A Unique Volume Balance Approach for Verifying the Three-Dimensional Hydrodynamic Numerical Models in Surface Waterbody Simulation

The hydrodynamic numerical modeling is increasingly becoming a widely used tool for simulating the surface waterbodies including rivers, lakes, and reservoirs. A challenging step in any model development is the verification tests, especially at the early stage of development. In this study, a unique approach was developed by implementing the volume balance principle in order to verify the three-dimensional hydrodynamic models for surface waterbody simulation. A developed and verified three-dimensional hydrodynamic and water quality model, called W3, was employed by setting a case study model to be verified using the volume balance technique. The model was qualified by calculating the error in the accumulated water volume within the domain every time step. Results showed that the volume balance reached a constant error over the simulation period, indicating a robust model setup

One-dimensional Model Predictions of Carbonaceous Biological Oxygen Demand and Dissolved Oxygen for Hilla River Water Quality, Iraq

Water quality of Hilla River, located in Iraq, has been varying due to the presences different illegal point and non-points sources along the river stream. This study highlights biochemical oxygen demand (CBOD) and dissolved oxygen (DO) levels for safe usage by applying QUẠL2K model and depending on hydraulic and water quality data collected along 6.8 km passing through the main city (Hilla City) on October 2022 (low flow season) and January 2023 (high flow season). The modeling results showed that the simulated predictions are in good agreement with field data. The outputs revealed the two parameters (CBOD and DO) ranged between (1.425 - 3.075) mg/L and (9.5 - 10.65) mg/L, respectively, during low flow season and between (0.745 - 2) mg/L and (9.5 - 10.5) mg/L, respectively, during high flow season. The river CBOD levels along the river follow same pattern during the high and low flow seasons, but the DO levels behaved inversely. However, both parameters were within the acceptable limits. Thus, the river health can be considered good for basic human usage

Prediction of Indoor Environmental Quality Using a Regression Model for Educational Buildings in Hot Arid Climate : A Case Study in the Al-Najaf Technical Institute – Iraq

In hot climates, achieving a good indoor environmental quality (IEQ) in existing buildings is important especially with climate change challenges as future heat waves will increase in frequency, duration, and intensity. In educational buildings, there is much more focus on the IEQ parameters and the interactions among them that need to be in line with the continuously changing learning environment. This study assesses the IEQ parameters (represented by noise, temperature and humidity) at three selected campus areas (lecture rooms of an administrative department building (LR), main hall of a management department building (MH) and a central library building (CL)) at the Al-Najaf Technical Institute (NTI), Al-Najaf City, Iraq, for the period from May to December 2019. A statistical analysis using a multi-linear regression model was performed to determine the relationship between the selected IEQ parameters and explain the noise level behavior as a function of the temperature and relative humidity. The research indicated that the noise levels and temperature values exceeded the maximum standard limits in all buildings reflecting the displeasing sound and heating quality within the studied areas, while the readings for relative humidity within each building environment complied with standards. Moreover, for both LR and MH buildings (R2 ≥ 0.8, significance F ≤ 0.01), the noise values were satisfactorily modeled by temperature and relative humidity highlighting the interactions between temperature, humidity and noise under consistent conditions. However, the results for the CL building (R2 = 0.6, significance F = 0.1) showed no relationship between the IEQ parameters, highlighting the fact that this building is exposed to unsteady conditions (an irregular number of people using this building during the daytime) resulting in a high variation of data measurements. The current results demonstrate that detailed modeling can be helpful to predict IEQ parameters depending on other known parameters in buildings. The results of the predictive model aligned with the directly measured data. Therefore, its performance is equally effective, but with a significant reduction in cost and time consumed