مدل سازی میزان تغذیه آب زیرزمینی آبخوان کارستی دالاهو با استفاده از مدل KARSTLOP

نوع مقاله: مقاله پژوهشی

نویسندگان

1 استادیار بخش تحقیقات حفاظت - خاک و آبخیزداری، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی خراسان رضوی، سازمان تحقیقات، آموزش و ترویج کشاورزی، مشهد

2 دکتری ژئومورفولوژی دانشگاه اصفهان

10.22131/sepehr.2020.38618

چکیده

تغذیه سفرههای کارستی ازنظر مقدار و توزیع مکانی بستگی به عوامل مختلف طبیعی مانند آبوهوا، توپوگرافی، پوشش گیاهی، خاک و زمینشناسی دارد. انتخاب یک روش مناسب برای ارزیابی میزان آب نفوذ یافته در مناطق کارستی اغلب موضوع مورد اختلاف محققان است. روشهای چند پارامتری با استفاده از ابزارهای سیستم اطلاعات جغرافیایی بهتازگی با موفقیت درحالتوسعه است. هدف این تحقیق، مدلسازی مناطق تغذیه آبخوان دالاهو در زاگرس چینخورده با استفاده از مدل KARSTLOP هست. بهمنظور تهیه نقشه پهنهبندی توسعه کارست سطحی، از مدل منطق فازی و عملگر گاما استفاده شد. و درنهایت با استفاده از مدل KARSTLOP نقشه مناطق تغذیه آبخوان کارستی دالاهو به دست آمد. با توجه به نقشه پهنهبندی توسعه کارست سطحی منطقه مورد مطالعه شامل چهار کلاس فاقد کارست، کارست با توسعه کم، کارست با توسعه متوسط و کارست توسعهیافته است. نتایج پهنهبندی تغذیه نشان میدهدکه میزان شارژ سالانه بهدستآمده برای آبخوان کارستی دالاهو بین 37 تا 81 درصد است. نتایج بهدستآمده تأیید میکنند که روش KARSTLOP میتواند یک ابزار مفید برای تحقیقات سفرههای آب کارستیک در اراضی کارستی باشد. همچنین نتایج بیانگر نقش اصلی ژئومورفولوژی کارست کوه دالاهو در توزیع مکانی مقادیر شارژ در آبخوان است. و نتایج پهنهبندی تغذیه با نتایج حاصل از پهنهبندی توسعه کارست سطحی، کاملاً منطبق است.

کلیدواژه‌ها


عنوان مقاله [English]

Modeling groundwater recharge rate in Dalahoo karst aquifer using KARSTLOP model

نویسندگان [English]

  • Ali Dastranj 1
  • Maryam Jafari Aghdam 2
1 Soil conservation and watershed management department, agricultural and natural resources research Center of Khorasan Razavi, Mashhhad. Iran
2 PhD in Geomorphology, University of Isfahan
چکیده [English]

Extended Abstract
Introduction
After United States of America, China and Turkey,Iran has the highest karst percentage, and karst formations cover more than 11%of our country. The volume of water stored in these areas can supply the water demand of many cities and villages. Characteristics of karst aquifers’feeding area determine the type of feed, flow andvulnerability of the aquifer tocontamination.Therefore, identification of feeding areas in karst aquifers plays a key role in understanding their hydrodynamic and hydrochemical characteristics, along with management and optimal scientific exploitation of them. Given the critical impact of karst water resources on human life and limited number of researcheson karst, any fundamental, applied, and developmental research performed with the aim of modelingkarst landforms and investigating the potential of karst water resources in these areas seems necessary. In order to assess andevaluatethe potential of karst water resources from a qualitativeand quantitative perspective, understand pollution, and vulnerability and also assessrisks facing aquifers,the present study models feeding areas of Dalahoowasaquifer using KARSTLOP model.
 Methodology
The present applied-developmental study is based on library research, field observation, and evaluation methods and seeks to prepare the map of karst water resourcesfeeding Dalahookarst aquifer. Fuzzy logic and gamma operator model were used to produce a zoning map for surface karst development. And finally, a map was produced for the feeding areas of Dalahoowaskarst aquifer using KARSTLOP model.
 Result
Using Natural Breaks method, the zoning map of Dalahoo’ssurface karst development divides the study area are into four classes: areas without karst formations (0-0.224), karst formations with low development (0.224-0.558), karst formations with moderate development (0.588-0.777) and developed karstformations(0.777-0.982).The final map of Dalahoo’sfeeding areas indicates that Bistoon karst aquifer has anannual charge rate of 37 to 81 percent.
 Discussion and conclusion
Systematic study of karst aquifer’s water tables is very important, especially for drinking and agricultural purposes. The final mapof feeding areas, as well as the layers obtained from KARSTLOP method can be used as inputs for modeling groundwater. They may also be used to address practical issues of karst in relation to water management, including water supply, spatial distribution of watersheds, transboundary management of water, and initial assessment of groundwater vulnerability. Results obtained from zoning of feeding areas are consistent with the results obtained from zoning of surface karst development. High feeding values as well as spatial distribution of the aquifer’s feeding zones indicate that the aquifer has a high potential to store groundwater resources.This potentialityshould be properly managed to makeharvestingand protecting groundwaterpossible.

کلیدواژه‌ها [English]

  • Multi-parameter methods
  • Modeling
  • Fuzzy logic
  • Surface karst
  • KARSTLOP
1. انتظاری، یمانی، جعفری‌اقدم؛ مژگان، مجتبی، مریم (1394). مدل‌سازی مکانی مناطق تغذیه آبخوان‌های کارستی با استفاده از مدل KARSTLOP (مطالعه موردی: آبخوان کارستی خورین). پژوهش‌های ژئومورفولوژی کمی. سال چهارم، شماره دو، ص 137-121.
2. حمیدی‌زاده، کلانتری، کشاورزی، چرچی؛ فروغ، نصرالله، محمدرضا، عباس (1391). بررسی هیدروژئولوژیکی و زمین ساختاری چشمه دره‌اناری در منطقه کارستی شیرین بهار استان خوزستان. مجله تحقیقات منابع آب ایران. سال هشتم، شماره یک.
3. مؤمنی، منصور (1389)، مباحث نوین تحقیق در عملیات، انتشارات دانشگاه تهران.
4.   Adiat, K. A. N., Nawawi, M. N. M., & Abdullah, K. (2012). Assessing the accuracy of GIS-based elementary multi criteria decision analysis as a spatial prediction tool–A case of predicting potential zones of sustainable groundwater resources. Journal of Hydrology, 440, 75-89.
5.   Afrasiabian, A. (2007). The importance of protection and management of Karst water as drinking water resources in Iran. Environmental geology, 52(4), 673-677.
6.   Agarwal, E., Agarwal, R., Garg, R. D., & Garg, P. K. (2013). Delineation of groundwater potential zone: An AHP/ANP approach. Journal of Earth System Science, 122(3), 887-898.
7.   Amin, M. M., Veith, T. L., Collick, A. S., Karsten, H. D., & Buda, A. R. (2017). Simulating hydrological and nonpoint source pollution processes in a karst watershed: A variable source area hydrology model evaluation. Agricultural Water Management, 180, 212-223.
8.   Andreo, B., Vías, J., Durán, J. J., Jiménez, P., López-Geta, J. A., & Carrasco, F. (2008). Methodology for groundwater recharge assessment in carbonate aquifers: application to pilot sites in southern Spain. Hydrogeology Journal, 16(5), 911-925.
9.   Awawdeh, M., Obeidat, M., Al-Mohammad, M., Al-Qudah, K., & Jaradat, R. (2014). Integrated GIS and remote sensing for mapping groundwater potentiality in the Tulul al Ashaqif, Northeast Jordan. Arabian Journal of Geosciences, 7(6), 2377-2392.
10. BAGHERI, S., DAVOODI, M., YARAHMADI, D., JAFARI-AGHDAM, M., & Soltani, M. (2013). Assessing and mapping the vulnerability of karstic aquifer using gis and cop model.
11. Bakalowicz, M. (2005). Karst groundwater: a challenge for new resources. Hydrogeology journal, 13(1), 148-160.
12. Carter B, G., (1996). Geomorphic information system for geoscientists (modeling for GIS) peradmen publication USA. Chapter 9.
13. Chenini, I., Mammou, A. B., & El May, M. (2010). Groundwater recharge zone mapping using GIS-based multi-criteria analysis: a case study in Central Tunisia (Maknassy Basin). Water Resources Management, 24(5), 921-939.
14. Elbeih, S. F. (2015). An overview of integrated remote sensing and GIS for groundwater mapping in Egypt. Ain Shams Engineering Journal, 6(1), 1-15.
15. Farfán, H., Corvea, J. L., & De Bustamante, I. (2010). Sensitivity analysis of APLIS method to compute spatial variability of karst aquifers recharge at the National Park of Viñales (Cuba). In Advances in Research in Karst Media (pp. 19-24). Springer Berlin Heidelberg.
16. Ford, D., & Williams, P. D., (2013). Karst hydrogeology and geomorphology. John Wiley & Sons.
17. Geyer T, Birk S, Liedl R, Sauter M (2008) Quantification of temporal distribution of recharge in karst systems from spring hydrographs. J Hydrol 348:452–463.
18. Healy RW (2010) Estimating groundwater recharge. Cambridge University Press, Cambridge.
19. Konkul, J., Rojborwornwittaya, W., & Chotpantarat, S. (2014). Hydrogeologic characteristics and groundwater potentiality mapping using potential surface analysis in the Huay Sai area, Phetchaburi province, Thailand. Geosciences Journal, 18(1), 89-103.
20. Kumar, A., & Pandey, A. C. (2016). Geoinformatics based groundwater potential assessment in hard rock terrain of Ranchi urban environment, Jharkhand state (India) using MCDM–AHP techniques. Groundwater for Sustainable Development, 2, 27-41.
21. Martinez-Santos P, Andreu JM (2010) Lumped and distributed approaches to model natural recharge in semiarid karst aquifers. J Hydrol 388:389–398.
22. Moghaddam, D. D., Rezaei, M., Pourghasemi, H. R., Pourtaghie, Z. S., & Pradhan, B. (2015). Groundwater spring potential mapping using bivariate statistical model and GIS in the Taleghan Watershed, Iran. Arabian Journal of Geosciences, 8(2), 913-929.
23. Moradi, S., Kalantari, N., & Charchi, A. (2016). Karstification Potential Mapping in Northeast of Khuzestan Province, Iran, using Fuzzy Logic and Analytical Hierarchy Process (AHP) techniques. Geopersia, 6(2), 265-282.
24. Nagarajan, M., & Singh, S. (2009). Assessment of groundwater potential zones using GIS technique. Journal of the Indian Society of Remote Sensing, 37(1), 69-77.
25. Oh, H. J., Kim, Y. S., Choi, J. K., Park, E., & Lee, S. (2011). GIS mapping of regional probabilistic groundwater potential in the area of Pohang City, Korea. Journal of Hydrology, 399(3), 158-172.
26. Oikonomidis, D., Dimogianni, S., Kazakis, N., & Voudouris, K. (2015). A GIS/Remote Sensing-based methodology for groundwater potentiality assessment in Tirnavos area, Greece. Journal of Hydrology, 525, 197-208.
27. Preeja, K. R., Joseph, S., Thomas, J., & Vijith, H. (2011). Identification of groundwater potential zones of a tropical river basin (Kerala, India) using remote sensing and GIS techniques. Journal of the Indian Society of Remote Sensing, 39(1), 83-94.
28. Radulovic, M. M. (2009). KARSTLOP method–Multiparameter analysis of karstic terrains potential for effective infiltration. Fac. Min. Geol., University of Belgrade, Belgrade.
29. Radulovic, M., Stevanovic, Z., & Radulovic, M. (2012). A new approach in assessing recharge of highly karstified terrains–Montenegro case studies. Environmental Earth Sciences, 65(8), 2221-2230.
30. Raeisi, E. (2008). Ground-water storage calculation in karst aquifers with alluvium or no-flow boundaries. Journal of cave and Karst studies, 70(1), 62-70.
31. Rahmati, O., Pourghasemi, H. R., & Melesse, A. M. (2016). Application of GIS-based data driven random forest and maximum entropy models for groundwater potential mapping: a case study at Mehran Region, Iran. Catena, 137, 360-372.
32. Rahmati, O., Samani, A. N., Mahmoodi, N., & Mahdavi, M. (2015). Assessment of the contribution of N-fertilizers to nitrate pollution of groundwater in western Iran (Case Study: Ghorveh–Dehgelan Aquifer). Water Quality, Exposure and Health, 7(2), 143-151.
33. Russo, T. A., Fisher, A. T., & Lockwood, B. S. (2015). Assessment of managed aquifer recharge site suitability using a GIS and modeling. Groundwater, 53(3), 389-400.
34. Sangani, K. Y., Mohammadzadeh, H., & Akbari, M. An Evaluation of Groundwater Potential Zones Using Combined Fuzzy-AHP Method and GIS/RS Technologies: A Case Study of NE Hezarmasjed Mountain, Khorasan Razavi Province.
35. Senanayake, I. P., Dissanayake, D. M. D. O. K., Mayadunna, B. B., & Weerasekera, W. L. (2016). An approach to delineate groundwater recharge potential sites in Ambalantota, Sri Lanka using GIS techniques. Geoscience Frontiers, 7(1), 115-124.
36. Stokes, T. R. (1999). Reconnaissance karst potential mapping for British Columbia. BC Min. For. Res. Br., Victoria, BC. www. for. gov. bc. ca/hfp/values/features/karst/index. ht m (Accessed May 2010).
37. Van Alphen, B. J., & Stoorvogel, J. J., (2000). A functional approach to soil characterization in support of precision agriculture. Soil Science Society of America Journal, 64(5), 1706-1713.
38. Venkateswaran, S., & Ayyandurai, R. (2015). Groundwater potential zoning in upper Gadilam river basin Tamil Nadu. Aquatic Procedia, 4, 1275-1282.