Hydraulic Parameters of Coastal Aquifer Systems by Direct Methods and an Extended Tide–Aquifer Interaction Technique

Adequate and reliable parameters are key to the sustainable management of vital groundwater resources. Present study focuses on the evaluation of direct methods (tidal efficiency and time lag methods) and an extended tide–aquifer interaction technique for determining the hydraulic parameter of coastal unconfined and confined aquifer systems. The hydraulic diffusivities of unconfined and confined aquifer systems were estimated using the tidal efficiency and time lag methods as well as they were optimized using the tide–aquifer interaction model and the Levenberg–Marquardt optimization technique. The hydraulic diffusivities were optimized by the Levenberg–Marquardt technique following two approaches: lumped tidal component approach and multi-tidal component approach. The effect of spring and neap tidal data on parameter estimates was also analyzed. The tide–aquifer interaction data for two unconfined sites and three confined sites were used in this study. For all the five sites under study, the aquifer hydraulic diffusivities based on the time lag method were found to be much larger (2 to 14 fold for the unconfined sites and 5 to 8 fold for the confined sites) than those based on the tidal efficiency method. The analysis of the optimization results indicated that the hydraulic diffusivities following “multi-tidal component approach” are more reliable and accurate for both unconfined and confined aquifers than those obtained following “lumped tidal component approach”. Consequently, the use of “multi-tidal component approach” is strongly recommended for the determination of aquifer parameters by the tide–aquifer interaction technique. Furthermore, the tide–interaction data corresponding to spring and neap tidal events were found to significantly affect the aquifer diffusivities yielded by the tide–aquifer interaction technique. It is concluded that a judicious use of tide–aquifer interaction technique is indispensable for the reliable estimates of hydraulic parameters of coastal aquifer systems.     

Optimal Design and Operation of a Hydropower Reservoir Plant Using a WEAP-Based Simulation–Optimization Approach

Water Resources Management - Optimal design and operation of a hydropower reservoir is a complex optimization problem in terms of formulation and solution. In this study, a...     

A Multivariate ANN-Wavelet Approach for Rainfall–Runoff Modeling

Without a doubt the first step in any water resources management is the rainfall–runoff modeling over the watershed. However considering high stochastic property of the process, many models are being still developed in order to define such a complex phenomenon in the field of hydrologic engineering. Recently Artificial Neural Network (ANN) as a non-linear inter-extrapolator is extensively used by hydrologists for rainfall–runoff modeling as well as other fields of hydrology. In the current research, the wavelet analysis was linked to the ANN concept for modeling Ligvanchai watershed rainfall–runoff process at Tabriz, Iran. For this purpose the main time series of two variables, rainfall and runoff, were decomposed to some multi-frequently time series by wavelet theory, then these time series were imposed as input data to the ANN to predict the runoff discharge 1 day ahead. The obtained results show the proposed model can predict both short and long term runoff discharges because of using multi-scale time series of rainfall and runoff data as the ANN input layer.     

Simulation–Optimization Modeling: A Survey and Potential Application in Reservoir Systems Operation

This paper presents a survey of simulation and optimization modeling approaches used in reservoir systems operation problems. Optimization methods have been proved of much importance when used with simulation modeling and the two approaches when combined give the best results. The main objective of this review article is to discuss simulation, optimization and combined simulation–optimization modeling approach and to provide an overview of their applications reported in literature. In addition to classical optimization techniques, application and scope of computational intelligence techniques, such as, evolutionary computations, fuzzy set theory and artificial neural networks, in reservoir system operation studies are reviewed. Conclusions and suggestive remarks based on this survey are outlined, which could be helpful for future research and for system managers to decide appropriate methodology for application to their systems.     

A GIS-based Land Cover Classification Approach Suitable for Fine‐scale Urban Water Management

Water Resources Management - In the context of climate stress, urbanisation and population growth, design and planning tools that assist in decentralised and environmental infrastructural planning...     

Reservoir Operation Using a Dynamic Programming Fuzzy Rule–Based Approach

A dynamic programming fuzzy rule–based (DPFRB) model for optimal operation of reservoirs system is presented in this paper. In the first step, a deterministic dynamic programming (DP) model is used to develop the optimal set of inflows, storage volumes, and reservoir releases. These optimal values are then used as inputs to a fuzzy rule–based (FRB) model to establish the general operating policies in the second step. Subsequently, the operating policies are evaluated in a simulation model. During the simulation step, the parameters of the FRB model are optimized after which the algorithm gets back to the second step in a feedback loop to establish the new set of operating rules using the optimized parameters. This iterative approach improves the value of the performance function of the simulation model and continues until the satisfaction of predetermined stopping criteria. This method results in deriving the operating policies, which are robust against the uncertainty of inflows. These policies are derived by using long-term synthetic inflows and an objective function that minimizes its variance. The DPFRB performance is tested and compared to a model, which uses the commonly used multiple regression–based operating rules. Results show that the DPFRB performs well in terms of satisfying the system target performances and computational requirements.     

A New Approach for SHP International Training

An International Training Workshop on Small Hydropower for African countries was held at Hangzhou Regional Center For Small Hydro Power （HRC） in 2-28 Sept 2005, as sponsored by Chinese Ministry of Commerce. Totally 24 participants attended this training workshop from 13 African countries （such as Morocco, Burundi, Mali, Rwanda, Mall, Niger, Mauritius and etc.）.     

Water Resources Assessment at Piracicaba,Capivari and Jundiaí River Basins: A Dynamic Systems Approach

The Piracicaba, Capivari, and Jundiaí River Basins (RB-PCJ) are mainly located in the State of São Paulo, Brazil. Using a dynamics systems simulation model (WRM-PCJ) to assess water resources sustainability, five 50-year simulations were run. WRM-PCJ was developed as a tool to aid decision and policy makers on the RB-PCJ Watershed Committee. The model has 254 variables. The model was calibrated and validated using available information from the 80s. Falkenmark Water Stress Index went from 1,403 m³ person^???1 year^???1 in 2004 to 734 m³ P^???1 year^???1 in 2054, and Xu Sustainability Index from 0.44 to 0.20. In 2004, the Keller River Basin Development Phase was Conservation, and by 2054 was Augmentation. The three criteria used to evaluate water resources showed that the watershed is at crucial water resources management turning point. The WRM-PCJ performed well, and it proved to be an excellent tool for decision and policy makers at RB-PCJ.     

From Water Poverty to Water Prosperity—A More Participatory Approach to Studying Local Water Resources Management

The Water Poverty Index (WPI), a tool designed for integrated analysis of water issues, was set-up in a community in Madhya Pradesh, India through a transparent and participatory process. Though the aim of the WPI is to primarily use existing statistical data, quantitative information from census and local records was combined with qualitative data from community interviews and participatory exercises. The inclusion of community chosen indicators and the adjustment of values so that higher numbers represent water prosperity rather than water poverty, led to the Water Prosperity Index (WPI⁺). The WPI?⁺?score was contrasted with the WPI at community level. It was also calculated for two community areas with different caste and socio-economic characteristics and weighted separately according to water issues prioritized by men and women. The WPI?⁺?revealed a great difference in water access between the two areas and in prioritized issues between men and women illustrating the importance of appropriate spatial representation and gender sensitive assessments for revealing important disparities. Results also showed that highly aggregated data hide these differences making it more difficult to target the most vulnerable groups when planning measures to increase equitable water allocation. While quantitative data reveal an important perspective of the water situation, qualitative data about adequacy of resources, services or institutions, improve understanding of which issues to prioritize. A valid and useful community water index must be based on representative participation, transparency and local influence on the methodology and subsequent results.     

Modular Wavelet–Extreme Learning Machine: a New Approach for Forecasting Daily Rainfall

Water Resources Management - A rainfall forecasting method based on coupling wavelet analysis and a novel artificial neural network technique called extreme learning machine (ELM) is proposed. In...     

Reservoir Inflow Monitoring for Improved Management of Treated Water Quality—A South Australian Experience

Large tributary inflows into water supply reservoirs caused by heavy catchment rain may be of concern due to problems associated with high levels of natural organic matter (NOM) present in the inflows. The movement of these inflows within a reservoir is dependent on its relative density to the receiving waters. For example, if the inflow is denser (colder) than the recipient water it will travel along the base of the reservoir as an underflow and can penetrate as far as the dam wall water off-take to a water treatment plant (WTP). Field studies were conducted to track the passage of underflows through two South Australian reservoirs, Little Para and Myponga. Samples were collected before and during storm event inflows and analyses undertaken to determine NOM concentration, alum demand, disinfection by-product formation potential, and quality of the water. We demonstrate that by monitoring the movement of inflows into reservoirs, combined with changes in reservoir off-take levels, that the risk of NOM entering a water treatment plant can be reduced which in turn will lower water treatment costs by reducing alum dosing levels and lessen the risk to human health by reducing disinfection by-product formation.     

Application of the Coupled Simulation–optimization Method for the Optimum Cut-off Design Under a Hydraulic Structure

A Genetic Algorithm model, coupled with Finite Element Programming (GA-FEP), has been developed to create an optimal design for hydraulic structures to address seepage problems. While the objective function of the optimization model was to minimize the construction costs of the hydraulic structure, the main constraints were to satisfy safety factors concerning uplift pressure and exit gradient. The GA-FEP model proposed here meets the requirements of an optimal hydraulic design in two stages. Firstly, a validated numerical model coded using Finite-element Programming (FEP), was used to analyze seepage problems. This was followed by application of Genetic Algorithm (GA) and finite-element programming (FEP) to establish the optimum depth and location for cut-offs. A MATLAB programming code was used to create the link between the numerical and optimization model, creating a simulation–optimization (S–O) model. The effects of hydraulic conductivity and anisotropic ratios on the hydraulic structure design, were also investigated. The results indicate that the proposed GA-FEP model will provide a safe, efficient and economical hydraulic cut-off design. Evaluation of the model revealed acceptable agreement between expected and simulated seepage parameters pertinent to the hydraulic structure design.

     

Soft Computing Techniques for Rainfall-Runoff Simulation: Local Non–Parametric Paradigm vs. Model Classification Methods

Accurate simulation of rainfall-runoff process is of great importance in hydrology and water resources management. Rainfall–runoff modeling is a non-linear process and highly affected by the inputs to the simulation model. In this study, three kinds of soft computing methods, namely artificial neural networks (ANNs), model tree (MT) and multivariate adaptive regression splines (MARS), have been employed and compared for rainfall-runoff process simulation. Moreover, this study investigates the effect of input size, including number of input variables and number of data time series on runoff simulation by the developed models. Inputs to the simulation models for calibration and validation purposes consist two parts: I1: five variables, including daily rainfall and runoff time series (30 years) with lag times, and I2: twelve variables, including daily rainfall and runoff time series (10 years). To increase the model performances, optimal number and type for input variables are identified. The efficiency of the training and testing performances using the ANNs, MT and MARS models is then evaluated using several evaluation criteria. To implement the methodology, Tajan catchment in the northern part of Iran is selected. Based on the results, it was found that using I1 as input to the developed models results in higher simulation performance. The results also provided evidence that MT (R = 0.897, RMSE = 6.70, RSE = 0.33) with set I2 is capable of reliable model for rainfall-runoff process compared with MARS (R = 0.892, RMSE = 7.47, RSE = 0.83) and ANNs (R = 0.884, RMSE = 7.40, RSE = 0.43) models. Therefore, size (length of data time series) and type of input variables have significant effects on the modeling results.     

A Coupled Water Quantity–Quality Model for Water Allocation Analysis

As the demand for water continuously increases with population growth and economic development, the gap between water supply and demand in China has become increasingly wide. In recent years worsening water pollution has caused this gap to become much more serious. Conventional allocation pattern, which mainly considers water quantity as the key factor, is no longer satisfying the water allocation need. A coupled water quantity–quality model in a river basin is presented in this paper to provide a tool for water allocation schemes analysis. The pollutants transport and hydrological cycling processes in a river basin are involved in the model. A river network is divided into different reaches. According to the division of river network, the areas out of the river are divided into a series of tanks. In each tank, hydrologic processes, pollutant loading production, water demand of users and water supply are calculated. In river network, hydrodynamics processes and water quality are simulated. Water quantity and quality exchanges between each tank and river are also considered. The time step of water quality calculation is 24 h, the same with that of water quantity calculation. In each time step period, the connections of river reaches and tanks are realized through the exchange of water quantity and quality between rivers and tanks: pollutants discharge from tanks to rivers and water intake from rivers to satisfy water demand in tanks. The water use in each tank includes three types: domestic, industrial and agricultural water use. Water allocation schemes are one of the input conditions of the model. Using the proposed model, in each tank, water demand and deficit of different uses, in both water quantity and quality, can be obtained under different water allocation schemes. According to the water deficit, water allocation schemes are analyzed to make proper allocation schemes. In this aspect, the proposed model can also be thought as a water allocation model. The model is tested and applied to the Jiaojiang River basin, Zhejiang Province, China, to analyze the different water resource allocation schemes.     

A modeling study of ice–water processes for Lake Erie applying coupled ice-circulation models

A hydrodynamic model that includes ice processes and is optimized for parallel processing was configured for Lake Erie in order to study the ice–water coupling processes in the lake. A hindcast from April 2003 to December 2004 with hourly atmospheric forcing was conducted. The model reproduced the seasonal variation of ice cover, but the development of ice extent in January and its decay in March somewhat preceded the observations. Modeled lake circulation in ice-free seasons is consistent with previous studies for Lake Erie. Thermal structure of the lake was reasonably comparable to both satellite-derived observations and in-situ measurements, with mean differences ranging from − 2 °C to 4 °C, depending on the season. The impacts of ice–water stress coupling and basal melting of ice were examined based on numerical experiments. The results show that: 1) ice–water stress coupling significantly dampens the subjacent lake circulation in winter due to packed ice cover that slows down the surface water, and 2) basal melting of ice contributes to widespread ice cover in the lake. The demonstrated model validity could lead to further studies of ice–water processes in the lake, including interannual variation and impacts on ecosystems.     

A novel method for tracking western Lake Erie Microcystis blooms, 2002–2011

After a period of improvement from the late 1970s through the mid 1990s, western Lake Erie has returned to eutrophic conditions and harmful algal blooms now dominated by the cyanobacterium Microcystis aeruginosa. The detection of long-term trends in Microcystis blooms would benefit from a convenient method for quantifying Microcystis using archived plankton tows. From 2002 to 2011, summer Microcystis blooms in western Lake Erie were quantified using plankton tows (N = 649). A flotation separation method was devised to quantify Microcystis biovolume in the tows, and the method was tested against whole water cell counts. Floating Microcystis biovolume (mL) in preserved tows was highly correlated with total Microcystis cells (R² = 0.84) and biomass (R² = 0.95) in whole water samples. We found that Microcystis annual biovolume was highly variable among years; the 2011 bloom was 2.4 times greater than the second largest bloom (2008) and 29.0 times greater than the smallest bloom (2002). Advantages of the method include use of archived samples, high sampling volume, and low effort and expense. Limitations include specificity for cyanobacterial blooms dominated by large Microcystis colonies and the need for site-specific validation. This study indicates that the flotation method can be used to rapidly assess past and present Microcystis in western Lake Erie and that there was high variability in the timing, duration, and intensity of the annual Microcystis blooms over a 10-year period. The data made possible by this method will aid further investigations into the underlying causal factors of blooms.     

A Hybrid Model Integrating Elman Neural Network with Variational Mode Decomposition and Box–Cox Transformation for Monthly Runoff Time Series Prediction

Water Resources Management - Precise and reliable monthly runoff prediction plays a vital role in the optimal management of water resources, but the nonstationarity and skewness of monthly runoff...     

A lake-wide approach for large lake zooplankton monitoring: Results from the 2006–2016 Lake Superior Cooperative Science and Monitoring Initiative surveys

Whole-lake surveys of Lake Superior were completed during late summer in 2006, 2011, and 2016 to assess lower food web conditions under the Cooperative Science and Monitoring Initiative (CSMI). These surveys used a spatially stratified probability approach based on depth to assess food web conditions within different depth zones. We evaluated differences in crustacean zooplankton biomass, rotifer density, and the community structure of both groups in nearshore (<30 m), midshore (30–100 m), and offshore (>100 m) depth zones and investigated changes in these parameters within zones over time. Although nearshore crustacean biomasses and rotifer densities were highly variable, the depth zones differed from each other based on these parameters and should be considered separately. Crustacean biomass, community structure, and vertical position were consistent over time across depth zones. The differences that did occur were within the range of known annual variability. Total rotifer densities were lower in 2016 than in 2006 in all depth zones, but the genera that contributed to the lower values were not the same across zones. Further studies are needed to know whether these differences reflect annual variability or long-term trends. Finally, we show how the depth zones used in this study can facilitate comparisons between monitoring programs. This is important because most zooplankton studies are limited to certain depth zones and changes in zooplankton parameters may not occur uniformly across zones. The high variability in nearshore zooplankton parameters suggests that additional research may be needed to effectively track changes there.