scholarly journals Assessment of Flood Risk Exposure for the Foshan-Zhongshan Region in Guangdong Province, China

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1159
Author(s):  
Qi Zhang ◽  
Wei Jian ◽  
Edmond Yat Man Lo
Keyword(s):  
Flood Risk ◽  
Pearl River Delta ◽  
Risk Exposure ◽  
Economic Losses ◽  
Flood Inundation ◽  
Rainfall Runoff ◽  
Proposed Model ◽  
Rainfall Runoff Model ◽  
The Pearl River ◽  
Runoff Model

Floods have caused 20% of the worldwide economic losses resulting from catastrophe events over 2008 to 2018. In China, the annual flood economic losses have exceeded CNY 100 billion from 1990 to 2010, which is equivalent to 1% to 3% of China’s Gross Domestic Product (GDP). This paper presents a rainfall-runoff model coupled with an inundation estimation to assess the flood risk for a basin within the Foshan-Zhongshan area of the Pearl River Delta (PRD) region in China. A Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) model was constructed for the crisscrossing river network in the study basin where the West and North Rivers meet, using publicly accessible meteorological, hydrological and topographical datasets. The developed model was used to analyze two recent flood events, that in July 2017 with large upstream river inflows, and in June 2018 with high local rainfall. Results were further used to develop the needed river rating curves within the basin. Two synthetic events that consider more severe meteorological and hydrological conditions were also analyzed. These results demonstrate the capability of the proposed model for quick assessment of potential flood inundation and the GDP exposure at risk within the economically important PRD region.

scholarly journals Application of a model-based rainfall-runoff database as efficient tool for flood risk management

2013 ◽  
Vol 17 (8) ◽  
pp. 3159-3169 ◽  
Author(s):  
L. Brocca ◽  
S. Liersch ◽  
F. Melone ◽  
T. Moramarco ◽  
M. Volk
Keyword(s):  
Flood Risk ◽  
Central Italy ◽  
Temporal Distribution ◽  
Database Management System ◽  
Specific Class ◽  
Rainfall Runoff ◽  
Rainfall Events ◽  
Operational Forecasts ◽  
Rainfall Runoff Model ◽  
Runoff Model

Abstract. A framework for a comprehensive synthetic rainfall-runoff database was developed to study catchment response to a variety of rainfall events. The framework supports effective flood risk assessment and management and implements simple approaches. It consists of three flexible components, a rainfall generator, a continuous rainfall-runoff model, and a database management system. The system was developed and tested at two gauged river sections along the upper Tiber River (central Italy). One of the main questions was to investigate how simple such approaches can be applied without impairing the quality of the results. The rainfall-runoff model was used to simulate runoff on the basis of a large number of rainfall events. The resulting rainfall-runoff database stores pre-simulated events classified on the basis of the rainfall amount, initial wetness conditions and initial discharge. The real-time operational forecasts follow an analogue method that does not need new model simulations. However, the forecasts are based on the simulation results available in the rainfall-runoff database (for the specific class to which the forecast belongs). Therefore, the database can be used as an effective tool to assess possible streamflow scenarios assuming different rainfall volumes for the following days. The application to the study site shows that magnitudes of real flood events were appropriately captured by the database. Further work should be dedicated to introduce a component for taking account of the actual temporal distribution of rainfall events into the stochastic rainfall generator and to the use of different rainfall-runoff models to enhance the usability of the proposed procedure.

scholarly journals Application of a model-based rainfall-runoff database as efficient tool for flood risk management

2013 ◽  
Vol 10 (2) ◽  
pp. 2089-2115
Author(s):  
L. Brocca ◽  
S. Liersch ◽  
F. Melone ◽  
T. Moramarco ◽  
M. Volk
Keyword(s):  
Flood Risk ◽  
Central Italy ◽  
Temporal Distribution ◽  
Database Management System ◽  
Rainfall Runoff ◽  
Rainfall Events ◽  
Uncertainty Range ◽  
Rainfall Runoff Model ◽  
Runoff Model

Abstract. A framework for a comprehensive synthetic rainfall-runoff database was developed to study catchment response to a variety of rainfall events. The framework supports effective flood risk assessment and management and implements simple approaches. It consists of three flexible components, a rainfall generator, a continuous rainfall-runoff model, and a database management system. The system has been developed and tested at two gauged river sections along the upper Tiber River (central Italy). One of the main questions was to investigate how simple such approaches can be without impairing the quality of the results. The rainfall-runoff model was used to simulate runoff on the basis of a large number of design rainfall events. The resulting rainfall-runoff database can be used as an effective tool to assess possible streamflow situations assuming different rainfall volumes for the previous and the following days. The application to the study site shows that magnitudes of real flood events were appropriately captured by the database within an uncertainty range. Further work should be dedicated to introducing a component for taking account of the actual temporal distribution of rainfall events into the stochastic rainfall generator.

scholarly journals Rainfall-Induced Landslide Susceptibility Using a Rainfall–Runoff Model and Logistic Regression

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1354 ◽  
Author(s):  
Hsun-Chuan Chan ◽  
Po-An Chen ◽  
Jung-Tai Lee
Keyword(s):  
Logistic Regression ◽  
Landslide Susceptibility ◽  
Hydrological Cycle ◽  
Characteristic Curve ◽  
Rainfall Runoff ◽  
Maximum Rainfall ◽  
Susceptibility Analysis ◽  
Proposed Model ◽  
Rainfall Runoff Model ◽  
Runoff Model

Conventional landslide susceptibility analysis adopted rainfall depth or maximum rainfall intensity as the hydrological factor. However, using these factors cannot delineate temporal variations of landslide in a rainfall event. In the hydrological cycle, runoff quantity reflects rainfall characteristics and surface feature variations. In this study, a rainfall–runoff model was adopted to simulate the runoff produced by rainfall in various periods of a typhoon event. To simplify the number of factors in landslide susceptibility analysis, the runoff depth was used to replace rainfall factors and some topographical factors. The proposed model adopted the upstream area of the Alishan River in southern Taiwan as the study area. The landslide susceptibility analysis of the study area was conducted by using a logistic regression model. The results indicated that the overall accuracy of predicted events exceeded 80%, and the area under the receiver operating characteristic curve (AUC) closed to 0.8. The results revealed that the proposed landslide susceptibility simulation performed favorably in the study area. The proposed model could predict the evolution of landslide susceptibility in various periods of a typhoon and serve as a new reference for landslide hazard prevention.

scholarly journals Cascading model uncertainty from medium range weather forecasts (10 days) through a rainfall-runoff model to flood inundation predictions within the European Flood Forecasting System (EFFS)

2005 ◽  
Vol 9 (4) ◽  
pp. 381-393 ◽  
Author(s):  
F. Pappenberger ◽  
K. J. Beven ◽  
N. M. Hunter ◽  
P. D. Bates ◽  
B. T. Gouweleeuw ◽  
...  
Keyword(s):  
Methodological Approach ◽  
Weather Forecast ◽  
Integrated System ◽  
Model Parameters ◽  
Flood Inundation ◽  
Rainfall Runoff ◽  
Ensemble Forecasts ◽  
Considerable Uncertainty ◽  
Rainfall Runoff Model ◽  
Runoff Model

Abstract. The political pressure on the scientific community to provide medium to long term flood forecasts has increased in the light of recent flooding events in Europe. Such demands can be met by a system consisting of three different model components (weather forecast, rainfall-runoff forecast and flood inundation forecast) which are all liable to considerable uncertainty in the input, output and model parameters. Thus, an understanding of cascaded uncertainties is a necessary requirement to provide robust predictions. In this paper, 10-day ahead rainfall forecasts, consisting of one deterministic, one control and 50 ensemble forecasts, are fed into a rainfall-runoff model (LisFlood) for which parameter uncertainty is represented by six different parameter sets identified through a Generalised Likelihood Uncertainty Estimation (GLUE) analysis and functional hydrograph classification. The runoff of these 52 * 6 realisations form the input to a flood inundation model (LisFlood-FP) which acknowledges uncertainty by utilising ten different sets of roughness coefficients identified using the same GLUE methodology. Likelihood measures for each parameter set computed on historical data are used to give uncertain predictions of flow hydrographs as well as spatial inundation extent. This analysis demonstrates that a full uncertainty analysis of such an integrated system is limited mainly by computer power as well as by how well the rainfall predictions represent potential future conditions. However, these restrictions may be overcome or lessened in the future and this paper establishes a computationally feasible methodological approach to the uncertainty cascade problem.

scholarly journals Development and Application of an Interactive Coupling Rainfall-Runoff Model According to Soil Texture

Water ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 3044
Author(s):  
Chang-Jae Kwak ◽  
Jung-Soo Kim
Keyword(s):  
Soil Texture ◽  
Goodness Of Fit ◽  
Rainfall Runoff ◽  
Analysis Model ◽  
Coupling Analysis ◽  
Proposed Model ◽  
Subsurface Flows ◽  
Channel Analysis ◽  
Rainfall Runoff Model ◽  
Runoff Model

In this study, we developed a model that simulates surface and subsurface flows for rainfall-runoff analyses using an interactive coupling method. To characterize the interaction between the surface and subsurface flows, we studied the coupling analysis model. The proposed model was designed following comparisons with existing models. For the analysis of the surface and subsurface flows, a governance equation was constructed. The goodness of fit of the model was also tested. To examine the sensitivity of the input parameters, simulations were performed while changing the major parameters of the model according to the soil texture. The developed model showed high applicability to actual watersheds after adjustment of the parameters. This model can be applied to the extension module for channel analysis; therefore, it can be used efficiently in urbanized watersheds wherein the upstream and downstream parts are pervious and impervious watersheds, respectively.

scholarly journals Effects of streamflow isotope sampling strategies on the calibration of a tracer‐aided rainfall‐runoff model

2021 ◽  
Author(s):  
Jamie Lee Stevenson ◽  
Christian Birkel ◽  
Aaron J. Neill ◽  
Doerthe Tetzlaff ◽  
Chris Soulsby
Keyword(s):  
Sampling Strategies ◽  
Rainfall Runoff ◽  
Rainfall Runoff Model ◽  
Runoff Model

scholarly journals Performance Evaluation of a Two-Parameters Monthly Rainfall-Runoff Model in the Southern Basin of Thailand

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1226
Author(s):  
Pakorn Ditthakit ◽  
Sirimon Pinthong ◽  
Nureehan Salaeh ◽  
Fadilah Binnui ◽  
Laksanara Khwanchum ◽  
...  
Keyword(s):  
Exchange Rate ◽  
Rainfall Runoff ◽  
Management Planning ◽  
Runoff Variation ◽  
Groundwater Exchange ◽  
Monthly Runoff ◽  
Rainfall Runoff Model ◽  
Two Parameters ◽  
Runoff Model

Accurate monthly runoff estimation is crucial in water resources management, planning, and development, preventing and reducing water-related problems, such as flooding and droughts. This article evaluates the monthly hydrological rainfall-runoff model’s performance, the GR2M model, in Thailand’s southern basins. The GR2M model requires only two parameters: production store (X1) and groundwater exchange rate (X2). Moreover, no prior research has been reported on its application in this region. The 37 runoff stations, which are located in three sub-watersheds of Thailand’s southern region, namely; Thale Sap Songkhla, Peninsular-East Coast, and Peninsular-West Coast, were selected as study cases. The available monthly hydrological data of runoff, rainfall, air temperature from the Royal Irrigation Department (RID) and the Thai Meteorological Department (TMD) were collected and analyzed. The Thornthwaite method was utilized for the determination of evapotranspiration. The model’s performance was conducted using three statistical indices: Nash–Sutcliffe Efficiency (NSE), Correlation Coefficient (r), and Overall Index (OI). The model’s calibration results for 37 runoff stations gave the average NSE, r, and OI of 0.657, 0.825, and 0.757, respectively. Moreover, the NSE, r, and OI values for the model’s verification were 0.472, 0.750, and 0.639, respectively. Hence, the GR2M model was qualified and reliable to apply for determining monthly runoff variation in this region. The spatial distribution of production store (X1) and groundwater exchange rate (X2) values was conducted using the IDW method. It was susceptible to the X1, and X2 values of approximately more than 0.90, gave the higher model’s performance.

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