A framework approach to address the trend and causes of flood stage change in a river reach downstream of a dam influenced by tributaries

The evaluation of the trend of flood stage changes in alluvial rivers downstream of dams is important for flood management. However, the flood stage associated with a given discharge generally is nonstationary in river reaches with multiple tributaries. This is not only because of the dam-induced shifting in the cross-sectional area and/or channel roughness but also because of the backwater induced by high flows from the tributaries. To determine the total trend of the flood stage and quantify the separate contributions of hydrological and geomorphic effects, the current study proposed a framework approach consisting of hydrological analysis and multiscenario numerical modeling. By this means, the trend in the flood stage could be distinguished from the stage oscillation driven by varying factors, including extreme hydrologic events. The effects of chronic changes, including channel incision and flow resistance increase, also were quantitatively separated. This framework was applied to the Chenglingji–Datong (CD) reach downstream of the Three Gorges Dam (TGD) in the Yangtze River, China. The results indicated that the effect of the roughness increase counterbalanced the effect of channel incision when the flow discharge was beyond the bankfull level. The backwater effect induced by tributary inflow was the major cause of the flood stage rise in recent years. The method presented in the current study provides a useful tool for managers and engineers to obtain better insight into the driving mechanisms of flood stage changes in river reaches that are downstream of dams. These findings indicate that the flood stage may not decline or may even occasionally increase, although the cross-sectional area was enlarged by channel incision. Special attention should be given to the flood risk situation in the study reach after the TGD began operation.     

On some aspects of peaks-over-threshold modeling of floods under nonstationarity using climate covariates

This paper discusses some aspects of flood frequency analysis using the peaks-over-threshold model with Poisson arrivals and generalized Pareto (GP) distributed peak magnitudes under nonstationarity, using climate covariates. The discussion topics were motivated by a case study on the influence of El Niño–Southern Oscillation on the flood regime in the Itajaí river basin, in Southern Brazil. The Niño3.4 (DJF) index is used as a covariate in nonstationary estimates of the Poisson and GP distributions scale parameters. Prior to the positing of parametric dependence functions, a preliminary data-driven analysis was carried out using nonparametric regression models to estimate the dependence of the parameters on the covariate. Model fits were evaluated using asymptotic likelihood ratio tests, AIC, and Q–Q plots. Results show statistically significant and complex dependence relationships with the covariate on both nonstationary parameters. The nonstationary flood hazard measure design life level (DLL) was used to compare the relative performances of stationary and nonstationary models in quantifying flood hazard over the period of records. Uncertainty analyses were carried out in every step of the application using the delta method.     

Distribution of erosion intensity in the Jingjiang reach influenced by the Three Gorges Dam

Elucidation of the fluvial processes influenced by dams provides better understanding of river protection and basin management. However, less attention has been given to the erosion intensity distribution of riverbeds and its association with channel morphology and hydrological conditions. Based on hydrological and topographic data, the spatial and temporal distributions of erosion intensity (2002–2014) influenced by the Three Gorges Dam (TGD) were analyzed for the Jingjiang reach of the Yangtze River. The mechanisms underlying the distribution of erosion intensity in response to hydrological conditions were investigated. The results are as follows: (1) The erosion intensities of different discharges were not uniform, and moderate flow (10 000–27 000 m³/s) produced the largest erosion magnitude among all flow ranges. Owing to the hydrological changes caused by flood reduction and prolongation of moderate flow duration after the TGD began operating, up to 70% of the erosion amount was caused by moderate flows. (2) The lateral distribution of erosion intensity was extremely uneven, as the proportion of cumulative erosion of the low‐flow channel within the bankfull channel reached 88% in 2013. This caused the channel to become narrower and deeper. (3) The longitudinal distribution of erosion intensity was inhomogeneous. The erosion intensity in the wide reaches was greater than that in the narrow reaches, leading to smaller differences in channel morphology along the river. (4) Changes in hydrological conditions influenced by the TGD, significant reduction of sediment concentration along with flood abatement, and increased duration of moderate flow discharges were the main factors affecting erosion distribution in the post‐dam period. Our conclusions can be applied to the Yangtze River as a basis for riverbed change estimations, and river management strategies. Copyright © 2018 John Wiley & Sons, Ltd.     

Acceleration of vegetation dynamics in hydrologically connected wetlands caused by dam operation

The dynamic responses of wetlands to upstream water conservancy projects are becoming increasingly crucial for watershed management. Poyang Lake is a dynamic wetland system of critical ecological importance and connected with the Yangtze river. However, in the context of disturbed water regime in Poyang Lake resulting from human activities and climate change, the responses of vegetation dynamics to the Three Gorges Dam (TGD) have not been investigated. We addressed this knowledge gap by using daily water level data and Landsat images from 1987 to 2018. Landsat images were acquired between October and December to ensure similar phenological conditions. Object-oriented Artificial Neural Network Regression for wetland classification was developed based on abundant training and validation samples. Interactions between vegetation coverage and water regimes pre and post the operation of the TGD were compared using classification and regression trees and the random forest model. Since the implementation of the TGD in 2003, Poyang Lake has become drier, especially during the dry season. A more rapid plant growth rate was observed post TGD (44.74 km² year⁻¹) compared to that of the entire study period (12.9 km² year⁻¹). Average water level for the antecedent 20 days most significantly affected vegetation before 2003, whereas average water level for the antecedent 5 or 10 days was more important after 2003. The impoundment of the TGD after the flood season accelerated the drawdown processes of Poyang Lake, and the rapidly exposed wetlands accelerated vegetation expansion during the dry seasons, resulting in shrinkage and degradation of the lake area. This study deepens our knowledge of the influences of newly developed dams on lakes and rivers.     

Model averaging versus model selection: estimating design floods with uncertain river flow data

ABSTRACT

This study compares model averaging and model selection methods to estimate design floods, while accounting for the observation error that is typically associated with annual maximum flow data. Model selection refers to methods where a single distribution function is chosen based on prior knowledge or by means of selection criteria. Model averaging refers to methods where the results of multiple distribution functions are combined. Numerical experiments were carried out by generating synthetic data using the Wakeby distribution function as the parent distribution. For this study, comparisons were made in terms of relative error and root mean square error (RMSE) referring to the 1-in-100 year flood. The experiments show that model averaging and model selection methods lead to similar results, especially when short samples are drawn from a highly asymmetric parent. Also, taking an arithmetic average of all design flood estimates gives estimated variances similar to those obtained with more complex weighted model averaging.     

Identification of flood seasonality and drivers across Canada

Floods are the most frequently occurring natural hazard in Canada. An in-depth understanding of flood seasonality and its drivers at a national scale is essential. Here, a circular, statistics-based approach is implemented to understand the seasonality of annual-maximum floods (streamflow) and to identify their responsible drivers across Canada. Nearly 80% and 70% of flood events were found to occur during spring and summer in eastern and western watersheds across Canada, respectively. Flooding in the eastern and western watersheds was primarily driven by snowmelt and extreme precipitation, respectively. This observation suggests that increases in temperature have led to early spring snowmelt-induced floods throughout eastern Canada. Our results indicate that precipitation (snowmelt) variability can exert large controls on the magnitude of flood peaks in western (eastern) watersheds in Canada. Further, the nonstationarity of flood peaks is modelled to account for impact of the dynamic behaviour of the identified flood drivers on extreme-flood magnitude by using a cluster of 74 generalized additive models for location scale and shape models, which can capture both the linear and nonlinear characteristics of flood-peak changes and can model its dependence on external covariates. Using nonstationary frequency analysis, we find that increasing precipitation and snowmelt magnitudes directly resulted in a significant increase in 50-year streamflow. Our results highlight an east–west asymmetry in flood seasonality, indicating the existence of a climate signal in flood observations. The understating of flood seasonality and flood responses under the dynamic characteristics of precipitation and snowmelt extremes may facilitate the predictability of such events, which can aid in predicting and managing their impacts.     

A dual two-stage stochastic model for flood management with inexact-integer analysis under multiple uncertainties

This study introduces a hybrid optimization approach for flood management under multiple uncertainties. An inexact two-stage integer programming (ITIP) model and its dual formation are developed by integrating the concepts of mixed-integer and interval-parameter programming techniques into a general framework of two-stage stochastic programming. The proposed approach provides a linkage to pre-defined management policies, deals with capacity-expansion planning issues, and reflects various uncertainties expressed as probability distributions and discrete intervals for a flood management system. Penalties are imposed when the policies are violated. The marginal costs are determined based on dual formulation of the ITIP model, and their effects on the optimal solutions are investigated. The developed model is applied to a case study of flood management. The solutions of binary variables represent the decisions of flood-diversion–capacity expansion within a multi-region, multi-flow-level, and multi-option context. The solutions of continuous variables are related to decisions of flood diversion toward different regions. The solutions of dual variables indicate the decisions of marginal costs associated with the resources of regions’ capacity, water availability, and allowable diversions. The results show that the proposed approach could obtain reliable solutions and adequately support decision making in flood management.     

Stationarity is undead: Uncertainty dominates the distribution of extremes

The increasing effort to develop and apply nonstationary models in hydrologic frequency analyses under changing environmental conditions can be frustrated when the additional uncertainty related to the model complexity is accounted for along with the sampling uncertainty. In order to show the practical implications and possible problems of using nonstationary models and provide critical guidelines, in this study we review the main tools developed in this field (such as nonstationary distribution functions, return periods, and risk of failure) highlighting advantages and disadvantages. The discussion is supported by three case studies that revise three illustrative examples reported in the scientific and technical literature referring to the Little Sugar Creek (at Charlotte, North Carolina), Red River of the North (North Dakota/Minnesota), and the Assunpink Creek (at Trenton, New Jersey). The uncertainty of the results is assessed by complementing point estimates with confidence intervals (CIs) and emphasizing critical aspects such as the subjectivity affecting the choice of the models’ structure. Our results show that (1) nonstationary frequency analyses should not only be based on at-site time series but require additional information and detailed exploratory data analyses (EDA); (2) as nonstationary models imply that the time-varying model structure holds true for the entire future design life period, an appropriate modeling strategy requires that EDA identifies a well-defined deterministic mechanism leading the examined process; (3) when the model structure cannot be inferred in a deductive manner and nonstationary models are fitted by inductive inference, model structure introduces an additional source of uncertainty so that the resulting nonstationary models can provide no practical enhancement of the credibility and accuracy of the predicted extreme quantiles, whereas possible model misspecification can easily lead to physically inconsistent results; (4) when the model structure is uncertain, stationary models and a suitable assessment of the uncertainty accounting for possible temporal persistence should be retained as more theoretically coherent and reliable options for practical applications in real-world design and management problems; (5) a clear understanding of the actual probabilistic meaning of stationary and nonstationary return periods and risk of failure is required for a correct risk assessment and communication.     

High-resolution flood hazard mapping based on nonstationary frequency analysis: case study of Ho Chi Minh City,Vietnam

Flood modelling inputs used to create flood hazard maps are normally based on the assumption of data stationarity for flood frequency analysis. However, changes in the behaviour of climate systems can lead to nonstationarity in flood series. Here, we develop flood hazard maps for Ho Chi Minh City, Vietnam, under nonstationary conditions using extreme value analysis, a coupled 1D–2D model and high-resolution topographical data derived from LiDAR (Light Detection and Ranging) data. Our findings indicate that ENSO (El Niño Southern Oscillation) and PDO (Pacific Decadal Oscillation) influence the magnitude and frequency of extreme rainfall, while global sea-level rise causes nonstationarity in local sea levels, having an impact on flood risk. The detailed flood hazard maps show that areas of high flood potential are located along river banks, with 0.60 km² of the study area being unsafe for people, vehicles and buildings (H5 zone) under a 100-year return period scenario.     

Use of a nonstationary copula to predict future bivariate low flow frequency in the Connecticut river basin

Frequency analysis of streamflow provides an essential ingredient in our understanding of hydrologic events and provides needed guidance in the design and management of water resources infrastructure. However, traditional hydrologic approaches often fail to include important external effects that can result in unpredictable or unforeseen changes in streamflow. Moreover, previous studies investigating multiple characteristics of streamflow do not address a nonstationary approach. This study explores nonstationary frequency analysis of bivariate characteristics, including occurrence and severity, of annual low flow in the Connecticut River Basin, United States. To investigate bivariate low flow frequency, copulas and their marginal distributions are constructed by using stationary and nonstationary approaches. Our study results indicate that streamflow used in this study demonstrate significant nonstationarity. Over time, the occurrence and severity of low flows are shown to be lower with the same probability based on the results of nonstationary copulas. Bivariate low flow frequencies in the years 1970, 2000, and 2030, and their joint return periods are estimated under the nonstationary copulas. Copyright © 2016 John Wiley & Sons, Ltd.     

Enhanced hysteresis of suspended sediment transport in response to upstream damming: An example of the middle Yangtze River downstream of the Three Gorges Dam

The peak in sediment transport in alluvial rivers generally lags behind the peak in discharge. It is thus not clear how the hysteresis in the sediment/discharge relationship may be impacted by damming, which can fundamentally alter the water and sediment regimes in the downstream reaches of the river. In this study, a total of 500 flood events in the Yichang–Chenglingji Reach (YCR) of the Middle Yangtze River immediately downstream of the Three Gorges Dam (TGD) are analysed to study the impacts of dam operations on the hysteresis of suspended sediment transport. Sediment rating curves, hysteresis patterns, as well as lag times, are investigated to determine the relationship between suspended sediment concentration (SSC) and flow discharge (Q) at different temporal scales, from inter-annual to individual flood events, for the pre- and post-TGD period from 1992 to 2002 and from 2003 to 2017, respectively. The results showed that the TGD operation decreased the frequency and magnitude of floods. The decrease in peak flow and increase in base flow weakened the flood contribution to the annual discharge by nearly 20%. However, the relative suspended sediment load contribution during flood events was much higher than the discharge contribution, and was little impacted by the dam. At seasonal and monthly scales, more than 80% of the suspended sediment was transported by ~65% of the water discharge in the summer and early autumn. The monthly SSC–Q relationship changed from a figure-eight to an anti-clockwise pattern after the construction of the TGD. For single flood events, the TGD operations significantly modified the downstream SSC–Q hysteresis patterns, increasing the frequency of anti-clockwise loops and the lag time between peak Q and peak SSC. These adjustments were mainly caused by differences in the propagation velocities of flood and sediment waves and the sediment ‘storage–mobilization–depletion’ process, whereas the influence of lateral diversions was small. © 2020 John Wiley & Sons, Ltd.     

Investigation of inner-basin variation: Impact of large reservoirs on water regimes of downstream water bodies

Large dams and reservoirs alter not only the natural flow regimes of streams and rivers but also their flooding cycles and flood magnitudes. Although the effect of dams and reservoirs has been reported for some vulnerable locations, the understanding of the inner-basin variation with respect to the effects remains limited. In this study, we analyse the Three Gorges Dam (TGD) built on the Changjiang mainstream (Yangtze River) to investigate the dam effect variations in the system of interconnected water bodies located downstream. We investigated the effect of flow alterations along the downstream river network using discharge time series at different gauging stations. The river–lake interactions (referring to the interactions between the Changjiang mainstream and its tributary lakes i.e. the Dongting and Poyang lakes) and their roles in modifying the TGD effect intensity were also investigated in the large-scale river–lake system. The results show that the water storage of the tributary lakes decreased after the activation of the TGD. Severe droughts occurred in the lakes, weakening their ability to recharge the Changjiang mainstream. As a consequence, the effect of the TGD on the Changjiang flow increase during the dry season diminished quickly downstream of the dam, whereas its impact on the flow decrease during the wet season gradually exacerbated along the mainstream, especially at sites located downstream of the lake outlets. Therefore, when assessing dam-induced hydrological changes, special attention should be paid to the changes in the storage of tributary lakes and the associated effects in the mainstream. This is of high importance for managing the water resource trade-offs between different water bodies in dam-affected riverine systems.     

Quantifying differences between reservoir inflows and dam site floods using frequency and risk analysis methods

Reservoirs are the most important constructions for water resources management and flood control. Great concern has been paid to the effects of reservoir on downstream area and the differences between inflows and dam site floods due to the changes of upstream flow generation and concentration conditions after reservoir’s impoundment. These differences result in inconsistency between inflow quantiles and the reservoir design criteria derived by dam site flood series, which can be a potential risk and must be quantificationally evaluated. In this study, flood frequency analysis (FFA) and flood control risk analysis (FCRA) methods are used with the long reservoir inflow series derived from a multiple inputs and single output model and a copula-based inflow estimation model. The results of FFA and FCRA are compared and the influences on reservoir flood management are also discussed. The Three Gorges Reservoir (TGR) in China is selected as a case study. Results show that the differences between the TGR inflow and dam site floods are significant which result in changes on its flood control risk rates. The mean values of TGR’s annual maximum inflow peak discharge and 3 days flood volume have increased 5.58 and 3.85% than the dam site ones, while declined by 1.82 and 1.72% for the annual maximum 7 and 15 days flood volumes. The flood control risk rates of middle and small flood events are increased while extreme flood events are declined. It is shown that the TGR can satisfy the flood control task under current hydrologic regime and the results can offer references for better management of the TGR.     

Regionalization of floods in New Brunswick (Canada)

This study uses the method of peaks over threshold (P.O.T.) to estimate the flood flow quantiles for a number of hydrometric stations in the province of New Brunswick, Canada. The peak values exceeding the base level (threshold), or `exceedances', are fitted by a generalized Pareto distribution. It is known that under the assumption of Poisson process arrival for flood exceedances, the P.O.T. model leads to a generalized extreme value distribution (GEV) for yearly maximum discharge values. The P.O.T. model can then be applied to calculate the quantiles X <sub>T</sub> corresponding to different return periods T, in years. A regionalization of floods in New Brunswick, which consists of dividing the province into `homogeneous regions', is performed using the method of the `region of influence'. The 100-year flood is subsequently estimated using a regionally estimated value of the shape parameter of the generalized Pareto distribution and a regression of the 100-year flood on the drainage area. The jackknife sampling method is then used to contrast the regional results with the values estimated at site. The variability of these results is presented in box-plot form. Received: June 1, 1997     

Regionalization of floods in New Brunswick (Canada)

This study uses the method of peaks over threshold (P.O.T.) to estimate the flood flow quantiles for a number of hydrometric stations in the province of New Brunswick, Canada. The peak values exceeding the base level (threshold), or `exceedances', are fitted by a generalized Pareto distribution. It is known that under the assumption of Poisson process arrival for flood exceedances, the P.O.T. model leads to a generalized extreme value distribution (GEV) for yearly maximum discharge values. The P.O.T. model can then be applied to calculate the quantiles X <sub>T</sub> corresponding to different return periods T, in years. A regionalization of floods in New Brunswick, which consists of dividing the province into `homogeneous regions', is performed using the method of the `region of influence'. The 100-year flood is subsequently estimated using a regionally estimated value of the shape parameter of the generalized Pareto distribution and a regression of the 100-year flood on the drainage area. The jackknife sampling method is then used to contrast the regional results with the values estimated at site. The variability of these results is presented in box-plot form. Received: June 1, 1997     

Safety assessment for dams of the cascade reservoirs system of Lancang River in extreme situations

Numerous dams have been constructed in the midstream and downstream regions of Lancang River, which form a complex cascade reservoirs system. The safety of dams is critical for water resource management of the whole system. To check the safety of dams, this study used the MIKE 11 model to simulate flood routing along the Lancang River from Xiaowan dam to Jinghong dam under extreme situations of 100-, 500-, 1000-, 5000-, and 10,000-year design floods throughout the whole cascade reservoirs system. The design flood events used as the input for the MIKE 11 model contains the design flood hydrograph of the upstream reservoirs and corresponding flood hydrographs of the intermediate areas. The design flood hydrograph of the upstream reservoirs was obtained using the Equal Frequency Factor Method, and the corresponding flood hydrograph of the intermediate areas was obtained using the Equivalent Frequency Regional Composition Method. The results show that all dams are safe for the 100-, 500-, 1000-, and 5000-year design flood situations throughout the whole cascade reservoirs system, whereas the Manwan and Jinghong dams have a risk of overtopping under a 10,000-year design flood. The curves showing the relationship between the highest water level and return period for the dams are also presented.     

An inexact fuzzy-chance-constrained two-stage mixed-integer linear programming approach for flood diversion planning under multiple uncertainties

In this study, an inexact fuzzy-chance-constrained two-stage mixed-integer linear programming (IFCTIP) approach is developed for flood diversion planning under multiple uncertainties. A concept of the distribution with fuzzy boundary interval probability is defined to address multiple uncertainties expressed as integration of intervals, fuzzy sets and probability distributions. IFCTIP integrates the inexact programming, two-stage stochastic programming, integer programming and fuzzy-stochastic programming within a general optimization framework. IFCTIP incorporates the pre-regulated water-diversion policies directly into its optimization process to analyze various policy scenarios; each scenario has different economic penalty when the promised targets are violated. More importantly, it can facilitate dynamic programming for decisions of capacity-expansion planning under fuzzy-stochastic conditions. IFCTIP is applied to a flood management system. Solutions from IFCTIP provide desired flood diversion plans with a minimized system cost and a maximized safety level. The results indicate that reasonable solutions are generated for objective function values and decision variables, thus a number of decision alternatives can be generated under different levels of flood flows.     

Improvement of a drainage system for flood management with assessment of the potential effects of climate change

Abstract

Runoff discharge in the Tuku lowlands, Taiwan, has increased with land development. Frequent floods caused by extreme weather conditions have resulted in considerable economic and social losses in recent years. Currently, numerous infrastructures have been built in the lowland areas that are prone to inundation; the measures and solutions for flood mitigation focus mainly on engineering aspects. Public participation in the development of principles for future flood management has helped both stakeholders and engineers. An integrated drainage–inundation model, combining a drainage flow model with a two-dimensional overland-flow inundation model is used to evaluate the flood management approaches with damage loss estimation. The proposed approaches include increasing drainage capacity, using fishponds as retention ponds, constructing pumping stations, and building flood diversion culverts. To assess the effects on the drainage system of projected increase of rainfall due to climate change, for each approach simulations were performed to obtain potential inundation extent and depth in terms of damage losses. The results demonstrate the importance of assessing the impacts of climate change for implementing appropriate flood management approaches.

Editor Z.W. Kundzewicz

Citation Chang, H.-K., Tan, Y.-C., Lai, J.-S., Pan, T.-Y., Liu, T.-M., and Tung, C.-P., 2013. Improvement of a drainage system for flood management with assessment of the potential effects of climate change. Hydrological Sciences Journal, 58 (8), 1581–1597.     

A Bayesian approach for estimating extreme flood probabilities with upper-bounded distribution functions

Some recent research on fluvial processes suggests the idea that some hydrological variables, such as flood flows, are upper-bounded. However, most probability distributions that are currently employed in flood frequency analysis are unbounded to the right. This paper describes an exploratory study on the joint use of an upper-bounded probability distribution and non-systematic flood information, within a Bayesian framework. Accordingly, the current PMF maximum discharge appears as a reference value and a reasonable estimate of the upper-bound for maximum flows, despite the fact that PMF determination is not unequivocal and depends strongly on the available data. In the Bayesian context, the uncertainty on the PMF can be included into the analysis by considering an appropriate prior distribution for the maximum flows. In the sequence, systematic flood records, historical floods, and paleofloods can be included into a compound likelihood function which is then used to update the prior information on the upper-bound. By combining a prior distribution describing the uncertainties of PMF estimates along with various sources of flood data into a unified Bayesian approach, the expectation is to obtain improved estimates of the upper-bound. The application example was conducted with flood data from the American river basin, near the Folsom reservoir, in California, USA. The results show that it is possible to put together concepts that appear to be incompatible: the deterministic estimate of PMF, taken as a theoretical limit for floods, and the frequency analysis of maximum flows, with the inclusion of non-systematic data. As compared to conventional analysis, the combination of these two concepts within the logical context of Bayesian theory, contributes an advance towards more reliable estimates of extreme floods.