ارزیابی تطبیقی آسیب‌پذیری توده‌های کارستی شاهو و مانشت با استفاده از روش COP

فصلنامه علمی برنامه ریزی منطقه ای

دوره 13، شماره 52، اسفند 1402، صفحه 273-286   

نوع مقاله: مقاله پژوهشی

شناسه دیجیتال (DOI): 10.30495/jzpm.2023.26434.3772

نویسندگان

عبدالمجید احمدی^{* 1}؛ عبدالکریم ویسی²

¹استادیار ژئومورفولوژی، گروه جغرافیا، دانشکده ادبیات و علوم انسانی، دانشگاه رازی، کرمانشاه، ایران

²دانش آموخته دکترای ژئومورفولوژی دانشگاه تهران

تاریخ دریافت: 10 آبان 1399،  تاریخ بازنگری: 16 دی 1401،  تاریخ پذیرش: 16 دی 1401 

چکیده

 چکیده
ارزیابی آسیب پذیری امری مهم برای مدیریت پایدار منابع آب کارست و برنامه­ریزی استفاده از زمین است. آبخوان­های کارستی شاهو و مانشت نقش حیاتی در تامین آب شرب و کشاورزی جوامع محلی اطراف خود دارند. هدف این پژوهش ارزیابی آسیب­پذیری در دو منطقه کارستی با استفاده از روش COP است. از پارامترهای هیدروژئولوژیکی از جمله ضریب آلفا و حجم ذخیره دینامیکی برای مشخص کردن نوع سیستم کارستی استفاده گردید. همچنین با استفاده ضریب تعیین بمنظور تعیین فاکتورهای مهم در آسیب­پذیری این مناطق مورد بررسی قرار گرفتند. نتایج نشان می­دهد که آبخوان­های کربناته دارای سیستم جریان افشان آسیب­پذیری کمتری نسبت به آبخوان­های کارستی دارای سیستم جریان مجرایی دارند. در کارست­های مجرایی فاکتورC  همبستگی مثبت بالایی را با شاخص آسیب­پذیری دارد در حالی که در کارست­های افشان فاکتور O همبستگی بیشتری با این شاخص دارد. عامل C به علت وسعت زیاد پهنه­های کارست تکامل­یافته در منطقه شاهو نقش اصلی را در بالابودن میزان آسیب­پذیری این منطقه نسبت به توده کارستی مانشت دارا می­باشد. همچنین نتایج طبقات آسیب­پذیری نشان می­دهد که 43 درصد توده کارستی شاهو در طبقه آسیب­پذیری زیاد و متوسط واقع شده است و در مقابل مساحت این طبقات در منطقه مانشت به مراتب کمتر (27 درصد) است. وجود اشکال کارستی توسعه­یافته از جمله دولین­ها، مگاکارن­ها، غارهای عمیق و درزه و شکاف فراوان در منطقه شاهو دال بر توسعه یافتگی بیشتر این منطقه نسبت به توده کارستی مانشت می­باشد. در نهایت می­توان گفت ارزیابی آسیب­پذیری آبخوان­های کارستی چنانچه با مطالعات ژئوفیزیکی آبخوان­ها و همچنین اجرای صحیح سیاست­های برنامه­ریزی استفاده از زمین همراه باشد، نتایج قابل توجهی را ارائه می­دهند.

کلیدواژه‌ها

آسیب‌پذیری کارست؛ روش COP؛ تحلیل آماری؛ آبخوان‌های کارستی

عنوان مقاله [English]

Comparative evaluation of the vulnerability of karst masses of Shahu and Manesht by COP method

نویسندگان [English]

Abdul Majid Ahmadi¹؛ abdolkarim Veysi²

¹Assistant Professor of Geomorphology, Department of Geography, Faculty of Literature and Humanities, Razi University, Kermanshah, Iran

²Ph.D in geomorphology

چکیده [English]

Abstract
Vulnerability assessment is important for sustainable management of karst water resources and land use planning. Shahu and Manshet karst aquifers play a vital role in supplying drinking water and agriculture to local communities around them. The aim of this research is to evaluate vulnerability in two karst regions using the COP method. Hydrogeological parameters including alpha coefficient and dynamic storage volume were used to determine the type of karst system. They were also investigated using the coefficient of determination in order to determine the important factors in the vulnerability of these areas. The results show that carbonate aquifers with spray flow system are less vulnerable than karst aquifers with channel flow system. In conduit karsts, factor C has a high positive correlation with the vulnerability index, while factor O has a higher correlation with this index in oozing karsts. Due to the large extent of developed karst areas in Shaho region, factor C has the main role in the high level of vulnerability of this region compared to the Manshet karst mass.Also, the results of the vulnerability classes show that 43% of the Shahu karst mass is located in the high and medium vulnerability class, and in contrast, the area of ​​these classes in Manshet region is much less (27%). The presence of developed karst forms, such as dolines, megakarns, deep caves and many cracks and crevices in the Shahu region indicates that this region is more developed than the Manshet karst mass. Finally, it can be said that the vulnerability assessment of karst aquifers, if accompanied by geophysical studies of aquifers as well as the correct implementation of land use planning policies, will provide significant results.
 
Extended Abstract
 
Introduction
The protection of environmental resources hinges on analyzing the risks of human activities to facilitate sustainable development. Risk involves factors such as hazard, vulnerability, exposure, and mitigation. For groundwater management, aquifer vulnerability maps are crucial, as they predict risks and prevent land misuse. Karst aquifers, in particular, are highly sensitive to pollution due to rapid transport times to saturated and unsaturated zones.Karst aquifers feature unique landforms that increase pollution risk by reducing protective cover. Despite the existence of various vulnerability models, a universal model applicable to all aquifers is lacking, complicating the determination of appropriate locations for vulnerability mapping. Researchers conduct extensive statistical analyses to identify relevant vulnerability indicators for each aquifer. For instance, sensitivity analysis helps ascertain the significance of different factors in vulnerability indices.Recent studies reveal that factors weakening environmental capacity strongly correlate with vulnerability indicators in fractured carbonate aquifers, while surface current concentration factors correlate more in karst aquifers. For example, Nukum and Hützel found significant differences in vulnerability maps using mean square analysis, emphasizing the importance of classification consistency.In northern Iran's Darfak region, research using the COPKAT model identified microbial and nitrate pollution from agriculture and livestock as major vulnerability sources. Similarly, in northern Italy, the COP+K model proved effective in highly sensitive karst systems. Other studies have linked vulnerability maps to groundwater quality maps.This research employs spatial and statistical analyses to create vulnerability maps using the COP method for two Zagros karst sites in Iran, a country facing a water scarcity crisis. With 11% of Iran's surface covered by high-quality groundwater-containing carbonate rocks, protecting these resources is critical. The studied areas differ in lithology, hydrogeology, climate, and karst evolution.Over the past decade, western Iran's semi-arid regions have faced severe pressure on karst water resources from overexploitation, pollution, and droughts. These vital water sources, essential for drinking and agriculture, are increasingly polluted by human activities. Given their geological and climatic context, safeguarding these aquifers through vulnerability assessment and management strategies is imperative.
.
Methodology
This applied development research uses various data sources, including a digital elevation model (10m resolution), geological maps (1:100,000), soil maps (1:250,000), vegetation maps, weather station rainfall and temperature statistics, karst spring discharge statistics, and field data. The COP method is employed to assess site vulnerability, based on concepts integral to European karst aquifer studies (Goldscheider et al., 2004). Developed under the European Cast 620 project, the COP model evaluates aquifer vulnerability and creates risk maps by considering three factors: covering layers (O), flow concentration layer (C), and precipitation regime (P).The covering layer includes soil thickness, porosity, permeability, and lithology of the unsaturated zone. The flow concentration factor pertains to areas with different infiltration conditions, especially where water infiltrates through protective layers. Two scenarios are distinguished: non-autogenous feeding from surface runoff via karst sinkholes, and areas of spontaneous feeding. The precipitation regime factor considers the amount and intensity of precipitation, influencing water’s capacity to transport pollutants to groundwater.The vulnerability index for the COP method ranges from 0 to 15, categorized into five classes. ARC Gis software digitized maps of required factors, and calculated C, O, and P values. These were overlaid to derive final vulnerability scores. Results were compared with aquifer hydrogeological characteristics using Pearson's correlation coefficient to measure the vulnerability distribution of COP index data. Adobe Illustrator CS6 was used for diagram drawing.
 
Results and Discussion
In order to calculate the COP indices, different scenarios of this method were used. In this regard, in order to calculate the C index, scenario 2 was used (Figure 2). First, sf was calculated based on the karst geomorphological features of the area and sv index was calculated based on the slope and vegetation map of the area. The final score of this factor for Shahu region is between 0.2 and 0.9. The heights of the studied areas have evolved karst and landforms such as dolines, karn fields and smooth karst areas. The middle parts of the Shahu karst massif, which is composed of Biston limestone formations and has metamorphosed karst, on the other hand, in the Manshet karst massif, which is mainly composed of Asmari limestone formation, metamorphosed karst landforms are less observed. and the variety of karst forms is less compared to the Shaho massif. Karst morphology has not been formed in the outcrops of marl formations and Quaternary deposits. In terms of vegetation, the Shaho region has less forest cover due to its stony and rocky terrain, while there is a semi-dense forest cover in the Manshet heights. The plains of both regions are used for agriculture. Vulnerable areas in factor C are located mainly corresponding to Biston limestone formations in Shahu and Asmari in Manshet, medium slope and dense to semi-dense vegetation. Zones with medium risk in the Shahu karst mass correspond to travertine formations and fossil limestones with semi-dense vegetation and moderate to high slopes. In the Manchet karst mass, the medium vulnerability class corresponds to carbonate karst with semi-dense vegetation and high slope. Low and very low risk zones in both regions mainly correspond to Quaternary and marl deposits that are mainly under agricultural land and lack karst geomorphology and have low slopes. In the C factor map in the study areas, karst geomorphology, slope and vegetation have the greatest effect on the amount of this factor. Figure 3 shows the area of ​​C factor vulnerability classes in Shahu and Manshet karst masses.
 
Conclusion
Dependence on karst water resources in western Iran highlights the need to assess their vulnerability. This study uses the COP method to compare two karst sites with different hydrogeological, climatic, and lithological characteristics. The Shahu area is more vulnerable than Manshet due to higher karst development, reducing surface protective layers, and the presence of karst dolines that concentrate infiltration, weakening the unsaturated zone's protection.Hydrogeological indicators confirm these findings. Shahu's aquifers feature a channel system, indicating extensive karst development, while Manshet's aquifers have less development and a seam and fissure system. Shahu’s vulnerability ranges from very low to high, whereas Manshet’s ranges from very low to medium, owing to less karst development and more protective soil and sediments.Factor C (flow concentration) significantly influences high vulnerability due to extensive karst development. Factor O (covering layers) shows average vulnerability because of permeable limestone and sand-gravel formations. Factor P (precipitation) indicates that lower rainfall in Manshet reduces pollution penetration and vulnerability.The COP index in Manshet ranges from 1 to 6.34, classifying vulnerability as very low to moderate. In Shahu, vulnerability spans from very low to high, especially on southern slopes with limestone formations. GIS-based evaluation of the COP index helps identify pollution potential in karst areas, improving water resource management and land use planning. Effective management measures are crucial to balancing socio-economic development and protecting karst water resources from pollution.
 

کلیدواژه‌ها [English]

karst vulnerability, COP method, statistical analysis, karstic aquifers

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