The rheological properties of ketchup as a function of different hydrocolloids and temperature

The flow properties of ketchup were assessed upon addition of commonly used food thickeners: guar, xanthan and CMC gum at three different concentrations (0.5%, 0.75% and 1%) and four temperatures (25, 35, 45 and 55 °C). The ketchup without supplementation served as a control. All ketchup formulations exhibited non-Newtonian, pseudoplastic behaviour at all temperatures and hydrocolloid levels. The Power-law and Herschel-Buckley model were successfully applied to fit the shear stress versus shear rate data. The flow behaviour indices, n and n' , varied in the range of 0.189–0.228 and 0.216–0.263, respectively. The consistency coefficients, k and k' , were in the range of 8.42–27.22 and 6.56–20.10 Pa s ⁿ , respectively. The addition of hydrocolloids increased the yield point (τ₀) and apparent viscosity of the ketchup in comparison to that of the control. The Arrhenius equation was successfully used to describe the effects of temperature on the apparent viscosity of the prepared formulations. The E _a value appeared in the range between 5492.6 and 21475.8 J mol⁻¹.     

Optimal Development of Agricultural Sectors in the Basin Based on Economic Efficiency and Social Equality

The limitation of freshwater resources and the growing demand for water, make the issue of water resource development planning and water allocation among stakeholders even more important. Ideally, water allocation should be economically efficient and socially equitable. In this study, a water allocation model is presented in an integrated framework that considers the interaction of water supply and demand according to economic and social factors. To achieve this, a reliability-based multi-objective optimization - simulation approach has been employed. The objective functions of the problem are: 1) maximizing GDP from agricultural sectors and 2) maximizing social equality in different provinces of the basin (measured using the Williamson coefficient). The fair development and allocation among the shared provinces in the basin can reduce conflicts in the region. Karkheh basin has been considered as a case study and decision variables of the problem are area under cultivation of agricultural development sectors in different provinces. The results show that, without harming the income of the agricultural sector, the spatial distribution of development projects can be done in such a way that equality (according to income level and the number of people working in each province) is achieved. One of the solutions of Pareto front compared to previous studies shows that, in addition to an increase of about 12% of the objective function 1 (GDP), the value of the objective function 2 (Williamson coefficient) decreased from 1.19 to 0.98. This indicates a decrease in income inequality among the provinces of the basin.

     

Evaluation of suspended load transport rate using transport formulas and artificial neural network models （Case study： Chelchay Catchment）＊

Accurate estimation of sediment load or transport rate is very important to a wide range of water resources projects. This study was undertaken to determine the most appropriate model to predict suspended load in the Chelchay Watershed, northeast of Iran. In total, 59 data series were collected from four gravel bed-rivers and a sand bed river and two depth integrating suspended load samplers to evaluate nine suspended load formulas and feed forward backpropagation Artificial Neural Network (ANN) structures. Although the Chang formula with higher correlation coefficient (r = 0.69) and lower Root Mean Square Error (RMSE = 0.013) is the best suspended load predictor among the nine studied formulas, the ANN models significantly outperform traditional suspended load formulas and show their superior performance for all statistical parameters. Among different ANN structures two models including 4 inputs, 4 hidden and one output neurons, and 4 inputs, 4 and one hidden and one output neurons provide the best simulation with the RMSE values of 0.0009 and 0.001, respectively.     

Application of Bayesian Decision Networks for Groundwater Resources Management Under the Conditions of High Uncertainty and Data Scarcity

This paper presents management of groundwater resource using a Bayesian Decision Network (BDN). The Kordkooy region in North East of Iran has been selected as study area. The region has been sub-divided into three zones based on transmissivity (T) and electrical conductivity (EC) values. The BDN parameters: prior probabilities and Conditional Probability Tables - CPTs) have been identified for each of the three zones. Three groups of management scenarios have been developed based on the two decision variables including “Crop pattern” and “Domestic water demand” across the three zones of the study area: 1) status quo management for all three zones represent current conditions; 2) the effect of change in cropping pattern on management endpoints and 3) the effect of future increased domestic water demand on management endpoints. The outcomes arising from implementing each scenario have been predicted by use of the constructed BDN for each of the zones. Results reveal that probability of drawdown in groundwater levels of southern areas is relatively high compared with other zones. Groundwater withdrawal from northern and northwestern areas of the study area should be limited due to the groundwater quality problems associated with shallow groundwater of these two zones. The ability of the Bayesian Decision Network to take into account key uncertainties in natural resources and perform meaningful analysis in cases where there is not a vast amount of information and observed data available – and opportunities for enabling inputs for the analysis based partly on expert elicitation,emphasizes key advantages of this approach for groundwater management and addressing the groundwater related problems in a data-scarce area.     

A Multi-Model Nonstationary Rainfall-Runoff Modeling Framework: Analysis and Toolbox

Water Resources Management - We present a framework and toolbox for multi-model (one at a time) nonstationary modeling of rainfall-runoff (RR) transformation. The designed time-varying nature of...     

Modeling River Mixing Mechanism Using Data Driven Model

Modeling river mixing mechanism in terms of pollution transmission in rivers is an important subject in environmental studies. Dispersion coefficient is an important parameter in river mixing problem. In this study, to model and predict the longitudinal dispersion coefficient (D _L ) in natural streams, two soft computing techniques including multivariate adaptive regression splines (MARS) as a new approach to study hydrologic phenomena and multi-layer perceptron neural network as a common type of neural network model were prepared. To this end, related dataset were collected from literature and used for developing them. Performance of MARS model was compared with MLP and the empirical formula was proposed to calculate D _L . To define the most effective parameters on D _L structure of obtained formula from MARS model and more accurate formula was evaluated. Calculation of error indices including coefficient of determination (R²) and root mean square error (RMSE) for the results of MARS model showed that MARS model with R²?=?0.98 and RMSE?=?0.89 in testing stage has suitable performance for modeling D _L . Comparing the performance of empirical formulas, ANN and MARS showed that MARS model is more accurate compared to others. Attention to the structure of developed MARS and the most accurate empirical formulas model showed that flow velocity, depth of flow (H) and shear velocity are the most influential parameters on D _L .     

Multi-Objective Surface Water Resource Management Considering Conflict Resolution and Utility Function Optimization

In the present research, a multi-objective model is developed for surface water resource management in the river basin area which is connected to the lake. This model considers different components of sustainable water resource management including economic, social and environmental aspects, and simultaneously tries to resolve conflicts between different stakeholders by means of non-symmetric Nash bargaining, which is linked to the multi-objective optimization method. This study proposes a new methodology to improve Nash Conflict Resolution through finding the optimum degree of the utility function. The proposed model is examined in the Zarrineh River basin in Iran. The results show that the amount of available resources or volume of reservoirs play a significant role in determining the optimal degree of the utility function and efficiency of the proposed method in such a way that the higher amount of resources or the larger reservoirs will result in the higher optimal degree of the utility function. In the proposed multi-objective model, two different amounts of surface water inflow are considered. The first assumed amount is the long-term average flow rate and the second one is equal to 80% of the first mode, which is reduced based on the estimated impacts of climate changes. This multi-objective allocation model could supply 100 and 97.5% of the environmental demand of Lake Urmia in the first and second situations, respectively.     

Numerical Simulation of Submarine Groundwater Flow in the Coastal Aquifer at the Palmahim Area, the Mediterranean Coast of Israel

The lower sub-aquifers of the Mediterranean coastal aquifer of Israel, at the Palmahim area, are hypothesized to be laterally blocked to connection with the sea, and thus to seawater intrusion. This is mostly due to the detection of fresh water bodies at these sub-aquifers. This study examine this hypothesis by using two dimensional numerical model simulations of the groundwater flow system at this area, which conducted in order to reveal which hydrogeological setting enables the existence of these fresh water bodies in the lower sub-aquifers and to assess the on-land pumping rates that will prevent their salinization. The hydrogeological settings were examined by steady state simulations followed by simulations of the last 15,000 years sea level changes. These simulations imply that the presence of fresh water in the lower sub-aquifer, whether blocked or connected to the sea, requires offshore separation between the upper and lower sub-aquifers. On-land pumping simulations, with a well located inside the lower sub-aquifers at the shoreline, show a maximum pumping rate of 250 m³/m strip width/year, hereafter m²/year, to prevent the salinization of the lower sub-aquifers. The various pumping scenarios revealed differences in salinization trends between the scenarios with impermeable separating layers and those with semi permeable layers. Scenarios with extreme pumping rates emphasize these differences, and together with field test, can allow assessing the amount of separation between the sub-aquifers.