scholarly journals Local and regional flood frequency analysis based on hierarchical Bayesian model: application to annual maximum streamflow for the Huaihe River basin

2018 ◽  
Author(s):  
Yenan Wu ◽  
Upmanu Lall ◽  
Carlos H.R. Lima ◽  
Ping-an Zhong
Keyword(s):  
Bayesian Model ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Hierarchical Bayesian Model ◽  
Annual Maximum ◽  
Huaihe River Basin ◽  
Huaihe River ◽  
Index Flood ◽  
Flood Quantiles ◽  
The Huaihe River

Abstract. We develop a hierarchical, multilevel Bayesian model for reducing uncertainties in local (at-site) and regional (ungauged or short data sites) flood frequency analysis. This model is applied to the annual maximum streamflow of 17 gauged sites in the Huaihe River basin, China. A Generalized Extreme Value (GEV) distribution is considered for each site, and its location and scale parameters depend on the site’s drainage area. We assume the hyper-parameters come from Non-informative (independent, uniform) prior distribution and sample values from posterior distribution by the MCMC method using Gibbs sampling. For comparison, the ordinary GEV fitting by Maximum Likelihood Estimate (MLE) and index flood method fitted by L-moments are also applied. The local simulation results show that for most sites the 95 % credible interval simulated by the Hierarchical Bayesian model are narrower than the at site GEV outputs thus reducing uncertainty. By comparison, the homogeneity assumption of the index flood method often leads to large deviations from the empirical flood frequency curve. Cross validated flood quantiles and associated uncertainty intervals are also derived. These results show that the proposed model can better estimate the flood quantiles and their uncertainty than the index flood method.

scholarly journals Evaluation on non-stationarity assumption of annual maximum peak flows during 1956-2016 in the Huaihe River Basin

2018 ◽  
Vol 30 (4) ◽  
pp. 1123-1137
Author(s):  
SUN Peng ◽  
◽  
SUN Yuyan ◽  
ZHANG Qiang ◽  
YAO Rui ◽  
...  
Keyword(s):  
River Basin ◽  
Annual Maximum ◽  
Huaihe River Basin ◽  
Huaihe River ◽  
Peak Flows ◽  
Maximum Peak ◽  
The Huaihe River

Hydrological simulation using multi-sources precipitation estimates in the Huaihe River Basin

2021 ◽  
Vol 14 (18) ◽  
Author(s):  
Mohammad Ilyas Abro ◽  
Dehua Zhu ◽  
Ehsan Elahi ◽  
Asghar Ali Majidano ◽  
Bhai Khan Solangi
Keyword(s):  
River Basin ◽  
Huaihe River Basin ◽  
Huaihe River ◽  
Hydrological Simulation ◽  
Precipitation Estimates ◽  
The Huaihe River

Atmospheric-hydrological modeling of severe precipitation and floods in the Huaihe River Basin, China

2006 ◽  
Vol 330 (1-2) ◽  
pp. 249-259 ◽  
Author(s):  
Charles A. Lin ◽  
Lei Wen ◽  
Guihua Lu ◽  
Zhiyong Wu ◽  
Jianyun Zhang ◽  
...  
Keyword(s):  
River Basin ◽  
Hydrological Modeling ◽  
Huaihe River Basin ◽  
Huaihe River ◽  
The Huaihe River

scholarly journals Improving TIGGE Precipitation Forecasts Using an SVR Ensemble Approach in the Huaihe River Basin

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Chenkai Cai ◽  
Jianqun Wang ◽  
Zhijia Li
Keyword(s):  
River Basin ◽  
Lead Time ◽  
Flood Control ◽  
Ensemble Methods ◽  
New Method ◽  
Support Vector ◽  
Huaihe River Basin ◽  
Huaihe River ◽  
Reservoir Regulation ◽  
The Huaihe River

Recently, the use of the numerical rainfall forecast has become a common approach to improve the lead time of streamflow forecasts for flood control and reservoir regulation. The control forecasts of five operational global prediction systems from different centers were evaluated against the observed data by a series of area-weighted verification and classification metrics during May to September 2015–2017 in six subcatchments of the Xixian Catchment in the Huaihe River Basin. According to the demand of flood control safety, four different ensemble methods were adopted to reduce the forecast errors of the datasets, especially the errors of missing alarm (MA), which may be detrimental to reservoir regulation and flood control. The results indicate that the raw forecast datasets have large missing alarm errors (MEs) and cannot be directly applied to the extension of flood forecasting lead time. Although the ensemble methods can improve the performance of rainfall forecasts, the missing alarm error is still large, leading to a huge hazard in flood control. To improve the lead time of the flood forecast, as well as avert the risk from rainfall prediction, a new ensemble method was proposed on the basis of support vector regression (SVR). Compared to the other methods, the new method has a better ability in reducing the ME of the forecasts. More specifically, with the use of the new method, the lead time of flood forecasts can be prolonged to at least 3 d without great risk in flood control, which corresponds to the aim of flood prevention and disaster reduction.

scholarly journals Spatial Pattern and Evolution of Urban System Based on Gravity Model and Whole Network Analysis in the Huaihe River Basin of China

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Yong Fan ◽  
Shengdi Zhang ◽  
Zongyi He ◽  
Biao He ◽  
Haicong Yu ◽  
...  
Keyword(s):  
Network Analysis ◽  
Spatial Pattern ◽  
Gravity Model ◽  
River Basin ◽  
Urban System ◽  
Huaihe River Basin ◽  
Analysis Method ◽  
Huaihe River ◽  
Research Issues ◽  
The Huaihe River

The spatial pattern and evolution of urban system have been hot research issues in the field of urban research. In this paper, the network analysis method based on the gravity model and the related measurements were used to reveal the properties of the spatial pattern and evolution of the urban system in the HRB (Huaihe River Basin) of China. The findings of this study are as follows: During the period from 2006 to 2014, the economic contact between the HRB cities has been strengthened, but the differences between cities have been expanding. In general, the HRB cities have not yet formed a close network structure, and a trend of economic integration has not been found. This paper expresses the spatial pattern and evolution of urban system in an intuitive way and helps to explain the evolution mechanism of urban system. The method was confirmed by empirical research. Because of the operational and visual expression, this method has broad application prospects in the urban system research.

scholarly journals Delineation of homogenous regions using hydrological variables predicted by projection pursuit regression

2016 ◽  
Vol 20 (12) ◽  
pp. 4717-4729 ◽  
Author(s):  
Martin Durocher ◽  
Fateh Chebana ◽  
Taha B. M. J. Ouarda
Keyword(s):  
Target Location ◽  
Projection Pursuit ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Projection Pursuit Regression ◽  
Index Flood ◽  
Regional Flood Frequency Analysis ◽  
Quantile Estimates ◽  
Target Locations ◽  
Hydrological Variables

Abstract. This study investigates the utilization of hydrological information in regional flood frequency analysis (RFFA) to enforce desired properties for a group of gauged stations. Neighbourhoods are particular types of regions that are centred on target locations. A challenge for using neighbourhoods in RFFA is that hydrological information is not available at target locations and cannot be completely replaced by the available physiographical information. Instead of using the available physiographic characteristics to define the centre of a target location, this study proposes to introduce estimates of reference hydrological variables to ensure a better homogeneity. These reference variables represent nonlinear relations with the site characteristics obtained by projection pursuit regression, a nonparametric regression method. The resulting neighbourhoods are investigated in combination with commonly used regional models: the index-flood model and regression-based models. The complete approach is illustrated in a real-world case study with gauged sites from the southern part of the province of Québec, Canada, and is compared with the traditional approaches such as region of influence and canonical correlation analysis. The evaluation focuses on the neighbourhood properties as well as prediction performances, with special attention devoted to problematic stations. Results show clear improvements in neighbourhood definitions and quantile estimates.

scholarly journals Drought assessment using a multivariate drought index in the Huaihe River basin of Eastern China

2015 ◽  
Vol 369 ◽  
pp. 61-67
Author(s):  
Q. Li ◽  
M. Zeng ◽  
H. Wang ◽  
P. Li ◽  
K. Wang ◽  
...  
Keyword(s):  
River Basin ◽  
Drought Index ◽  
Eastern China ◽  
Standardized Precipitation Index ◽  
Cumulative Distribution ◽  
Huaihe River Basin ◽  
Huaihe River ◽  
Drought Assessment ◽  
The Huaihe River ◽  
Multivariate Drought Index

Abstract. The Huaihe River Basin having China's highest population density (662 persons per km2) lies in a transition zone between the climates of North and South China, and is thus prone to drought. Therefore, the paper aims to develop an appropriate drought assessment approach for drought assessment in the Huaihe River basin, China. Based on the Principal Component Analysis of precipitation, evapotranspiration, soil moisture and runoff, the three latter variables of which were obtained by use of the Xin'anjiang model, a new multivariate drought index (MDI) was formulated, and its thresholds were determined by use of cumulative distribution function. The MDI, the Standardized Precipitation Index (SPI) and the self-calibrating Palmer Drought Severity Index (sc-PDSI) time series on a monthly scale were computed and compared during 1988, 1999/2000 and 2001 drought events. The results show that the MDI exhibited certain advantages over the sc-PDSI and the SPI in monitoring drought evolution. The MDI formulated by this paper could provide a scientific basis for drought mitigation and management, and references for drought assessment elsewhere in China.

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