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تعیین آلودگی کل مجاز رودخانه و تخصیص بار آلودگی براساس تغییرات فصلی، الگویی برای استانداردسازی و پایش چندپارامتره و محلی کیفیت آب
|مقاله 9، دوره 44، شماره 3، آذر 1397، صفحه 519-531 اصل مقاله (933.14 K)|
|نوع مقاله: مقاله پژوهشی|
|شناسه دیجیتال (DOI): 10.22059/jes.2019.264374.1007725|
|منوچهر حیدرپور1؛ شروین جمشیدی* 2|
|1گروه مهندسی آب، دانشکده مهندسی کشاورزی، دانشگاه صنعتی اصفهان|
|2گروه مهندسی عمران دانشگاه اصفهان|
|یک چالش برای تعیین حداکثر مجاز انتشار آلودگی رودخانه وجود نوسانات کمی و کیفی فصلی ناشی از فعالیتهای زراعی است. این پژوهش با استفاده از مدل Qual2k و شبیهسازی رودخانه تجن نشان میدهد چگونه میتوان حداکثر بار آلودگی و غلظت مجاز پارامترها، مولفه کلیدی پایش، میزان خودپالایی و تخصیص بهینه بار آلودگی را در شرایط نوسانات فصلی تعیین نمود. مطابق بررسیهای بعمل آمده و به منظور حفظ شرایط زیستی سالانه آبزیان، برآورد شد مجموعاً 4500 تن COD و 2500 تن نیتروژن کل ظرفیت نهایی بار آلودگی در دهانه رودخانه بوده و در این شرایط استاندارد غلظت مجاز پارامترهای COD، نیتروژن و فسفر کل در به ترتیب 9، 5 و 0.5 میلیگرم بر لیتر تعیین میگردد. همچنین میزان خودپالایی رودخانه در کاهش بار نیتروژن، فسفر و COD در مسیر جریان به ترتیب 6%، 9% و 50% برآورد شده که باعث میشود سهم آلودگی نقطه پایش از منابع آلاینده غیرنقطهای در مسیر رودخانه به نسبت مخزن بالادست برای انتشار ترکیبات نیتروژن و فسفر بیش از 80% و برای COD تنها 20% باشد. بنابراین برای بهسازی کیفی رودخانه توصیه میشود با مدیریت مزرعه و کاهش 45% بار آلودگی مواد مغذی از زهابهای کشاورزی، غلظت مجاز اکسیژن محلول برای حفظ آبزیان رعایت گردد.|
|تخلیه مجاز؛ حداکثر بار آلودگی؛ خودپالایی رودخانه؛ کیفیت آب؛ مدلسازی|
|عنوان مقاله [English]|
|Determining total allowable pollution and waste load allocation in rivers regarding seasonal variations, a framework for local multi-parameter water quality standardization and monitoring|
|Manouchehr Heidarpour1؛ shervin jamshidi2|
|1Department of Water Engineering, Faculty of agriculture, Isfahan University of Technology|
|2Department of Civil Engineering, University of Isfahan|
There are two approaches for water quality standardization and monitoring the pollution loads discharged into the water bodies, like rivers and estuaries. In the conventional system of command and control, the monitoring organization focuses on limiting the concentrations of physicochemical parameters of water, such as dissolved oxygen (DO), biochemical oxidation demand (BOD), chemical oxidation demand (COD), total nitrogen (TN), total phosphorous (TP), total kjeldahl nitrogen (TKN), and etc in the effluents of point-sources. This framework is easy for monitoring and penalizing, particularly for industrial and domestic polluters with continuous annual discharge flow. However, it has several shortcomings. The main weakness is the inflexibility of water quality standards regarding the environmental conditions of rivers, their self purification and vulnerability potential, and the seasonal variations of water quality and quantity of rivers. Besides, the conventional approach neglects controlling the discharges of non-point sources (NPS), including agricultural activities, as they may not be continuous or precise in location for sampling. These faults are introduced as a reason of pollution accumulation and Eutrophication in surface waters.
In the second approach termed as controlling ambient discharges, the water quality standards are determined in local scales regarding the environmental potential and conditions of rivers. Here, water quality monitoring is focused on the critical points in the river itself and limiting the pollution loads rather than concentrations in these stations. This approach in monitoring considers other issues like the self-purification potential of river, and the total pollution loads (TPL) discharged by both point and non-point sources upstream. However, there are some challenges that make this framework more complicated. 1) Finding a proper standardization and TPL in a multi-parameter framework, 2) waste load allocation (WLA) and fair sharing of penalties among polluters, and 3) uncertainties regarding the seasonal variations of emissions and the fluctuations in river water quality and quantity.
In this research, a methodology is introduced regarding the ambient discharge framework to calculate an optimal multi-parameter WLA among emission sources. This intends to determine an allowable TPL in a river with high seasonal variations and challenges in the aquatic life. For this purpose, we chose Tajan River in northern Iran as the study area. This river has 51 km length with annual average water volume of 15 million m3. It ends to the Caspian Sea where the estuary currently encounters DO deficiency in some seasons and endangers the aquatic life. This may be due to the pollutions discharged from point and non-point sources, including paddy fields, pulp and paper industry and municipal effluents of Sari city with the rural areas upstream.
In order to find a proper WLA and TPL, a simulation is carried out on Tajan River with 18 reaches by Qual2kw software with 100 times iteration for calibration. This simulation includes two steps. In the farming season (FS) of the study area, more than 5 m3/s of water is allocated for paddy fields that reduces one third of river overall flow at headwater. This lessens the remediation potential of river for diluting pollutions discharged particularly the nutrients concentrations exist in the drainage of NPS. Conversely, in non-farming seasons (NFS), DO profile and base-flow of river increases and environmental pollution limits to the point sources. Therefore, simulation is calibrated with respect to the sampling results in the first scenario of FS and later validated by other data in NFS.
Regarding the fitness function and auto-calibration based on the genetic algorithm, the simulated model with 100 iterations presented 71% accuracy. For that, the water quality data sampled from three stations between 2014 and 2015 in the upper, middle and lower lands of river are used.
Figure 1 illustrates DO deficiency of river in two periods. It is obvious that in FS, DO deficiency exceeds 2.5 mg/L (for a DO saturation of 8.5 mg/L) that endangers aquatic life in the last 15 km of river to the terminus point but this is rather normal in NFS. Besides, in FS the concentrations of nutrients like TN and TP respectively increases more than 5 and 1.5 folds in comparison with NFS. It should be noted that about 40% of TN is made of TKN in FS that shows two points. First, chemical fertilizers are the main pollution origins of NPS discharges, and second, it may devour considerable amount of DO in the nitrification process. Therefore, NPS like agricultural activities are introduced as the main reason of seasonal pollutions. In addition, both nutrients and carbonaceous compounds are highlighted as influential parameters on DO reduction. Therefore, DO is assumed as the key factor in multi-parameter WLA and decision-making. Here, it is assumed that 5 mg/L should be met as the minimum limit of DO throughout a year even in the most polluted periods FS, while 6 mg/L must be met annually in average.
The sensitivity analysis on the origins of pollutions showed that the self purification potential of river for nutrients reduction will not exceed 10%, but it easily reaches 50% for carbonaceous organic loads. This result adds up the significance of NPS pollution control in decision-making for WLA in river. Therefore, regarding the simulated pollution loads of the terminus point in FS and NFS, the annual TPL in WLA is determined in a way that DO profile responds to the assumed limits. As shown in Table 1, the maximum allowable loads of TN and COD are respectively considered 2500 tons/yr and 4500 tons/yr. TPL for other parameters like TKN, nitrate, and TP are respectively 500, 2000, and 250 tons/yr.
By these limits, the local concentrations of pollutants can be set as the standard level for better monitoring. For TN, TP and COD the recommended monitoring concentrations are 5, 0.5 and 9 mg/L, respectively. By these conditions, it is expected that DO remains on the assumed standard level as shown in Figure 2. Here, WLA is set on 45% removal of pollutions discharged by NPS. This value may reduce 34% of TN, 46% of TP and 14% of COD at the terminus point.
In this research a method in introduced with respect to the ambient-based framework for water quality monitoring to find TPL and consequently the annual average concentrations of main water quality parameters. In the case of Tajan River, it is realized that the estuary is highly sensitive to the seasonal variations of water quality and quantity. The main source of these variations is marked as the agricultural activities of paddy fields that recommended to be mainly focused for multi-parameter WLA and decision-making. For this purpose, it is also recommended that DO is selected as the key controlling index because it reflects the effects of both carbonaceous and nitrogenous compounds and is crucial for the aquatic life. Finally, with respect to the self purification potential of river, TPL and WLA are determined. This approach can be similarly used in other cases to find local standards for water quality monitoring.
|Allowable discharge, maximum pollution load, river self remediation, simulation, Water quality|
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