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 A coupled stochastic rainfall-evapotranspiration model for hydrological impact analysis

2017 ◽  
Author(s):  
Minh Tu Pham ◽  
Hilde Vernieuwe ◽  
Bernard De Baets ◽  
Niko E. C. Verhoest
Keyword(s):  
Time Series ◽  
Impact Analysis ◽  
Hydrological Model ◽  
Hydrological Cycle ◽  
Rainfall Runoff ◽  
Hydrological Impact ◽  
Long Time ◽  
Rainfall Runoff Model ◽  
The Impact ◽  
Runoff Model

Abstract. A hydrological impact analysis concerns the study of the consequences of certain scenarios on one or more variables or fluxes in the hydrological cycle. In such exercise, discharge is often considered, as especially extreme high discharges often cause damage due to the coinciding floods. Investigating extreme discharges generally requires long time series of precipitation and evapotranspiration that are used to force a rainfall-runoff model. However, such kind of data may not be available and one should resort to stochastically-generated time series, even though the impact of using such data on the overall discharge, and especially on the extreme discharge events is not well studied. In this paper, stochastically-generated rainfall and coinciding evapotranspiration time series are used to force a simple conceptual hydrological model. The results obtained are comparable to the modelled discharge using observed forcing data. Yet, uncertainties in the modelled discharge increase with an increasing number of stochastically-generated time series used. Notwithstanding this finding, it can be concluded that using a coupled stochastic rainfall-evapotranspiration model has a large potential for hydrological impact analysis.

scholarly journals A coupled stochastic rainfall–evapotranspiration model for hydrological impact analysis

2018 ◽  
Vol 22 (2) ◽  
pp. 1263-1283 ◽  
Author(s):  
Minh Tu Pham ◽  
Hilde Vernieuwe ◽  
Bernard De Baets ◽  
Niko E. C. Verhoest
Keyword(s):  
Time Series ◽  
Impact Analysis ◽  
Hydrological Cycle ◽  
Rainfall Runoff ◽  
Hydrological Impact ◽  
Long Time ◽  
Rainfall Runoff Model ◽  
The Impact ◽  
Vine Copulas ◽  
Runoff Model

Abstract. A hydrological impact analysis concerns the study of the consequences of certain scenarios on one or more variables or fluxes in the hydrological cycle. In such an exercise, discharge is often considered, as floods originating from extremely high discharges often cause damage. Investigating the impact of extreme discharges generally requires long time series of precipitation and evapotranspiration to be used to force a rainfall-runoff model. However, such kinds of data may not be available and one should resort to stochastically generated time series, even though the impact of using such data on the overall discharge, and especially on the extreme discharge events, is not well studied. In this paper, stochastically generated rainfall and corresponding evapotranspiration time series, generated by means of vine copulas, are used to force a simple conceptual hydrological model. The results obtained are comparable to the modelled discharge using observed forcing data. Yet, uncertainties in the modelled discharge increase with an increasing number of stochastically generated time series used. Notwithstanding this finding, it can be concluded that using a coupled stochastic rainfall–evapotranspiration model has great potential for hydrological impact analysis.

scholarly journals A Comparison of Design Storms for Urban Drainage System Applications

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 757 ◽  
Author(s):  
Balbastre-Soldevila ◽  
García-Bartual ◽  
Andrés-Doménech
Keyword(s):  
Temporal Pattern ◽  
Drainage System ◽  
Rainfall Data ◽  
Data Series ◽  
Rainfall Time Series ◽  
Rainfall Runoff ◽  
Maximum Rainfall ◽  
Intensity Duration Frequency ◽  
Rainfall Runoff Model ◽  
Runoff Model

The present research develops a systematic application of a selected family of 11 well-known design storms, all of them obtained from the same rainfall data sample. Some of them are fully consistent with the intensity–duration–frequency (IDF) curves, while others are built according to typical observed patterns in the historical rainfall series. The employed data series consists on a high-resolution rainfall time series in Valencia (Spain), covering the period from 1990 to 2012. The goal of the research is the systematic comparison of these design storms, paying special attention to some relevant quantitative properties, as the maximum rainfall intensity, the total cumulative rainfall depth or the temporal pattern characterising the synthetic storm. For comparison purposes, storm duration was set to 1 hour and return period equal to 25 years in all cases. The comparison is enhanced by using each of the design storms as rainfall input to a calibrated urban hydrology rainfall–runoff model, yielding to a family of hydrographs for a given neighbourhood of the city of Valencia (Spain). The discussion and conclusions derived from the present research refer to both, the comparison between design storms and the comparison of resulting hydrographs after the application of the mentioned rainfall–runoff model. Seven of the tested design storms yielded to similar overall performance, showing negligible differences in practice. Among them, only Average Variability Method (AVM) and Two Parameter Gamma function (G2P) incorporate in their definition a temporal pattern inferred from empirical patterns identified in the historical rainfall data used herein. The remaining four design storms lead to more significant discrepancies attending both to the rainfall itself and to the resulting hydrograph. Such differences are ~8% concerning estimated discharges.

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 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 Assessment of the Impact of Changes in Deforestation under the Effect of Severe Windstorms on Runoff Conditions in Small River Basins

2019 ◽  
Vol 27 (3) ◽  
pp. 37-43
Author(s):  
Zuzana Štefunková ◽  
Kamila Hlavčová ◽  
Marija Mihaela Labat
Keyword(s):  
River Basin ◽  
Forest Cover ◽  
Hydrological Cycle ◽  
Rainfall Runoff ◽  
Current Topic ◽  
Rainfall Runoff Model ◽  
The Impact ◽  
The Given ◽  
Runoff Model ◽  
Natural Means

Abstract Forests represent the most natural means of retaining water in a basin. Assessing the impact of a forest on a hydrological cycle is a very current topic that hydrologists and water managers deal with. The differences between site conditions and a forest itself, together with various methods of exploring this issue, lead to inconsistent opinions on the extent of the ability of a forest cover to prevent or minimize surface runoff. This article is therefore focused on an assessment of the impact of changes in the composition of a forest under the effect of severe windstorms on runoff conditions in the selected river basin. The most severe windstorms in the last 25 years and their impact on changes in forest cover in the selected area of the Ipoltica River basin have been assessed in this article. The most significant severe windstorm in terms of its impact on changes in the forest communities was Filip, which occurred in the year 2007. Therefore, the impact of changes in forest cover on the given territory was examined for the period after the year 2007. The WetSpa rainfall-runoff model was used to assess the changes.

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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