flood hydrograph and defines the factors that determine the intensity of the flood. Also, a follow-up of the flooded areas in the valley is carried out using remote sensing. The results show that the flood hydrograph has been similar since the 1970s drought, due to the reduction in contributions from the Bafing after the construction of the Manantali Dam. As a result, the high floods depend now on the rainfall pattern in the Sudano-Sahelian zone of the watershed.

Research areas: Floods
Long-Term Changes in Global Socioeconomic Benefits of Flood Defenses and Residual Risk Based on CMIP5 Climate Models (2018)

A warmer climate is expected to accelerate the global hydrological cycle, causing more intense precipitation and floods. Despite recent progress in global flood risk assessment, the socioeconomic benefits of flood defenses (i.e., reduction in population/economic exposure) and the residual risk (i.e., residual population/economic exposure) are poorly understood globally and regionally. To address these knowledge gaps, we use the runoff data from a baseline and 11 Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models to drive the Catchment-based Macro-scale Floodplain model incorporating the latest satellite river width information. From the simulated annual maxima, we use a Gumbel distribution to estimate the river water depth-flood return period relationship. We independently evaluate flood impacts on population and economy (i.e., gross domestic product) for a range of flood return periods. We estimate the socioeconomic benefits and the corresponding residual risk for the globe and 26 subcontinental regions. The global population (gross domestic product) exposed to flooding is ∼8% (∼7%) per year lower when implementing existing flood protection infrastructure extracted from the FLOod PROtection Standards database. If the current flood defenses were to be unchanged in the future (Representative Concentration Pathway 4.5 [RCP4.5] and RCP8.5, i.e., ∼2 to ∼4.3°C above the preindustrial levels), the globe and most of the regions (particularly where developing countries are concentrated) would experience an increase in residual risk. This increase is especially obvious when the gap of climate forcing between RCP8.5 and RCP4.5 widens by the end of the 21st century. We finally evaluate the impact of changed flood defense levels on the socioeconomic benefits and the corresponding residual risk.

Research areas: Floods
Urban surface water flood modelling–a comprehensive review of current models and future challenges (2021)

Abstract. Urbanisation is an irreversible trend as a result of social and economic development. Urban areas, with high concentration of population, key infrastructure, and businesses, are extremely vulnerable to flooding and may suffer severe socio-economic losses due to climate change. Urban flood modelling tools are in demand to predict surface water inundation caused by intense rainfall and to manage associated flood risks in urban areas. These tools have been rapidly developing in recent decades. In this study, we present a comprehensive review of the advanced urban flood models and emerging approaches for predicting urban surface water flooding driven by intense rainfall. The study explores the advantages and limitations of existing model types, highlights the most recent advances, and identifies major challenges. Issues of model complexities, scale effects, and computational efficiency are also analysed. The results will inform scientists, engineers, and decision-makers of the latest developments and guide the model selection based on desired objectives.

Research areas: Floods
The failed-levee effect: Do societies learn from flood disasters? (2015)

Human societies have learnt to cope with flood risks in several ways, the most prominent ways being engineering solutions and adaptive measures. However, from a more sustainable point of view, it can be argued that societies should avoid or at least minimize urban developments in floodplain areas. While many scientists have studied the impact of human activities on flood risk, only a few studies have investigated the opposite relationships, i.e. the impacts of past flood events on floodplain development. In this study, we make an initial attempt to understand the impact of the occurrence of flood disasters on the spatial distribution of population dynamics in floodplain areas. Two different methodologies are used to uncover this relationship, a large-scale study for the USA and a case-study analysis of the 1993 Mississippi flood. The large-scale analysis is performed at county level scale for the whole of the USA and indicates a positive relationship between property damage due to flood events and population growth. The case-study analysis examines a reach of the Mississippi river and the territory, which was affected by flooding in 1993. Contrary to the large-scale analysis, no significant relationship is found in this detailed study. However, a trend of dampened population growth right after the flood followed by an accelerated growth a decade later could be identified in the raw data and linked to explanations found in the literature.

Research areas: Floods
Landsat-MODIS image fusion and object-based image analysis for observing flood inundation in a heterogeneous vegetated scene (2019)

Typhoon flooding normally occurs suddenly with short duration, and the thick cloud cover limits the ability of one single satellite to timely capture the inundation extent. Landsat satellite data with a spatial resolution of 30 m is spatially applicable for flooding research; however, its 16-day observation frequency is typically insufficient to observe short-term typhoon inundation. Alternatively, despite the coarse spatial resolutions, the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor provide daily data, which is well suited for flood-related investigations. Accordingly, the idea of combining these two sources of data to generate a high spatial and temporal image would be useful. In this study, the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) was applied to generate cloud-free Landsat/MODIS synthesized data with a spatial resolution of 30 m for the delineation of the inundated areas during a flood event. This approach produces a Landsat-scale image for fine-scale flood mapping of areas where there are no observed cloud-free Landsat or similar resolution satellite images. The fusion model was implemented on atmospherically corrected surface reflectance, and the resultant reflectance values were validated by comparing with observed Landsat reflectance before further data interpretation. The blending results indicate that the synthetic Landsat-scaled image is highly correlated with Landsat surface reflectance, captured a day after the synthetic image acquisition date, over cloud-free areas. For image interpretation, an object-based image analysis (OBIA) approach with an optimal-scale segmentation and the support vector machine (SVM) classifier was applied for flood classification. The flood mapping result was validated by comparing with a reference flood map derived from an observed Landsat image. This study demonstrates that the techniques of image fusion and object-based image analysis are useful for observing flood inundation in the heterogeneous vegetated area.

Research areas: Floods
Flood Hazard Mapping Using Fuzzy Logic, Analytical Hierarchy Process, and Multi-Source Geospatial Datasets (2021)

Iran is among the driest countries in the world, where many natural hazards, such as floods, frequently occur. This study introduces a straightforward flood hazard assessment approach using remote sensing datasets and Geographic Information Systems (GIS) environment in an area located in the western part of Iran. Multiple GIS and remote sensing datasets, including Digital Elevation Model (DEM), slope, rainfall, distance from the main rivers, Topographic Wetness Index (TWI), Land Use/Land Cover (LULC) maps, soil type map, Normalized Difference Vegetation Index (NDVI), and erosion rate were initially produced. Then, all datasets were converted into fuzzy values using a linear fuzzy membership function. Subsequently, the Analytical Hierarchy Process (AHP) technique was applied to determine the weight of each dataset, and the relevant weight values were then multiplied to fuzzy values. Finally, all the processed parameters were integrated using a fuzzy analysis to produce the flood hazard map with five classes of susceptible zones. The bi-temporal Sentinel-1 Synthetic Aperture Radar (SAR) images, acquired before and on the day of the flood event, were used to evaluate the accuracy of the produced flood hazard map. The results indicated that 95.16% of the actual flooded areas were classified as very high and high flood hazard classes, demonstrating the high potential of this approach for flood hazard mapping.

Research areas: Floods
Evaluating natural infrastructure for flood management within the watersheds of selected global cities (2019)

Cities are dependent on their upstream watersheds for storage and gradual release of water into river systems. These watersheds act as important flood mitigation infrastructure, providing an essential ecosystem service. In this paper we use metrics from the WaterWorld model to examine the flood management-relevant natural infrastructure of the upstream watersheds of selected global cities. These metrics enable the characterisation of different types, magnitudes and geographical distributions of potential natural flood storage. The storages are categorised as either green (forest canopy, wetland and soil) or blue (water body and floodplain) storages and the proportion of green to blue indicates how different city upstream basin contexts provide different types and levels of storage which may buffer flood risk. We apply the WaterWorld method for examining flood risk as the ratio of accumulated modelled annual runoff volume to accumulated available green and blue water storage capacity. The aim of these metrics is to highlight areas where there is more runoff than storage capacity and thus where the maintenance or restoration of further natural infrastructure (such as canopy cover, wetlands and soil) could aid in storing more water and thus better alleviate flood risks. Such information is needed by urban planners, city authorities and governments to help prepare cities for climate change impacts.

Research areas: Floods
Linking flow-stream variability to grain size distribution of suspended sediment from a satellite-based analysis of the Tiber River plume (Tyrrhenian Sea) (2019)

Several coastal regions on Earth have been increasingly affected by intense, often catastrophic, flash floods that deliver significant amounts of sediment along shorelines. One of the critical questions related to the impact of these impulsive runoffs is are flash floods more efficient in delivering non-cohesive sandy sediment along the coasts? Here we relate flow stages (i.e., from erratic to persistent) to the grain size distribution of the suspended load, by performing a synergic analysis of in-situ river discharge and satellite-retrieved grain size distribution, from 2002 to 2014, covering the 2012 Tiber River (Italy) exceptional flood event. Our analysis shows novel and promising results regarding the capability of remote sensing in characterizing suspended sediment in terms of grain size distribution and reveals that erratic stages favour delivering of non-cohesive sandy sediment more than the persistent stages. This conclusion is supported by numerical simulations and is consistent with previous studies on suspended sediment rating curves.

Research areas: Floods
Quantification of flood mitigation services by urban green spaces using InVEST model: a case study of Hyderabad city, India (2021)

Urban floods have become more frequent across the globe. The transformation of the urban landscape with increased concretization and dwindling green cover has resulted in excess run-off generation thereby causing the flash floods. The protective role and ecosystem benefits of urban green spaces needs to be quantified so that it will unlock the possibilities of integrating natural capital thinking into policymaking. Hence in this study, we quantified the flood mitigation service of green spaces and estimated the tangible economic damage to the built infrastructure in the Hyderabad metropolitan city, India using the Integrated Valuation of Ecosystem Services and Trade-offs model. The analysis was carried out for 2-years and 5-years design precipitation of 1 h duration. Results show that 4450% of the precipitation is retained by the urban green and open spaces. With an increase of 13% in the rainfall intensity (from 2-years to 5-years), the run-off volume has increased by 21%, while the run-off retained has increased only by 5%, which indicates that even slight increase in rainfall intensity results in huge run-off generation that causes commensurate economic damages. The economic damage due to flood inundation of the built infrastructure is estimated to be 1.39 million USD using the unit cost method. Overall, the indicator of run-off retention service is quantified as 4.25E + 13 and 4.46E + 13 for the 2-years and 5-years return period precipitation, respectively. The structural and non-structural flood mitigation measures are also enumerated along with the limitations of the model.

Research areas: Floods
Flood Hazard Mapping and Vulnerability Analysis Along Seti River in Pokhara Metropolitan City (2021)

Flood is frequent during every monsoon in Nepal which poses threat to life and property in lowland areas. Among 6000 rivers and rivulets, most are prone to floods in Nepal. Seti River flows from Machhapuchhre Rural Municipality in the north, along the center of Pokhara Metropolitan City, and toward Tanahu which meets with Madi River there. Seti flood of 2012 was one of the devastating floods which took the life of many people and destroyed infrastructures along its way. So, Pokhara Metropolitan City lies at a high risk of flood impacts. Hydrodynamic simulation using HEC-RAS and GIS is one of the important methods of estimating the probable loss due to flood of various scenarios quantitatively. In this study, flood hazard maps of Seti River across Pokhara Metropolitan City has been prepared for different flood scenarios. The flood frequency analysis was performed using Gumbel, Log-Pearson, Log Normal, and Fullers Method. The goodness of fit was performed using chi square test, and results of Gumbel method was used as it was found more appropriate than other methods for this basin. One-dimensional steady hydrodynamic modeling was done to create water surface profile which was used to prepare hazard maps and vulnerability maps for various return periods. The model was evaluated using statistical parameters, coefficient of determination R2), and NashSutcliffe efficiency (NSE) whose values were found to be 0.951 and 0.819, respectively. The maps prepared can be used for planning the built-up areas along the river sides and may help in decision making for flood mitigation measures.

Research areas: Floods
Intercomparison of snow water equivalent observations in the Northern Great Plains (2018)

AbstractIn the Northern Great Plains, melting snow is a primary driver of spring flooding, but limited knowledge of the magnitude and spatial distribution of snow water equivalent (SWE) hampers flood forecasting. Passive microwave remote sensing has the potential to enhance operational river flow forecasting but is not routinely incorporated in operational flood forecasting. We compare satellite passive microwave estimates from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSRE) to the National Oceanic and Atmospheric Administration Office of Water Prediction (OWP) airborne gamma radiation snow survey and U.S. Army Corps of Engineers (USACE) ground snow survey SWE estimates in the Northern Great Plains from 2002 to 2011. AMSRE SWE estimates compare favourably with USACE SWE measurements in the low relief, low vegetation study area (mean difference = 3.8 mm, root mean squared difference [RMSD] = 34.7 mm), but less so with OWP airborne gamma SWE estimates (mean difference = 9.5 mm, RMSD = 42.7 mm). An error simulation suggests that up to half of the error in the former comparison is potentially due to subpixel scale SWE variability, limiting the maximum achievable RMSD between ground and satellite SWE to approximately 2633 mm in the Northern Great Plains. The OWP gamma versus AMSRE SWE comparison yields larger error than the pointscale USACE versus AMSRE comparison, despite a larger measurement footprint (57 km2 vs. a few square centimetres, respectively), suggesting that there are unshared errors between the USACE and OWP gamma SWE data.

Research areas: Validation
A Dusty Atmospheric River Brings Floods to the Middle East (2021)

Torrential rainfall and rapid snowmelt in April 2017 caused deadly floods in northwestern Iran. An atmospheric river (AR), propagating across the Middle East and North Africa, was found responsible for this extreme event. The snowmelt was triggered by precipitation and warm advection associated with the AR. Total satellite-based rainfall for April 2017 was moderately below normal, suggesting that a heavy flood can happen during dry years. The AR was fed by moisture from the Mediterranean and Red Seas. Despite its adverse societal consequences, this event was beneficial to the recovery of the desiccating Lake Urmia. The impacts of this AR were not limited to flooding; it also facilitated dust transport to the region. This distinct characteristic of the ARs in the Middle East is attributed to major mineral dust sources located along their pathways. This event was reasonably predicted at 7-day lead time, crucially important for successful early warning systems.

Research areas: Floods