PHYSICAL MODELING OF HYDRAULIC DESILTATION IN TAPU RESERVOIR

1 INTRODUCTIONIn recent years, the concePt of long-term sustained use of reservoirs has been addressed because areservoir is very much considered to be a nonrenewable resource (Morris and Fan, l998). Technically,many options for reservoir sedAnentation control can be utlized to pursue the sustainable develoPment ofwater resources. In general, reduction of incoming sedimen yields from watersheds is often emPloyedin conjunction with hydraulic methods such as flushing or density currnt vot…     

Optimization and simulation of reservoir operation with sediment evacuation: a case study of the Tarbela Dam,Pakistan

Many reservoirs around the world are being operated based on rule curves developed without considering the evacuation of deposited sediment. Current reservoir simulation and optimization models fall short of incorporating the concept of sustainability because the reservoir storage losses due to sedimentation are not considered. This study develops a new model called Reservoir Optimization‐Simulation with Sediment Evacuation (ROSSE) model. The model utilizes genetic algorithm based optimization capabilities and embeds the sediment evacuation module into the simulation module. The sediment evacuation module is implemented using the Tsinghua university flushing equation. The ROSSE model is applied to optimize the rule curves of Tarbela Reservoir, the largest reservoir in Pakistan with chronic sedimentation problems. In the present study, rule curves are optimized for maximization of net economic benefits from water released. The water released can be used for irrigation, power production, sediment evacuation, and for flood control purposes. Relative weights are used to combine the benefits from these conflicting water uses. Nine sets of rule curves are compared, namely existing rule curves and proposed rule curves for eight scenarios developed for various policy options. These optimized rule curves show an increase of net individual economic benefits ranging from 9 to 248% over the existing rule curves. The shortage of irrigation supply during the simulation period is reduced by 38% and reservoir sustainability is enhanced by 28% through increased sediment evacuation. The study concludes that by modifying the operating policy and rule curves, it is possible to enhance the reservoir's sustainability and maximize the net economic benefits. The developed methodology and the model can be used for optimization of rule curves of other reservoirs with sedimentation problems. Copyright © 2008 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.     

A REVIEW OF RESERVOIR DESILTATION

I INTRODUCTIONThe number of dam constructions has increased during the last decades, pafticularly in the tropics andsemi-arid areas where high sediment yields are prominent, and therefore also the problems of reservoirsedimentation. In 1900 there were 42 large dams, i.e. higher than 15 m, while in 1950 and 1986 therewere 5,268 and about 39,000 respectively (ICOLD, 1988). In the period 1975 to 1990, the regions withthe largest increase of large dams were Central and South America, Asia …     

Numerical modeling of sediment flushing from Lewis and Clark Lake

Lewis and Clark Lake is located on the main stream of the Missouri River. The reservoir is formed behind Gavins Point dam near Yankton, South Dakota, U.S.A. The Lewis and Clark Lake reach extends about 40 km from the Gavins Point dam. The reservoir delta has been growing since the closure of Gavins Point dam in 1955 and has resulted in a 21% reduction of storage within the maximum pool of the reservoir. Among several sediment management methods, drawdown flushing has been recommended as a possible management technique. The engineering viability of removing sediments deposited in the lake should be examined by numerical modeling before implementing a drawdown flushing. GSTARS4 was used for this study and calibrated by using measured data from 1975 to 1995. Channel cross-section changes and amount of flushed sediment were predicted with four hypothetical flow scenarios. The flushing efficiencies of all scenarios were estimated by comparing the ratios between water consumption and flushed sediment during flushing.     

PHENOMENA AND CONTROLLING FACTORS IN DRAWDOWN FLUSHING PROCESSES

IINTRODUCTIONByutilizingthenatUralpowerofflow,hydraulicflushingisaneconomicaltechniquetoremovethedepositedsedimentineitherasettlingbasinorareservoir.Inmanyreservoirsaroundtheworld,hydraulicflushinghasbeenprovenasaneffectivemethodtosustainthereservoirstoragecapacity.Hydraulicflushingprocessesmayinvolveboththeprocessesofscouringpreviousdepositsandpassingincomingsediment-ladenflow,suchasgravitycurrent,throughareservoirtobereleased.Inthisarticle,onlytheformercaseisdiscussed.Thekeythinginthef…     

Intelligent control for modeling of real‐time reservoir operation,part II: artificial neural network with operating rule curves

To bridge the gap between academic research and actual operation, we propose an intelligent control system for reservoir operation. The methodology includes two major processes, the knowledge acquired and implemented, and the inference system. In this study, a genetic algorithm (GA) and a fuzzy rule base (FRB) are used to extract knowledge based on the historical inflow data with a design objective function and on the operating rule curves respectively. The adaptive network‐based fuzzy inference system (ANFIS) is then used to implement the knowledge, to create the fuzzy inference system, and then to estimate the optimal reservoir operation. To investigate its applicability and practicability, the Shihmen reservoir, Taiwan, is used as a case study. For the purpose of comparison, a simulation of the currently used M‐5 operating rule curve is also performed. The results demonstrate that (1) the GA is an efficient way to search the optimal input–output patterns, (2) the FRB can extract the knowledge from the operating rule curves, and (3) the ANFIS models built on different types of knowledge can produce much better performance than the traditional M‐5 curves in real‐time reservoir operation. Moreover, we show that the model can be more intelligent for reservoir operation if more information (or knowledge) is involved. Copyright © 2004 John Wiley & Sons, Ltd.     

Intelligent control for modelling of real‐time reservoir operation

This paper presents a new approach to improving real‐time reservoir operation. The approach combines two major procedures: the genetic algorithm (GA) and the adaptive network‐based fuzzy inference system (ANFIS). The GA is used to search the optimal reservoir operating histogram based on a given inflow series, which can be recognized as the base of input–output training patterns in the next step. The ANFIS is then built to create the fuzzy inference system, to construct the suitable structure and parameters, and to estimate the optimal water release according to the reservoir depth and inflow situation. The practicability and effectiveness of the approach proposed is tested on the operation of the Shihmen reservoir in Taiwan. The current M‐5 operating rule curves of the Shihmen reservoir are also evaluated. The simulation results demonstrate that this new approach, in comparison with the M‐5 rule curves, has superior performance with regard to the prediction of total water deficit and generalized shortage index (GSI). Copyright © 2001 John Wiley & Sons, Ltd.     

A MATHEMATICAL MODEL OF RESERVOIR SEDIMENTATION

1 INTRODUCTIONBed aggradation and degradation haPpen to be the most imPOrtant aspects of the alluvial processes instreams if the equilibrium conditions among water discharge, sediment flow, and channel shaPe areclistuIbed by natural or man-made factOfs, e.g., the constrUchon of a dam, change in the sediment suPplyrate, or base level changing. Reliable and quanhtative estimation of the bed aggradation or degradation isimPortant in rivertalning engineering and water management projects. …     

Numerical modeling of sedimentation control scenarios in the approach channel of the Nakdong River Estuary Barrage,South Korea

The effects of sedimentation reduction at the Nakdong River Estuary Barrage (NREB) in Korea were quantitatively analyzed with respect to different sediment control methods using the calibrated and validated two-dimensional model. The countermeasures of sediment dredging, sediment flushing, channel geometry change, and a combination of flushing and channel geometry change were examined for the approach channel of the NREB. The flood event and channel geometries of the 3.8 km section upstream of the NREB surveyed before and after dredging in 2007 were used for modeling conditions. As a result, the half of sediments dredged in 2007 could be eliminated naturally by floods without dredging. The numerical simulation of sediment flushing indicated that the deposition height decreased in the entire simulation section with the minimum and maximum reductions from 0.3 m to 1.3 m in deposition height. The channel contraction method produced quantitatively the largest amount of sedimentation reduction and sediment flushing and dredging followed. Sedimentation reduction by a combination of flushing and channel contraction was up 10%compared to the individual method of channel contraction.     

Optimizing the reservoir operating rule curves by genetic algorithms

Genetic algorithms, founded upon the principle of evolution, are applicable to many optimization problems, especially popular for solving parameter optimization problems. Reservoir operating rule curves are the most common way for guiding and managing the reservoir operation. These rule curves traditionally are derived through intensive simulation techniques. The main aim of this study is to investigate the efficiency and effectiveness of two genetic algorithms (GAs), i.e., binary coded and real coded, to derive multipurpose reservoir operating rule curves. The curves are assumed to be piecewise linear functions where the coordinates of their inflection points are the unknowns and we want to optimize system performance. The applicability and effectiveness of the proposed methods are tested on the operation of the Shih‐Men reservoir in Taiwan. The current M‐5 operating curves of the Shih‐Men reservoir are also evaluated. The results show that the GAs provide an adequate, effective and robust way for searching the rule curves. Both sets of operating rule curves obtained from GAs have better performance, in terms of water release deficit and hydropower, than the current M‐5 operating rule curves, while the real‐coded GA is more efficient than the binary‐coded GA. Copyright © 2005 John Wiley & Sons, Ltd.     

Estimating sediment deposition volume in a reservoir using the physiographic soil erosion-deposition model

A traditional way to estimate the amount of sediment deposition in a reservoir is simply based on the variation in the elevation measurements made at different times.In the present study,a physiographic soil erosion-deposition(PSED) model is applied to.Tseng-Wen reservoir watershed to compute the discharge and sediment concentration into the reservoir,and the deposition volume.The PSED model is verified using three storm events and then compared to the historic data recorded at the hydrological stations in the reservoir watershed,which shows close agreement between the simulated and recorded values of the flow discharge into the reservoir and the corresponding sediment yield. The numerical simulation was also conducted for all rainfall events from 1996 to 2001 to estimate the annual sediment deposition volume in the reservoir.Similarly,the simulated result was compared to that obtained from the cross-section elevation measurement.It is found that some measured data points had large uncertainty or were questionable.On the contrary,the model results and the measured data that renders the model credible.Therefore,regardless of the estimation for the flow discharge into the reservoir induced by a single rainfall event,the sediment yield,or the sediment deposition,the PSED model has successfully demonstrated its ability.     

A combined simulation–genetic algorithm optimization model for optimal rule curves of a reservoir: a case study of the Nam Oon Irrigation Project,Thailand

A combined simulation–genetic algorithm (GA) optimization model is developed to determine optimal reservoir operational rule curves of the Nam Oon Reservoir and Irrigation Project in Thailand. The GA and simulation models operate in parallel over time with interactions through their solution procedure. A GA is selected as an optimization model, instead of traditional techniques, owing to its powerful and robust performance and simplicity in combining with a simulation technique. A GA is different from conventional optimization techniques in the way that it uses objective function information and does not require its derivatives, whereas in real‐world optimization problems the search space may include discontinuities and may often include a number of sub‐optimum peaks. This may cause difficulties for calculus‐based and enumerative schemes, but not in a GA. The simulation model is run to determine the net system benefit associated with state and control variables. The combined simulation–GA model is applied to determine the optimal upper and lower rule curves on a monthly basis for the Nam Oon Reservoir, Thailand. The objective function is maximum net system benefit subject to given constraints for three scenarios of cultivated areas. The monthly release is calculated by the simulation model in accordance with the given release policy, which depends on water demand. The optimal upper and lower rule curves are compared with the results of the HEC‐3 model (Reservoir System Analysis for Conservation model) calculated by the Royal Irrigation Department, Thailand, and those obtained using the standard operating policy. It was found that the optimal rule curves yield the maximum benefit and minimum damages caused by floods and water shortages. The combined simulation–GA model shows an excellent performance in terms of its optimization results and efficient computation. Copyright © 2007 John Wiley & Sons, Ltd.     

Reservoir operation using grey fuzzy stochastic dynamic programming

This paper presents an optimal regulation programme, grey fuzzy stochastic dynamic programming (GFSDP), for reservoir operation. It is composed of a grey system, fuzzy theory and dynamic programming. The grey system represents data by covering the whole range without loss of generality, and the fuzzy arithmetic takes charge of the rules of reservoir operation. The GFSDP deals with the multipurpose decision‐making problem by fuzzy optimization theorem. The practicability and effectiveness of the proposed approach is tested on the operation of the Shiman reservoir in Taiwan. The current M5 operating rule curves of this reservoir also are evaluated. The simulation results demonstrate that this new approach, in comparison with the M5 rule curves, has superior performance with regard to the total water deficit and number of monthly deficits. Copyright © 2002 John Wiley & Sons, Ltd.     

Continuous flushing of contaminants from ballast water tanks

The transport of non-indigenous species (NIS) with ship ballast water is a major environmental problem. The International Maritime Organisation (IMO) have recommended that ballast tanks are flushed through with sea water to remove NIS contaminants. The flushing efficiency is studied using mathematical models and a scaled experimental model of a ballast tank. The density contrast between the ballast water and water used for flushing is important when the Froude number Fr(w)=U(w)/sqr rt|g(')|H < 1 (defined in terms of average horizontal flow U(w), reduced buoyancy g', and H the vertical dimension in the tank). When denser water is used to flush a ballast tank, from below, it efficiently displaces lighter ballast water; but flushing through with light water creates a buoyant gravity current which effectively short circuits part of the tank. When Fr(w)>1, the density contrast between the ballast water and water used for flushing is not important and flushing is controlled by a bulk Péclet number, Pe(w). For Pe(w)<1 perfect mixing occurs, while for Pe(w)>1 displacement flushing occurs. Laboratory experiments of flushing were performed using a model two-dimensional ballast tank employing dye attenuation to measure the whole concentration field and these experiments confirm the essential features of the mathematical models. The results of this study are discussed in the context of current IMO flushing protocols.     

Optimized reservoir operation to balance human and riverine ecosystem needs: model development,and a case study for the Tanghe reservoir,Tang river basin,China

Reservoirs impose many negative impacts on riverine ecosystems. To balance human and ecosystem needs, we propose a reservoir operation method that combines reservoir operating rule curves with the regulated minimum water release policy to meet the environmental flow requirements of riverine ecosystems. Based on the relative positions of the reservoir and the water intakes, we consider three scenarios: water used for human needs (including industrial, domestic and agricultural) is directly withdrawn from (1) the reservoir; (2) both reservoirs and downstream river channels and (3) downstream river. The proposed method offers two advantages over traditional methods: First, it can be applied to finding the optimal reservoir operating rule curves with the consideration of environmental flow requirement, which is beneficial to the sustainable water uses. Second, it avoids a problem with traditional approaches, which prescribe the minimum environmental flow requirements as the regulated minimum environmental flow releases from reservoirs, implicitly giving lower priority to the riverine ecosystem. Our method instead determines the optimal regulated minimum releases of water to sustain environmental flows while more effectively balancing human and ecosystem needs. To demonstrate practical use of the model, we present a case study for operation of the Tanghe reservoir in China's Tang river basin for the three above‐mentioned scenarios. The results demonstrate that this approach will help the reservoir's managers satisfy both human and environmental requirements. Copyright © 2009 John Wiley & Sons, Ltd.     

SEDIMENT MANAGEMENT IN NANQIN RESERVOIR

In order to preserve the storage capacity of the Nanqin Reservoir for long-term service, several remedial measures have been worked out: (a) measures to control the upstream extension of backwater deposits and to prevent gravel bed load from entering into the reservoir, so that no armour layer will be formed; (b) sediment sluicing by density current to reduce deposits of suspended load; (c) periodical sediment flushing by emptying reservoir to restore the effective storage capacity. In addition, conceptions of flood plain elevation in reservoir, storage volume required in the routing of turbid flow (density flow), the storage capacity that can be restored after being lost by deposition, and the storage volume for sediment regulation are also discussed.     

Geostatistical seismic Amplitude‐versus‐angle inversion

Seismic inversion plays an important role in reservoir modelling and characterisation due to its potential for assessing the spatial distribution of the sub‐surface petro‐elastic properties. Seismic amplitude‐versus‐angle inversion methodologies allow to retrieve P‐wave and S‐wave velocities and density individually allowing a better characterisation of existing litho‐fluid facies. We present an iterative geostatistical seismic amplitude‐versus‐angle inversion algorithm that inverts pre‐stack seismic data, sorted by angle gather, directly for: density; P‐wave; and S‐wave velocity models. The proposed iterative geostatistical inverse procedure is based on the use of stochastic sequential simulation and co‐simulation algorithms as the perturbation technique of the model parametre space; and the use of a genetic algorithm as a global optimiser to make the simulated elastic models converge from iteration to iteration. All the elastic models simulated during the iterative procedure honour the marginal prior distributions of P‐wave velocity, S‐wave velocity and density estimated from the available well‐log data, and the corresponding joint distributions between density versus P‐wave velocity and P‐wave versus S‐wave velocity. We successfully tested and implemented the proposed inversion procedure on a pre‐stack synthetic dataset, built from a real reservoir, and on a real pre‐stack seismic dataset acquired over a deep‐water gas reservoir. In both cases the results show a good convergence between real and synthetic seismic and reliable high‐resolution elastic sub‐surface Earth models.     

Incorporating inflow uncertainty into risk assessment for reservoir operation

An attempt of using stochastic hydrologic technique to assess the intrinsic risk of reservoir operation is made in this study. A stochastic simulation model for reservoir operation is developed. The model consists of three components: synthetic generation model for streamflow and sediment sequences, one-dimensional delta deposit model for sediment transport processes in reservoirs, and simulation model for reservoir operation. This kind of integrated simulation model can be used to simulate not only the inflow uncertainty of streamflow and sedimentation, but also the variation in operation rules of reservoirs. It is herein used for the risk assessment of a reservoir, and the simulation is performed for different operation scenarios. Simulation for the 100-year period of sediment transport and deposition in the river-reservoir system indicates that the navigation risk is much higher than that of hydropower generation or sediment deposition in the reservoir. The risk of sediment deposition at the river-section near the backwater profile is also high thereby the navigation at the river-segment near this profile takes high risk because of inadequate navigation depth.     

Numerical simulation of agricultural sediment and pesticide runoff: RZWQM and PRZM comparison

Agricultural sediment and pesticide runoff is a widespread ecological and human health concern. Numerical simulation models, such as Root Zone Water Quality Model (RZWQM) and Pesticide Root Zone Model (PRZM), have been increasingly used to quantify off‐site agricultural pollutant movement. However, RZWQM has been criticized for its inability to simulate sedimentation processes. The recent incorporation of the sedimentation module of Groundwater Loading Effects of Agricultural Management Systems has enabled RZWQM to simulate sediment and sediment‐associated pesticides. This study compares the sediment and pesticide transport simulation performance of the newly released RZWQM and PRZM using runoff data from 2 alfalfa fields in Davis, California. A composite metric (based on coefficient of determination, Nash–Sutcliffe efficiency, index of agreement, and percent bias) was developed and employed to ensure robust, comprehensive assessment of model performance. Results showed that surface water runoff was predicted reasonably well (absolute percent bias <31%) by RZWQM and PRZM after adjusting important hydrologic parameters. Even after calibration, underestimation bias (?89% ≤ PBIAS  ≤ ?36%) for sediment yield was observed in both models. This might be attributed to PRZM's incorrect distribution of input water and uncertainty in RZWQM's runoff erosivity coefficient. Moreover, the underestimation of sediment might be less if the origin of measured sediment was considered. Chlorpyrifos losses were simulated with reasonable accuracy especially for Field A (absolute PBIAS  ≤ 22%), whereas diuron losses were underestimated to a great extent (?98% ≤ PBIAS  ≤ ?65%) in both models. This could be attributed to the underprediction of herbicide concentration in the top soil due to the limitations of the instantaneous equilibrium sorption model as well as the high runoff potential of herbicide formulated as water‐dispersible granules. RZWQM and PRZM partitioned pesticides into the water and sediment phases similarly. According to model predictions, the majority of pesticide loads were carried via the water phase. On the basis of this study, both RZWQM and PRZM performed well in predicting runoff that carried highly adsorptive pesticides on an event basis, although the more physically based RZWQM is recommended when field‐measured soil hydraulic properties are available.