scholarly journals A Remote Sensing Based Integrated Approach to Quantify the Impact of Fluvial and Pluvial Flooding in an Urban Catchment

2019 ◽  
Vol 11 (5) ◽  
pp. 577 ◽  
Author(s):  
Manoranjan Muthusamy ◽  
Monica Rivas Casado ◽  
Gloria Salmoral ◽  
Tracy Irvine ◽  
Paul Leinster
Keyword(s):  
Remote Sensing ◽  
Digital Terrain Model ◽  
Integrated Approach ◽  
Flood Management ◽  
Flood Damage ◽  
Water Flooding ◽  
Surface Model ◽  
Pluvial Flooding ◽  
Residential Properties ◽  
The Impact

Pluvial (surface water) flooding is often the cause of significant flood damage in urbanareas. However, pluvial flooding is often overlooked in catchments which are historically knownfor fluvial floods. In this study, we present a conceptual remote sensing based integrated approachto enhance current practice in the estimation of flood extent and damage and characterise the spatialdistribution of pluvial and fluvial flooding. Cockermouth, a town which is highly prone to flooding,was selected as a study site. The flood event caused by named storm Desmond in 2015 (5-6/12/2015)was selected for this study. A high resolution digital elevation model (DEM) was produced from acomposite digital surface model (DSM) and a digital terrain model (DTM) obtained from theEnvironment Agency. Using this DEM, a 2D flood model was developed in HEC-RAS (v5) 2D forthe study site. Simulations were carried out with and without pluvial flooding. Calibrated modelswere then used to compare the fluvial and combined (pluvial and fluvial) flood damage areas fordifferent land use types. The number of residential properties affected by both fluvial and combinedflooding was compared using a combination of modelled results and data collected from UnmannedAircraft Systems (UAS). As far as the authors are aware, this is the first time that remote sensingdata, hydrological modelling and flood damage data at a property level have been combined todifferentiate between the extent of flooding and damage caused by fluvial and pluvial flooding inthe same event. Results show that the contribution of pluvial flooding should not be ignored, evenin a catchment where fluvial flooding is the major cause of the flood damages. Although theadditional flood depths caused by the pluvial contribution were lower than the fluvial flood depths,the affected area is still significant. Pluvial flooding increased the overall number of affectedproperties by 25%. In addition, it increased the flood depths in a number of properties that wereidentified as being affected by fluvial flooding, in some cases by more than 50%. These findingsshow the importance of taking pluvial flooding into consideration in flood management practices.Further, most of the data used in this study was obtained via remote sensing methods, includingUAS. This demonstrates the merit of developing a remote sensing based framework to enhancecurrent practices in the estimation of both flood extent and damage.

scholarly journals A remote sensing based integrated approach to quantify the impact of fluvial and pluvial flooding in an urban catchment

2020 ◽  
Author(s):  
Manoranjan Muthusamy ◽  
Monica Rivas Casado ◽  
Gloria Salmoral ◽  
Tracy Irvine ◽  
Paul Leinster
Keyword(s):  
Remote Sensing ◽  
Urban Areas ◽  
Management Practices ◽  
Current Practice ◽  
Integrated Approach ◽  
Flood Damage ◽  
Water Flooding ◽  
Surface Model ◽  
Pluvial Flooding ◽  
The Impact

<p>Pluvial (surface water) flooding is often the cause of significant flood damage in urban areas. However, pluvial flooding is often overlooked in catchments which are historically known for fluvial floods. In this study, we present a conceptual remote sensing-based integrated approach to enhance current practice in the estimation of flood extent and damage and characterise the spatial distribution of pluvial and fluvial flooding. Cockermouth, a small town in England which is highly prone to flooding, was selected as a study site and the flood event caused by storm Desmond in 2015 (5-6/12/2015) was selected for this study. A high-resolution digital elevation model (DEM) was produced from a composite digital surface model (DSM) and a digital terrain model (DTM) obtained from the Environment Agency. Using this DEM, a 2D flood model was developed in HEC-RAS (v5) 2D for the study site. Simulations were carried out with and without pluvial flooding. Calibrated models were then used to compare the fluvial and combined (pluvial and fluvial) flood damage areas for different land-use types. The number of residential properties affected by fluvial and combined flooding was compared using a combination of modelled results and data collected from Unmanned Areal System (UAS). As far as the authors are aware, this is the first time remote sensing data, hydrological modelling and flood damage data at property level have been combined to differentiate between the flood extents and damage caused by fluvial and pluvial flooding in the same event. Results show that the contribution of pluvial flooding should not be ignored even in a catchment where fluvial flooding is the major cause of the flood damages. Although the additional flood depths caused by the pluvial contribution were lower than the fluvial flood depths, the affected area is still significant. Pluvial flooding increased the overall number of affected properties by 25%. In addition, it increased the flood depths in a number of properties that were identified as being affected by fluvial flooding, in some cases by more than 50%. These findings show the importance of taking pluvial flooding into consideration in flood management practices. Further, most of the data used in this study were obtained via remote sensing methods, including UASs. This demonstrates the merit of developing a remote sensing-based framework to enhance current practice in the estimation of flood extent and damage.</p>

scholarly journals Effects of high spatial and temporal resolution Earth observations on simulated hydrometeorological variables in a cropland (southwestern France)

2017 ◽  
Vol 21 (11) ◽  
pp. 5693-5708 ◽  
Author(s):  
Jordi Etchanchu ◽  
Vincent Rivalland ◽  
Simon Gascoin ◽  
Jérôme Cros ◽  
Tiphaine Tallec ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Land Surface ◽  
Agricultural Landscapes ◽  
Surface Model ◽  
Spatial And Temporal Variability ◽  
Area Index ◽  
The Impact ◽  
Sentinel 2

Abstract. Agricultural landscapes are often constituted by a patchwork of crop fields whose seasonal evolution is dependent on specific crop rotation patterns and phenologies. This temporal and spatial heterogeneity affects surface hydrometeorological processes and must be taken into account in simulations of land surface and distributed hydrological models. The Sentinel-2 mission allows for the monitoring of land cover and vegetation dynamics at unprecedented spatial resolutions and revisit frequencies (20 m and 5 days, respectively) that are fully compatible with such heterogeneous agricultural landscapes. Here, we evaluate the impact of Sentinel-2-like remote sensing data on the simulation of surface water and energy fluxes via the Interactions between the Surface Biosphere Atmosphere (ISBA) land surface model included in the EXternalized SURface (SURFEX) modeling platform. The study focuses on the effect of the leaf area index (LAI) spatial and temporal variability on these fluxes. We compare the use of the LAI climatology from ECOCLIMAP-II, used by default in SURFEX-ISBA, and time series of LAI derived from the high-resolution Formosat-2 satellite data (8 m). The study area is an agricultural zone in southwestern France covering 576 km2 (24 km  ×  24 km). An innovative plot-scale approach is used, in which each computational unit has a homogeneous vegetation type. Evaluation of the simulations quality is done by comparing model outputs with in situ eddy covariance measurements of latent heat flux (LE). Our results show that the use of LAI derived from high-resolution remote sensing significantly improves simulated evapotranspiration with respect to ECOCLIMAP-II, especially when the surface is covered with summer crops. The comparison with in situ measurements shows an improvement of roughly 0.3 in the correlation coefficient and a decrease of around 30 % of the root mean square error (RMSE) in the simulated evapotranspiration. This finding is attributable to a better description of LAI evolution processes with Formosat-2 data, which further modify soil water content and drainage of soil reservoirs. Effects on annual drainage patterns remain small but significant, i.e., an increase roughly equivalent to 4 % of annual precipitation levels with simulations using Formosat-2 data in comparison to the reference simulation values. This study illustrates the potential for the Sentinel-2 mission to better represent effects of crop management on water budgeting for large, anthropized river basins.

scholarly journals Assessing the impact of arid area urbanization on flash floods using GIS, remote sensing, and HEC-HMS rainfall–runoff modeling

2016 ◽  
Vol 47 (6) ◽  
pp. 1142-1160 ◽  
Author(s):  
Mohamed El Alfy
Keyword(s):  
Remote Sensing ◽  
Hydrologic Modeling ◽  
Integrated Approach ◽  
Flash Floods ◽  
Landsat 8 ◽  
Arid Areas ◽  
Rainfall Runoff ◽  
Rapid Urbanization ◽  
Runoff Modeling ◽  
The Impact

This study uses an integrated approach, bringing together geographic information system (GIS), remote sensing, and rainfall–runoff modeling, to assess the urbanization impact on flash floods in arid areas. Runoff modeling was carried out as a function of the catchment characteristics and the maximum daily rainfall parameters. Land-use types were extracted from the supervised classification of SPOT-5 (2010) and Landsat-8 (2015) satellite images and were validated during field checks. Catchment morphometric characteristics were carried out using the correlated Topaz and Arc-Hydro tools. Maximum floods of the catchment were evaluated by coupling GIS and remote sensing with Hydrologic Engineering Center–Hydrologic Modeling System (HEC-HMS) hydrologic modeling. Peak discharges were estimated, and the abstraction losses were computed for different return periods. The model results were calibrated according to actual runoff event. The research shows that rapid urbanization adversely affects hydrological processes, since the sprawl on the alluvial channels is significant. This reduces infiltration into the underlying alluvium and increases runoff, leading to higher flood peaks and volumes even for short duration low intensity rainfall. To retain a considerable amount of water and sediments in these arid areas, construction of small dams at the fingertip channels at the outlet of the lower order sub-basins is recommended.

Evaluation of Assumptions in Soil Moisture Triple Collocation Analysis

2014 ◽  
Vol 15 (3) ◽  
pp. 1293-1302 ◽  
Author(s):  
M. Tugrul Yilmaz ◽  
Wade T. Crow
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Land Surface ◽  
Land Surface Model ◽  
Microwave Remote Sensing ◽  
Surface Model ◽  
Correlated Errors ◽  
Cross Covariance ◽  
Mutual Independence ◽  
The Impact

Abstract Triple collocation analysis (TCA) enables estimation of error variances for three or more products that retrieve or estimate the same geophysical variable using mutually independent methods. Several statistical assumptions regarding the statistical nature of errors (e.g., mutual independence and orthogonality with respect to the truth) are required for TCA estimates to be unbiased. Even though soil moisture studies commonly acknowledge that these assumptions are required for an unbiased TCA, no study has specifically investigated the degree to which errors in existing soil moisture datasets conform to these assumptions. Here these assumptions are evaluated both analytically and numerically over four extensively instrumented watershed sites using soil moisture products derived from active microwave remote sensing, passive microwave remote sensing, and a land surface model. Results demonstrate that nonorthogonal and error cross-covariance terms represent a significant fraction of the total variance of these products. However, the overall impact of error cross correlation on TCA is found to be significantly larger than the impact of nonorthogonal errors. Because of the impact of cross-correlated errors, TCA error estimates generally underestimate the true random error of soil moisture products.

scholarly journals Effects of multi-temporal high-resolution remote sensing products on simulated hydrometeorological variables in a cultivated area (southwestern France)

2017 ◽  
Author(s):  
Jordi Etchanchu ◽  
Vincent Rivalland ◽  
Simon Gascoin ◽  
Jérôme Cros ◽  
Aurore Brut ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Land Cover ◽  
Land Surface ◽  
Agricultural Landscapes ◽  
Annual Precipitation ◽  
Surface Model ◽  
Area Index ◽  
The Impact ◽  
Sentinel 2

Abstract. Agricultural landscapes often include a patchwork of crop fields whose seasonal evolution is dependent on specific crop rotation patterns and phenologies. This temporal and spatial heterogeneity affects surface hydrometeorological processes as simulated by land surface and distributed hydrological models. Sentinel-2 mission satellite remote sensing products allow for the monitoring of land cover and vegetation dynamics at unprecedented spatial resolutions and revisit frequencies (20 m and 5 days, respectively) that are fully compatible with such heterogeneous agricultural landscapes. Here, we evaluate the impact of Sentinel-2-like remote sensing data on the simulation of surface water and energy flux via the ISBA-SURFEX land surface model. The study area is a 24 km by 24 km agricultural zone in southwestern France. An initial reference simulation was conducted from 2006–2010 using the ECOCLIMAP-II database. This global numerical land ecosystem database was created at a 1 km resolution and includes an ecosystem classification with a consistent set of land surface parameters required for the model, such as the Leaf Area Index (LAI) and albedo measures. The LAI of ECOCLIMAP is climatologic and derived from a 2000–2005 analysis of MODIS satellite products. This low resolution induces that several vegetation covers can be mixed in a model cell. The climatic construction of LAI dynamics also suggests that there is no interannual variability in the vegetation cycle. A second simulation was performed by forcing the same model with annual land cover maps and monthly LAI values derived from a series of 105 8 m-resolution Formosat-2 images for the same period. Both simulations were conducted at the parcel scale, i.e., a computation unit covers an area of connected pixels of the same vegetation type (a crop field, forest patch, etc.). To evaluate our simulations, we used in situ measurements of evapotranspiration and latent and sensible heat flux from two eddy covariance stations in the study area. Our results show that the use of Formosat-2 high-resolution products significantly improves simulated evapotranspiration results with respect to ECOCLIMAP-II, especially when a surface is covered with summer crops (the correlation coefficient with monthly measurements is increased by roughly 0.3 and the root mean square error is decreased by roughly 31 %). This finding is attributable to a better description of LAI evolution processes reflected by Formosat-2 data, which further modify soil water content and drainage levels of deep soil reservoirs. Effects on annual drainage patterns remain small but significant, i.e., an increase roughly equivalent to 4 % of annual precipitation levels from Formosat-2 data in comparison to reference values. In smaller proportions, runoff is also increased by roughly 1 % of annual precipitation when using Formosat-2 data. This study illustrates the potential for the Sentinel-2 mission to better represent effects of crop management on water budgeting for large, anthropized river basins.

scholarly journals Deteksi Tinggi Vegetasi di Delta Mahakam dengan Penginderaan Jauh

2019 ◽  
Vol 4 (3) ◽  
pp. 175
Author(s):  
Nanin Anggraini ◽  
Atriyon Julzarika
Keyword(s):  
Remote Sensing ◽  
Ground Surface ◽  
Digital Terrain Model ◽  
Remote Sensing Data ◽  
Surface Model ◽  
Geoid Model ◽  
Alos Palsar ◽  
Vegetation Height ◽  
Vertical Accuracy ◽  
Mahakam Delta

<strong>Detection of Vegetation Height in Mahakam Delta Using Remote Sensing. </strong>The vegetation height is a vertical distance between top of the vegetation to ground surface. Vegetation height is one of the parameters for vegetation growth. There are various methods to measure vegetation height; one of them is the use of remote sensing technology. This study aims to map vegetation height in Mahakam Delta by using height models derived from remote sensing data. Such models are Digital Surface Model (DSM) and Digital Terrain Model (DTM). DSM was generated using a combination of interferometric processing of ALOS PALSAR interferometry, X-SAR, Shuttle Radar Topography Mission (SRTM), and geodetic height of Icesat/GLAS satellite imagery. This integration technique incorporated the Digital Elevation Model (DEM) method. The geoid model used in this study was EGM 2008. The following step was the correction of height errors of DSM. Terrain correction was undertaken to convert DSM into DTM, while vegetation heights were obtained from subtraction of DSM and DTM. Vertical accuracy verification refers to a tolerance of 1.96σ (95%) or ~80 cm. In DSM, a vertical accuracy value of 60.4 cm was obtained so that the DSM is feasible for mapping with scale of 1: 10,000, while the DTM was 37 cm so it is also applicable for mapping with such scale. Based on the subtraction of DSM and DTM, the vegetation heights in Mahakam Delta varied between 0 and 64 m.

scholarly journals Slope stability and rockfall assessment of volcanic tuffs using RPAS with 2-D FEM slope modelling

2018 ◽  
Vol 18 (2) ◽  
pp. 583-597 ◽  
Author(s):  
Ákos Török ◽  
Árpád Barsi ◽  
Gyula Bögöly ◽  
Tamás Lovas ◽  
Árpád Somogyi ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Cross Sections ◽  
Laser Scanning ◽  
Digital Terrain Model ◽  
Field Measurements ◽  
Satellite System ◽  
Surface Model ◽  
Rockfall Hazard ◽  
Terrain Model ◽  
Remote Sensing Techniques

Abstract. Steep, hardly accessible cliffs of rhyolite tuff in NE Hungary are prone to rockfalls, endangering visitors of a castle. Remote sensing techniques were employed to obtain data on terrain morphology and to provide slope geometry for assessing the stability of these rock walls. A RPAS (Remotely Piloted Aircraft System) was used to collect images which were processed by Pix4D mapper (structure from motion technology) to generate a point cloud and mesh. The georeferencing was made by Global Navigation Satellite System (GNSS) with the use of seven ground control points. The obtained digital surface model (DSM) was processed (vegetation removal) and the derived digital terrain model (DTM) allowed cross sections to be drawn and a joint system to be detected. Joint and discontinuity system was also verified by field measurements. On-site tests as well as laboratory tests provided additional engineering geological data for slope modelling. Stability of cliffs was assessed by 2-D FEM (finite element method). Global analyses of cross sections show that weak intercalating tuff layers may serve as potential slip surfaces. However, at present the greatest hazard is related to planar failure along ENE–WSW joints and to wedge failure. The paper demonstrates that RPAS is a rapid and useful tool for generating a reliable terrain model of hardly accessible cliff faces. It also emphasizes the efficiency of RPAS in rockfall hazard assessment in comparison with other remote sensing techniques such as terrestrial laser scanning (TLS).

scholarly journals Potential Dam Breach Analysis and Flood Wave Risk Assessment Using HEC-RAS and Remote Sensing Data: A Multicriteria Approach

Water ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 364
Author(s):  
Emmanouil Psomiadis ◽  
Lefteris Tomanis ◽  
Antonis Kavvadias ◽  
Konstantinos X. Soulis ◽  
Nikos Charizopoulos ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Water Volume ◽  
Surface Model ◽  
Flood Wave ◽  
Dam Breach ◽  
Sensing Data ◽  
Crete Island ◽  
Hydrogeological Characteristics ◽  
The Impact

Dam breach has disastrous consequences for the economy and human lives. Floods are one of the most damaging natural phenomena, and some of the most catastrophic flash floods are related to dam collapses. The goal of the present study is to analyse the impact of a possible failure–collapse on a potentially affected area downstream of the existing Bramianos dam on southern Crete Island. HEC-RAS hydraulic analysis software was used to study the dam breach, the flood wave propagation, and estimate the extent of floods. The analysis was performed using two different relief datasets of the same area: a digital elevation model (DEM) taken from very high-resolution orthophoto images (OPH) of the National Cadastre and Mapping Agency SA and a detailed digital surface model (DSM) extracted from aerial images taken by an unmanned aerial vehicle (UAV). Remote sensing data of the Sentinel-2 satellite and OPH were utilised to create the geographic information system (GIS) layers of a thorough land use/cover classification (LULC) for the potentially flooded area, which was used to assess the impact of the flood wave. Different dam breach and flood scenarios, where the water flows over man-made structures, settlements, and olive tree cultivations, were also examined. The study area is dominated mainly by three geological formations with different hydrogeological characteristics that dictated the positioning and structure of the dam and determine the processes that shape the geomorphology and surface roughness of the floodplain, affecting flow conditions. The results show that the impact of a potential dam break at Bramianos dam is serious, and appropriate management measures should be taken to reduce the risk. The water flow downstream of the collapsed dam depends on the water volume stored in the reservoir. Moreover, the comparison of DSM and DEM cases shows that the detailed DSM may indicate more accurately the surface relief and existing natural obstacles such as vegetation, buildings, and greenhouses, enabling more realistic hydraulic simulation results. Dam breach flood simulations and innovative remote sensing data can provide valuable outcomes for engineers and stakeholders for decision-making and planning in order to confront the consequences of similar incidents worldwide.

scholarly journals FLOOD MANAGEMENT IN BOSNIA AND HERZEGOVINA: ROLE OF REMOTE SENSING AND GIS

2015 ◽  
pp. 49-57
Keyword(s):  
Remote Sensing ◽  
Geographical Information Systems ◽  
Flood Hazard ◽  
Historical Analysis ◽  
Flood Management ◽  
Flood Damage ◽  
Water Levels ◽  
Geographical Information ◽  
Floodplain Management ◽  
Flood Impacts

The worst flooding that ever hit Bosnia was in May 2014. The official estimates indicate that over 1.5 million people were affected in Bosnia and Serbia after a week of flooding. The assessments of the damage in Bosnia go up to €2billion of euro. The loss in floods is estimated 5 to 10% of GDP (as per WorldBank estimate). The effective floodplain management is a combination of the corrective and preventative measures for reducing flood damage. These measures require integrating data from a variety of sources, including zoning, subdivision, or building requirements, and the special-purpose floodplain ordinances.There are varieties of tools to generate a flood forecasting model to identify the potentially affected zones, so as to prioritize for remediation or the damage assessment. Furthermore, it is possible to analyze the time-related data and to explore trends and phenomena, to conduct the historical analysis and ―what–if‖ scenarios, and to track and monitor events such as excessive rainfall, track water levels, etc. Bosnia is just starting to develop these tools and methods and this could be the way to improve capability to tackle such natural disasters. This paper describes some applications of Remote Sensing (RS) and Geographical Information Systems (GIS) in identifying flood hazard zones and flood shelters and are therefore important tools for planners and decision makers. The purpose is to describe a simple and efficient methodology to accurately delineate flood inundated areas, flood-hazard areas, and suitable areas for flood shelter to minimize flood impacts.

scholarly journals Improving evapotranspiration in a land surface model using biophysical variables derived from MSG/SEVIRI satellite

2012 ◽  
Vol 16 (8) ◽  
pp. 2567-2583 ◽  
Author(s):  
N. Ghilain ◽  
A. Arboleda ◽  
G. Sepulcre-Cantò ◽  
O. Batelaan ◽  
J. Ardö ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Real Time ◽  
Land Surface ◽  
Land Surface Model ◽  
Surface Model ◽  
Area Index ◽  
Continental Scale ◽  
Western Africa ◽  
Large Gradient ◽  
The Impact

Abstract. Monitoring evapotranspiration over land is highly dependent on the surface state and vegetation dynamics. Data from spaceborn platforms are desirable to complement estimations from land surface models. The success of daily evapotranspiration monitoring at continental scale relies on the availability, quality and continuity of such data. The biophysical variables derived from SEVIRI on board the geostationary satellite Meteosat Second Generation (MSG) and distributed by the Satellite Application Facility on Land surface Analysis (LSA-SAF) are particularly interesting for such applications, as they aimed at providing continuous and consistent daily time series in near-real time over Africa, Europe and South America. In this paper, we compare them to monthly vegetation parameters from a database commonly used in numerical weather predictions (ECOCLIMAP-I), showing the benefits of the new daily products in detecting the spatial and temporal (seasonal and inter-annual) variability of the vegetation, especially relevant over Africa. We propose a method to handle Leaf Area Index (LAI) and Fractional Vegetation Cover (FVC) products for evapotranspiration monitoring with a land surface model at 3–5 km spatial resolution. The method is conceived to be applicable for near-real time processes at continental scale and relies on the use of a land cover map. We assess the impact of using LSA-SAF biophysical variables compared to ECOCLIMAP-I on evapotranspiration estimated by the land surface model H-TESSEL. Comparison with in-situ observations in Europe and Africa shows an improved estimation of the evapotranspiration, especially in semi-arid climates. Finally, the impact on the land surface modelled evapotranspiration is compared over a north–south transect with a large gradient of vegetation and climate in Western Africa using LSA-SAF radiation forcing derived from remote sensing. Differences are highlighted. An evaluation against remote sensing derived land surface temperature shows an improvement of the evapotranspiration simulations.

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