scholarly journals Reconstruction of the 1874 <i>Santa Tecla</i>'s rainstorm in Western Catalonia (NE Spain) from flood marks and historical accounts

2010 ◽  
Vol 10 (11) ◽  
pp. 2317-2325 ◽  
Author(s):  
J. C. Balasch ◽  
J. L. Ruiz-Bellet ◽  
J. Tuset ◽  
J. Martín de Oliva
Keyword(s):  
Soil Moisture ◽  
Flash Flood ◽  
Hydrological Modelling ◽  
Probability Analysis ◽  
Ungauged Basins ◽  
Flood Probability ◽  
Historical Accounts ◽  
Ne Spain

Abstract. The Santa Tecla flash flood, a very heavy event occurred in western Catalonia (NE Spain) in 1874, was reconstructed with hydraulic and hydrological modelling tools in three basins. The hydrograph obtained in a first step and the basin soil moisture information ultimately allowed the estimation of the range of the rainstorm magnitude which caused the flash flood. The reconstruction of historical floods has proved useful to improve the flood probability analysis, especially in ungauged basins.

scholarly journals Reconstructing the 1874 Santa Tecla flash flood in the Ondara River (Ebro Basin, NE Spain)

2010 ◽  
Vol 26 ◽  
pp. 45-48 ◽  
Author(s):  
J. C. Balasch ◽  
J. Tuset ◽  
J. L. Ruiz-Bellet
Keyword(s):  
Soil Moisture ◽  
Iberian Peninsula ◽  
Flash Flood ◽  
Hydrological Modelling ◽  
Probability Analysis ◽  
Ungauged Basins ◽  
Ebro Basin ◽  
Flood Probability ◽  
Ne Iberian Peninsula ◽  
Ne Spain

Abstract. The Santa Tecla flash flood, a very heavy event occurred in Tàrrega (Catalonia, NE Iberian Peninsula) in 1874, was reconstructed with hydraulic and hydrological modelling tools. The hydrograph obtained in a first stage and the basin soil moisture information ultimately allowed the estimation of the range of the rainstorm magnitude which caused the flash flood. The reconstruction of historical floods has proved useful to improve the flood probability analysis, especially in ungauged basins.

Flash flood warning based on rainfall thresholds and soil moisture conditions: An assessment for gauged and ungauged basins

2008 ◽  
Vol 362 (3-4) ◽  
pp. 274-290 ◽  
Author(s):  
Daniele Norbiato ◽  
Marco Borga ◽  
Silvia Degli Esposti ◽  
Eric Gaume ◽  
Sandrine Anquetin
Keyword(s):  
Soil Moisture ◽  
Flash Flood ◽  
Ungauged Basins ◽  
Rainfall Thresholds ◽  
Flood Warning ◽  
Moisture Conditions

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.

scholarly journals SHETRAN and HEC HMS Model Evaluation for Runoff and Soil Moisture Simulation in the Jičinka River Catchment (Czech Republic)

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 872
Author(s):  
Vesna Đukić ◽  
Ranka Erić
Keyword(s):  
Soil Moisture ◽  
Czech Republic ◽  
Hydrological Model ◽  
Flash Flood ◽  
Model Performance ◽  
Rainfall Runoff ◽  
The Czech Republic ◽  
River Catchment ◽  
Hydrological Variable ◽  
Model Structures

Due to the improvement of computation power, in recent decades considerable progress has been made in the development of complex hydrological models. On the other hand, simple conceptual models have also been advanced. Previous studies on rainfall–runoff models have shown that model performance depends very much on the model structure. The purpose of this study is to determine whether the use of a complex hydrological model leads to more accurate results or not and to analyze whether some model structures are more efficient than others. Different configurations of the two models of different complexity, the Système Hydrologique Européen TRANsport (SHETRAN) and Hydrologic Modeling System (HEC-HMS), were compared and evaluated in simulating flash flood runoff for the small (75.9 km2) Jičinka River catchment in the Czech Republic. The two models were compared with respect to runoff simulations at the catchment outlet and soil moisture simulations within the catchment. The results indicate that the more complex SHETRAN model outperforms the simpler HEC HMS model in case of runoff, but not for soil moisture. It can be concluded that the models with higher complexity do not necessarily provide better model performance, and that the reliability of hydrological model simulations can vary depending on the hydrological variable under consideration.

scholarly journals Analysis of an Extreme Weather Event in a Hyper Arid Region Using WRF-Hydro Coupling, Station, and Satellite data

2018 ◽  
Author(s):  
Youssef Wehbe ◽  
Marouane Temimi ◽  
Michael Weston ◽  
Naira Chaouch ◽  
Oliver Branch ◽  
...  
Keyword(s):  
Soil Moisture ◽  
United Arab Emirates ◽  
Hydrological Modeling ◽  
Flash Flood ◽  
Pearson Correlation ◽  
Global Radiation ◽  
Wrf Model ◽  
Extreme Weather ◽  
Extreme Weather Event ◽  
Weather Event

Abstract. This study investigates an extreme weather event that impacted the United Arab Emirates (UAE) in March 2016 using the Weather Research and Forecasting (WRF) model version 3.7.1 coupled with its hydrological modeling extension package (Hydro). Six-hourly forecasted forcing records at 0.5o spatial resolution, obtained from the NCEP Global Forecast System (GFS), are used to drive the three nested downscaling domains of both standalone WRF and coupled WRF/WRF-Hydro configurations for the recent flood-triggering storm. Ground and satellite observations over the UAE are employed to validate the model results. Precipitation, soil moisture, and cloud fraction retrievals from GPM (30-minute, 0.1o product), AMSR2 (daily, 0.1o product), and MODIS (daily, 5 km product), respectively, are used to assess the model output. The Pearson correlation coefficient (PCC), relative bias (rBIAS) and root-mean-square error (RMSE) are used as performance measures. Results show reductions of 24 % and 13 % in RMSE and rBIAS measures, respectively, in precipitation forecasts from the coupled WRF/WRF-Hydro model configuration, when compared to standalone WRF. The coupled system also shows improvements in global radiation forecasts, with reductions of 45 % and 12 % for RMSE and rBIAS, respectively. Moreover, WRF-Hydro was able to simulate the spatial distribution of soil moisture reasonably well across the study domain when compared to AMSR2 satellite soil moisture estimates, despite a noticeable dry/wet bias in areas where soil moisture is high/low. The demonstrated improvement, at the local scale, implies that WRF-Hydro coupling may enhance hydrologic forecasts and flash flood guidance systems in the region.

Spatial scale effects on model parameter estimation and predictive uncertainty in ungauged basins

2012 ◽  
Vol 44 (3) ◽  
pp. 441-453 ◽  
Author(s):  
Denis A. Hughes ◽  
Evison Kapangaziwiri ◽  
Jane Tanner
Keyword(s):  
Parameter Estimation ◽  
Spatial Scale ◽  
Scale Effects ◽  
Physical Property ◽  
Hydrological Modelling ◽  
Ungauged Basins ◽  
Estimation Equations ◽  
Property Data ◽  
Physical Property Data ◽  
Parameter Values

The most appropriate scale to use for hydrological modelling depends on the model structure, the purpose of the results and the resolution of available data used to quantify parameter values and provide the climatic forcing. There is little consensus amongst the community of model users on the appropriate model complexity and number of model parameters that are needed for satisfactory simulations. These issues are not independent of modelling scale, the methods used to quantify parameter values, nor the purpose of use of the simulations. This paper reports on an investigation of spatial scale effects on the application of an approach to quantify the parameter values (with uncertainty) of a rainfall-runoff model with a relatively large number of parameters. The quantification approach uses estimation equations based on physical property data and is applicable to gauged and ungauged basins. Within South Africa the physical property data are available at a finer spatial resolution than is typically used for hydrological modelling. The results suggest that reducing the model spatial scale offers some advantages. Potential disadvantages are related to the need for some subjective interpretation of the available physical property data, as well as inconsistencies in some of the parameter estimation equations.

scholarly journals Assessing flood probability for transportation infrastructure based on catchment characteristics, sediment connectivity and remotely sensed soil moisture

2019 ◽  
Vol 661 ◽  
pp. 393-406 ◽  
Author(s):  
Zahra Kalantari ◽  
Carla Sofia Santos Ferreira ◽  
Alexander J. Koutsouris ◽  
Anna-Klara Ahlmer ◽  
Artemi Cerdà ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Remotely Sensed ◽  
Transportation Infrastructure ◽  
Catchment Characteristics ◽  
Flood Probability ◽  
Sediment Connectivity

scholarly journals Assessing Hydrological Modelling Driven by Different Precipitation Datasets via the SMAP Soil Moisture Product and Gauged Streamflow Data

2018 ◽  
Vol 10 (12) ◽  
pp. 1872 ◽  
Author(s):  
Lu Yi ◽  
Wanchang Zhang ◽  
Xiangyang Li
Keyword(s):  
Soil Moisture ◽  
Data Assimilation ◽  
Weather Prediction ◽  
Eastern China ◽  
Hydrological Modelling ◽  
Heavy Rainfall Event ◽  
In Situ Observation ◽  
Rainfall Runoff ◽  
Study Case

To compare the effectivenesses of different precipitation datasets on hydrological modelling, five precipitation datasets derived from various approaches were used to simulate a two-week runoff process after a heavy rainfall event in the Wangjiaba (WJB) watershed, which covers an area of 30,000 km2 in eastern China. The five precipitation datasets contained one traditional in situ observation, two satellite products, and two predictions obtained from the Numerical Weather Prediction (NWP) models. They were the station observations collected from the China Meteorological Administration (CMA), the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (GPM IMERG), the merged data of the Climate Prediction Center Morphing (merged CMORPH), and the outputs of the Weather Research and Forecasting (WRF) model and the WRF four-dimensional variational (4D-Var) data assimilation system, respectively. Apart from the outlet discharge, the simulated soil moisture was also assessed via the Soil Moisture Active Passive (SMAP) product. These investigations suggested that (1) all the five precipitation datasets could yield reasonable simulations of the studied rainfall-runoff process. The Nash-Sutcliffe coefficients reached the highest value (0.658) with the in situ CMA precipitation and the lowest value (0.464) with the WRF-predicted precipitation. (2) The traditional in situ observation were still the most reliable precipitation data to simulate the study case, whereas the two NWP-predicted precipitation datasets performed the worst. Nevertheless, the NWP-predicted precipitation is irreplaceable in hydrological modelling because of its fine spatiotemporal resolutions and ability to forecast precipitation in the future. (3) Gauge correction and 4D-Var data assimilation had positive impacts on improving the accuracies of the merged CMORPH and the WRF 4D-Var prediction, respectively, but the effectiveness of the latter on the rainfall-runoff simulation was mainly weakened by the poor quality of the GPM IMERG used in the study case. This study provides a reference for the applications of different precipitation datasets, including in situ observations, remote sensing estimations and NWP simulations, in hydrological modelling.

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