Iraqi Journal of Civil Engineering

Iran has recently started a well-planned project, called Tropical Water Project (TWP), to build more dams, tunnels, and canals on the main tributaries of the Diyala River (Sirwan and Zmkan) to irrigate agricultural areas inside and outside the Diyala River basin. One task in the TWP project is diverting a large volume of the water flowing through the Sirwan and Zmkan rivers through a series of tunnels. The largest one, called Nowsud water conveyance tunnel, transports water from Hirwa dam to Azgala dam to irrigate millions of hectares of new agricultural areas extending from Kermanshah province in the AL Ahwaz province. This research aims to identify the different features and the size of this project as well as the extent of its impact on the Diyala River and Darbandikhan dam. From the results, it was found that the TWP project consists of 14 dams constructed on Sirwan and Zmkan rivers and their tributaries with a total storage capacity of 1.9 Milliard cubic meters and of about 150 km long tunnels to divert more than one Milliard m3 of water to another basin. In addition, it has been found that after the full operation of the TWP project, the catchment area of Darbandikhan dam will lose 77% of its original one.

The management of water resources requires adequate information on the quantities of water supplied from the basins that outfall into a river, especially during the flood seasons. The study area located in the western part of Iraq within the administrative boundaries of the Heet district about 70 km from Haditha Dam, 45km from Ramadi in Anbar province. The study aims to evaluate the amount of surface runoff through a long-term period (1981-2019). Soil and Water Assessment Tool (SWAT) related to Geographic Information System (ArcGIS) was used for the simulation. The input data was the Digital Elevation Model (DEM) of SRTM with resolution 30m, land use/land cover map from the European Space Agency (ESA) with resolution 300m and, soil map from the Food and Agriculture Organization (FAO). The weather data used in the study were obtained from the Climate Forecast System Reanalysis (CFSR) combined with the weather data from the Surface meteorology and Solar Energy (SSE) produced by NASA. These weather data prepared using SWAT weather database software to be ready for the simulation processes. Al-Mohammedi valley was calibrated and validated using SWAT-CUP software using the available recorded discharges at Heet, Ramadi, and Al-Warar gauge stations. The calibration is based on the meteorological data for the period January 1, 2002, to December 31, 2006, and the validation was based on the data between January 1, 2007, to December 31, 2009. The model calibration and validation results based on two objective functions “Nash-Sutcliffe (NS) and coefficient of determination(R2)” showed that SWAT was successfully simulated Al-Mohammedi valley with NS = 0.72 and R2 = 0.76 for calibration, and NS = 0.63 and R2 = 0.65 for validation. According to SWAT results, the average runoff volume in the long-term period of simulation from January 1, 1981, to October 31, 2019, was 79.2 million m3 while the average runoff depth was 18.25 mm with about 17 % of rainfall becomes surface runoff.

The main objective of this study is to evaluate the comparative performance of three artificial neural network techniques (radial basis functions “RBF”, multilayer perceptron “MLP”, and group method of data handling “GMDH”) based approach with the Penman–Monteith “PM” method for determining the group reference evapotranspiration “ET0” on monthly basis in Basrah City, south of Iraq. Climate information extends over 22 years (1991- 2012), monthly records of maximum temperature (Tmax), mean temperature (Tmean), minimum temperature (Tmin), wind speed (U) and relative humidity (RH) are used in this research. The architecture of artificial neural network models is performed during the process of training. The efficiency of trained model is checked by using the testing data, which is not used in the process of training. The evaluating of the artificial neural model performance is carried out by using cross-validation, a set of rows for each validation fold is determined randomly after stratification on the target variable “ET0”. Various set of climate inputs variables are used for creating nine artificial neural network models. The efficiency of artificial neural network models with two predictor variables (Tmean & U) for simulating ET0 is highly efficient according to the evaluation criteria. There is a significant improvement in the results of all artificial neural network models when using three input combination variables (Tmean, U, & RH) compared with the models that have only two-climate variables. Artificial neural network models especially (RBF, MLP, and GMDH) are efficient and powerful techniques for simulating ET0.

Construction delays are common problems in civil engineering projects in Arab countries. Because of the importance of this problem, the study reviewed many studies that dealt with the topic of delay in the construction projects of their countries. The study included the delay in projects in Iraq. Jorden, Palestine, Saudi Arabia, United Arab Emirates, Qatar, Yemen, Egypt, Sudan, Algeria and Morocco. The projects included infrastructure facilities, public buildings, housing complexes, water treatment plants, sports facilities, water supply, roads. Quantitative method via a structured questionnaire was implemented in all these studies, the questionnaires were distributed to experienced project parties such as the owner, contractor, consultant and other parties. The relative importance method was used to analyze the results of the questionnaire to obtain the highest ten or five factors with the highest rank which cause delay. The results showed that the groups of contractor and owner has the highest percentage and were repeated several times compared to the rest of the groups. The top five factors causing delay of construction projects in Arab countries are, problems of cash flow and financial by owner, difficulties in financing the project by the contractor, Poor site management and supervision of the contractor, selecting the contractor who has the lowest bid and ineffective planning and scheduling by contractors

Surface infiltration plays an important role in watershed management and flood forecasting; Furthermore increase the efficiency of irrigation system and reduce water losses during the irrigation process. Experiments carried out on the Wadi AL-Ratga of the western desert, Iraq during 2019; which had been selected as a study area. The infiltration rate data were collected using double ring infiltrometer at selected ten points of the selected study area. The duration of double ring test ranged between 30 minutes to one hour based on the infiltration speed in the soil, about 6 to 12 readings were recorded for the infiltration rate at each points. The aim of this paper is to check the ability of the common infiltration models such as Horton’s, Kostikov’s and Philip’s to accurate estimated infiltration rate. These models were fitted to the observed infiltration data for estimation of models parameters and to find appropriate model for this region. Horton’s infiltration model’s parameters such as infiltration decay constants ’k’ And the value of infiltration capacity at onset of infiltration (fo) had been calculated in the ranges of 3.38-6.97 hr-1 and 21 to 47.8 cm.hr-1; respectively; for all the ten points. Philip’s infiltration model’s parameters such as the values of conductivity constant ‘A’ and sorptivity ’S’ were obtained in the ranges of 3.48-12.49 cm.hr-1 and 9.96 to 17.2 cm/hr0.5; respectively. Similarly; the Kostikov’s model’s parameters ‘a’ and ‘b’ were obtained in the range of 8.85-24.38 and 0.732-0.829; respectively. Based on results of infiltration models at the selected points the predicated parameters have realistic capability predication. The results showed that all models provided the acceptable values for Root Mean Square Error (RMSE) as1.45, 2.01, 1.88 cm.hr-1 for Horton’s, Kostikov’s and Philip’s model; respectively; The highest model efficiency (ME) as 99% for all models; and the maximum Relative Error (RE) values as 16% at all points except point 2 was calculated as 21%. This indicated that infiltration can be well-described by the Horton’s model little more than other models at the study area.

One of the most popular non- destructive techniques is ultrasonic pulse velocity (UPV) which used in assessment of concrete properties. A statistical experimental program was carried out in the present study to establish an accurate relation between the UPV and the concrete compressive strength. The program involved testing of concrete cubes cast with specified test variables. The variables are the age and density of concrete. In this research, all the samples were tested by direct ultrasonic pulse velocity (DUPV) and surface ultrasonic pulse velocity (SUPV) to measure the wave velocity in concrete and the compressive strength for each sample. An experimental study was conducted to compare between the velocities of ultrasonic waves that transmitted along the two paths; direct and indirect. A total of more than 150 cubes having dimensions of 150 mm side were prepared to conduct both non-destructive and the compressive strength (destructive testing). The results from experimental program were used as input data in a statistical program (SPSS) to predict the best equation, which can represent the relation between the UPV (direct, indirect), and compressive strength, a linear equation is proposed for this purpose. The UPV measurement and compressive strength tests were carried out at the concrete age of 7, 28, 56 days. A relationship curves were drawn between DUPV, SUPV, compressive strength and density. The mixes composition in this study consists of ordinary Portland cement, fine sand, gravel, super-plasticizer, and water. All the specimens were under (20) Cº. The statistical analysis revealed that the possibility in evaluating the properties of the concrete by using direct and indirect wave velocities