scholarly journals Evaluation of Hydrological and Hydraulic Models Applied in Typical Mediterranean Ungauged Watersheds Using Post-Flash-Flood Measurements

Hydrology ◽  
2020 ◽  
Vol 7 (1) ◽  
pp. 12 ◽  
Author(s):  
Aristeidis Kastridis ◽  
Dimitrios Stathis
Keyword(s):  
Goodness Of Fit ◽  
Flash Flood ◽  
Hydraulic Models ◽  
Rain Gauges ◽  
Critical Success ◽  
Small Watersheds ◽  
Flood Simulations ◽  
Flood Generation ◽  
Analysis System ◽  
Ungauged Watersheds

In this paper, three different flash floods episodes were analyzed, which occurred in October 2006, February 2010, and June 2018 in the Chalkidiki peninsula (North Greece). The Soil Conservation Service (SCS) model and a revised assessment of the CN parameter were applied to estimate the flood hydrographs, and Hydrologic Engineering Center’s-River Analysis System (HEC-RAS) software was used for the flood simulations. Initially, hydrological and hydraulic models were calibrated at Vatonias watershed (240.90 km2, North Greece), where three rain gauges and one water level station are located. Vatonias is located very close to the Stavros ungauged watersheds and presents similar geomorphology and land use conditions. The effectiveness and accuracy of the methodology were validated using post-flash-flood measurements. The root mean square error goodness of fit was used to compare the observed and simulated flood depths. Critical success index was calculated for the assessment of the accuracy of observed and modeled flooded areas. The results showed that the dense forest vegetation was not capable of preventing the flash flood generation or reducing the peak discharge, especially in small watersheds characterized by short concentration times. The main cause of flash flood generation was the human interference that influenced the hydraulic characteristics of streams and floodplains. The revised assessment of the CN parameter enhanced the estimation and spatial distribution of CN over the entire watershed. The results revealed that the proposed methodology could be a very useful tool to researchers and policy makers for flood risk assessment of higher accuracy and effectiveness in ungauged Mediterranean watersheds.

Impact of the models structure uncertainty in flood simulations: Simbach case study

2020 ◽  
Author(s):  
Qing Lin ◽  
Jorge Leandro ◽  
Markus Disse ◽  
Daniel Sturm
Keyword(s):  
Flash Flood ◽  
Drainage System ◽  
Model Structure ◽  
Flood Simulation ◽  
Hydraulic Models ◽  
Uncertainty Factor ◽  
Model Component ◽  
Model Structure Uncertainty ◽  
Flood Simulations ◽  
Model Structures

<p>The quantification of model structure uncertainty on hydraulic models is very important for flash flood simulations. The choice of an appropriate model structure complexity and assessment of the impacts due to infrastructure failure can have a huge impact on the simulation results. To assess the risk of flash floods, coupled hydraulic models, including 1D-sewer drainage and 2D-surface run-off models are required for urban areas because they include the bidirectional water exchange, which occurs between sewer and overland flow in a city [1]. By including various model components, we create different model structures. For example, modelling the inflow to the city with the 2D surface-runoff or with the delineated 1D model; including the sewer system or use a surrogate as an alternative; modifying the connectivity of manholes and pumps; or representing the drainage system failures during flood events. As the coupling pattern becomes complex, quantifying the model structure uncertainty is essential for the model structure evaluation. If one model component leads to higher model uncertainty, it is reasonable to conclude that the new component has a large impact in our model and therefore needs to be accounted for; if one component has a less impact in the overall uncertainty, then the model structure can be simplified, by removing that model component.</p> <p>In this study, we set up seven different model structures [2] for the German city of Simbach. By comparison with two inflow calculation types (1D-delineated inflow or 2D-catchment), the existence of drainage system and infrastructure failures, the Model Uncertainty Factor (MUF) is calculated to quantify the model structure uncertainties and further trade-off values with Parameter Uncertainty Factor (PUF) [3]. Finally, we can obtain a more efficient hydraulic model with the essential model structure for urban flash flood simulation.</p> <p> </p> <ol>1. Leandro, J., Chen, A. S., Djordjevic, S., and Dragan, S. (2009). "A comparison of 1D/1D and 1D/2D coupled hydraulic models for urban flood simulation." Journal of Hydraulic Engineering-ASCE, 6(1):495-504.</ol> <ol>2. Leandro, J., Schumann, A., and Pfister, A. (2016). A step towards considering the spatial heterogeneity of urban, key features in urban hydrology flood modelling. J. Hydrol., Elsevier, 535 (4), 356-365.</ol> <ol>3. Van Zelm, R., Huijbregts, M.A.J. (2013). Quantifying the trade-off between parameter and model structure uncertainty in life cycle impact assessment, Environ. Sci. Technol., 47(16), pp. 9274-9280.</ol> <p> </p>

Comparing Three Hydrological Models for Flash Flood Simulations in 13 Humid and Semi-humid Mountainous Catchments

2021 ◽  
Vol 35 (5) ◽  
pp. 1547-1571
Author(s):  
Xiaoyan Zhai ◽  
Liang Guo ◽  
Ronghua Liu ◽  
Yongyong Zhang ◽  
Yongqiang Zhang
Keyword(s):  
Flash Flood ◽  
Hydrological Models ◽  
Mountainous Catchments ◽  
Flood Simulations

scholarly journals Rainfall Threshold for Flash Flood Warning Based on Model Output of Soil Moisture: Case Study Wernersbach, Germany

Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1061
Author(s):  
Thanh Thi Luong ◽  
Judith Pöschmann ◽  
Rico Kronenberg ◽  
Christian Bernhofer
Keyword(s):  
Soil Moisture ◽  
Flash Flood ◽  
Rainfall Threshold ◽  
Probability Of Detection ◽  
Water Levels ◽  
Critical Success ◽  
Flood Warning ◽  
Critical Discharge ◽  
Critical Success Index

Convective rainfall can cause dangerous flash floods within less than six hours. Thus, simple approaches are required for issuing quick warnings. The flash flood guidance (FFG) approach pre-calculates rainfall levels (thresholds) potentially causing critical water levels for a specific catchment. Afterwards, only rainfall and soil moisture information are required to issue warnings. This study applied the principle of FFG to the Wernersbach Catchment (Germany) with excellent data coverage using the BROOK90 water budget model. The rainfall thresholds were determined for durations of 1 to 24 h, by running BROOK90 in “inverse” mode, identifying rainfall values for each duration that led to exceedance of critical discharge (fixed value). After calibrating the model based on its runoff, we ran it in hourly mode with four precipitation types and various levels of initial soil moisture for the period 1996–2010. The rainfall threshold curves showed a very high probability of detection (POD) of 91% for the 40 extracted flash flood events in the study period, however, the false alarm rate (FAR) of 56% and the critical success index (CSI) of 42% should be improved in further studies. The proposed adjusted FFG approach has the potential to provide reliable support in flash flood forecasting.

Modelling Sediment Transport in the disastrous Flash Flood of November 2017 in Mandra (Attica, Greece)  

2021 ◽  
Author(s):  
Vasiliki Sant ◽  
George Mitsopoulos ◽  
Aristides Bloutsos ◽  
Anastasios Stamou
Keyword(s):  
Sediment Transport ◽  
Flash Flood ◽  
Catastrophic Event ◽  
Marine Research ◽  
National Network ◽  
The Third ◽  
Debris Transport ◽  
Sediment Transport Equation ◽  
Analysis System ◽  
General Secretariat

<p> </p><p><strong>Abstract</strong></p><p>The flash flood in Mandra on the 15<sup>th</sup> of November 2017 was the third most disastrous “November” flood in Attica; it was characterized by heavy sediment and debris transport that can be easily observed in Figure 1.</p><p>We applied the Hydrologic Engineering Center's-River Analysis System (HEC-RAS) to model sediment transport using the Ackers-White sediment transport equation that is engraved in HEC-RAS to analyze sediment transport characteristics. The required input data were based on a limited number of available studies, which mainly include a survey performed by the Hellenic Centre for Marine Research in the coastal area of the Elefsis Bay where sediments were deposited after the catastrophic event. We compared the results of the model with calculations performed within a previous Thesis in 2018 using TELEMAC-2D and SISYPHE.</p><p>The present paper is based on the Diploma Thesis of the first author; it was performed within the project “National Network on Climate Change and its Impacts (CLIMPACT)” of the General Secretariat of Research and Technology.</p><p> </p><p><img src="https://contentmanager.copernicus.org/fileStorageProxy.php?f=gepj.5d3d3b91860061319301161/sdaolpUECMynit/12UGE&app=m&a=0&c=bc7fbb3ecf180060dec33436ebc2faea&ct=x&pn=gepj.elif&d=1" alt=""></p><p>Figure 1. The greater area of Mandra (a) before and (b) after the flood event</p>

scholarly journals Optimization of Rain Gauge Networks for Arid Regions Based on Remote Sensing Data

2021 ◽  
Vol 13 (21) ◽  
pp. 4243
Author(s):  
Mona Morsy ◽  
Ruhollah Taghizadeh-Mehrjardi ◽  
Silas Michaelides ◽  
Thomas Scholten ◽  
Peter Dietrich ◽  
...  
Keyword(s):  
Arid Regions ◽  
Flash Flood ◽  
Primary Source ◽  
Remote Sensing Data ◽  
Test Site ◽  
Rain Gauge ◽  
Cumulative Distribution ◽  
Climatic Data ◽  
Empirical Cumulative Distribution Function ◽  
Rain Gauges

Water depletion is a growing problem in the world’s arid and semi-arid areas, where groundwater is the primary source of fresh water. Accurate climatic data must be obtained to protect municipal water budgets. Unfortunately, the majority of these arid regions have a sparsely distributed number of rain gauges, which reduces the reliability of the spatio-temporal fields generated. The current research proposes a series of measures to address the problem of data scarcity, in particular regarding in-situ measurements of precipitation. Once the issue of improving the network of ground precipitation measurements is settled, this may pave the way for much-needed hydrological research on topics such as the spatiotemporal distribution of precipitation, flash flood prevention, and soil erosion reduction. In this study, a k-means cluster analysis is used to determine new locations for the rain gauge network at the Eastern side of the Gulf of Suez in Sinai. The clustering procedure adopted is based on integrating a digital elevation model obtained from The Shuttle Radar Topography Mission (SRTM 90 × 90 m) and Integrated Multi-Satellite Retrievals for GPM (IMERG) for four rainy events. This procedure enabled the determination of the potential centroids for three different cluster sizes (3, 6, and 9). Subsequently, each number was tested using the Empirical Cumulative Distribution Function (ECDF) in an effort to determine the optimal one. However, all the tested centroids exhibited gaps in covering the whole range of elevations and precipitation of the test site. The nine centroids with the five existing rain gauges were used as a basis to calculate the error kriging. This procedure enabled decreasing the error by increasing the number of the proposed gauges. The resulting points were tested again by ECDF and this confirmed the optimum of thirty-one suggested additional gauges in covering the whole range of elevations and precipitation records at the study site.

scholarly journals Quality-Based Combination of Multi-Source Precipitation Data

2020 ◽  
Vol 12 (11) ◽  
pp. 1709 ◽  
Author(s):  
Anna Jurczyk ◽  
Jan Szturc ◽  
Irena Otop ◽  
Katarzyna Ośródka ◽  
Piotr Struzik
Keyword(s):  
Spatial Resolution ◽  
Flash Flood ◽  
Radar Data ◽  
Rain Gauge ◽  
Quality Information ◽  
Precipitation Data ◽  
Spatial Error ◽  
Rain Gauges ◽  
Precipitation Measurement ◽  
Temporal And Spatial

A quantitative precipitation estimate (QPE) provides basic information for the modelling of many kinds of hydro-meteorological processes, e.g., as input to rainfall-runoff models for flash flood forecasting. Weather radar observations are crucial in order to meet the requirements, because of their very high temporal and spatial resolution. Other sources of precipitation data, such as telemetric rain gauges and satellite observations, are also included in the QPE. All of the used data are characterized by different temporal and spatial error structures. Therefore, a combination of the data should be based on quality information quantitatively determined for each input to take advantage of a particular source of precipitation measurement. The presented work on multi-source QPE, being implemented as the RainGRS system, has been carried out in the Polish national meteorological and hydrological service for new nowcasting and hydrological platforms in Poland. For each of the three data sources, different quality algorithms have been designed: (i) rain gauge data is quality controlled and, on this basis, spatial interpolation and estimation of quality field is performed, (ii) radar data are quality controlled by RADVOL-QC software that corrects errors identified in the data and characterizes its final quality, (iii) NWC SAF (Satellite Application Facility on support to Nowcasting and Very Short Range Forecasting) products for both visible and infrared channels are combined and the relevant quality field is determined from empirical relationships that are based on analyses of the product performance. Subsequently, the quality-based QPE is generated with a 1-km spatial resolution every 10 minutes (corresponding to radar data). The basis for the combination is a conditional merging technique that is enhanced by involving detailed quality information that is assigned to individual input data. The validation of the RainGRS estimates was performed taking account of season and kind of precipitation.

scholarly journals Improved input to distributed hydrologic model in areas with sparse subdaily rainfall data using multivariate daily rainfall disaggregation

2018 ◽  
Vol 20 (4) ◽  
pp. 784-797 ◽  
Author(s):  
Marija Ivković ◽  
Andrijana Todorović ◽  
Jasna Plavšić
Keyword(s):  
Daily Rainfall ◽  
Flood Forecasting ◽  
Rain Gauge ◽  
Hydrologic Model ◽  
Rainfall Data ◽  
Rain Gauges ◽  
Observation Network ◽  
Hourly Rainfall ◽  
Extreme Flood ◽  
Flood Simulations

Abstract Flood forecasting relies on good quality of observed and forecasted rainfall. In Serbia, the recording rain gauge network is sparse and rainfall data mainly come from dense non-recording rain gauges. This is not beneficial for flood forecasting in smaller catchments and short-duration events, when hydrologic models operating on subdaily scale are applied. Moreover, differences in rainfall amounts from two types of gauges can be considerable, which is common in operational hydrological practice. This paper examines the possibility of including daily rainfall data from dense observation networks in flood forecasting based on subdaily data, using the extreme flood event in the Kolubara catchment in May 2014 as a case study. Daily rainfall from a dense observation network is disaggregated to hourly scale using the MuDRain multivariate disaggregation software. The disaggregation procedure results in well-reproduced rainfall dynamics and adjusts rainfall volume to the values from the non-recording gauges. The fully distributed wflow_hbv model, which is under development as a forecasting tool for the Kolubara catchment, is used for flood simulations with two alternative hourly rainfall data. The results show an improvement when the disaggregated rainfall from denser network is used, thus indicating the significance of better representation of rainfall temporal and spatial variability for flood forecasting.

scholarly journals An objective cross-validation framework for mapping rainfall hazard based on rain gauge data

2018 ◽  
Author(s):  
Juliette Blanchet ◽  
Emmanuel Paquet ◽  
Pradeebane Vaittinada Ayar ◽  
David Penot
Keyword(s):  
Goodness Of Fit ◽  
Cumulative Distribution Function ◽  
Cross Validation ◽  
Daily Rainfall ◽  
Rain Gauge ◽  
Cumulative Distribution ◽  
Rain Gauge Data ◽  
Weather Patterns ◽  
Rain Gauges ◽  
Validation Framework

Abstract. We propose an objective framework for estimating rainfall cumulative distribution function within a region when data are only available at rain gauges. Our methodology is based on the evaluation of several goodness-of-fit scores in a cross-validation framework, allowing to assess goodness-of-fit of the full distribution but with a particular focus on its tail. Cross-validation is applied both to select the most appropriate statistical distribution at station locations and to validate the mapping of these distributions. Our methodology is applied to daily rainfall in the Ardèche catchment in South of France, a 2260 km2 catchment with strong disparities in rainfall distribution. Results show preference for a mixture of Gamma distribution over seasons and weather patterns, with parameters interpolated with thin plate spline across this region. However the framework presented in this paper is general and could be likewise applied in any region, with possibly different conclusion depending on the subsequent rainfall processes.

scholarly journals Flash flood occurrence and relation to the rainfall hazard in a highly urbanized area

2015 ◽  
Vol 3 (5) ◽  
pp. 3119-3149
Author(s):  
K. Papagiannaki ◽  
K. Lagouvardos ◽  
V. Kotroni ◽  
A. Bezes
Keyword(s):  
Flash Flood ◽  
Flood Hazard ◽  
Local Level ◽  
Geographical Area ◽  
Fire Service ◽  
Flood Events ◽  
Rain Gauges ◽  
Weather Events ◽  
Urbanized Region

Abstract. The paper examines the flash flood events that occurred during a decade in the Attica prefecture, the most urbanized region of Greece, with the aim of assessing the local vulnerability to the flash flood hazard and the effect of rainfall upon the magnitude of the induced damages. The analysis incorporates rainfall records from a network of 28 surface meteorological stations and information on the spatial distribution of the flash flood events that is derived from the active database of damaging weather events maintained by the atmospheric modelling group of the National Observatory of Athens. The main findings concern the relation between the flash flood impact, as measured by the Fire Service operations in flooded properties, and precipitation in various time intervals, as well as the possibility to define rainfall intensity thresholds for flood triggering at a more local level. It is shown that the quality of the produced thresholds depends on the distribution and density of the rain gauges that cover each specified geographical area of the Attica region.

scholarly journals Sub-daily hydrological-hydrodynamic simulation in flash flood basins: Una river (Pernambuco/Brazil)

2020 ◽  
Vol 15 (5) ◽  
pp. 1
Author(s):  
Otacílio Correia Lima Neto ◽  
Alfredo Ribeiro Neto ◽  
Fellipe Henrique Borba Alves ◽  
José Almir Cirilo
Keyword(s):  
Mean Squared Error ◽  
Flash Flood ◽  
Infiltration Rate ◽  
Hydrodynamic Simulation ◽  
Mountainous Regions ◽  
Coefficient Estimation ◽  
Numerical Instabilities ◽  
Analysis System ◽  
Sensitive Parameters ◽  
The City

Flash floods are observed in the Una River Basin, Pernambuco/Brazil. This particular type of flood is a short-duration hydrological event with occurrence of the peak flow within minutes to few hours after the onset of the rainfall, taking place typically in mountainous regions. The objective of the paper was to assess the sub-daily hydrological and hydrodynamic modeling of flood events in 2011 and 2017. Sub-daily precipitation and streamflow were applied to the models Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) and River Analysis System (HEC-RAS). Model evaluation methods such as Nash-Sutcliffe efficiency (NSE), percent bias, and the ratio of the root mean squared error to the standard deviation of measured data (RSR) were used in the calibration process. The maximum infiltration rate and the Snyder peak coefficient estimation were the most sensitive parameters in the hydrological model. The calibration of the HEC-HMS showed good performances (Catende station NSE=0.78 and RSR=0.46; Palmares station NSE=0.68 and RSR=0.57). During HEC-RAS 1D flow simulations, steep regions in the Una River caused numerical instabilities. The 2D solution was needed to overcome this problem, allowing us to represent the water level in the city of Palmares satisfactorily.

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