A simple procedure for the real-time estimation of the average rainfall over a catchment area is described. The rainfall is modelled as a 2-dimensional random field (RF). The average areal rainfall is computed by a linear unbiased minimum variance estimation method (Kriging) which requires the knowledge of the variogram of the random field. A time-varying estimator for the variogram which takes into account the influences of both the seasonal variations and the rainfall intensity is proposed. The average areal rainfall estimator has been implemented in practice. Its application to real data in two river basins in Belgium is presented. Finally, it is shown how the method can be used for the optimal selection of the rain-gauge locations in a basin.

Optimal estimation of the average areal rainfall and optimal selection of rain-gauge locations

Particle methods in ocean and coastal engineering

Examining global electricity supply vulnerability to climate change using a high-fidelity hydropower dam model.

Water quality management and control has high importance in planning and developing of water resources. This study investigated application of Genetic Algorithm (GA), Ant Colony Optimization for Continuous Domains (ACOR) and Differential Evolution (DE) in improving the performance of adaptive neuro-fuzzy inference system (ANFIS), for evaluating the quality parameters of Gorganroud River water, such as Electrical Conductivity (EC), Sodium Absorption Ratio (SAR) and Total Hardness (TH). Accordingly, initially most suitable inputs were estimated for every model using sensitivity analysis and then all of the quality parameters were predicted using mentioned models. Investigations showed that for predicting EC and TH in test stage, ANFIS-DE with R2 values of 0.98 and 0.97, respectively and RMSE values of 73.03 and 49.55 and also MAPE values of 5.16 and 9.55, respectively were the most appropriate models. Also, ANFIS-DE and ANFIS-GA models had the best performance in prediction of SAR (R2 = 0.95, 0.91; RMSE = 0.43, 0.37 and MAPE = 13.43, 13.72) in test stage. It is noteworthy that ANFIS showed the best performance in prediction of all mentioned water quality parameters in training stage. The results indicated the ability of mentioned algorithms in improving the accuracy of ANFIS for predicting the quality parameters of river water.

Prediction of Water Quality Parameters Using ANFIS Optimized by Intelligence Algorithms (Case Study: Gorganrood River)

Evaporation plays a key role in water resources management in arid and semiarid climatic regions. This is the first time that an artificial neural network (ANN) model is applied to estimate evaporation in a hot and dry region (BWh climate by the Koppen classification). It has been found that ANN works very well at the study site and, further, an integrated ANN and autoregressive with exogeneous inputs can have an improved performance over the traditional ANN. Both models significantly outperformed the two empirical methods. It has been demonstrated that the important weather factors to be included in the model inputs are wind speed, saturation vapor pressure deficit, and relative humidity. This result is different from all those reported in the literature and is interestingly linked with a 1936 study by Anderson, who emphasized the importance of saturation vapor pressure deficit. As evaporation is a nonlinear dynamic process, the selection of suitable input weather variables has been a complicated and tim...

Closure to "Daily Pan Evaporation Modeling in a Hot and Dry Climate"

The labyrinth spillway continues to be a popular type of the control structures. The focus of the present study is that on the optimization of the shape of the labyrinth spillway through the minimization of the construction costs because the use of it is a suitable solution in the rehabilitation process of existing reservoirs. An Adaptive Neural Fuzzy Inference System (ANFIS) model was developed to determine the discharge coefficient of the labyrinth spillway as a function of the angle between alignment of the crest and direction of flow, the relative depth of flow over spillway and its crest height. Differential Evolution (DE) algorithm and Genetic Algorithm (GA) were adopted to minimize the spillway cost as the objective function by considering certain hydraulic conditions as the constraints of the optimization procedure. The results indicated that DE and GA can respectively reduce 19.3% and 16.6% the construction cost of a real benchmark design.

Optimal design of labyrinth spillways using meta-heuristic algorithms

Meshfree particle numerical modelling of sub-aerial and submerged landslides

A multiphase meshfree particle method for continuum-based modeling of dry and submerged granular flows

One of the most valuable physical characteristics of dams and their reservoirs are area-capacity curves. The main objective of this paper is to substitute the reservoir capacity equation by a more precise dimensionless capacity equation which has fewer unknown parameters and coefficients. This proposed equation has only one unknown dimensionless parameter named “reservoir coefficient” N which should be obtained for each reservoir. The reservoir coefficient equation and reservoir area equation are obtained by differentiating the proposed reservoir capacity equation. The numerical values for N are obtained by using a trial and error procedure to minimize the Sum of Squared Errors (SSEs) of reservoir area and capacity equations and analytical values of N are obtained by deriving reservoir coefficient equation. Also, the results of the new proposed equation and the previous equation are evaluated and compared with each other for 20 reservoirs. In this study, it is concluded that the new proposed equation is more precise and much easier to solve in comparison with the previous one.

A new equation for calculation of reservoir’s area-capacity curves

From 1970s, studies have been conducted on the hydraulic design of stepped spillways and many empirical formulas were developed. Despite the simple geometry of these spillways, their hydraulic behavior is complicated. As a result, for many cases, the physical models are studied to verify the design. Numerical simulation is considered as a tool to reduce the laboratory tests, in order to save time and money. Furthermore, the parameters which are not investigated or measured in physical models could be evaluated. In this paper, the results of numerical simulations are compared with the results of physical models and empirical formulas for the spillway of Renwick dam studied in a 1/8 scale model by Hunt and Kadavy (World Environmental and Water Resources Congress. ASCE, Great Rivers, pp. 3061–3071, 2009). Numerical simulation of flow is achieved by a mixture multi-phase flow model and a realizable k-\({\varepsilon}\) turbulence model proposed by Qian et al. (Sci China Ser E-Tech Sci 52(7), 1958–1965, 2009). Grid sensitivity is accomplished and the size of mesh is reduced in locations where a high gradient of certain parameters exists or a higher precision is required. The numerical simulation results conform to the physical model tests. The velocity profile, energy dissipation, and the location of inception point where air entrainment in the flow is guaranteed, are investigated and compared to the scale model results. Also, thanks to this satisfaction, we could obtain the parameters such as pressure field which are not measured in the physical model.

Khosrow Hosseini

Papers

Optimal design of labyrinth spillways using meta-heuristic algorithms

Meshfree particle numerical modelling of sub-aerial and submerged landslides

A multiphase meshfree particle method for continuum-based modeling of dry and submerged granular flows

A new equation for calculation of reservoir’s area-capacity curves

The Effect of the Step Height on Energy Dissipation in Stepped Spillways Using Numerical Simulation