Investigating the Potential of Groundwater Resources in Hard Formations as a Way to Manage Water Crisis (Case Study: Kalat Naderi Basin)

Document Type : مقاله پژوهشی

Authors

• Alirea Oliaei ¹
• Naser Parvian ²
• Azra Khosravi ²

¹ Tehran University

² Ferdowsi University of Mashhad

10.22067/geo.v6i4.60380

Abstract

1. Introduction
Water shortage problem has gained new complicated dimensions in a variety of countries located in arid regions of our planet including Iran which has forced the researchers to think of the solutions for this problem. Water resources in the depth of hard formations are considered as one of the most significant resources of fresh waters. On the other hand, there are a wide range of these types of formations in Iran which have attracted a huge amount of studies. Therefore, there is a necessity in studying the baseline of the springs originating from hard formations in optimum managing and exploiting underground waters. Land morphological features are commonly used for preparing underground potential existence maps. Additionally, in aquifers located in hard cracked formations, a variety of parameters including surface topography, lithology, cracking density, ground water feeding rates, land uses, slope classes, drainage patterns, atmospheric status or a group of them are used in order to map moving underground waters.
In a comprehensive GIS–RS and logistic regression model based research run in Maxent software package environment, this paper determined the maximum amount of parameters which affect spring flooding patterns in hard formations located in Kalat Naderi region through which simulated springs' distribution patterns using GIS, Maxnet software based on logistic regression and measurement in a comprehensive.
Kalat Naderi watershed is located in Khorasan Razavi province, northeast of Iran between 18'63‌°58 " to "35'79‌°60 of eastern longitude and 09'53‌°37 to "25'32°36‌ of northern latitude. Geologically, the study area is located in Bojnurd – Shirvan lithology sheets mostly in Koppedagh zone. Stratigraphical history of Kalat Naderi watershed dates back to Ordovician period in Paleozoic and quaternary eras. The studied watershed is 8565 square kilometers of area with 236 and 3069 meters from seed level in lowest and highest points, respectively.
2. Material and Methods
We used 13 parameters (fault density, distance from faults, distance from rivers, land use, profile curvature, tangent curvature, total curvature, surface ratio, mean rainfall, elevation, lithology, geographical aspects and slope degrees) in order to analytically prepare springs existence map layers and verify the maps in the field. Indeed, all of the aforementioned parameters have influence on groundwater infiltration, feeding or harvesting amount. A report of 895 springs located in the study area was gained from Iranian Water Resources Management Office (IWRMO) and regression model in Maxent software environment was used in order to verify the data. Fifity replications and 895 random points were used to model the gathered data. Also, 75% of the selected points were used as the learning points and 25% of the remaining points were utilized to plot the model. It is worth mentioning that lithology, land use and geographical maps were classified based on surface infiltration potentials and spring outcrop entered to the model.
The other maps were entered to the model in a continuous rasterized format. Jackknife resampling method was used in order to define the importance of each variable on species distribution patterns. Furthermore, ROC curve was utilized to define model's accuracy and efficiency.
3. Results and Discussion
Sensitivity analysis for morphometric factors, jackknife analysis and the logistic regression in Maxent software environment for defining the chance of existence of springs showed that precipitation related variables and lithological characteristics are the most significant factors which directly influence the chance of springs to exist so that the more their frequency are, the more the chance of springs existence. In addition, the results revealed that more porosity of the lithological sheets show a higher chance for the springs to exist. Forests and westward- northward aspects showed higher chance for the springs to exist. A negative relationship was seen among distances from faults and distances from rivers with the chance of springs existence. Also, there is a positive relationship among springs distribution patterns and elevation from see level up to 2800 meters.
Results showed a decreased chance of springs existence with increased slope degrees due to less infiltration amount. A positive relationship was seen between fault density and the chance of springs to exist.
Finally, the groundwater potential quality map was classified into four (very low, low, medium and high) classes with 33.03, 14.07, 4.01 and 48.9 percent of the total area. ROC curve showed a high accuracy of 92.3 % for the model.
Finally, it is concluded that, due to its accordance with the existing data, the model is considered as a suitable method for tracking groundwater tables especially in hard formations which result in a high efficient management for water resources.

Keywords

• Kalat Naderi
• Maxent
• ArcGIS
• Regression
• Water Resources
• Hard formations

---

References

اولیایی، علیرضا؛ 1393. بررسی هیدروژئومرفولوژی و پهنه‌بندی مناطق کارستیک در رابطه با پتانسیل منابع آب (مطالعه موردی حوزه آبخیز بجنورد). پایان نامه کارشناسی ارشد. دانشکده منابع طبیعی. دانشگاه تهران.

حسین‌زاده، سیدرضا؛ 1396. مبانی سیستم‌های اطلاعات جغرافیایی (GIS). در حال ویراستاری. چاپ اول. مشهد: انتشارات جهاد دانشگاهی مشهد.

خلاصی اهوازی، لیلا، زارع چاهوکی، محمدعلی، حسینی، سیدزین العادین؛ 1394. مدل سازی پراکنش جغرافیایی رویشگاه گونه‌های Artemisia aucheri و Artemisia sieberi بر اساس روش‌های مبتنی بر حضور (MaxEnt و ENFA). مجله تحقیقات منابع طبیعی تجدید شونده. دوره 6. شماره 1. صفحه 57 -73.

درواری، زهرا، غلام. ی، وحید، جوکار سرهنگی، عیسی؛ 1390. شبیه‌سازی آبدهی چشمه‌های کارستی با استفاده از شبکه عصبی مصنوعی (مطالعه موردی ارتفاعات البرز مرکزی). مجله پژوهش‌های جغرافیایی. شماره 77. صفحه 68-57.

رامشت، محمد حسین، عرب عامری، علیرضا؛ 1392. پهنه‌بندی حوضه آبخیز بیاضیه به منظور تغذیه مصنوعی آب‌های زیرزمینی با استفاده از روش AHP و تکنیک.ARCGIS مجله علمی پژوهشی جغرافیا و برنامه ریزی. دوره 17. شماره 45. صفحه 69-96.

صابری، عظیم، رنگزن، کاظم، مهجوری، رضا، کشاورز، محمدرضا؛ 1391. پتانسیل‌یابی منابع آب زیرزمینی با تلفیق سنجش‌ازدور و ARCGIS به روش تحلیل سلسله مراتبی (AHP) در تاقدیس کمستان استان خوزستان. مجله زمین‌شناسی کاربردی پیشرفته. شماره 6. صفحه 20-11.

محمدی فتیده، محمد؛ 1378. بررسی آبخوان‌ها و عوامل مؤثر بر پتانسیل‌های منابع آب در شرق استان گیلان مطالعه موردی: دشت‌های آبرفتی املش، رودسر و کلاچای. نشریه علوم کشاورزی ایران. شماره 1. صفحه 155 تا 171.

Adiat, K., Olayanju, G., Omosuyi, G., & Ako, B. (2009). Electromagnetic sounding electrical resistance profile and groundwater in the study of complex-case example of ODA underground city in southwestern Nigeria. Ozean Journal of Applied Sciences, 2, 333-359.

Anderson, J. R., Hardy, E., Roach. J. T., & Witmer, R. E. (2001). A land use and land cover classification system for use with remote sensor data. Washington: Geological Survey Professional United States. US Government Printing Office.

Chowdhury, A., Jha, M. K., Chowdary, V. M., & Mal, B. C. (2009). Integrated remote sensing and GIS‐based approach for assessing groundwater potential in West Medinipur district, West Bengal, India. International Journal of Remote Sensing, 30(1), 231-250.

Das, D. (1990). Satellite remote sensing in subsurface water targeting. . In 1990 ACSM-ASPRS Annual Convention, Denver, CO Proceedings of ACSM-ASPRS annual convention 99–103.

Egan, J. P. (1975). Signal detection theory and {ROC} analysis: Series in cognition and perception. New York: Academic Press.

Elith, J., Phillips, S. J., Hastie, T., Dudik, M., Chee, Y. E., & Yates, C. J. (2011). A statistical explanation of MaxEnt for ecologists. Diversity and Distributions, 17(1), 43-57.

Fetter, C. W. (1999). Contaminant hydrogeology (2nd ed.). New Jersey: Prentice Hall.

Ford, D. C., & Williams, P. W. (1989). Karst geomorphology and hydrology. London: Unwin Hyman.

Ganapuram, S., Kumar, G. V., Krishna, I. M., Kahya, E., & Demirel, M. C. (2009). Mapping of groundwater potential zones in the Musi basin using remote sensing data and GIS. Advances in Engineering Software, 40(7), 506-518.

Gholami, V. A. H. I. D., Azodi, M., & Taghvaye Salimi, E. (2008). Modeling of karst and alluvial springs discharge in the central Alborz highlands and on the Caspian southern coasts. Caspian Journal of Environmental Sciences, 6(1), 41-45.

Greenbaum, D. (1992). Structural influences on the occurrence of groundwater in SE Zimbabwe. Geological Society, London, Special Publications, 66(1), 77-85.

Guisan, A., & Zimmermann, N. E. (2000). Predictive habitat distribution models in ecology. Ecological Modelling, 135(2), 147-186.

Jansen, L. J., & Di Gregorio, A. (2002). Parametric land cover and land-use classifications as tools for environmental change detection. Agriculture, Ecosystems, and Environment, 91(1), 89-100.

Jha, M. K., Chowdhury, A., Chowdary, V. M., & Peiffer, S. (2007). Groundwater management and development by integrated remote sensing and geographic information systems: Prospects and constraints. Water Resources Management, 21(2), 427-467.

Kazemi, R., Porhemmat, J., & Kheirkhah, M. (2009). Investigation of lineaments related to ground water occurrence in a karstic area; A case study in Lar catchment, Iran. Research Journal of Environment Research, 3(3), 367-375.

Mathew, J., Jha, V. K., & Rawat, G. S. (2007). Weights of evidence modelling for landslide hazard zonation mapping in part of Bhagirathi valley, Uttarakhand. Current Science Bangalore, 92(5), 628-638.

Nandi, A., & Shakoor, A. (2010). A GIS-based landslide susceptibility evaluation using bivariate and multivariate statistical analyses. Engineering Geology, 110(1), 11-20.

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.

Ozdemir, A. (2011). Using a binary logistic regression method and GIS for evaluating and mapping the groundwater spring potential in the Sultan Mountains (Aksehir, Turkey). Journal of Hydrology, 405(1), 123-136.

Phillips, S. J., Anderson, R. P., & Schapire, R. E. (2006). Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190(3), 231-259.

Schmidt, J., Evans, I. S., & Brinkmann, J. (2003). Comparison of polynomial models for land surface curvature calculation. International Journal of Geographical Information Science, 17(8), 797-814.

Shuin, Y., Hotta, N., Suzuki, M., & Ogawa, K. I. (2012). Estimating the effects of heavy rainfall conditions on shallow landslides using a distributed landslide conceptual model. Physics and Chemistry of the Earth, Parts A/B/C, 49, 44-51.