Method for Probabilistic Flood Forecasting Considering Rainfall and Model Parameter Uncertainties

Jiang, Xiaolei; Liang, Zhongmin; Qian, Mingkai; Zhang, Xuebin; Chen, Yuanfang; Li, Binquan; Fu, Xiaolei

doi:10.1061/(asce)he.1943-5584.0001861

Cited by 8 publications

(4 citation statements)

References 38 publications

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“…Muñoz et al (2012) used data from 25 watersheds located in Chile, developed a reliable peak flow estimation method that required rainfall data and geomorphologic descriptors as inputs, and related the instant peak flow with the time of concentration rainfall flux. Jiang et al (2019) presented a method of rainfall calculation uncertainty assessment by using an inverse sampling gauge approach, in which the influencing factors of the rainfall calculation uncertainty are addressed in the calculated area precipitation and standard deviation. Abdollahi et al (2016) developed a spatially distributed hydrological model, which is analogous to a network of electrical resistance-capacitance with five circuits, to describe the hydrological processes leading to floods.…”

Section: Topic 2 -Pollutionmentioning

confidence: 99%

The time of concentration application in studies around the world: a review

Almeida

Guarienti

et al. 2021

Environ Sci Pollut Res

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The time of concentration (Tc) is the main hydrological parameter used to characterize the response of a given Hydrological Response Unit (HRU) to a precipitation event. Because of its importance, the determining Tc is an integral step in several studies involving runoff. Thus, this work presents an unprecedented review of the application of Tc in different lines of research involving water resources around the world. In this article, 1252 publications were listed, obtained from seven different databases, published by 2020, that presented the expressions "time of concentration," "runoff," and "watershed." The articles and conference papers obtained in this research were classified into 12 topics. The number of publications per topic and per country was measured and a cluster analysis was developed to verify the similarity of the distribution of topics per country. In addition, 125 equations applied in related publications for the estimation of Tc are also listed.

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Section: Topic 2 -Pollutionmentioning

confidence: 99%

The time of concentration application in studies around the world: a review

Almeida

Guarienti

et al. 2021

Environ Sci Pollut Res

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“…In this study, drawing on the concept of the station sampling method (Liang et al 2016), n stations (n = 1, 2, 3, ...) were sampled from all rainfall stations to obtain N spatial distribution schemes with different station densities. Then, the inverse distance weighting (IDW) method was used to spatially interpolate the rainfall data of each scheme.…”

Section: Spatial Processing Of Rainfall Schemesmentioning

confidence: 99%

Impact of rainfall spatiotemporal variability and model structures on flood simulation in semi-arid regions

Liu

et al. 2021

Stoch Environ Res Risk Assess

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The spatiotemporal heterogeneity in precipitation and underlying surfaces and hybrid runoff generation mechanism make hydrological modelling and forecasting in semiarid regions becoming a challenge work. Therefore, to provide a reference for the development of hydrological models in such regions, two nested hydrological experimental watersheds in semi-arid regions were selected for attribution analysis. Based on the concept of large-sample hydrology, Large-scale numerical simulation experiments were performed by constructing different spatial and temporal scale rainfall schemes and combining three hydrological models with different runoff generation mechanisms. Finally, the influences of the time step, station density, and model structure on the flood simulations in semi-arid regions were evaluated. The spatial interpolation technique was used simultaneously to describe the highdimensional complicated nonlinear relationships between the influencing factors and simulation results. The results show the following: ① the flood simulation accuracy was more sensitive to the time step than the spatial station density of the rainfall schemes and was highly dependent on the time step of the original observation data; and ② compared with the accuracy of the rainfall schemes, the model structure plays a dominant role in flood simulation accuracy. Thus, the hybrid model has significant potential for flood forecasting in semi-arid regions by combining different runoff generation mechanisms. ③ The spatial interpolation technique based on the k-nearest neighbour algorithm can construct a high-dimensional distribution of the influencing factors, yield high model simulation accuracy, and describe the complicated relationships among the time step, station density, model structure, and simulations.

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“…The formation process of runoff in nature is a complex process under the interaction of many factors. Although it has a certain randomness, regularities can be found from it [9] For example, the variable infiltration capacity model (VIC) was used to simulate the energy balance and water balance in the process of water cycle at the same time. Environmental policy integrated climate model (EPIC) was employed to quantitatively assess the integrated dynamics of the climate-soil-crop-management system.…”

Section: Introductionmentioning

confidence: 99%

Using SWAT Model to Assess the Impacts of Land Use and Climate Changes on Flood in the Upper Weihe River, China

Yin-ge

Zhao

et al. 2022

Water

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Flood disasters have occurred frequently in recent years, but there is no consensus on the mechanism and influencing factors. Taking the upper reaches of Weihe River Basin as a case in Western China, a soil and water assessment tool (SWAT) model was established to quantitatively simulate the impact of land use and climate change on runoff changes, while 4 extreme land-use scenarios and 24 temperature and precipitation scenarios assumptions were proposed to simulate the response of runoff to land use and climate changes. The SWAT simulation results showed that the sensitivity parameters affecting the model simulation were the CANMX, CN2, SOL_K, CH_N2, and SOL_AWC. The correlation index R2 and the efficiency coefficient ENS of the upper Weihe River were both in the range of 0.75–0.78, the relative error PS between the simulated results and the measured runoff was below 10%, suggesting the good applicability of the SWAT model in this study area. Using the improved SWAT model to simulate the peak runoff (flood) simulation value is generally smaller than the measured value, and the absolute value of the error is less than 6%. The expansion of wasteland increased the runoff by over 90% on average, the expansion of cultivated land increased the runoff by 8% on average, and the expansion of woodland and grassland increased the surface runoff by 6% on average. When the precipitation decreased by 25% and the temperature increased by 22%, the smallest runoff was obtained in the simulation. Accordingly, when the precipitation increased by 25% and the temperature decreased by 22%, the maximum annual runoff was obtained. By decomposing the contribution rate of human activities and climate change to runoff, it showed that the contribution rate of human activities to the reduction of runoff was greater than that of climate change. This study can provide scientific reference for the simulation and prediction of future floods.

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Method for Probabilistic Flood Forecasting Considering Rainfall and Model Parameter Uncertainties

Cited by 8 publications

References 38 publications

The time of concentration application in studies around the world: a review

The time of concentration application in studies around the world: a review

Impact of rainfall spatiotemporal variability and model structures on flood simulation in semi-arid regions

Using SWAT Model to Assess the Impacts of Land Use and Climate Changes on Flood in the Upper Weihe River, China

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