پایش کیفیت آب رودخانۀ کارون بزرگ بر‌اساس شاخص irwqisc در بهار 1401

در پژوهش حاضر کیفیت آب رودخانۀ کارون بزرگ از ابتدای ورودی رودخانۀ دز تا محل اتصال به رودخانۀ اروند با استفاده از شاخص  irwqiscارزیابی شد. در این مطالعه برای محاسبۀ‌ این شاخص 12 ایستگاه نمونه‌برداری با فاصله‌های به‌نسبت مساوی از یکدیگر (بین 25 تا 35 کیلومتر) و نیز بر‌مبنای ورودی‌های اصلی به رودخانه تعیین شد. در‌ادامه، از ضریب همبستگی اسپیرمن و تحلیل خوشه‌ای سلسله‌مراتبی و رگرسیون کاربری زمین با روش ماشین‌بردار پشتیبان برای درک بیشتر روابط میان پارامترهای کیفیت آب و توزیع آنها در رودخانه استفاده شد. مقدار‌های irwqisc محاسبه‌شده بین 30.65 و 48.98 در منطقۀ مطالعه‌شده متغیر بود. نتایج نشان داد که به‌جزء دو ایستگاه 1 (کشت و صنعت نیشکر دهخدا) و 4 (ورودی شهر اهواز) با وضعیت متوسط (به‌ترتیب 48.98 و46.32) سایر ایستگاه‌ها در وضعیت به‌نسبت بد قرار دارد. همچنین، نتایج نشان داد که مقدار‌های bod و هدایت الکتریکی در تمامی ایستگاه‌ها از استانداردهای کیفیت آب شرب ایران فراتر رفته ‌است. مقدار‌های فسفات (0.006 تا 0.021 mg/l) و آمونیوم (0.4 تا 2.08 mg/l) نیز در ایستگاه‌های پایین‌دست افزایش چشمگیری داشته است. تحلیل همبستگی اسپیرمن نشان‌دهندۀ رابطۀ قوی میان هدایت الکتریکی و سختی کل (0.81) بود. خوشه‌بندی سلسله‌مراتبی ایستگاه‌ها نشان داد که ایستگاه‌های 10،9 و 12 بیشترین آلودگی را دارد که ناشی از ورود آلاینده‌های کشاورزی، صنعتی و شهری است. تحلیل رگرسیون کاربری زمین (0.78 r2= ) نشان داد که الگوهای فضایی کیفیت آب را می‌توان پیش‌بینی کرد. این نتایج بر لزوم مدیریت آلاینده‌ها و پایش مستمر برای بهبود کیفیت آب رودخانه تاکید دارد.

monitoring the water quality of the karun bozorg river based on the irwqisc index in the spring of 2022

abstractthis study assessed the water quality of the karun bozorg (greater) river, from the junction of the dez river to the junction with the arvand river, using the irwqisc index. twelve sampling stations were established at relatively equal distances (between 25 and 35 km) based on the main access points to the river. to analyze the relationships between water quality parameters and their distribution, we employed spearman’s correlation coefficient, hierarchical cluster analysis, and land use regression using the support vector machine method. the calculated irwqisc values ranged from 30.65 to 48.98 within the study area. the results indicated that, with the exception of two stations (1: dehkhoda sugarcane cultivation and industry and 4: ahvaz city entrance) that exhibited average conditions (48.98 and 46.32, respectively), the remaining stations were in relatively poor conditions. furthermore, bod and electrical conductivity levels at all stations exceeded iran’s drinking water quality standards. phosphate concentrations ranged from 0.006 to 0.021 mg/l, while ammonium levels varied from 0.4 to 2.08 mg/l, with significant increases observed at downstream stations. spearman’s correlation analysis revealed a strong relationship between electrical conductivity and total hardness (0.81). the hierarchical clustering of the stations indicated that stations 9 to 12 experienced the highest pollution levels, primarily due to the influx of agricultural, industrial, and urban pollutants. the land use regression analysis demonstrated an r² value of 0.78, suggesting that spatial patterns of water quality could be effectively predicted. these findings underscored the necessity for improved pollutant management and continuous monitoring to enhance the river’s water quality. keywords: water resource, water quality classification, cluster analysis, physicochemical parameters, land use regression. introductionwater bodies, particularly rivers, are vital for the sustainability and development of human societies. therefore, maintaining water quality within permissible limits is essential, depending on the characteristics of surface water and its intended use. previous studies on the water quality of the karun river have typically been limited in scope, focusing on a small number of sampling stations primarily located around major cities like ahvaz and khorramshahr. as a result, they fail to capture the changes occurring along the entire length of the karun bozorg (greater) river. this river, which extends from the junction of the dez and karun rivers to the junction with the arvand river, is crucial for supplying water to cities, villages, large industries, fisheries, and agricultural activities. given the fluctuations in water volume over the past few years, this study aimed to achieve the following objectives: (1) to map and display the current status and spatial variations of water quality parameters along the karun bozorg river, (2) to investigate the relationships between these water quality parameters, and (3) to cluster sampling stations based on their water quality. materials & methodsin this study, the water quality index of the karun bozorg river was calculated by establishing 12 sampling stations at relatively equal distances from one another based on the main access points to the river—from the dez river inlet to the outlet at the arvand river. sampling was conducted on may 13, 2022, during which 11 parameters were measured: bod5, cod, electrical conductivity (ec), dissolved oxygen percentage (do%), turbidity, total water hardness (twh), phosphate, nitrate, ammonium, temperature, and ph. to analyze the relationships among the measured parameters, spearman’s correlation coefficient was employed to group them based on their degree of similarity. hierarchical cluster analysis was then utilized to categorize the sampling stations. additionally, to visualize the spatial distribution of water quality in the karun river, land use regression was conducted using the support vector machine method in r software. for this analysis, bands 1 to 7 of sentinel 2 satellite images, which were captured from the study area at 2-day intervals, were utilized. given the limited number of sampling stations, the data collected from all stations were used for modeling and validation. the accuracy of the constructed model was assessed using r² and rmse statistics. research findingsthe assessment of water quality in the karun bozorg river revealed significant insights based on the irwqisc index, with calculated values ranging from 30.65 to 48.98 across 12 sampling stations. notably, only two stations (1: dehkhoda sugarcane cultivation and industry and 4: ahvaz city entrance) demonstrated an average status (48.98 and 46.32, respectively), while the remaining stations were classified as being in relatively poor conditions. key findings included:bod and ec: all sampling stations exhibited bod and ec levels that exceeded iran’s drinking water quality standards, indicating serious concerns regarding water safety.nutrient levels: phosphate concentrations ranged from 0.006 to 0.021 mg/l and ammonium levels ranged from 0.4 to 2.08 mg/l with significant increases observed at downstream stations.correlation analysis: spearman’s correlation coefficient revealed a strong positive relationship between ec and twh (0.81), as well as between ammonium and ec (0.87). this suggested that as conductivity increased, so did hardness and ammonium levels.cluster analysis: hierarchical clustering categorized the sampling stations, revealing that stations 9 to 12 had the highest pollution levels primarily attributed to urban, agricultural, and industrial runoff.land use regression: the land use regression analysis, with an r² value of 0.78, showed that the spatial patterns of water quality could be effectively predicted, highlighting the influence of land use on water quality dynamics.the results underscored the urgent need for improved pollutant management and continuous monitoring to enhance the water quality of the karun bozorg river. the integration of spatial distribution maps aids decision-makers in visualizing and addressing the deteriorating conditions of the river’s water quality, emphasizing the necessity for critical conservation measures and better agricultural practices. discussion of results & conclusionthe calculated water quality index (wqi) results indicated a decreasing trend from station 1 to station 12, with wqi values ranging from 30.65 at station 12 to 48.98 at station 1. the findings revealed that all stations were in relatively poor conditions with the exception of two stations (1 and 4), which exhibited mediocre water quality. notably, fecal coliform and phosphate parameters had the highest average effective weights compared to other factors. this situation was primarily attributed to the inflow of urban, rural, and hospital sewage, along with the discharge from extensive industrial activities along the river. correlation matrix analysis showed a significant positive correlation between ammonium and ec (0.87), as well as between twh and ec (0.81). cluster analysis further revealed that stations 1 (dehkhoda sugarcane cultivation and industry) and 12 (khoramshahr) differed significantly from the other sampled stations. additionally, mapping the river’s water quality status using the support vector machine method demonstrated an accuracy of 78%, highlighting the efficacy of this approach even with a limited number of training points.the correlation results indicated that ec, ammonium, twh, and phosphate levels increased from station 1 (upstream of the dez river junction) to station 12 (khoramshahr). while phosphate concentrations remained below the standard at all stations, other parameters exceeded acceptable limits at several locations. the tidal phenomenon might also exacerbate sudden spikes in ec, particularly at station 12.due to the adverse effects of human pollutants, the water quality of the karun bozorg river was deteriorating. consequently, it is imperative for responsible managers and decision-makers to implement critical conservation measures, such as improved agricultural practices, in conjunction with planned river usage. spatial distribution maps can enhance the effectiveness of this information, enabling decision-makers to visualize the river’s water quality conditions more clearly in the study area.