پیوندهای مفید
اخبار و اعلانات
آمار
| تعداد نشریات | 161 |
| تعداد شمارهها | 6,532 |
| تعداد مقالات | 70,501 |
| تعداد مشاهده مقاله | 124,095,244 |
| تعداد دریافت فایل اصل مقاله | 97,201,451 |
Evaluation of Groundwater Vulnerability Using Data Mining Technique in Hashtgerd Plain | ||
| فیزیک زمین و فضا | ||
| مقاله 4، دوره 42، شماره 4، دی 1395، صفحه 35-41 اصل مقاله (476.36 K) | ||
| شناسه دیجیتال (DOI): 10.22059/jesphys.2016.57743 | ||
| نویسندگان | ||
| Saman Javadi* 1؛ S. Mehdy Hashemy2 | ||
| 1Department of Water Engineering, College of Abouraihan, University of Tehran, | ||
| 2Department of Water Engineering, College of Abouraihan, University of Tehran, Tehran, Iran | ||
| چکیده | ||
| Groundwater vulnerability assessment would be one of the effective informative methods to provide a basis for determining source of pollution. Vulnerability maps are employed as an important solution in order to handle entrance of pollution into the aquifers. A common way to develop groundwater vulnerability map is DRASTIC. Meanwhile, application of the method is not easy for any aquifer due to choosing appropriate constant values of weights and ranks. Clustering technique would be an influential method for regionalization of groundwater flow zone to facilitate vulnerability assessment of groundwater aquifers. In this study, a new approach using k-means clustering is applied to make vulnerability maps. Four features of depth to groundwater, hydraulic conductivity, recharge value and vadose zone were considered at the same time as features of clustering. Five regions are recognized out of the Hashtgerd plain. Each zone corresponds to a different level of vulnerability. The results show that clustering provides a realistic vulnerability map so that, Pearson’s correlation coefficients between nitrate concentrations and clustering vulnerability is 72%. | ||
| کلیدواژهها | ||
| Groundwater؛ Vulnerability assessment؛ Clustering؛ Data Mining | ||
| مراجع | ||
|
Aller, L., Bennet, T., Lehr, J. H., Petty, R. J. and Hackett, G., 1987, Drastic: a standardized system for evaluating groundwater pollution potential using hydrogeological settings, US Environmental Protection Agency.
Baalousha, H., 2006, Vulnerability assessment for the Gaza Strip, Palestine using Drastic, Environmental Geology, 50, 405-414.
Batelaan, O., De Smedt F. and Triest L., 2003, Regional ground-water discharge: phreatophyte mapping, groundwater modelling and impact analysis of land-use change, J. Hydrol., 275 (1-2) 86-108.
Davies, D. L. and Bouldin, D. W., 1979, A cluster separation measure, IEEE transaction on pattern analysis and machine intelligence, 1(4), 224-227.
Feil, B., 2006, Fuzzy clustering in process of data mining, PHD thesis, Department of Process Engineering, University of Veszprem Hungry.
Frapporti, G., Vriend, P. and Van Gaans, P. F. M., 1993, Hydro-geochemistry of the shallow Dutch groundwater: interpretation of the national groundwater quality monitoring network, Water Resources Research, 29(9), 2993-3004.
Han, J. and Kamber, M., 2006, Data mining, concepts and techniques, San Francisco, U.S.A: Morgan Kaufman Publishers.
Javadi, S., Kavehkar, N., Mohammadi, K., Khodadi, A. and Kahawita, K. 2011a, Calibration Drastic using field measurements, sensitivity analysis and statistical method to assess groundwater vulnerability, Water International, 36, 719-732.
Javadi, S., Kavehkar, N., Mousavizadeh, M. H. and Mohammadi, K., 2011b, Modification of Drastic model to map groundwater vulnerability to pollution using nitrate measurements in agricultural areas, Journal of Agricultural Science Technology, 13, 239-249.
Kim, D. W., Lee, K. H. and Lee, D., 2004, On cluster validity index for estimation of the optimal number of fuzzy clusters. Journal of Pattern Recognition Society, 37(10), 2009-2025.
Koskela J., 2004, Pattern recognition in water resources management, A literature review and an application to long-term inflow forecasting, Master of Science thesis, Department of Civil and Environmental Engineering, Helsinki University of Technology.
Margat, J., 1968, Vulnerabilite des mappes d’eau souterraine a la pollution, Orleans: BRGM Publication.
Neshat, A., Pradhan, B. and Dadras, M., 2014, Groundwater vulnerability assessment using an improved Drastic method in GIS Resources, Conservation and Recycling, 86, 74-86.
Niknam, R., Mohammadi, K. and Majd, V. J., 2009, Aquifer vulnerability assessment using GIS and fuzzy system: a case study in Tehran-Karaj aquifer, Iran. Environmental Geology, 58, 437-446.
Nobre, R. C. M., Filho, O. C. R., Mansur, W. J., Nobre, M. M. M. and Cosenza, C. A. N., 2007, Groundwater vulnerability and risk mapping using GIS, modeling and a fuzzy logic tool, Journal of Contaminant Hydrology, 94, 277-292. Ochsenkuhn, K. M., Kontoyannakos, J. and Ochsenku hn-Petropulu, M., 1997, A new approach to a hydrochemical study of groundwater flow, Journal of Hydrology, 194(1), 64-75.
Panagopoulos, G. P., Antonakos, A. K. and Lambrakis, N. J., 2006, Optimization of the Drastic method for groundwater vulnerability assessment via the use of simple statistical methods and GIS, Hydrogeology Journal, 14, 894-911.
Pedroli, B., 1990, Classification of shallow groundwater types in a dutch covers and landscape, Journal of Hydrology, 115, 361-375.
Riley, J. A., Steinhorst, R. K., Winter, G. V. and Williams, R. E., 1990, Statistical analysis of the hydrochemistry of ground waters in Columbia River basalts, Journal of Hydrology, 119(1-4), 245-262.
Saidi, S., Bouria, S., Dhiaa, H. B. and Anselmeb, B., 2011, Assessment of groundwater risk using intrinsic vulnerability and hazard mapping: application to Souassi aquifer, Tunisian Sahel, Agricultural Water Management, 98, 1671-1682.
Theodoridis, S. and Koutroumbas, k., 2003, Pattern recognition, Second edition. USA: Elsevier press.
Van der Heijden, F. and Duin, R. P. W. and De Ridder, D. and Tax, D. M. J., 2004, Classification, parameter estimation and state estimation, West Sussex, England, John wiley & sons Ltd.
Wang, J., He, J. and Chen, H., 2012, Assessment of groundwater contamination risk using hazard quantification, a modified Drastic model and groundwater value, Beijing Plain, China. Sci. Total Environ, 432, 216-226.
Weatherill, G. and Burton, P. W., 2008, Delineation of shallow seismic source zones using K-means cluster analysis, with application to the Aegean region, Geophysical Journal International, 176(2), 565-588.
Zhou, H., Wang, G. and Yang, Q., 1999, A multi-objective fuzzy pattern recognition model for assessing groundwater vulnerability based on the Drastic system, Hydrological Sciences Journal, 44(4), 611-618. | ||
|
آمار تعداد مشاهده مقاله: 2,011 تعداد دریافت فایل اصل مقاله: 1,209 |
||