Safer_RAIN: A DEM-based hierarchical filling-&-spilling algorithm for pluvial flood hazard assessment and mapping across large urban areas

The increase in frequency and intensity of extreme precipitation events caused by the changing climate (e.g., cloudbursts, rainstorms, heavy rainfall, hail, heavy snow), combined with the high population density and concentration of assets, makes urban areas particularly vulnerable to pluvial flooding. Hence, assessing their vulnerability under current and future climate scenarios is of paramount importance. Detailed hydrologic-hydraulic numerical modeling is resource intensive and therefore scarcely suitable for performing consistent hazard assessments across large urban settlements. Given the steadily increasing availability of LiDAR (Light Detection And Ranging) high-resolution DEMs (Digital Elevation Models), several studies highlighted the potential of fast-processing DEM-based methods, such as the Hierarchical Filling-&-Spilling or Puddle-to-Puddle Dynamic Filling-&-Spilling Algorithms (abbreviated herein as HFSAs). We develop a fast-processing HFSA, named Safer_RAIN, that enables mapping of pluvial flooding in large urban areas by accounting for spatially distributed rainfall input and infiltration processes through a pixel-based Green-Ampt model. We present the first applications of the algorithm to two case studies in Northern Italy. Safer_RAIN output is compared against ground evidence and detailed output from a two-dimensional (2D) hydrologic and hydraulic numerical model (overall index of agreement between Safer_RAIN and 2D benchmark model: sensitivity and specificity up to 71% and 99%, respectively), highlighting potential and limitations of the proposed algorithm for identifying pluvial flood-hazard hotspots across large urban environments

Urban flood modelling : a GIS based approach in Lomma, Skåne region

Urbanization triggers flooding because it replaces pervious land surfaces with impervious surfaces that have less capacity to infiltrate and store water into the ground. Detailed analysis and modelling of flooding in urban areas can be performed with GIS-based distributed hydrological models. However, the implementation of these models require high-level proficiency in GIS and hydrology. Thus, many municipalities hire consultants to do the task. In this study, a GIS-based model that can perform urban flood modelling is developed. The process begins with pre-processing the original DEM so that it represents the urban terrain with its constructed streets and building that can change the direction of drainage path. This is done through integrating spatial data using Arc Hydro tools. Flow routing of water over the modified DEM is then calculated using two flow direction algorithms (1) the deterministic eight-node algorithm (D8) and (2) the Triangular Form Based Multiple Flow algorithm (TFM). D8 algorithm assumes that flow at a point follows only the steepest downhill slope to one of the eight possible directions. TFM algorithm on the other hand estimates flow distribution values proportionally to the slope gradient in each direction. The effect of street inlets flow interception is introduced in the analysis through preparing a weight raster. To develop the weight raster, two approaches are applied depending on which algorithm is used to assign flow direction over the terrain. In D8 method, flow accumulation at street inlet points is calculated from the sub-watershed areas delineated for each inlet point. Weight value assignment of cells within a sub-watershed is then calculated as a proportion of volume to be consumed by street inlet to the total volume generated from the sub-watershed. In TFM method, flow accumulation at inlets is calculated by running TFM algorithm with input DEM having since cells at locations of street inlets. Weight value assignment of cells is done by reducing the flow which is intercepted by inlets from the flow accumulation value at sink cells. In addition, the capacity of street inlets to intercept flow is also estimated. This study shows the capability of performing flooding in GIS environment. The results also show that the outcome of GIS-based urban flood modelling is different depending on which algorithm is used to calculate flow direction. Results of flow accumulation before the inclusion of street inlets interception effect in the analysis is 57,271 m3 and 45,028 m3 using D8 and TFM methods respectively. After street inlets interception effect is included in the analysis however, the results show that weighted flow accumulation is reduced to 33,316 m3 and 10,893 m3 using D8 and TFM methods respectively. In addition, 202 flooding incidents at sink cells are identified using D8 method, this number drops to 80 sink cells using TFM method.Simplified GIS-based models for urban flood modelling Urbanization replaces pervious surfaces by impervious ones having low capacity to infiltrate and store water into the ground. GIS-based distributed hydrological models such as PCSWMM and Mike Urban can perform a detailed analysis and modelling of flooding in urban areas. However, the implementation of such models requires high-level proficiency in hydrology and GIS. In addition, this approach is generally beyond the municipality’s budget in time and cost. For this reason, municipalities often hire consultants to do this. In this study, simplified GIS-based models are developed to perform flooding in urban environment. DEM can be used for watershed boundary delineation and drainage pattern extraction in rural environment. However, in urban areas similar analysis is complicated due to the constructed terrain of streets and buildings which can change the direction of drainage path. Therefore, the original DEM has to be modified so that it represents the urban terrain more accurately. This is done in the DEM pre-processing step through integration of spatial data such as street inlets, buildings and the DEM in Arc Hydro tools and ArcGIS. In the next step flow routing of water over the terrain is calculated using two flow direction algorithms namely the Deterministic eight-node (D8) algorithm and Triangular Form Based Multiple Flow Direction (TFM) algorithm. D8 algorithm assumes that in a 3 X 3 cells moving window flow at a point follows only the steepest downhill slope to one of the eight possible directions. TFM algorithm on the other hand estimates flow distribution values proportionally to the slope gradient in each direction. Flow interception by the stormwater collection points (street inlets) is included in the analysis. To do this street inlets flow interception capacity is estimated and used to develop a weight raster. The developed weight raster is then used as input weight during flow accumulation calculation. To prepare a weight raster input using D8 flow direction algorithm, first sub-watershed areas contributing flow to each of the street inlets are delineated and flow accumulation generated by the sub-catchments is calculated. Weight value assignment of cells within a sub-watershed is then calculated as a proportion of volume to be consumed by street inlet to the total volume generated from the sub-watershed. In TFM method, first sink structures are created at locations of street inlet points. This DEM with sinks is then used to calculate flow direction and flow accumulation in MATLAB. Flow accumulation values at the sink cells are then extracted and used to prepare weight raster. Weight value assignment is done by reducing a value which is equal to flow interception capacity of street inlets from the extracted flow accumulation values at street inlets. The weight raster is used as input to run flow accumulation with weight using a different tool that can operate with negative value. This study shows the capability of GIS to perform flooding in urban area. The results also show that GIS-based flood modelling produce different results depending on which algorithm is used to calculate flow direction, Flow accumulation before the inclusion of street inlets interception effect in the analysis is 57,271 m3 and 45,028 m3 using D8 and TFM methods respectively. After street inlets interception effect is included in the analysis however, the results show that weighted flow accumulation of 33,316 m3 and 10,893 m3 using D8 and TFM methods respectively. In addition, 202 flooding incidents at sink cells are identified using the D8 method, this number drops to 80 sink cell using TFM method

Enhancing Operational Flood Detection Solutions through an Integrated Use of Satellite Earth Observations and Numerical Models

Among natural disasters floods are the most common and widespread hazards worldwide (CRED and UNISDR, 2018). Thus, making communities more resilient to flood is a priority, particularly in large flood-prone areas located in emerging countries, because the effects of extreme events severely setback the development process (Wright, 2013). In this context, operational flood preparedness requires novel modeling approaches for a fast delineation of flooding in riverine environments. Starting from a review of advances in the flood modeling domain and a selection of the more suitable open toolsets available in the literature, a new method for the Rapid Estimation of FLood EXtent (REFLEX) at multiple scales (Arcorace et al., 2019) is proposed. The simplified hydraulic modeling adopted in this method consists of a hydro-geomorphological approach based on the Height Above the Nearest Drainage (HAND) model (Nobre et al., 2015). The hydraulic component of this method employs a simplified version of fluid mechanic equations for natural river channels. The input runoff volume is distributed from channel to hillslope cells of the DEM by using an iterative flood volume optimization based on Manning\u2019s equation. The model also includes a GIS-based method to expand HAND contours across neighbor watersheds in flat areas, particularly useful in flood modeling expansion over coastal zones. REFLEX\u2019s flood modeling has been applied in multiple case studies in both surveyed and ungauged river basins. The development and the implementation of the whole modeling chain have enabled a rapid estimation of flood extent over multiple basins at different scales. When possible, flood modeling results are compared with reference flood hazard maps or with detailed flood simulations. Despite the limitations of the method due to the employed simplified hydraulic modeling approach, obtained results are promising in terms of flood extent and water depth. Given the geomorphological nature of the method, it does not require initial and boundary conditions as it is in traditional 1D/2D hydraulic modeling. Therefore, its usage fits better in data-poor environments or large-scale flood modeling. An extensive employment of this slim method has been adopted by CIMA Research Foundation researchers for flood hazard mapping purposes over multiple African countries. As collateral research, multiple types of Earth observation (EO) data have been employed in the REFLEX modeling chain. Remotely sensed data from the satellites, in fact, are not only a source to obtain input digital terrain models but also to map flooded areas. Thus, in this work, different EO data exploitation methods are used for estimating water extent and surface height. Preliminary results by using Copernicus\u2019s Sentinel-1 SAR and Sentinel-3 radar altimetry data highlighted their potential mainly for model calibration and validation. In conclusion, REFLEX combines the advantages of geomorphological models with the ones of traditional hydraulic modeling to ensure a simplified steady flow computation of flooding in open channels. This work highlights the pros and cons of the method and indicates the way forward for future research in the hydro-geomorphological domain

Quality Assessment of Hydrogeomorphological Features Derived from Digital Terrain Models

Digital terrain models (DTM) provide a model for representing the continuous earth elevation surface that can contain errors introduced by the main phases of generation and modelling. Uncertainty of the model is rarely considered by users. Assessment of uncertainty require information on the nature, amount and spatial structure of the errors. DTMs of di®erent original resolution were compared in order to assess the quality of derived hydrological and morphological features. SRTM dataset with resolution of 100m, DEM dataset mosaic from various sources with a resolution of 60m and ASTER derived dataset with a resolution of 30m were used. The error propagation was modelled with a stochastic approach. The probabilistic distribution of extracted hydrological features was drawn considering the spatial structure of errors in the datasets. The features considered were stream network and watershed divides net. The distribution of the Strahler order of the features was studied. An analysis of the overall probability of features extracted from variously prepared datasets was carried in order to get information on where is the most probable stream network or watershed divides net.JRC.H.6-Spatial data infrastructure

A GIS-based methodological framework to identify superficial water sources and their corresponding conduction paths for gravity-driven irrigation systems in developing countries

The limited availability of fresh water is a major constraint to agricultural productivity and livelihood security in many developing countries. Within the coming decades, smallholder farmers in drought-prone areas are expected to be increasingly confronted with local water scarcity problems, but their access to technological knowledge and financial resources to cope with these problems is often limited. In this article, we present a methodological framework that allows for identifying, in a short period of time, suitable and superficial water sources, and cost-effective water transportation routes for the provisioning of gravity-driven irrigation systems. As an implementation of the framework, we present the automated and extensible geospatial toolset named “AGRI’’, and elaborate a case study in Western Honduras, where the methodology and toolset were applied to provide assistance to field technicians in the process of identifying water intake sites and transportation routes. The case study results show that 28 % of the water intake sites previously identified by technicians (without the support of AGRI) were found to be not feasible for gravity-driven irrigation. On the other hand, for the feasible water intake sites, AGRI was able to provide viable and shorter water transportation routes to farms in 70 % of the cases. Furthermore, AGRI was able to provide alternative feasible water intake sites for all considered farms, with correspondingly viable water transportation routes for 74 % of them. These results demonstrate AGRI’s potential to reduce time, costs and risk of failure associated with the development of low-cost irrigation systems, which becomes increasingly needed to support the livelihoods of some of the world’s most vulnerable populations

Identifying Locations Of Highly Eroded Agricultural Land In The Devils Lake Basin, ND Using GIS Terrain Analysis Modeling

Soil erosion modeling using terrain analysis holds great potential due to the simplicity of the models, and the ease in running the analysis in a GIS. Terrain analysis of the upper Devils Lake basin was conducted using a 3-meter Light Detection and Ranging-derived digital elevation model. Portions of the Mauvais Coulee and Calio Coulee watersheds in the basin were analyzed to evaluate soil erosion potential and determine if terrain analysis was an accurate tool for modeling erosion in this fairly flat landscape. The analysis used slope, flow accumulation, and stream power index (SPI) within a GIS to identify highly eroded areas. The study found that 1.5% of the 262.8 km2 study area exhibited channelized erosion. It was determined that the terrain analysis accurately identified 92 (79%) of the 116 survey points established for field verification. Finally, the findings support that the use of terrain analysis for erosion modeling in the Devils Lake basin is highly accurate, and can be a useful tool in locating and implementing best management practices (BMPs) to aid in the reduction of surface runoff entering Mauvais and Calio Coulees from channelized erosion

Mapping Techniques For Soil Erosion: Modeling Stream Power Index In Eastern North Dakota

ABSTRACT Soil erosion is a worldwide problem that can negatively affect surface water through the introduction of sediment, nutrients (eg. nitrogen, phosphorus), pesticides, and other chemicals. Soil erosion is often exacerbated by agricultural and other types of land use. The objective of this study was to identify gully locations in agricultural fields adjacent to the Turtle and Forest rivers in eastern North Dakota that accumulate surface flow resulting in areas of critical surface erosion in a GIS using the Stream Power Index (SPI). A field survey was conducted to verify the accuracy of the terrain analysis at identifying 391 gully and inlet locations. Sediment samples were collected from 44 inlets/gully locations and analyzed for soil texture, pH and conductivity to characterize the material being eroded and transported. The pH levels for the soil samples ranged from neutral to moderately alkaline and the EC values represented soils that were either non-saline or slightly saline. Sand was the dominant separate for both study areas. This study found that SPI signatures at or above critical erosion levels can be used to target precision conservation in individual fields adjacent to the Turtle and Forest rivers

Using Lidar Data to Analyse Sinkhole Characteristics Relevant for Understory Vegetation under Forest Cover\u2014Case Study of a High Karst Area in the Dinaric Mountains

In this article, we investigate the potential for detection and characterization of sinkholes under dense forest cover by using airborne laser scanning data. Laser pulse returns from the ground provide important data for the estimation of digital elevation model (DEM), which can be used for further processing. The main objectives of this study were to map and determine the geomorphometric characteristics of a large number of sinkholes and to investigate the correlations between geomorphology and vegetation in areas with such characteristics. The selected study area has very low anthropogenic influences and is particularly suitable for studying undisturbed karst sinkholes. The information extracted from this study regarding the shapes and depths of sinkholes show significant directionality for both orientation of sinkholes and their distribution over the area. Furthermore, significant differences in vegetation diversity and composition occur inside and outside the sinkholes, which indicates their presence has important ecological impacts