Real-time flood forecasting by relating local stage and remote discharge

Abstract

The rating curve model (RCM) proposed by Moramarco and co-authors is modified here for flood forecasting purposes without using rainfall information. The RCM is a simple approach for discharge assessment at a river site of interest based on relating the local recorded stage and the remote discharge monitored at an upstream gauged river site located some distance away. The proposed RCM for real-time application (RCM-RT), involves only two parameters and can be used for river reaches where significant lateral flows occur. The forecast lead time depends on the mean wave travel time of the reach. The model is found to be accurate for a long reach of the Po River (northern Italy) and for two branches of the Tiber River (central Italy) characterized by different intermediate drainage areas and wave travel times. Moreover, the assessment of the forecast uncertainty coming from the model parameters is investigated by performing a Monte Carlo simulation. Finally, the model capability to accurately forecast the exceedence of fixed hydrometric thresholds is analysed.

Editor D. Koutsoyiannis; Associate editor C. Perrin     

Predicting and forecasting flow discharge at sites receiving significant lateral inflow

Two models, one linear and one non‐linear, were employed for the prediction of flow discharge hydrographs at sites receiving significant lateral inflow. The linear model is based on a rating curve and permits a quick estimation of flow at a downstream site. The non‐linear model is based on a multilayer feed‐forward back propagation (FFBP) artificial neural network (ANN) and uses flow‐stage data measured at the upstream and downstream stations. ANN predicted the real‐time storm hydrographs satisfactorily and better than did the linear model. The results of sensitivity analysis indicated that when the lateral inflow contribution to the channel reach was insignificant, ANN, using only the flow‐stage data at the upstream station, satisfactorily predicted the hydrograph at the downstream station. The prediction error of ANN increases exponentially with the difference between the peak discharge used in training and that used in testing. ANN was also employed for flood forecasting and was compared with the modified Muskingum model (MMM). For a 4‐h lead time, MMM forecasts the floods reliably but could not be applied to reaches for lead times greater than the wave travel time. Although ANN and MMM had comparable performances for an 8‐h lead time, ANN is capable of forecasting floods with lead times longer than the wave travel time. Copyright © 2007 John Wiley & Sons, Ltd.     

Assessment of river flow with significant lateral inflow through reverse routing modeling

The discharge hydrograph estimation in rivers based on reverse routing modeling and using only water level data at two gauged sections is here extended to the most general case of significant lateral flow contribution, without needing to deploy rainfall–runoff procedures. The proposed methodology solves the Saint‐Venant equations in diffusive form also involving the lateral contribution using a “head‐driven” modeling approach where lateral inflow is assumed to be function of the water level at the tributary junction. The procedure allows to assess the discharge hydrograph at ends of a selected river reach with significant lateral inflow, starting from the stage recorded there and without needing rainfall data. Specifically, the MAST 1D hydraulic model is applied to solve the diffusive wave equation using the observed stage hydrograph at the upstream section as upstream boundary condition. The other required data are (a) the observed stage hydrograph at the downstream section, as benchmark for the parameter calibration, and (b) the bathymetry of the river reach, from the upstream section to a short distance after the downstream gauged section. The method is validated with different flood events observed in two river reaches with a significant intermediate basin, where reliable rating curves were available, selected along the Tiber River, in central Italy, and the Alzette River, in Luxembourg. Very good performance indices are found for the computed discharge hydrographs at both the channel ends and along the tributaries. The mean Nash‐Sutcliffe value (NS_q) at the channel ends of two rivers is found equal to 0.99 and 0.86 for the upstream and downstream sites, respectively. The procedure is also validated on a longer stretch of the Tiber River including three tributaries for which appreciable results are obtained in terms of NS_q for the computed discharge hydrographs at both the channel ends for three investigated flood events.     

Flash flood forecasting model for the Ayalon stream,Israel

Abstract

A composite model for real time forecasting of flash floods in the Ayalon stream in central Israel has been constructed. The model is composed of four kinds of sub-models: an autoregressive model for discharges at upstream stations on the two major tributaries; a travel-time model for the flow from these stations to the downstream station located on the main stem of the stream; a time-area concentration curve for subwatershed drainage between the upstream and downstream stations; and a recession curve for the downstream station. The model incorporates an adaptive mechanism for continuous correction of forecast errors. This mechanism is calibrated during an initial period of operation, and is subsequently operated throughout a flow event. The model issues simultaneous forecasts for seven lead times ranging from 0.5 to 3.5 h. This provides a proper input for a flood warning system which is required for safe operation of a major highway running along the banks of a torrent stream in the metropolitan area of Tel-Aviv.     

Confidence interval of real‐time forecast stages provided by the STAFOM‐RCM model: the case study of the Tiber River (Italy)

This study proposes a statistically based procedure to quantify the confidence interval (CI) to be associated to the stages forecast by a simple model called STAge FOrecasting Model‐Rating Curve Model (STAFOM‐RCM). This model can be used for single river reaches characterized by different intermediate drainage areas and mean wave travel times when real‐time stage records, cross section surveys and rating curves are available at both ends. The model requires, at each time of forecast, an estimate of the lateral contribution q_for between the two sections delimiting the reach. The CI of the stage is provided by analyzing the statistical properties of model output in terms of lateral flow, and it is derived from the CI of the lateral contribution q_for which, in turn, is set up by associating to each q_for the q_opt which allows STAFOM‐RCM to reproduce the exact observed stage. From an operative point of view, the q_for values are ranked in order of magnitude and subdivided in classes where the q_opt values can be represented through normal distributions of proper mean and variance from which an interval of selected confidence level for q_for is computed and transferred to the stage. Three river reaches of the Tiber river, in central Italy, are used as case study. A sensitivity analysis is also performed in order to identify the minimum calibration set of flood events. The CIs obtained are consistent with the level of confidence selected and have practical utility. An interesting aspect is that different CI widths can be produced for the same forecast stage since they depend on the estimate of q_for made at the time of forecast. Overall, the proposed procedure for CI estimate is simple and can be conveniently adapted for other forecasting models provided that they have physically based parameters which need to be updated during the forecast. Copyright © 2012 John Wiley & Sons, Ltd.     

A data based mechanistic approach to nonlinear flood routing and adaptive flood level forecasting

Operational flood forecasting requires accurate forecasts with a suitable lead time, in order to be able to issue appropriate warnings and take appropriate emergency actions. Recent improvements in both flood plain characterization and computational capabilities have made the use of distributed flood inundation models more common. However, problems remain with the application of such models. There are still uncertainties associated with the identifiability of parameters; with the computational burden of calculating distributed estimates of predictive uncertainty; and with the adaptive use of such models for operational, real-time flood inundation forecasting. Moreover, the application of distributed models is complex, costly and requires high degrees of skill. This paper presents an alternative to distributed inundation models for real-time flood forecasting that provides fast and accurate, medium to short-term forecasts. The Data Based Mechanistic (DBM) methodology exploits a State Dependent Parameter (SDP) modelling approach to derive a nonlinear dependence between the water levels measured at gauging stations along the river. The transformation of water levels depends on the relative geometry of the channel cross-sections, without the need to apply rating curve transformations to the discharge. The relationship obtained is used to transform water levels as an input to a linear, on-line, real-time and adaptive stochastic DBM model. The approach provides an estimate of the prediction uncertainties, including allowing for heterescadasticity of the multi-step-ahead forecasting errors. The approach is illustrated using an 80 km reach of the River Severn, in the UK.     

基于洪水预报系统误差反演的多河段联合校正方法

提出一种基于洪水预报误差系统反演的多河段联合校正方法.采用马斯京根法矩阵方程描述多河段多区间入流的河道汇流过程,基于动力系统反演理论建立洪水预报误差的递推方程,最后利用修正后的多河段状态变量经演算得到预报断面的洪水过程,进而达到多河段联合校正目的.对大渡河上游的应用示例结果表明：多河段联合校正方法考虑了河系中断面间的水力联系及预报误差在时程上的传递规律,可充分利用上游多断面实测和校正信息进行下游预报断面的误差修正,因此具有更高的校正精度和稳定性.     

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.     

ANALYTICAL HAYAMI SOLUTION FOR THE DIFFUSIVE WAVE FLOOD ROUTING PROBLEM WITH LATERAL INFLOW

The diffusive wave equation is generally used in flood routing in rivers. The two parameters of the equation, celerity and diffusivity, are usually taken as functions of the discharge. If these two parameters can be assumed to be constant without lateral inflow, the diffusive wave equation may have an analytical solution: the Hayami model. A general analytical method, based on ‘Hayami’s hypothesis, is developed here which resolves the diffusive wave flood routing equation with lateral inflow or outflow uniformly distributed over a channel reach. Flood routing parameters are then identified using observed inflow and outflow and the Hayami model used to simulate outflow. Two examples are discussed. Firstly, the prediction of the hydrograph at a downstream section on the basis of a knowledge of the hydrograph at an upstream section and the lateral inflow. The second example concerns lateral inflow identification between an upstream and a downstream section on the basis of a knowledge of hydrographs at the upstream and downstream sections. The new general Hayami model was applied to flood routing simulation and for lateral inflow identification of the River Allier in France. The major advantages of the method relate to computer simulation, real-time forecasting and control applications in examples where numerical instabilities, in the solution of the partial differential equations must be avoided.     

Fuzzy computing based rainfall–runoff model for real time flood forecasting

This paper analyses the skills of fuzzy computing based rainfall–runoff model in real time flood forecasting. The potential of fuzzy computing has been demonstrated by developing a model for forecasting the river flow of Narmada basin in India. This work has demonstrated that fuzzy models can take advantage of their capability to simulate the unknown relationships between a set of relevant hydrological data such as rainfall and river flow. Many combinations of input variables were presented to the model with varying structures as a sensitivity study to verify the conclusions about the coherence between precipitation, upstream runoff and total watershed runoff. The most appropriate set of input variables was determined, and the study suggests that the river flow of Narmada behaves more like an autoregressive process. As the precipitation is weighted only a little by the model, the last time‐steps of measured runoff are dominating the forecast. Thus a forecast based on expected rainfall becomes very inaccurate. Although good results for one‐step‐ahead forecasts are received, the accuracy deteriorates as the lead time increases. Using the one‐step‐ahead forecast model recursively to predict flows at higher lead time, however, produces better results as opposed to different independent fuzzy models to forecast flows at various lead times. Copyright © 2004 John Wiley & Sons, Ltd.     

Diffusive wave solutions for open channel flows with uniform and concentrated lateral inflow

The diffusive wave equation with inhomogeneous terms representing hydraulics with uniform or concentrated lateral inflow into a river is theoretically investigated in the current paper. All the solutions have been systematically expressed in a unified form in terms of response function or so called K-function. The integration of K-function obtained by using Laplace transform becomes S-function, which is examined in detail to improve the understanding of flood routing characters. The backwater effects usually resulting in the discharge reductions and water surface elevations upstream due to both the downstream boundary and lateral inflow are analyzed. With a pulse discharge in upstream boundary inflow, downstream boundary outflow and lateral inflow respectively, hydrographs of a channel are routed by using the S-functions. Moreover, the comparisons of hydrographs in infinite, semi-infinite and finite channels are pursued to exhibit the different backwater effects due to a concentrated lateral inflow for various channel types.     

Large wood distribution,mobility, and recruitment in an inter‐dam river reach: A comparison with geomorphic process on the Garrison Reach of the Missouri River pre and post the historical 2011 flood

This study assessed the effect of the largest flood since dam regulation on geomorphic and large wood (LW) trends using LW distributions at three time periods on the 150 km long Garrison Reach of the Missouri River. In 2011, a flood exceeded 4390 m³/s for a two‐week period (705% above mean flow; 500 year flood). LW was measured using high resolution satellite imagery in summer 2010 and 2012. Ancillary data including forest character, vegetation cover, lateral bank retreat, and channel capacity. Lateral bank erosion removed approximately 7400 standing trees during the flood. Other mechanisms, that could account for the other two‐thirds of the measured in‐channel LW, include overland flow through floodplains and islands. LW transport was commonly near or over 100 km as indicated by longitudinal forest and bank loss and post‐flood LW distribution. LW concentrations shift at several locations along the river, both pre‐ and post‐flood, and correspond to geomorphic river regions created by the interaction of the Garrison Dam upstream and the Oahe Dam downstream. Areas near the upstream dam experienced proportionally higher rates of bank erosion and forest loss but in‐channel LW decreased, likely due to scouring. A large amount of LW moved during this flood, the chief anchoring mechanism was not bridges or narrow channel reaches but the channel complexity of the river delta created by the downstream reservoir. Areas near the downstream dam experienced bank accretion and large amounts of LW deposition. This study confirms the results of similar work in the Reach: despite a historic flood longitudinal LW and channel trends remain the same. Dam regulation has created a geomorphic and LW pattern that is largely uninterrupted by an unprecedented dam regulation era flood. River managers may require other tools than infrequent high intensity floods to restore geomorphic and LW patterns. Copyright © 2018 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.     

Seasonal and annual maximum streamflow forecasting using climate information: application to the Three Gorges Dam in the Yangtze River basin,China / Prévision d'écoulements saisonnier et maximum annuel à l'aide d'informations climatiques: application au Barrage des Trois Gorges dans le bassin du Fleuve Yangtze,Chine

Abstract

This paper explores the potential for seasonal prediction of hydrological variables that are potentially useful for reservoir operation of the Three Gorges Dam, China. The seasonal flow of the primary inflow season and the peak annual flow are investigated at Yichang hydrological station, a proxy for inflows to the Three Gorges Dam. Building on literature and diagnostic results, a prediction model is constructed using sea-surface temperatures and upland snow cover available one season ahead of the prediction period. A hierarchical Bayesian approach is used to estimate uncertainty in the parameters of the prediction model and to propagate these uncertainties to the predictand. The results show skill for both the seasonal flow and the peak annual flow. The peak annual flow model is then used to estimate a design flood (50-year flood or 2% exceedence probability) on a year-to-year basis. The results demonstrate the inter-annual variability in flood risk. The predictability of both the seasonal total inflow and the peak annual flow (or a design flood volume) offers potential for adaptive management of the Three Gorges Dam reservoir through modification of the operating policy in accordance with the year-to-year changes in these variables.     

Amplification of flood discharge caused by the cascading failure of landslide dams

The cascading failure of multiple landslide dams can trigger a larger peak flood discharge than that caused by a single dam failure.Therefore,for an accurate numerical simulation,it is essential to elucidate the primary factors affecting the peak discharge of the flood caused by a cascading failure,which is the purpose of the current study.First,flume experiments were done on the cascading failure of two landslide dams under different upstream dam heights,downstream dam heights,and initial downstream reservoir water volumes.Then,the experimental results were reproduced using a numerical simulation model representing landslide dam erosion resulting from overtopping flow.Finally,the factors influencing the peak flood discharge caused by the cascading failure were analyzed using the numerical simulation model.Experimental results indicated that the inflow discharge into the downstream dam at the time when the downstream dam height began to rapidly erode was the main factor responsible for a cascading failure generating a larger peak flood discharge than that generated by a single dam failure.Furthermore,the results of a sensitivity analysis suggested that the upstream and downstream dam heights,initial water volume in the reservoir of the downstream dam,upstream and downstream dam crest lengths,and distance between two dams were among the most important factors in predicting the flood discharge caused by the cascading failure of multiple landslide dams.     

PUBLICATIONS OF THE IAHS

Abstract

Gauging stations where the stage—discharge relationship is affected by hysteresis due to unsteady flow represent a challenge in hydrometry. In such situations, the standard hydrometric practice of fitting a single-valued rating curve to the available stage—discharge measurements is inappropriate. As a solution to this problem, this study provides a method based on the Jones formula and nonlinear regression, which requires no further data beyond the available stage—discharge measurements, given that either the stages before and after each measurement are known along with the duration of each measurement, or a stage hydrograph is available. The regression model based on the Jones formula rating curve is developed by applying the monoclinal rising wave approximation and the generalized friction law for uniform flow, along with simplifying assumptions about the hydraulic and geometric properties of the river channel in conjunction with the gauging station. Methods for obtaining the nonlinear least-squares rating-curve estimates, while factoring in approximated uncertainty, are discussed. The broad practical applicability and appropriateness of the method are demonstrated by applying the model to: (a) an accurate, comprehensive and detailed database from a hydropower-generated highly dynamic flow in the Chattahoochee River, Georgia, USA; and (b) data from gauging stations in two large rivers in the USA affected by hysteresis. It is also shown that the model is especially suitable for post-modelling hydraulic and statistical validation and assessment.     

Peak discharge increase in hyperconcentrated floods

The peak of river floods usually decreases in the downstream direction unless it is compensated by freshwater inflow from tributaries. In the Yellow River (China) the opposite is regularly observed, where the peak discharge of river floods increases in the downstream direction (at a rate far exceeding the contribution from tributaries). This flood peak discharge increase is probably related to rapid morphological changes, to a modified bed friction, or to a combination of both. Yet the relative role of these processes is still poorly understood. This paper aims to analyze the relative contribution of bed erosion and friction change to the peak discharge increase, based on available data and a recently developed numerical model. Using this high-resolution, fully coupled morphodynamic model of non-capacity sediment transport, two hyperconcentrated floods characterized by downstream peak discharge increase are numerically reproduced and analyzed in detail. The results reveal that although erosion effects may contribute to the downstream discharge increase (especially in case of extreme erosion), for most cases the increase must be mainly due to a reduction in bed friction during peak discharge conditions. Additionally, based on the concept of channel storage reduction, the effects of decreasing bed friction and (very strong) bed erosion can be integrated in explaining the peak discharge increase.     

Bayesian estimation of inflow hydrographs in ungauged sites of multiple reach systems

A Bayesian Geostatistical Approach to evaluate unknown upstream flow hydrographs in multiple reach systems is implemented. The methodology was, firstly, tested through three synthetic examples of river confluences, that differ in the available data, boundary conditions and number of the estimated inflow time series. Input discharge hydrographs were routed downstream by means of the widely known HEC-RAS river analysis system to obtain the downstream stage hydrographs used as known observations for the reverse procedure. In almost all cases, the observed water levels were corrupted with random errors to highlight the reliability of the methodology in preventing instabilities and overfitting. Then the procedure was applied to the real case study of the Parma–Baganza river confluence located at the city of Parma (Italy) to assess the tributary Baganza River inflow hydrograph (supposed completely ungauged) using water level data collected downstream on the main reach. The results show that the methodology properly reproduces the unknown inflows even in presence of errors affecting the downstream water levels. The practical applicability of the proposed approach is also demonstrated in complex river systems.     

The effects of floods on the temperature of riparian groundwater

The transition area between rivers and their adjacent riparian aquifers, which may comprise the hyporheic zone, hosts important biochemical reactions, which control water quality. The rates of these reactions and metabolic processes are temperature dependent. Yet the thermal dynamics of riparian aquifers, especially during flooding and dynamic groundwater flow conditions, has seldom been studied. Thus, we investigated heat transport in riparian aquifers during 3 flood events of different magnitudes at 2 sites along the same river. River and riparian aquifer temperature and water‐level data along the Lower Colorado River in Central Texas, USA, were monitored across 2‐dimensional vertical sections perpendicular to the bank. At the downstream site, preflood temperature penetration distance into the bank suggested that advective heat transport from lateral hyporheic exchange of river water into the riparian aquifer was occurring during relatively steady low‐flow river conditions. Although a small (20‐cm stage increase) dam‐controlled flood pulse had no observable influence on groundwater temperature, larger floods (40‐cm and >3‐m stage increases) caused lateral movement of distinct heat plumes away from the river during flood stage, which then retreated back towards the river after flood recession. These plumes result from advective heat transport caused by flood waters being forced into the riparian aquifer. These flood‐induced temperature responses were controlled by the size of the flood, river water temperature during the flood, and local factors at the study sites, such as topography and local ambient water table configuration. For the intermediate and large floods, the thermal disturbance in the riparian aquifer lasted days after flood waters receded. Large floods therefore have impacts on the temperature regime of riparian aquifers lasting long beyond the flood's timescale. These persistent thermal disturbances may have a significant impact on biochemical reaction rates, nutrient cycling, and ecological niches in the river corridor.     

Real-time correction of water stage forecast during rainstorm events using combination of forecast errors

This study proposes a real-time error correction method for the forecasted water stage using a combination of forecast errors estimated by the time series models, AR(1), AR(2), MA(1) and MA(2), and the average deviation model to update the water stage forecast during rainstorm events. During flood forecasting and warning operations, the proposed real-time error correction method takes advantage of being individually and continuously implemented and the results not being updated to the hydrological model and hydraulic routings so as to save computational time by recalibrating the parameters of the proposed methods with real-time observation. For model validation, the current study adopts the observed and forecasted data on a severe typhoon, Morakot, collected at eight water level gauges in Southern Taiwan and provided by the flood forecast system FEWS_Taiwan, which is linked with the reliable quantitative precipitation forecast (QPF) at 3 h of lead time provided by the Center Weather Bureau in Taiwan, as the model validation. The results of numerical experiments indicate that the proposed real-time error correction method can effectively reduce the errors of forecasted water stages at the 1-, 2-, and 3-h lead time and so enhance the reliability of forecast information issued by the FEWS_Taiwan. By means of real-time estimating potential forecast error, the uncertainties in hydrology, modules as well as associated parameters, and physiographical features of the river can be reduced.