Mohammad Rezaie-Balf

• M.Sc Graduated in water resources management
• Graduate University of Advanced Technology

The goal of this study is mapping flood risks over Golestan province in Iran using one of the artificial intelligence methods called multivariate adaptive regression splines (MARS). In this sense, 14 flood conditioning factors were considered and the maps were made in ArcGIS. Additionally, two novel metaheuristic algorithms namely cat swarm optimiz...

Entropy models have been recently adopted in many studies to evaluate the shear stress distribution in open-channel flows. Although the uncertainty of Shannon and Tsallis entropy models were analyzed separately in previous studies, the uncertainty of other entropy models and comparisons of their reliability remain an open question. In this study, a...

Total organic carbon (TOC) has vital significance for measuring water quality in river streamflow. The detection of TOC can be considered as an important evaluation because of issues on human health and environmental indicators. This research utilized the novel hybrid models to improve the predictive accuracy of TOC at Andong and Changnyeong statio...

This study evaluated the effectiveness of Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) satellite rainfall data for the development of multi-step ahead streamflow forecasting models. Daily time scale precipitation data of nearly three decades (1986-2012) over the Varahi river basin in Western Ghats of Karnataka, India were used...

Monitoring the water contaminants is of utmost importance in water resource management. Prediction of the total dissolved solid (TDS) is particularly essential for water quality management and planning in the areas exposed to a mixture of pollutants. TDS primarily includes inorganic minerals and organic matters, and various salts and increasing the...

Short-term forecasts such as daily forecasts of river flow (RF) and water level (WL) play an important and fundamental role in flood analyses. The daily prediction of flow and water level components in two major rivers Mississauga Golf and Country Club and Old Derry located in Mississauga, Ontario, Canada, has been conducted. It was found that the...

Forecasting daily solar radiation (DSR) is a critical concern while implementing solar energy harnessing projects, energy utility and stakeholder decisions. In developing forecast models based on data-driven technique, challenges are encountered by virtue of the chaotic nature of meteorological data that can exhibit a high degree of irregularities,...

Water quality has a crucial impact on human health; therefore, water quality index modeling is one of the challenging issues in the water sector. The accurate prediction of water quality index is an essential requisite for water quality management, human health, public consumption, and domestic uses. A comprehensive review as an initial attempt is...

The construction and maintenance of roads pavement was a critical problem in the last years. Therefore, the use of roller-compacted concrete pavement (RCCP) in road problems is widespread. The compressive strength (fc) is the key characteristic of the RCCP caused to significant impact on the cost of production. In this study, an evolutionary-based...

Hydrological modeling is one of the important subjects in managing water resources and the processes of predicting stochastic behavior. Developing Data-Driven Models (DDMs) to apply to hydrological modeling is a very complex issue because of the stochastic nature of the observed data, like seasonality, periodicities, anomalies, and lack of data. As...

The entropy models have been recently adopted in many studies to evaluate the distribution of the shear stress in circular channels. However, the uncertainty in their predictions and their reliability remains an open question. We present a novel method to evaluate the uncertainty of four popular entropy models, including Shannon, Shannon-Power Low...

The potential of the most recent pre–processing tool, namely, complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), is examined for providing AI models (artificial neural network, ANN; M5–model tree, M5–MT; and multivariate adaptive regression spline, MARS) with more informative input–output data and, thence, evaluate their...

In this paper, surrogate models such as multivariate adaptive regression splines (MARS) and M5P model tree (M5P MT) methods have been investigated in order to propose a new formulation for the 28-days compressive strength of self-compacting concrete (SCC) incorporating metakaolin as a supplementary cementitious materials. A database comprising expe...

Due to large number of decision variables and several hydraulic constraints, optimal design of water distribution networks (WDNs) is considered as one of the most complex optimization problems. This paper introduces and applies a new optimization approach, improved crow search algorithm (ICSA), based on the improvement of original crow search algor...

Accurate pan evaporation (E_pan) predicting is taken into account as a crucial issue in water resources management, particularly in designing the rural water resource systems, management of irrigation systems, and water utilization and demand assessments. In this study, on the basis of the 33-years (1965-2008) of observations from Turkey’s Siirt an...

This study compares single and hybrid soft computing models for estimating daily solar radiation flux for two scenarios. Scenario I developed single soft computing models, including multilayer perceptron (MLP), support vector machines (SVM), adaptive neuro-fuzzy inference system (ANFIS) and multivariate adaptive regression splines (MARS), for estim...

Developing hydrologic models based on data-driven approaches (DDA) is very complicated due to the complex nature of meteorological data. For example, a high degree of irregularities, periodicities, jumps, and other forms of stochastic behavior influence the accuracy of river flow forecasting. In this study, M5 model tree (M5Tree) and multivariate a...

The precise forecasting of daily solar radiation (DSR) is receiving prominent attention among thriving solar energy studies. In this study, three standalone models, including gene expression programing (GEP), multivariate adaptive regression splines (MARS), and self-adaptive MARS (SaMARS), were evaluated to forecast DSR. A SaMARS model was classifi...

Accurate prediction of daily streamflow plays an essential role in various applications of water resources engineering, such as flood mitigation and urban and agricultural planning. This study investigated a hybrid ensemble decomposition technique based on ensemble empirical mode decomposition (EEMD) and variational mode decomposition (VMD) with ge...

Accurate prediction of pan evaporation (PE) is one of the crucial factors in water resource management and planning in agriculture. In this research, two hybrid models, self-adaptive time-frequency methodology, ensemble empirical mode decomposition (EEMD) coupled with support vector machine (EEMD-SVM) and EEMD model tree (EEMD-MT) were employed to...

Stepped weir is a commonly used hydraulic structure in water treatment plants to enhance the air-water transfer of oxygen or nitrogen and volatile organic components. The flow regimes on stepped weir are classified into nappe, transition and skimming flow. This study presents the novel application of artificial intelligence methods to evaluate the...

Sluice gates commonly control water levels and flow rates in rivers and channels. They are also used in wastewater treatment plants and to recover minerals in mining operations and in watermills. Hence, scour phenomena downstream of sluice gates have attracted the attention of engineers to present a precise prediction of the local scour depth. Most...

The fate of pollutants in rivers is mainly affected by the longitudinal dispersion coefficient (Kx). Thus, improved Kx estimation could greatly enhance the water quality management of rivers. In this regard, evolutionary polynomial regression (EPR) was used to accurately predict Kx in rivers as a function of flow depth, channel width, and average a...

Rock riprap is commonly used to protect levees, embankment dam, steep channels, and other structures being vulnerable to deteriorative erosion caused by overtopping flow. A review of the literature in this context indicates that over 24 riprap design expressions exist to predict the stone size in the riprap layer. However, each equation was origina...

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 multivariat...

In this study, two different machine learning models, Multivariate Adaptive Regression Splines (MARS) and M5 Model Trees (MT) have been applied to simulate the groundwater level (GWL) fluctuations of three shallow open wells within diverse unconfined aquifers. The Wavelet coupled MARS and MT hybrid models were developed in an attempt to further inc...

Streamflow forecasting is crucial in hydrology and hydraulic engineering since it is capable of optimizing water resource systems or planning future expansion. This study investigated the performances of three different soft computing methods, multilayer perceptron neural network (MLPNN), optimally pruned extreme learning machine (OP-ELM), and evol...

Scouring in the channel contractions occurs due to the flow concentration within them inducing sexcessive bed shear stress. This is a complex process, so it is difficult to describe it through a general empirical model, the present research work describes contemporary conceptual relationships to estimate the local scour depth under equilibrium and...

Debris accumulation fundamentally reduces the flow area which causes deviation of flow and increase the velocity around bridge piers. Therefore, debris flow increases local scour depth and expedites sediment transportation process around piers. Hence, pier scour phenomena in presence of debris accumulation have been attracted the attention of engin...