Isam Issa Omran

@atu.edu.iq

Building & Constructions Techniques Engineering Department/ Technical College of Al-Mussaib
Al-Furat Al-Awsat Technical University

I am currently working at the Technical College of Al-Mussaib, Al-Furat Al-Awsat Technical University. I work in research fields related to the disciplines of environmental engineering, water resources engineering, and civil engineering. My current research project is "Evaluating the Sustainability of Municipal Solid Wastes Treatment Techniques: a Case Study in Baghdad City/ Iraq".

EDUCATION

Ph.D., Professor (Full)

RESEARCH INTERESTS

Sanitary and Environmental Engineering
Water Resources Engineering
Civil Engineering

8

Scopus Publications

Scopus Publications

  • Estimation of Muskingum's equation parameters using various numerical approaches: flood routing by Muskingum's equation
    I. I. Omran, M. A. A. Kadim, and N. H. Al-Saati

    Springer Science and Business Media LLC

  • Evaluation of Flood Routing Models and Their Relationship to the Hydraulic Properties of the Diyala River Bed
    M A Kadhim, N K Al-Bedyry, and I I Omran

    IOP Conference Series: Earth and Environmental Science IOP Publishing
    Abstract In this study, four types of flood routing approaches were studied which give significantly varied results represented by the differences between computed and observed flows and also differ considerably on the friction coefficient and bed slope of the channels. First two approaches use a hydraulic solution to solve the equations of unsteady flow, while the third approach uses the hydrological solution, and the fourth algorithm solves Muskingum approach with seven parameters. All these approaches were run with the same input parameters, the results were compared and tested with four Error Measurement Indices, Sum of Squared Deviations, Error of Peak Discharge, Variance Index, and agreement index. Diyala River was selected for this application. Dynamic wave method gave accurate results, followed by the characteristic method, and then the linear Muskingum-Cunge method, but Symbiotic Organisms Search Algorithm not gave any senses due to change in roughness or bed slope and gave very identical values with recorded outflow in all conditions, which means that the hydraulic solution is better compared to the hydrological solution. The results also showed that the difference between the calculated and observed flows diminished with a decrease in the coefficient of friction and an increase in the bed slope channel.

  • A new framework for assessing the sustainability of municipal solid waste treatment techniques applying multi-criteria decision analysis
    I. I. Omran, N. H. Al-Saati, A. A. Salman, and K. Hashim

    Springer Science and Business Media LLC

  • Optimization of the Nonlinear Muskingum Model Parameters for the River Routing, Tigris River a Case Study
    Maher Abd Ameer Kadim, Isam Issa Omran, and Alaa Ali Salman Al-Taai

    International Information and Engineering Technology Association
    Flood forecasting and management are one of the most important strategies necessary for water resource and decision planners in combating flood problems. The Muskingum model is one of the most popular and widely used applications for the purpose of predicting flood routing. The particle swarm optimization (PSO) methodology was used to estimate the coefficients of the nonlinear Muskingum model in this study, comparing the results with the methods of genetic algorithm (GA), harmony search (HS), least-squares method (LSM), and Hook-Jeeves (HJ). The average monthly inflow for the Tigris River upstream at the Al-Mosul dam was selected as a case study for estimating the Muskingum model's parameters. The analytical and statistical results showed that the PSO method is the best application and corresponds to the results of the Muskingum model, followed by the genetic algorithm method, according to the following general descending sequence: PSO, GA, LSM, HJ, HS. The PSO method is characterized by its accurate results and does not require many assumptions and conditions for its application, which facilitates its use a lot in the subject of hydrology. Therefore, it is better to recommend further research in the use of this method in the implementation of future studies and applications.

  • Sustainability assessment of wastewater treatment techniques in urban areas of iraq using multi-criteria decision analysis (Mcda)
    Isam I. Omran, Nabeel H. Al-Saati, Hyam H. Al-Saati, Khalid S. Hashim, and Zainab N. Al-Saati

    Water Practice and Technology IWA Publishing
    Abstract Sustainable development is based on environmental, social, economic, and technical dimensions. In this study, the sustainability of wastewater treatment techniques in urban areas of Iraq was assessed using a multi-criteria decision analysis (MCDA)/the weighted sum model (WSM). The analysis was performed on 13 operating wastewater treatment plants in 10 provinces, Iraq, using a questionnaire sheet with the assistance of 52 specialists in the Ministry of Municipalities and Public Works, Iraq. Four types of wastewater treatment techniques (Conventional Treatment, Oxidation Ditches, Aeration Lagoons, and membrane bio-reactor (MBR)) were assessed. The environmental, social, economic, and technical dimensions were represented by 11, 5, 7, and 4 indicators, respectively. The main results of this study indicate that the sustainability of MBR recorded the highest total importance; the order of the total importance from the highest to the lowest was: MBR > Oxidation Ditches > Aeration Lagoons > Conventional Treatment. The environmental dimension proved its dominance in the four studied treatment techniques' sustainability as it recorded the maximum contribution to sustainability. While the technical dimension recorded the least contribution to sustainability, the order from the highest to the lowest was: Environmental Dimension > Economic Dimension > Social Dimension > Technical Dimension.

  • Statistical modeling of monthly streamflow using time series and artificial neural network models: Hindiya barrage as a case study
    Nabeel H. Al-Saati, Isam I. Omran, Alaa Ali Salman, Zainab Al-Saati, and Khalid S. Hashim

    Water Practice and Technology IWA Publishing
    Abstract Autoregressive Integrated Moving Average (ARIMA) Box-Jenkins models combine the autoregressive and moving average models to a stationary time series after the appropriate transformation, while the nonlinear autoregressive (N.A.R.) or the autoregressive neural network (ARNN) models are of the kind of multi-layer perceptron (M.L.P.), which compose an input layer, hidden layer and an output layer. Monthly streamflow at the downstream of the Euphrates River (Hindiya Barrage) /Iraq for the period January 2000 to December 2019 was modeled utilizing ARIMA and N.A.R. time series models. The predicted Box-Jenkins model was ARIMA (1,1,0) (0,1,1), while the predicted artificial neural network (N.A.R.) model was (M.L.P. 1-3-1). The results of the study indicate that the traditional Box-Jenkins model was more accurate than the N.A.R. model in modeling the monthly streamflow of the studied case. Performing a one-step-ahead forecast during the year 2019, the forecast accuracy between the forecasted and recorded monthly streamflow for both models was as follows: the Box-Jenkins model gave root mean squared error (RMSE = 48.7) and the coefficient of determination = 0.801), while the (NAR) model gave (RMSE = 93.4) and = 0.269). Future projection of the monthly stream flow through the year 2025, utilizing the Box-Jenkins model, indicated the existence of long-term periodicity.

  • Assessment of heavy metal pollution in the great al-mussaib irrigation channel
    Isam I. Omran, , Nabeel H. Al-Saati, Khalid S. Hashim, Zainab N. Al-Saati, P. Kot, Rafid Al Khaddar, Dhiya Al-Jumeily, Andy Shaw, Felicite Ruddock,et al.

    Desalination Publications
    The Great Al-Mussaib channel (GMC), in Babylon province, Iraq, has been selected as a case study to measure the concentration of nine heavy metals (Pb, Ni, Zn, Fe, Cd, Cr, Cu, Mn and Co) in both water and sediments of the GMC. The channel is used as a raw water source for two cities, which reveals the importance of the current study. Where, any heavy metals pollution could cause significant health problems for the population of these cities. The obtained results revealed that the concentrations of the studied heavy metals in the water of the GMC were less than the pollution levels and followed the order: Pb < Ni < Cu < Cr < Mn < Zn < Fe. It is noteworthy to highlight that the concentrations of Co and Cd were below the detectable limits. Additionally, the results obtained from the analyses of the studied sediment samples showed, according to the values of pollution load index and geo-accumulation index (Igeo), that the concentrations of studied metals were less than the pollution levels (except for a few cases) and followed the order: Cd < Co < Cu < Pb < Ni < Cr < Zn < Mn < Fe.

  • Evaluation of the soil moisture content using GIS technique and SWAT model, (Wadi Al-Naft region: As a case study)
    Mahmood J. Mohamed, Isam I. Omran, and Wisam A. Abidalla

    IOP Publishing
    Soil moisture content is one of the basic parameters required to study the strategy of sustainable water management within urban and rural uses. Wadi Al-Nafat region was chosen as a study site within a total area of 8,820 km2, which is located in the northeast of Diyala province in the country of Iraq. The net area of the main catchment planning was 4926 km2 or about 56% of the total study area. The main catchment area was divided into 83 sub - catchments for the purpose of completing the application of the GIS technique and SWAT model. They were used to calculate the soil moisture content based on input data represented by the digital model of the elevation levels, meteorological data, uses of land and soil at the study site with the application of the SCS-CN mathematical model, and then determined water losses associated with average Annual Curve Number 73 during the period 2010 to 2016.The results of SWAT simulation showed that the annual rate of soil moisture content is 41.26 mm comparing with the 46.74 mm from field works during the same period with a difference of about 11%. The study also explained the efficient use of SWAT model and GIS technique in predicting the soil moisture content values and compares them with field results. It is noted that the correlation coefficient between soil moisture content measured by field works and soil moisture content calculated according to SWAT model simulation is 97%. Study results are encouraging the use of these techniques in areas lacking hydrologic and topographic parameters and thereby reduce the need for human and economic sources.