Modelling reservoir sedimentation and estimating historical deposition rates using a data-based mechanistic (DBM) approach

Abstract

The data-based mechanistic (DBM) modelling methodology is applied to the study of reservoir sedimentation. A lumped-parameter, discrete-time model has been developed which directly relates rainfall to suspended sediment load (SSL) at the reservoir outflow from the two years of measured data at Wyresdale Park Reservoir (Lancashire, UK). This nonlinear DBM model comprises two components: a rainfall to SSL model and a second model, relating the SSL at the reservoir inflow to the SSL at the reservoir spillway. Using a daily measured rainfall series as the input, this model is used to reconstruct daily deposition rates between 1911 and 1996. This synthetic sediment accretion sequence is compared with the variations in sand content within sediment cores collected from the reservoir floor. These profiles show good general agreement, reflecting the importance of low reoccurrence, high magnitude events. This preliminary study highlights the potential of this DBM approach, which could be readily applied to other sites.     

Application of a data‐based mechanistic modelling (DBM) approach for predicting runoff generation in semi‐arid regions

This paper addresses the application of a data‐based mechanistic (DBM) modelling approach using transfer function models (TFMs) with non‐linear rainfall filtering to predict runoff generation from a semi‐arid catchment (795 km²) in Tanzania. With DBM modelling, time series of rainfall and streamflow were allowed to suggest an appropriate model structure compatible with the data available. The model structures were evaluated by looking at how well the model fitted the data, and how well the parameters of the model were estimated. The results indicated that a parallel model structure is appropriate with a proportion of the runoff being routed through a fast flow pathway and the remainder through a slow flow pathway. Finally, the study employed a Generalized Likelihood Uncertainty Estimation (GLUE) methodology to evaluate the parameter sensitivity and predictive uncertainty based on the feasible parameter ranges chosen from the initial analysis of recession curves and calibration of the TFM. Results showed that parameters that control the slow flow pathway are relatively more sensitive than those that control the fast flow pathway of the hydrograph. Within the GLUE framework, it was found that multiple acceptable parameter sets give a range of predictions. This was found to be an advantage, since it allows the possibility of assessing the uncertainty in predictions as conditioned on the calibration data and then using that uncertainty as part of the decision‐making process arising from any rainfall‐runoff modelling project. Copyright © 2001 John Wiley & Sons, Ltd.     

Subglacial drainage system changes of the Gulkana Glacier,Alaska: discharge and sediment load observations and modelling

Hydrological characteristics of englacial and subglacial drainage systems in Gulkana Glacier, Alaska, were examined by analysing temporal variations of discharge and sediment load in the proglacial Phelan Creek in 2001. From data plots on semi‐log paper, it appeared appropriate to separate both discharge and sediment load into fast and slow components. The two components were possibly produced by two different drainage systems: an englacial and subglacial, ‘channellized’ system in the ablation zone, and a subglacial, ‘distributed’ system in the accumulation zone. The data indicate the occurrence of an event during which part of the ‘distributed’ drainage system changed into the ‘channellized’ drainage system. The daily time‐series of discharge and sediment load were represented using a tank model. In the model, the drainage from an additional tank was added, supposing that a subglacial reservoir full of water and sediment collapsed slowly when the subglacial drainage system changed from distributed to channellized. The simulation with the collapsed tank gave much more reasonable results than those with no collapsed tank. The contribution of the collapsed tank to total sediment load is 24%, which is much larger than 9% to total discharge. Copyright © 2006 John Wiley & Sons, Ltd.     

Optimization of the Sefid-Roud Dam desiltation process using a sophisticated one-dimensional numerical model

Although water and soil conservation activities reduce reservoir sedimentation, it is inevitable that reservoirs fed by rivers transporting high amounts of sediment will experience sedimentation. The Ghezel-Ozan and Shah-Roud rivers, which flow to the Sefld-Roud reservoir dam, are both highly sediment-laden and transport significant amounts of sediment in both bed load and suspended load forms to the reservoir. Hence, it seems that the only practical way to remove the sediment from the reservoir is to flush it out using the Chasse method. In the present paper, field measurements of Chasse operation characteristics taken in previous years are presented, and a numerical model that simulates this process is introduced. After calibrating the model using field measured data, the calculated results （for reservoir pressure flushing and released sediment volume） of the numerical model were compared with other measured data for the same Chasse operation and the results agree well. Finally, using the numerical simulation results, the best approaches to ensure highly effective flushing while conserving reservoir water are presented （at least for the Sefid-Roud dam）. The operation of the bottom outlet gates, the shape of the output hydrograph, and the reservoir water level variation during flushing were optimized. In addition, the numerical model and related parameters, which need to be calibrated, are discussed.     

Including spatial distribution in a data‐driven rainfall‐runoff model to improve reservoir inflow forecasting in Taiwan

Multi‐step ahead inflow forecasting has a critical role to play in reservoir operation and management in Taiwan during typhoons as statutory legislation requires a minimum of 3‐h warning to be issued before any reservoir releases are made. However, the complex spatial and temporal heterogeneity of typhoon rainfall, coupled with a remote and mountainous physiographic context, makes the development of real‐time rainfall‐runoff models that can accurately predict reservoir inflow several hours ahead of time challenging. Consequently, there is an urgent, operational requirement for models that can enhance reservoir inflow prediction at forecast horizons of more than 3 h. In this paper, we develop a novel semi‐distributed, data‐driven, rainfall‐runoff model for the Shihmen catchment, north Taiwan. A suite of Adaptive Network‐based Fuzzy Inference System solutions is created using various combinations of autoregressive, spatially lumped radar and point‐based rain gauge predictors. Different levels of spatially aggregated radar‐derived rainfall data are used to generate 4, 8 and 12 sub‐catchment input drivers. In general, the semi‐distributed radar rainfall models outperform their less complex counterparts in predictions of reservoir inflow at lead times greater than 3 h. Performance is found to be optimal when spatial aggregation is restricted to four sub‐catchments, with up to 30% improvements in the performance over lumped and point‐based models being evident at 5‐h lead times. The potential benefits of applying semi‐distributed, data‐driven models in reservoir inflow modelling specifically, and hydrological modelling more generally, are thus demonstrated. Copyright © 2012 John Wiley & Sons, Ltd.     

Evaluating spatial variation of suspended sediment rating curves in the middle Yellow River basin,China

Abstract The suspended sediment load in the middle Yellow River basin (YRB) cannot be well predicted by capacity‐based transport formulas because a large fraction of suspended sediment load is composed of wash load. This study evaluated the spatial variations of sediment rating curves (SRCs) in the middle YRB. Both power and linear SRCs were used to fit daily flow and suspended sediment concentration (SSC) historical data at 49 gauging stations throughout the middle YRB. The spatial variation in regression coefficients was investigated, and the relationship between regression coefficients and the physical characteristics of watersheds was discussed. The results indicate that SRC regression coefficients vary with drainage area and basin slope, but their responses to these parameters are remarkably different in watersheds with different underlying surfaces, which indicates the significance of sediment availability, erodibility, and grain size distribution. For power SRCs representing sediment transport in unsaturated flows, the regression coefficients are more closely correlated with the drainage area in loess regions and with the basin slope in rock mountain regions. For linear SRCs representing sediment transport in saturated flows, saturated SSCs vary with coarse (particle size > 0.05 mm) and fine (particle size < 0.01 mm) fractions in suspended sediment. The maximum saturated SSC among the different gauging stations is associated with the optimal grain size composition of suspended sediment, which has been proposed for loess regions in previous studies. This study provides theoretical support for estimating the regression parameters for sediment transport modelling, especially in ungauged basins.     

Composite suspended sediment particles in river systems: their incidence,dynamics and physical characteristics

Most of the existing data on the effective particle size characteristics of fluvial suspended sediment derive from instantaneous sampling methods that may not be representative of the overall suspended sediment loads. This presents difficulties when there is a need to incorporate effective particle size data into numerical models of floodplain sedimentation and sediment‐associated contaminant transfer. We have used a field‐based water elutriation apparatus (WEA) to assemble a large (36 flood) database on the time‐integrated nature of the effective and absolute particle size characteristics of suspended sediment in four subcatchments of the River Exe basin of southwest England. These catchments encompass a wide range of terrains and fluvial environments that are broadly representative of much of the UK and temperate, low relief northwest Europe. The WEA provides important data on the physical characteristics of composite particles that are not attainable using other methods. This dataset has allowed, for the first time, detailed interbasin comparisons of the time‐integrated particle size characteristics of suspended sediment and reliable estimates of the contribution of five effective size classes to the mean annual suspended sediment load of the study catchments. The suspended sediment load of each river is dominated by composite rather than primary particles, with, for example, almost 60% (by mass) of the sediment load of the River Exe at Thorverton transported as composite particles > 16 µm in size. All the effective size classes contain significant clay components. A key outcome of this study is the recognition that each catchment has a distinctive time‐integrated effective particle size signature. In addition, the time‐integrated effective particle size characteristics of the suspended loads in each of the catchments display much greater spatial variability than the equivalent absolute particle size distributions. This indicates that the processes producing composite particles vary significantly between these catchments, and this has important implications for our understanding of the dynamics of suspended sediment properties. Copyright © 2007 John Wiley & Sons, Ltd.     

A neuro-fuzzy-based modelling approach for sediment transport computation

Abstract

The application of a data-driven adaptive neuro-fuzzy modelling technique for predicting bed load and total bed-material load for the River Rhine is summarized. Four main parameters affecting sediment transport are used to construct the model, using 560 and 510 measured bed load and total bed-material load data, respectively. Two-thirds of the available data sets are used for training and one third for testing. The initial fuzzy model is obtained by grid partitioning of the input variables. The optimization of the model is performed by data-driven tuning of the fuzzy model parameters using the adaptive neuro-fuzzy inference system, so that the model output is able to reproduce the measured value. A sensitivity analysis for the combination of input parameters, as well as the number and type of membership functions, is also performed. The model results show that the data-driven adaptive neuro-fuzzy modelling approach can be a powerful alternative technique for estimating both bed load and total bed-material load.

Editor D. Koutsoyiannis

Citation Wieprecht, S., Tolossa, H.G., and Yang, C.T., 2013. A neuro-fuzzy-based modelling approach for sediment transport computation. Hydrological Sciences Journal, 58 (3), 587–599.     

Integration of the life of field seismic data with the reservoir model at the Valhall Field‡

The frequent time‐lapse observations from the life of field seismic system across the Valhall field provide a wealth of information. The responses from the production and injection wells can be observed through time‐shift and amplitude changes. These observations can be compared to modelled synthetic seismic responses from a reservoir simulation model of the Valhall Field. The observed differences between the observations and the modelling are used to update and improve the history match of the reservoir model. The uncertainty of the resulting model is reduced and a more confident prediction of future reservoir performance is provided. A workflow is presented to convert the reservoir model to a synthetic seismic response and compare the results to the observed time‐lapse responses for any time range and area of interest. Correlation based match quality factors are calculated to quantify the visual differences. This match quality factor allows us to quantitatively compare alternative reservoir models to help identify the parameters that best match the seismic observations. Three different case studies are shown where this workflow has helped to reduce the uncertainty range associated with specific reservoir parameters. By updating various reservoir model parameters we have been able to improve the match to the observations and thereby improve the overall reservoir model predictability. The examples show positive results in a range of different reservoir modelling issues, which indicates the flexibility of this workflow and the ability to have an impact in most reservoir modelling challenges.     

2D stream hydrodynamic,sediment transport and bed morphology model for engineering applications

A 2D depth‐averaged hydrodynamic, sediment transport and bed morphology model named STREMR HySeD is presented. The depth‐averaged sediment transport equations are derived from the 3D dilute, multiphase, flow equations and are incorporated into the hydrodynamic model STREMR. The hydrodynamic model includes a two‐equation turbulence model and a correction for the mean flow due to secondary flows. The suspended sediment load can be subdivided into different size classes using the continuum (two‐fluid) approach; however, only one bed sediment size is used herein. The validation of the model is presented by comparing the suspended sediment transport module against experimental measurements and analytical solutions for the case of equilibrium sediment‐laden in a transition from a rigid bed to a porous bed where re‐suspension of sediment is prevented. On the other hand, the bed‐load sediment transport and bed evolution numerical results are compared against bed equilibrium experimental results for the case of a meander bend. A sensitivity analysis based on the correction for secondary flow on the mean flow including the effect of secondary flow on bed shear stresses direction as well as the downward acceleration effect due to gravity on transverse bed slopes is performed and discussed. In general, acceptable agreement is found when comparing the numerical results obtained with STREMR HySeD against experimental measurements and analytical solutions. Copyright © 2007 John Wiley & Sons, Ltd.     

Prediction of Density Flow Plunging Depth in Dam Reservoirs: An Artificial Neural Network Approach

Experimental findings and observations indicate that plunging flow is related to the formation of bed load deposition in dam reservoirs. The sediment delta begins to form in the plunging region where the inflow river water meets the ambient reservoir water. Correct estimation of dam reservoir flow, plunging point, and plunging depth is crucial for dam reservoir sedimentation and water quality issues. In this study, artificial neural network (ANN), multi‐linear regression (MLR), and two‐dimensional hydrodynamic model approaches are used for modeling the plunging point and depth. A multi layer perceptron (MLP) is used as the ANN structure. A two‐dimensional model is adapted to simulate density plunging flow through a reservoir with a sloping bottom. In the model, nonlinear and unsteady continuity, momentum, energy, and k–ε turbulence equations are formulated in the Cartesian coordinates. Density flow parameters such as velocity, plunging points, and plunging depths are determined from the simulation and model results, and these are compared with previous experimental and model works. The results show that the ANN model forecasts are much closer to the experimental data than the MLR and mathematical model forecasts.     

Numerical modelling of floodplain hydraulics and suspended sediment transport and deposition at the event scale in the middle river Elbe,Germany

The objective of this case study was to calibrate and verify detailed transport model of sediment in a 4‐kilometre stretch of the middle Elbe floodplains in Germany. The hydraulic RMA‐2 model and the SED2d‐WES sediment transport model were used. These models were calibrated and validated by detailed measurement of the surface water elevations, the velocities at six profiles, and the suspended sediment concentration and deposition (by means of 10 sediment traps). The flow was modelled for three steady‐state discharges. The surface water elevations were calculated to an accuracy of less than 5 cm compared to measurements. The differences between the calculated and measured velocities were with one exception smaller than 0.2 m/s (measured range 0.1…?1.0 m/s). An average sediment input of 35 g/(m² d) was calculated for the flood event studied. The highest calculated sedimentation rates of 700 g/(m² d) (dry density 90 kg/m³) occurred in quiescent zones and abandoned channels. Twenty‐five percent of the deposited sediment settled in the quiescent zones (which only account for 13% of the area). The most sensitive parameters of the sediment transport model were the settling velocity and critical shear stress. The modelling techniques used allowed sediment deposition on the floodplains of the Elbe to be realistically depicted.     

Evaluation of a dynamic multi‐class sediment transport model in a catchment under soil‐conservation agriculture

Soil erosion models are essential tools for the successful implementation of effective and adapted soil conservation measures on agricultural land. Therefore, models are needed that predict sediment delivery and quality, give a good spatial representation of erosion and deposition and allow us to account for various soil conservation measures. Here, we evaluate how well a modified version of the spatially distributed multi‐class sediment transport model (MCST) simulates the effectiveness of control measures for different event sizes. We use 8 year runoff and sediment delivery data from two small agricultural watersheds (0·7 and 3·7 ha) under optimized soil conservation. The modified MCST model successfully simulates surface runoff and sediment delivery from both watersheds; one of which was dominated by sheet and the other was partly affected by rill erosion. Moreover, first results of modelling enrichment of clay in sediment delivery are promising, showing the potential of MCST to model sediment enrichment and nutrient transport. In general, our results and those of an earlier modelling exercise in the Belgian Loess Belt indicate the potential of the MCST model to evaluate soil erosion and deposition under different agricultural land uses. As the model explicitly takes into account the dominant effects of soil‐conservation agriculture, it should be successfully applicable for soil‐conservation planning/evaluation in other environments. Copyright © 2008 John Wiley & Sons, Ltd.     

Estimation of suspended sediment loads in a seasonal stream in the wet‐dry tropics,Northern Territory,Australia

One year of instantaneous suspended sediment concentration, C, and instantaneous discharge, Q, data collected at Ngarradj downstream of the Jabiluka mine site indicate that the use of a simple C–Q rating curve is not a reliable method for estimating suspended sediment loads from the Ngarradj catchment. The C–Q data are not only complicated by hysteresis effects within the rising and falling stages of individual events, but also by variable depletion of available suspended sediment through multipeaked runoff events. Parameter values were fitted to an event‐based suspended sediment load–Q relationship as an alternative to the C–Q relationship. Total suspended sediment load and Q data for 10 observed events in the Ngarradj stream catchment were used to fit parameter values to a suspended sediment load–Q relationship, using (a) log–log regression and (b) iterative parameter fitting techniques. A more reliable and statistically significant prediction of suspended sediment load from the Ngarradj catchment is obtained using an event‐based suspended sediment load–Q relationship. Fitting parameters to the event‐based suspended sediment load–Q relationship using iterative techniques better predicts long‐term suspended sediment loads compared with log–log regression techniques. Copyright © 2004 John Wiley & Sons, Ltd.     

Load or concentration,logged or unlogged? Addressing ten years of uncertainty in neural network suspended sediment prediction

This paper addresses current inconsistencies in methodological approaches for neural network modelling of suspended sediment. An expansion in the number of case studies being published over the last decade has yet to result in agreed guidelines on whether suspended sediment load or concentration should be modelled, and whether log‐transformation of data is either necessary or potentially beneficial. This contrasts with the well‐recognized guidelines that direct traditional sediment rating curve studies. The paper reports a comprehensive set of single‐input single‐output neural network suspended sediment modelling experiments performed on two catchments in Puerto Rico. It examines the impact of internal complexity, input variable choice and data transformation on the form, consistency and physical rationality of model outputs, the existence of localized overfitting and the usefulness of global performance metrics. Sound guidance on whether to model sediment load or concentration, and whether to model log‐transformed data is provided. Copyright © 2011 John Wiley & Sons, Ltd.     

Suspended sediment load estimation and the problem of inadequate data sampling: a fractal view

Suspended sediment load estimation at high resolutions is an extremely difficult task, because: (1) it depends on the availability of high‐resolution water discharge and suspended sediment concentration measurements, which are often not available; (2) any errors in the measurements of these two components could significantly influence the accuracy of suspended sediment load estimation; and (3) direct measurements are very expensive. The purpose of this study is to approach this sampling problem from a new perspective of fractals (or scaling), which could provide important information on the transformation of suspended sediment load data from one scale to another. This is done by investigating the possible presence of fractal behaviour in the daily suspended sediment load data for the Mississippi River basin (at St. Louis, Missouri). The presence of fractal behaviour is investigated using five different methods, ranging from general to specific and from mono‐fractal to multi‐fractal: (1) autocorrelation function; (2) power spectrum; (3) probability distribution function; (4) box dimension; and (5) statistical moment scaling function. The results indicate the presence of multi‐fractal behaviour in the suspended sediment load data, suggesting the possibility of transformation of data from one scale to another using a multi‐dimensional model. Copyright © 2005 John Wiley & Sons, Ltd.     

Temporal variations of reservoir sediment sources in a small mountainous catchment in Korea

An understanding of the temporal variation in reservoir sedimentation and identification of the main sources of sediment are necessary for the maintenance of sustainable reservoirs. For this purpose, field measurements, sampling, and fingerprinting of reservoir sediment were undertaken from July 2005 to November 2007. Source fingerprinting of reservoir sediment was conducted using cesium‐137 (¹³⁷Cs). The relative contributions of gully bank and forest road, and forest floor material to reservoir sediment were calculated using a mixing model. Bank and forest road material, estimated to make up about 96% of the reservoir sediment, was the dominant source. Enormous reservoir sedimentation, which amounted to about 60% of the total reservoir sedimentation during the observation period, occurred during a heavy rainstorm with an 80‐year recurrence time. To maintain the sustainability of the reservoir in this study, therefore, temporal and spatial preparation strategies for heavy rainstorms and bank and forest road erosion should be considered. However, spatial information on sediment sources from ¹³⁷Cs fingerprinting is limited. To better identify the sediment sources spatially and temporally, further studies applying soil erosion models and more detailed field studies are needed. Copyright © 2013 John Wiley & Sons, Ltd.     

Morphodynamic assessment of side channel systems using a simple one‐dimensional bifurcation model and a comparison with aerial images

Side channel construction is a common intervention applied to increase a river's conveyance capacity and to increase its ecological value. Past modelling efforts suggest two mechanisms affecting the morphodynamic change of a side channel: (1) a difference in channel slope between the side channel and the main channel and (2) bend flow just upstream of the bifurcation. The objective of this paper was to assess the conditions under which side channels generally aggrade or degrade and to assess the characteristic timescales of the associated morphological change. We use a one‐dimensional bifurcation model to predict the development of side channel systems and the characteristic timescale for a wide range of conditions. We then compare these results to multitemporal aerial images of four side channel systems. We consider the following mechanisms at the bifurcation to be important for side channel development: sediment diversion due to the bifurcation angle, sediment diversion due to the transverse bed slope, partitioning of suspended load, mixed sediment processes such as sorting at the bifurcation, bank erosion, deposition due to vegetation, and floodplain sedimentation. There are limitations to using a one‐dimensional numerical model as it can only account for these mechanisms in a parametrized manner, but the model reproduces general behaviour of the natural side channels until floodplain‐forming processes become important. The main result is a set of stability diagrams with key model parameters that can be used to assess the development of a side channel system and the associated timescale, which will aid in the future design and maintenance of side channel systems. © 2017 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.     

Time‐lapse seismic modelling of CO2 fluid substitution in the Devonian Redwater Reef,Alberta, Canada

Common shot ray tracing and finite difference seismic modelling experiments were undertaken to evaluate variations in the seismic response of the Devonian Redwater reef in the Alberta Basin, Canada after replacement of native pore waters in the upper rim of the reef with CO₂. This part of the reef is being evaluated for a CO₂ storage project. The input geological model was based on well data and the interpretation of depth‐converted, reprocessed 2D seismic data in the area. Pre‐stack depth migration of the ray traced and finite difference synthetic data demonstrate similar seismic attributes for the Mannville, Nisku, Ireton, Cooking Lake, and Beaverhill Lake formations and clear terminations of the Upper Leduc and Middle Leduc events at the reef margin. Higher amplitudes at the base of Upper‐Leduc member are evident near the reef margin due to the higher porosity of the foreslope facies in the reef rim compared to the tidal flat lagoonal facies within the central region of the reef. Time‐lapse seismic analysis exhibits an amplitude difference of about 14% for Leduc reflections before and after CO₂ saturation and a travel‐time delay through the reservoir of 1.6 ms. Both the ray tracing and finite difference approaches yielded similar results but, for this particular model, the latter provided more precise imaging of the reef margin. From the numerical study we conclude that time‐lapse surface seismic surveys should be effective in monitoring the location of the CO₂ plume in the Upper Leduc Formation of the Redwater reef, although the differences in the results between the two modelling approaches are of similar order to the effects of the CO₂ fluid replacement itself.     

Sediment yield modelling for small agricultural catchments: land‐cover parameterization based on remote sensing data analysis

Vegetation and soil properties and their associated changes through time and space affect the various stages of soil erosion. The island of Ishigaki in Okinawa Prefecture, Japan is of particular concern because of the propensity of the red‐soil‐dominated watersheds in the area to contribute substantial sediment discharge to adjacent coastal areas. This paper discusses the application of remote sensing techniques in the retrieval of vegetation and soil parameters necessary for the distributed soil‐loss modelling in small agricultural catchments and analyses the variation in erosional patterns and sediment distribution during rainfall events using numerical solutions of overland flow simulations and sediment continuity equations. To account for the spatial as well as temporal variability of selected parameters of the soil‐loss equations, a method is proposed to account for the variability of associated vegetation cover based on their spectral characteristics as captured by remotely sensed data. To allow for complete spatial integration, modelling the movement of sediment is accomplished under a loose‐coupled GIS computational framework. This study lends a theoretical support and empirical evidence to the role of vegetation as a potential agent for soil erosion control. Copyright © 2003 John Wiley & Sons, Ltd.