Simulation of Potential Oyster Density with Variable Freshwater Inflow (1965–2000) to the Caloosahatchee River Estuary, Southwest Florida, USA

Oyster beds are disappearing worldwide through a combination of over-harvesting, diseases, and salinity alterations in the coastal zone. Sensitivity of oysters to variable discharge and salinity is particularly acute in small sub-tropical estuaries subject to regulated freshwater releases. South Florida has sub-tropical estuaries where watershed flood control sometimes results in excessive freshwater inflow to estuaries during the wet season (May–Oct) and reduced discharge and increased salinities in the dry season (Nov–Apr). The potential to reserve freshwater accumulated during the wet season could offer the capacity to regulate freshwater at different temporal scales, thus optimizing salinity conditions for estuarine biota. The goal of this study was to use simulation modeling to explore the effects of freshwater inflows and salinity on adult oyster survival in the Caloosahatchee River Estuary (CRE) in southwest Florida. Water managers derived three different freshwater inflow scenarios for the CRE based on historical and modified watershed attributes for the time period of 1965–2000. Three different salinity time series were generated from the inflow scenarios at each of three sites in the lower CRE and used to conduct nine different oyster simulations. Overall, the predicted densities of adult oysters in the upstream site were 3–4 times greater in seasons that experienced reduced freshwater inflow (e.g., increased salinity) with oyster density in the lower estuary much less influenced by the inflows. Potential storage of freshwater reduced the frequency of extreme flows in the wet season and helped to maintain minimum inflow in the dry season near the estuarine mouth. Analyses of inflows indicated that discharges ranging from 0 to 1,500 cfs could promote favorable salinities of 10–25 in the lower CRE depending on wet versus dry season climatic conditions. This range of inflows is similar to that derived in other studies of the CRE and emphasizes the value of simulation models to help prescribe freshwater releases which benefit estuarine biota.     

A STOCHASTIC DYNAMIC PROGRAMMING BASED APPROACH TO THE OPERATION OF A MULTI-RESERVOIR SYSTEM1

ABSTRACT: An heuristic iterative technique based upon stochastic dynamic programming is presented for the analysis of the operation of a three reservoir ‘Y’ shaped hydroelectric system. The technique is initiated using historical inflow data for the downstream reservoir. At each iteration the optimal policies for the downstream hydroelectric generating unit are used to provide relative weightings or targets for operation of upstream reservoirs. New input inflows to the downstream reservoir are then obtained by running the historical streamflow record through the optimal policies for the upstream reservoirs. These flows are then used to develop a new operating policy for the downstream reservoir and hence new targets for the upstream reservoirs. The process is continued until the operating policies for each reservoir provide the same overall system benefit for two successive iterations. Results obtained from the procedure are compared to the results obtained by historical operation of the system. The procedure is shown to develop operating policies which give benefits which are as close to the historical benefits as can be expected given the choice of the number of storage state variables.     

APPLICATION OF THE HEC-4 MONTHLY STREAM FLOW SIMULATION MODEL1

ABSTRACT: The HEC-4 monthly stream flow simulation model, developed by the Hydrologic Engineering Center, Davis, California, is used to extend the available historical stream flow records in the Central Ohio area. The principal objective of this paper is to examine the effectiveness of the HEC-4 model in generating synthetic monthly flows. Important statistical parameters are evaluated in order to relate the statistical properties of the historical and generated flows. In doing so, it is observed that the mean, standard deviation, and skewness of the generated flows are consistently larger than the corresponding estimates based on historical flows. However, results show that these statistics, as well as the lag-1 serial correlation, are generally well maintained by the generated sequences. The degree to which any statistical dissimilarities would be critical, from an engineering design point of view, is demonstrated by utilizing their low flow characteristics. Estimates of reservoir safe-yields, based on a nonsequential mass-curve analysis of the historical and generated low flows, indicate a nominal difference in this particular study.     

INDEXED SEQUENTIAL HYDROLOGIC MODELING FOR HYDROPOWER CAPACITY ESTIMATION1

ABSTRACT: The indexed sequential hydrologic modeling (ISM) methodology is utilized by the Western Area Power Administration as the basis for risk-based estimation of project-dependable hydropower capacity for several federally owned/operated projects. ISM is a technique based on synthetic generation of a series of overlapping short-term inflow sequences obtained directly from the historical record. The validity of ISM is assessed through application to the complex multireservoir hydropower system of the Colorado River basin for providing risk estimates associated with determination of reliable hydrogeneration capacity. Performance of ISM is compared with results from stochastically generated streamflow input data to the Colorado River Simulation System (CRSS). Statistical analysis and comparison of results are based on monthly power capacity, energy generation, and downstream water deliveries. Results indicate that outputs generated from ISM synthetically generated sequences display an acceptable correspondence with those obtained from stochastically generated hydrologic data for the Colorado River Basin.     

FORECASTING QUARTER-MONTHLY RIVERFLOW1

Recent developments with respect to transfer function-noise models are reviewed and used to model and forecast quarter-monthly (i.e., near-weekly) natural inflows to the Lac St-Jean reservoir in the Province of Quebec, Canada. The covariate series are rainfall and snowmelt, the latter being a novel derivation from daily rainfall, snowfall and temperature series. It is clearly demonstrated using the residual variance and the Akaike information criterion that modeling is improved as one starts with a deseasonalized ARMA model of the inflow series and successively adds transfer functions for the rainfall and snowmelt series. It is further demonstrated that the transfer function-noise model is better than a periodic autoregressive model of the inflow series. A split-sample experiment is used to compare one-step-ahead forecasts from this transfer function-noise model with forecasts from other stochastic models as well as with forecasts from a so-called conceptual hydrological model (i.e., a model which attempts to mathematically simulate the physical processes involved in the hydrological cycle). It is concluded that the transfer function-noise model is the preferred model for forecasting the quarter-monthly Lac St-Jean inflow series.     

OPTIMAL CAPACITIES OF WATER SUPPLY RESERVOIRS IN SERIES AND PARALLEL1

ABSTRACT: The planning of water supply reservoirs has traditionally been based on the Rippl or sequent peak analysis which applies to the design of a single reservoir. This paper incorporates the sequent peak method as the central feature in establishing a procedure for determining the sizes of several potential reservoirs located in a system of one or more rivers. Separate algorithms are developed for sites on parallel streams and for sites on the same stream. In both cases the approach is to find the combination of reservoirs which can satisfy a given constant monthly demand at a minimum total construction cost. It is shown that both problems can be cast in the form of a dynamic programming problem. A more complex system is then a combination of reservoirs in parallel and in series. An extension is given if the monthly demand is not constant but each reservoir satisfies a constant fraction of the monthly demand.     

Coastal Environmental Impacts Brought About by Alterations to Freshwater Flow in the Gulf of Mexico

/ Freshwater inflow is one of the most influential landscape processes affecting community structure and function in lagoons, estuaries, and deltas of the world; nevertheless there are few reviews of coastal impacts associated with altered freshwater inputs. A conceptual model of the possible influences of freshwater inflows on biogeochemical and trophic interactions was used to structure this review, evaluate dominant effects, and discuss tools for coastal management. Studies in the Gulf of Mexico were used to exemplify problems commonly encountered by coastal zone managers and scientists around the world. Landscape alteration, impacting the timing and volume of freshwater inflow, was found to be the most common stress on estuarine systems. Poorly planned upstream landscape alterations can impact wetland and open-water salinity patterns, nutrients, sediment fertility, bottom topography, dissolved oxygen, and concentrations of xenobiotics. These, in turn, influence productivity, structure, and behavior of coastal plant and animal populations. Common biogeochemical impacts include excessive stratification, eutrophication, sediment deprivation, hypoxia, and contamination. Common biological impacts include reduction in livable habitats, promotion of "exotic" species, and decreased diversity. New multiobjective statistical models and dynamic landscape simulations, used to conduct policy-relevant experiments and integrate a wide variety of coastal data for freshwater inflow management, assume that optimum estuarine productivity and diversity is found somewhere between the stress associated with altered freshwater flow and the subsidy associated with natural flow. These models attempt to maximize the area of spatial overlap where favorable dynamic substrates, such as salinity, coincide with favorable fixed substrates, such as bottom topography. Based upon this principle of spatial overlap, a statistical performance model demonstrates how population vitality measurements (growth, survival, and reproduction) can be used to define sediment, freshwater, and nutrient loading limits. Similarly, a spatially articulate landscape simulation model demonstrates how cumulative impacts and ecosystem processes can be predicted as a function of changes in freshwater, sediment, and nutrient inflows.KEY WORDS: Resource management; Landscape impacts; Freshwater discharge; Coastal, ecosystem models; Coastal wetlands     

STOCHASTIC MODELING OF MONTHLY AND DAILY RAINFALL SEQUENCES1

ABSTRACT: A monthly model and two daily models (I and II) are presented for the purpose of generating monthly and daily rainfall sequences in the Quae Yai river basin in Thailand. Performance of the models are evaluated by comparing the statistical parameters of the generated sequences with those from historical data. For monthly generation, Thomas-Fiering model worked satisfactorily in spite of the monthly correlations being weak, if any. Daily Model I, which assumes no persistence between daily rainfall amounts within the wet spells, could not preserve some important parameters regardless of the simplicity in model construction. Application of multi-state transition probability matrix model gave good results, although the user has to modify some parameters looking at the performance of the model for each historical record.     

GENERATION OF SYNTHETIC AND MISSING CLIMATIC DATA FOR PUERTO RICO1

ABSTRACT: Climatic data such as temperature, solar radiation, relative humidity, and wind speed have been widely used to estimate evapotranspiration. Moat of the solar radiation data and portions of the relative humidity data are either not available or missing from the records in Puerto Rico. Depending upon the availability and data characteristics of records, three methods (including a regression technique, an averaging of historical data, and a regional average) were used to generate missing data, and a time series analysis was used to synthesize a series of climatic data. The limitations and applicability of each method are discussed. The results showed that the time series analysis method can be successfully used to synthesize a series of monthly solar radiations for several stations. The regression technique and the regional average can be successfully applied to generate missing monthly solar radiation data. The regression technique and the averaging of historical data have been satisfactorily used to interpolate missing monthly relative humidity. The explained variance (R²) varied from 0.68 to 0.88, which are both significant at the 0.05 level of significance.     

LIMNOLOGICAL PROPERTIES OF A ROCKY MOUNTAIN HEADWATER RESERVOIR1

ABSTRACT: Hyalite Reservoir, Montana, was studied to determine properties of this small, montane, headwater, deep-release reservoir relative to reservoirs at lower elevations. While retention times for waters were as brief as 12 d, the mean residency of 40 d from mid-March to mid-December was within the range reported for other reservoirs. No significant through-reservoir gradients for suspended sediments were observed, contrasting to observations for most reservoirs. Thermal stratification, evident during the first part of the summer, was disrupted in August by cool, dense tributary inflows and strong wind-induced mixing. Dissolved oxygen concentrations paralleled temperature patterns in the reservoir; lowest average values for both occurred in waters sampled nearest the outlet. Total phosphorus averaged greater than twice the total nitrogen concentrations; greatest average concentrations for both were found in the near-bottom waters nearest the outlet. Enrichment of nitrogen concentrations in outflow over inflow waters is hypothesized to occur through nitrogen fixation by Aphanizonwnon flos-aquae. Despite the relatively high quality of waters from tributary inflows, an algal bloom, chlorophyll a concentrations, and primary productivity estimates suggested that the reservoir was mesotrophic. Circulation of waters within the reservoir was primarily influenced by wind-induced mixing, thermal gradients, and currents produced by the deep-water outlet.     

RESERVOIR OPERATION ANI EVALUATION OF DOWNSTREAM FLOW AUGMENTATION1

ABSTRACT: Operation of a storage‐based reservoir modifies the downstream flow usually to a value higher than that of natural flow in dry season. This could be important for irrigation, water supply, or power production as it is like an additional downstream benefit without any additional investment. This study addresses the operation of two proposed reservoirs and the downstream flow augmentation at an irrigation project located at the outlet of the Gandaki River basin in Nepal. The optimal operating policies of the reservoirs were determined using a Stochastic Dynamic Programming (SDP) model considering the maximization of power production. The modified flows downstream of the reservoirs were simulated by a simulation model using the optimal operating policy (for power maximization) and a synthetic long‐term inflow series. Comparing the existing flow (flow in river without reservoir operation) and the modified flow (flow after reservoir operation) at the irrigation project, the additional amount of flow was calculated. The reliability analysis indicated that the supply of irrigation could be increased by 25 to 100 percent of the existing supply over the dry season (January to April) with a reliability of more than 80 percent.     

ESTIMATION OF WATER TEMPERATURE EXCEEDANCE PROBABILITIES USING THERMO-HYDRODYNAMIC MODELING1

ABSTRACT: A continuous simulation approach is proposed for estimating water temperature exceedance probabilities using thermo-hydrodynamic modeling. The approach uses (1) a deterministic unsteady flow and heat transport model, (2) continuous hydrological and meteorological data for a long historical period, and (3) synthetic records of tributary water temperatures and other model inputs. Representative historical records of streamflow, air temperatures, and other hydrometeorological variables are obtained from nearby gages. Stochastic modeling methods are used to construct synthetic records for other model inputs, including inflow water temperatures. An application of this deterministic-stochastic approach is presented for a complex waterway in northeastern Illinois with heat discharges from several power plants and wastewater treatment plants. Statistical results from the continuous simulations are compared to results obtained from traditional event simulations. The application illustrates the information that engineers and biologists can obtain for (1) evaluating compliance with water temperature standards, and (2) assessing the effect of water temperatures on aquatic habitat.     

Modeling the Fate and Transport of Plunging Inflows to Onondaga Lake

The transport and fate of two plunging tributaries, Onondaga and Ninemile Creeks, in Onondaga Lake, New York, are quantified based on application of hydrodynamic/transport models. Short‐term transport is simulated with a three‐dimensional Estuary Lake and Coastal Ocean Model (ELCOM), while the longer term fate is represented by a previously validated one‐dimensional model (UFILS4). The validation of ELCOM for the vertical distribution of tributary inflow into the lake's water column is demonstrated for four dye tracer experiments. The models are applied for three years to represent the dynamics of transport and fate for the two tributaries, with ELCOM predictions serving as input for UFILS4. The models together quantify the distribution of these inflows between the upper mixed layer (UML) and stratified depths, and the subsequent transport from stratified depths to the UML by vertical mixing. Substantial short‐term variations are predicted for both tributaries in response to variability in hydrology and weather. Increased inflow to the UML is predicted for high runoff periods. The fraction of Ninemile Creek's inflow directly entering the UML is predicted to be 50% greater than for Onondaga Creek due to Ninemile's lower negative buoyancy. The plunging phenomenon has important water quality implications, by reducing the effective loading to the UML, particularly for constituents with large rates of loss/transformation relative to the rate of vertical transport from stratified depths.     

COMPARISON OF STOCHASTIC AND DETERMINISTIC DYNAMIC PROGRAMMING FOR RESERVOIR OPERATING RULE GENERATION1

ABSTRACT: Two dynamic programming models — one deterministic and one stochastic — that may be used to generate reservoir operating rules are compared. The deterministic model (DPR) consists of an algorithm that cycles through three components: a dynamic program, a regression analysis, and a simulation. In this model, the correlation between the general operating rules, defined by the regression analysis and evaluated in the simulation, and the optimal deterministic operation defined by the dynamic program is increased through an iterative process. The stochastic dynamic program (SDP) describes streamflows with a discrete lag-one Markov process. To test the usefulness of both models in generating reservoir operating rules, real-time reservoir operation simulation models are constructed for three hydrologically different sites. The rules generated by DPR and SDP are then applied in the operation simulation model and their performance is evaluated. For the test cases, the DPR generated rules are more effective in the operation of medium to very large reservoirs and the SDP generated rules are more effective for the operation of small reservoirs.     

A MULTICOMPONENT MODEL OF PHOSPHORUS DYNAMICS IN RESERVOIRS1

The models available for simulating phosphorus dynamics and trophic state in impoundments vary widely. The simpler empirically derived phosphorus models tend to be appropriate for long-term, steady or near steady state analyses. The more complex ecosystem models, because of computational expense and the importance of input parameter uncertainty, are impractical for very long-term simulation and most applicable for time-variable water quality simulations generally of short to intermediate time frames. An improved model for time variable, long-term simulation of trophic state in reservoirs with fluctuating inflow and outflow rates and volume is needed. Such a model is developed in this paper representing the phosphorus cycle in two-layer (i.e., epilimnion and hypolimnion) reservoirs. The model is designed to simulate seasonally varying reservoir water quality and eutrophication potential by using the phosphorus state variable as the water quality indicator. Long-term simulations with fluctuating volumes and variable influent and effluent flow rates are feasible and practical. The model utility is demonstrated through application to a pumped storage reservoir characteristic of these conditions.     

A Method to Consider Whether Dams Mitigate Climate Change Effects on Stream Temperatures

This article provides a method for examining mesoscale water quality objectives downstream of dams with anticipated climate change using a multimodel approach. Coldwater habitat for species such as trout and salmon has been reduced by water regulation, dam building, and land use change that alter stream temperatures. Climate change is an additional threat. Changing hydroclimatic conditions will likely impact water temperatures below dams and affect downstream ecology. We model reservoir thermal dynamics and release operations (assuming that operations remain unchanged through time) of hypothetical reservoirs of different sizes, elevations, and latitudes with climate‐forced inflow hydrologies to examine the potential to manage water temperatures for coldwater habitat. All models are one dimensional and operate on a weekly timestep. Results are presented as water temperature change from the historical time period and indicate that reservoirs release water that is cooler than upstream conditions, although the absolute temperatures of reaches below dams warm with climate change. Stream temperatures are sensitive to changes in reservoir volume, elevation, and latitude. Our approach is presented as a proof of concept study to evaluate reservoir regulation effects on stream temperatures and coldwater habitat with climate change.     

Comparison of the Performance of Statistical Models in Forecasting Monthly Total Dissolved Solids in the Rio Grande1

Abudu, S., J.P. King, Z. Sheng, 2011. Comparison of the Performance of Statistical Models in Forecasting Monthly Total Dissolved Solids in the Rio Grande. Journal of the American Water Resources Association (JAWRA) 48(1): 10‐23. DOI: 10.1111/j.1752‐1688.2011.00587.x Abstract: This paper presents the application of autoregressive integrated moving average (ARIMA), transfer function‐noise (TFN), and artificial neural networks (ANNs) modeling approaches in forecasting monthly total dissolved solids (TDS) of water in the Rio Grande at El Paso, Texas. Predictability analysis was performed between the precipitation, temperature, streamflow rates at the site, releases from upstream reservoirs, and monthly TDS using cross‐correlation statistical tests. The chi‐square test results indicated that the average monthly temperature and precipitation did not show significant predictability on monthly TDS series. The performances of one‐ to three‐month‐ahead model forecasts for the testing period of 1984‐1994 showed that the TFN model that incorporated the streamflow rates at the site and Caballo Reservoir release improved monthly TDS forecasts slightly better than the ARIMA models. Except for one‐month‐ahead forecasts, the ANN models using the streamflow rates at the site as inputs resulted in no significant improvements over the TFN models at two‐month‐ahead and three‐month‐ahead forecasts. For three‐month‐ahead forecasts, the simple ARIMA showed similar performance compared to all other models. The results of this study suggested that simple deseasonalized ARIMA models could be used in one‐ to three‐month‐ahead TDS forecasting at the study site with a simple, explicit model structure and similar model performance as the TFN and ANN models for better water management in the Basin.     

A COMPARISON OF STREAMFLOW GENERATION MODELS FOR RESERVOIR CAPACITY-YIELD ANALYSIS1

ABSTRACT: An analysis of four streamflow generation schemes for the use in the estimation of the required conservation storage for a single reservoir is presented. The comparison of the generating schemes should aid in the selection of an appropriate model type for the reservoir sizing problem. The streamflow generation models are compared using two criteria. The first comparison is between the statistics of the generated streamflow sequences and the corresponding statistics from the historical record. The second evaluation compares the median reservoir size determined by each model with the required storage based on the historical flow sequence. The results of a comparative analysis for monthly streamflow data for the Rzav River in Yugoslavia are presented and discussed. The results indicate that both evaluation criteria are required to discriminate between the various options.     

Joint operation rules considering the uncertainty of energy available for multiple cascaded hydropower system

Multi-reservoir operation rules have been widely used in practice operation. The operation rules are often derived from historical or simulated run-off information through implicit stochastic optimization or parameterization-simulation-optimization. The output decisions of operation rules are usually obtained without considering inflow forecasting or using perfect runoff forecast information, which is hardly implemented in practical applications. This paper proposes robust joint operation rules for multiple cascaded reservoirs considering the uncertainty of energy available. The rule parameters are optimized using multi-step genetic algorithm for minimum-power maximization. A case study for a three-cascaded-reservoirs system shows that, compared with deterministic joint operation rules, the accuracy of energy available estimation of joint operation rules is increased by 2.3%, considering inflow uncertainty. The simulated minimum-power decision of joint operation rules considering the uncertainty of energy available is 40.4% higher than that of determinate joint operation rules. Results indicate that there is a possibility of obtaining greater and more effective power decisions through the joint operation rules considering the uncertainty of available energy.     

DISTRIBUTION AND STOCHASTIC GENERATION OF ANNUAL AND MONTHLY PRECIPITATION ON A MOUNTAINOUS WATERSHED IN SOUTHWEST IDAHO1

ABSTRACT: The 18-year precipitation record from the dense gage network on the Reynolds Creek Experimental Watershed located in southwest Idaho was used to determine the spatial distribution of annual and monthly precipitation on a mountainous watershed. Analyses of these data showed a linear relationship between annual amounts and elevation. This relationship was best when the gages were grouped into downwind and upwind sites. This grouping was appropriate because most of the winter storms moved over the watershed from the west and southwest, and the heaviest precipitation was on the west (downwind) side of the watershed. Gage sites along the western and southern watershed borders were most representative of the upwind gages on the east side, because they measured the precipitation from the air moving upwind onto the watershed. The maximum annual precipitation on the watershed was just leeward of the western watershed boundary. The monthly precipitation and elevation relationship was also best represented by grouping the gage sites into upwind and downwind sites. However, during the summer when there are only small amounts of pre cipitation and thunderstorms are the source of most precipitation, one equation can be used to represent the elevation relationship. This study also showed that the log-normal distribution could be used to generate the annual synthetic series, and the cube-root-normal distribution could be used to generate monthly synthetic series for all locations on the watershed.