Up to journal
for Research & Developement
Journal of Materials Science: Materials in Electronics
Impact Factor
0/000
Available
2000 - 2020
Volumes
15
Issues
54
Articles
875
Open Access
532


Iranian Water Researches Journal
Quantitative-qualitative hydrodynamic simulation and routing of transmission of pollution in domestic rivers using a combination of WASP and HEC-RAS models


 submission: 27/02/2019 | acception: 26/01/2020 | publication: 14/09/2020

DOI 

Authors
amirali abdollahi1, hossein babazadeh2*, bahman yargholi3, lobat taghavi4

1-Science and Research Branch,Tehran،abdollahi_67@yahoo.com

2-Science and Research Branch,Tehran،h_babazadeh@srbiau.ac.ir

3-Research Organization, Training and promoting agriculture, Karaj, Iran،yar_bahman@yahoo.com

4-Science and Research Branch,Tehran،taghavi_lobat@yahoo.com



151 Downloads

Abstract

Hydrodynamic prediction and simulation of rivers’ qualitative parameters is very important for determining the rate of loading of pollutants and their manner of transmission in aquatic ecosystems, in relation to rivers’ self-purification capacity. From the beginning of human life, rivers and surface waters have always been considered essential because of the need for water for living purposes. Cities and industrial and agricultural centers, in fact entire civilizations, arose near the rivers in order to use sources of water. However, by developing industry and technology, human beings started destroying nature. Knowledge of the quality of water resources is one of the most important requirements in the planning and development of water resources and their conservation and control. Hence, in order to ensure the monitoring and management of the quality of this natural resource, some methods can be used that entail the least cost and time to attain these objectives. To develop these studies, sampling and environmental tests for water qualitative parameters were initially conducted. For performing this step, six stations were determined for monitoring in the basin of the Balikhlouchai. The parameters considered were then measured and the results were compared with existing standards. The purpose of conducting this study is to route the pollution of Balikhlochai River, establishing a relationship between the results of two quantitative and qualitative simulated hydrodynamic models (HEC-RAS and WASP) and comparing the results with statistical indices (mean absolute error, root mean square error, Relative volume error, and Nash–Sutcliffe model efficiency coefficient). Given their self-purification and self-regulation capabilities, rivers in normal situations can undertake the natural load of pollution imposed by the environment and solve them. In situations in which pollution has human origins and the load is more than the river’s carrying capacity, this will be associated with destruction, and the death of river ecosystems. The reasons for the increase in pollution load are the entry of surface runoff from the rainfall into the river, washing of various pesticides and organic fertilizers, phosphate and nitrate due to drainage of agricultural land, and the organic load entering the urban and rural. Wastewater into the river along the route is the source of food for algae and, as a result, increases the pollution burden and reduces the health of the river. Calibration and validation of the model were performed based on samples taken from six monitoring stations during 2015-2016. According to the validation results, MAE, RMSE, RE and NSE statistical indices for DO were 0.04, 7.2, 4.7 and 0.84, respectively, and 0.07, 8.2, 5.2 and 0.81 for the river flow rate, respectively, representing the optimal and reliable results of the output of simulation models. The results obtained from statistical indices showed that the simulation of the research variables was well performed, the simulation results were reliable and both models have good performance in predicting water quality. Due to the increasing population and growth of various kinds of pollution, the qualitative conditions of the rivers and aquifers become worse in the field of surface water. According to the results of the models’ output, the river discharge along the route ranged from 1.2 to 0.3 m³/s and DO ranged from 7.5 to 3.5 mg/l, indicating a severe reduction in the river flow rate and DO. Comparing these results gives a more accurate analysis of the pollution process in the Balkhlohai River; as the river's downstream is lowered, the loading rate of the pollutants is increased. So, the river is naturally unable to reduce pollutants and return the river to its normal state. It happens because both velocity of the water flow and the depth of the river are reduced. Therefore the amount of water mixing in the river decreases, as well as the amount of dissolved oxygen in the river due to reduced mixing. So, the pollution load and pollution of the river increases. Studying the pollution process in Balikhlochai River indicated that river pollution was due to the entry of urban wastewater and runoff from agricultural drainage-water into the basin, as well as the severe reduction in river self-purification capacity and Eutrophication phenomenon. The decade's prediction shows that if the measures needed to manage the current status of river water quality are not met, the river's health is compromised and should be stepped up to restore the river. The results indicate that the river downstream from the point of view of quality management should be prioritized and the study results can be used in determining the strategies for coping with pollution and promoting management in the Basin of Balikhlochai River.




Keywords

hydrodynamic simulation  prediction  routing of pollution  domestic rivers 



Download fulltext PDF


Open Access

Download

Citation
عبداللهی ا. ع. بابازاده ح. یارقلی ب. و تقوی ل. 1399. شبیه‌سازی و روند‌یابی هیدرودینامیکی کمی-کیفی انتقال آلودگی در رودخانة شهری با استفاده از تلفیق مدل WASP و HEC-RAS. مجله پژوهش آب ایران. 38: 21-31.




References

Barnwell T. O. Brown L. C. and Whittemore R. C. 2004. Importance of Field Data in Stream Water Quality Modeling Using QUAL2E-UNCAS. Journal of Environmental Engineering. 130(6): 643-647

Bennett N. D. Croke B. F. Guariso G. Guillaume J. H. Hamilton S. H. Jakeman A. J. and Pierce S. A. 2013. Characterising performance of environmental models. Environ. Model. Software. 40: 1-20

Brunner GW. 2010. HEC-RAS River Analysis System. Hydraulic Reference Manual. Version 4.1. Davis, CA: US Army Corps of Engineers, Institute for Water Resources, Hydrologic Engineering Center. 790 p

Cecile A. Keren J. C. and Sean R. 2010. Inundation mapping using hydraulic model’s case studies of steady and unsteady models on the Tar river, NC’, Advanced Hydrologic Prediction Service (AHPS) web pages published by North Carolina University. pp: 1-10

Cerucci M. Jaligama G. K. and Ambrose R. B. 2010. Comparison of the monod and droop methods for dynamic water quality simulations. Journal of Environmental Engineering. 136(10): 1009-1019

Chen Q. Wu W. Blanckaert K. Ma. J. and Huang G. 2012. Optimization of water quality monitoring network in a large river by combining measurements, a numerical model and matter-element analyses. Journal of  Environment Management. 110: 116-124

Cho J. H. 2010. Water quality modeling of a lake considering rainfall-runoff pollution loads and water quality improvement by diffuse pollution control. Proceedings of the 5th Conference on Water, Climate and Environment, BALWOIS, Ohrid, Republic of Macedonia, 25-29 may. 10 p

Chuersuwan N. Nimrat S. and Chuersuwan S. 2013. Empowering Water Quality Management in Lamtakhong River Basin. Thailand Using WASP Model. Research Journal of Applied Sciences, Engineering and Technology. 6(23): 4485-4491

.Fan C. Ko C. H. and Wang W. S. 2009. An innovative modeling approach using Qual2K and HEC-RAS integration to assess the impact of tidal effect on River Water quality simulation. J Environ Manage. 90(5): 1824-1832

Gibson S. Pak J. and Fleming M. 2010. Modeling watershed and riverine sediment processes with HEC-HMS and HEC-RAS. Paper presented at: Watershed Management Conference, Davis, CA

Goodell CR. 2005. Dam breaks modeling for tandem reservoirs: a case study using HEC-RAS and HEC-HMS. Paper presented at: Impacts of Global Climate Change, World Water and Environmental Resources Congress, May 15-19, Anchorage, Alaska, United States. 11 p

Guidelines for the Determination of Hydraulic Roughness Coefficient of Rivers. 2015. Regulation 688. Ministry of Energy, Office of Technical, Engineering, Social and Environmental Standards for Water and Wastewater. http://seso.moe.gov.ir

Haghiabi A. H. Nasrolahi A. H. and Parsaie A. 2018. Water quality prediction using machine learning methods, Water Quality Research Journal. 53(1): 3-13

Heng L. K. Hsiao T. C. Evett S. Howell T. and Steduto P. 2009. Validation the FAO aquacrop model for irrigated and water deficient field maize. Agronomy Journal. 101: 488-498

Husain A. 2017. Flood modelling by using HEC-RAS. International Journal of Engineering Trends and Technology (IJETT) , 50(1),1-7

Husain A. Sharif M. and Ahmad ML. 2018. Simulation of Floods in Delhi Segment of River Yamuna Using HEC-RAS. American Journal of Water Resources. 6(4): 162-168

Johnson J. L. Wolfe C. and Waidler D. 2012. An economic assessment of water quality improvement BMPs for the Eagle Mountain Lake Watershed. Proceedings of the 2012 Agricultural and Applied Economics Association Meetings. Seattle, Washington, USA, 13-16 p

Khattak M. SAnwar F. Saeed T. U. Sharif M. Sheraz Kh. and Ahmed A. 2016. Floodplain Mapping Using HEC-RAS and ArcGIS: A Case Study of Kabul River. Arabian Journal for Science and Engineering (Springer). 41(4): 1375-1390

Kowalczuk Z. Świergal M. and Wroblewski M. 2018. River Flow Simulation Based on the HEC-RAS System., Advanced Solutions in Diagnostics and Fault Tolerant Control, Advances in Intelligent Systems and Computing 635, Springer International Publishing AG 2018., DOI 10.1007/978-3-319-64474-5_21

Li H. Zhang Y. and Zhou X. 2015. Predicting surface runoff from catchment to large region. Advances in Meteorology. Article ID 720967. 13 p

Liu H. F. Genard M. Guichard S. and Bertin N. 2007. Model-assisted analysis of tomato fruit growth in relation to carbon and water fluxes. Journal of Experimental Botnay. 58(13): 3567-3580

Narasimhan B. Srinivasan R. Bednatz S. T. Ernst M. R. and Allen P. M. 2010. A comprehensive modeling approach for reservoir water quality assessment and management due to point and nonpoint source pollution. American Society of Agricultural and Biological Engineers. 53(5): 1605-1617

Parsa AS. Qalo N. Heydari M. and Mohd Amin NF. 2013. Introduction to flood­plain zoning simulation models through dimensional approach. International Journal of Advance Civil Structure Environment Engineering. 1(1): 20-23

Peng S. Fu G. Y. and Zhao X. 2010. Integration of USEPA WASP model in a GIS platform. Journal of Zhejiang University-SCIENCE A. 11(12): 1015-1024

Robert B. Ambrose Jr. Tim A. Wool and Thomas O. Barnwell Jr. 2009. Development of Water Quality Modeling in the United States. Environ. Eng. Res. 2009 December, 14(4): 200-210

Sergey S. Khrapov Andrey V. and Pisarev Ivan A. 2013. The Numerical Simulation of Shallow Water: Estimation of the Roughness Coefficient on the Flood Stage., Advances in Mechanical Engineering., Article ID 787016. 11 p

Wang J. Zhang Zh. Greimann B. and Huang B. 2018. Application and evaluation of the HEC-RAS – riparian vegetation simulation module to the Sacramento River., Ecological Modelling, Elsevier. 368: 158-168

Wool T. Ambrose R. Martin L. and Comer E. 2003. Water Quality Analysis Simulation Program (WASP) 6.0, Draft: User’s Manual. U.S. Environmental Protection Agency, Washington D.C., USA. 156 p


جعفری سلیم ب. نبی بیدهندی غ. سالمی آ. طاهریون م. و اردستانی م. 1388. بررسی کیفیت آب رودخانه قشلاق با استفاده از شاخص‌های کیفی آب، نشریه علوم محیطی. 6(4): 19-28.

گلین شریف دینی ن. امیرنژاد ر. و صائب ک. 1393. پهنه‌بندی کیفی آب رودخانه دوهزار تنکابن بر اساس شاخص NSFWQI با استفاده از سامانه اطلاعات جغرافیای GIS)(. مجله دانشگاه علوم پزشکی مازندران. 24(119): 29-39.





Announcements  

  •  No announces available
Indexes  

 


ISC
magiran
Civilica
SID
nali