ارزیابی کارایی مدل‌های فردی و ترکیبی در شناسایی پهنه‌های مستعد نفوذپذیری (حوزۀ آبخیز ماربره- استان لرستان)

احمدی، ف.، رادمنش، ف.، و ﻣﯿﺮﻋﺒﺎﺳﯽ ﻧﺠﻒ آبادی، ر. (1394). ﻣﻘﺎیسۀ ﻋﻤﻠﮑﺮد روشﻫﺎی ﻣﺎﺷﯿﻦ­ﺑﺮدار ﭘﺸﺘﯿﺒﺎن و ﺷﺒﮑﻪﻫﺎی ﺑﯿﺰﯾﻦ در ﭘﯿﺶﺑﯿﻨﯽ ﺟﺮﯾﺎن روزاﻧۀ رودﺧﺎﻧﻪ (مطالعۀ ﻣﻮردی: رودﺧﺎﻧۀ ﺑﺎراﻧﺪوزﭼﺎی). ﭘﮋوﻫﺶﻫﺎی ﺣﻔﺎﻇﺖ آب و ﺧﺎک، 22(6)، 171 – 186.

آخونی پورحسینی، ف.، و قربانی، م. (1397). کاربرد آنتروپی شانون برای انتخاب ورودی‌های بهینه در پیش‌بینی جریان رودخانه با استفاده از مدل‌های هوشمند (مطالعۀ موردی: صوفی­ چای). علوم و مهندسی آبیاری، 41(2)، 183 – 195.

آوند، م.ت.، جانی‌زاده، س.، و فرزین، م. (1398). تعیین پتانسیل آب زیرزمینی با استفاده از روش‌های داده‌کاوی و آماری در منطقۀ یاسوج – سی‌سخت. منابع طبیعی ایران، 72 (3)، 609 – 623.

باقری دادوکلایی، ا.، محمدولی‌سامانی، ج.، و سروریان، ج. (1396). تعیین بهترین مکان برای اجرای طرح حوضچه‌های تغذیۀ مصنوعی آب زیرزمینی با استفاده از دو روش بولین و AHP. مهندسی و مدیریت ساخت، 2(1)، 12-16.

شرکت آب منطقه‌ای لرستان، (1380). مطالعات توجیهی حفاظت خاک و آبخیزداری حوزه‌های آبخیز ماربره و بخش کوچکی از رودخانه تیره در شمال دورود.

شرکت مهندسی مشاور پارس رای آب، (1391). گزارش جامع ازنا الیگودرز، فصول دوم، سوم، ششم و شانزدهم.

نوروزی، ح.، ندیری، ع.، اصغری مقدم، ا.، و قره‌خانی، م. (1396). ﭘﯿﺶﺑﯿﻨﯽ ﻗﺎﺑﻠﯿﺖ اﻧﺘﻘﺎل آﺑﺨﻮان دﺷﺖ ﻣﻠﮑﺎن ﺑﺎ اﺳﺘﻔﺎده از روش ﺟﻨﮕﻞ تصادفی. دانش آب و خاک، 27(2)، 61 – 75.

Ahmadi, F., & Radmanesh, F., & Mirabbasi Najafabadi, R. (2016). Comparing the performance of support vector machines and bayesian networks in predicting daily river flow (case study: baranduz chai river). Journal of Water and Soil Conservation (Journal of Agricultural Sciences and Natural Resources), 22(6), 171-186 (in Persian).

Akhoni Pourhosseini, f., & Ghorbani, M. (2018). Application of Shannon Entropy for Selecting the Optimum input Variables in River Flow Simulation using Intelligent Models (Case Study: SofyChay). Irrigation Sciences and Engineering (JISE) (Scientific Journal of Agriculture), 41(2 ), 183-195 (in Persian).

Al-Abadi, A.M., Pradhan, B., & Shahid, S. (2016). Prediction of groundwater flowing well zone at An-Najif Province, central Iraq using evidential belief functions model and GIS. Environmental monitoring and assessment, 188(10), 549.

Al-Fugara, A.K., Pourghasemi, H.R., Al-Shabeeb, A.R., Habib, M., Al-Adamat, R., Al-Amoush, H., & Collins, A.L. (2020). A comparison of machine learning models for the mapping of groundwater spring potential. Environmental Earth Sciences, 79, 1-19.

Althuwaynee, O.F., Pradhan, B., Park, H.-J. & Lee, J.H. (2014). A novel ensemble decision tree-based CHi-squared Automatic Interaction Detection (CHAID) and multivariate logistic regression models in landslide susceptibility mapping. Landslides 11, 1063–1078.

Arthur, J.D., Wood, H.A.R., Baker, A.E., Cichon, J.R., & Raines, G.L. (2007). Development and implementation of a Bayesian-based aquifer vulnerability assessment in Florida. Natural Resources Research, 16(2), 93-107.

ASTM (American Society for Testing Materials), (1998). Standard Test Method for Particle- Analysis of Soils, D422-63.

Avand, M., & Janizadeh, S., & Farzin, M. (2019). Groundwater Potential Determination on Yasouj-Sisakht area Using Random Forest and Generalized Linear Statistical Models. Journal of Range and Watershed Management (Iranian Journal of Natural Resources), 72(3 ), 609-623 (in Persian).

Bagheri Dadvokalaii, O., Mohammadvali Samani, J., Sarvarian, J. (2017). Determine the best place to implement groundwater artificial pond design by using two methods of boolean and AHP. Journal of Engineering & Construction Management, 2(1), 12-16 (in Persian).

Chen, W.B., Pradhan, S., Li, H., Shahabi, H.M., Rizeei, E. H., & Wang, S. (2019). Novel Hybrid Integration Approach of Bagging-Based Fisher’s Linear Discriminant Function for Groundwater Potential Analysis. Natural Resources Research, 1-20.

Farmani, R., Henriksen, H.J., & Savic, D. (2009), An evolutionary Bayesian belief network methodology for participatory decision making under uncertainty: an application to groundwater management. Integrated Environmental Assessment and Management, 8(3), 456-461.

Fielding, A.H., & Bell, J.F. (1997). A review of methods for the assessment of prediction errors in conservation presence/absence models. Environmental Conservation, 24, 38–49.

Gelman, A., Carlin, J.B., Stern Hal, S., Dunson David, B., Vehtari, Aki, R., & Donald, B. (2013). Bayesian Data Analysis. 3rd Edition: Chapman and Hall/CRC, 657 pages.

Graham, W.D., & Neff, C.R. (1994). Optimal estimation of spatially variable recharge and transmissivity fields under steady-state groundwater flow. Part 2. Case study. Journal of Hydrology, 157(1-4), 267-285.

Guo, C., Montgomery, D.R., Zhang, Y., Wang, K., & Yang, Z. (2015). Quantitative assessment of landslide susceptibility along the Xianshuihe fault zone, Tibetan Plateau, China. Geomorphology Journal, 248, 93–110.

Jeffreys, H. (2011). Scientific Inference. 3rd Edition: Cambridge University Press, 282 pages.

Konikow, L.F., & Kendy. E. (2005). Groundwater depletion: A global problem. Hydrogeology Journal, 13(1), 317-320.

Kordestani, M.D., Naghibi, S.A., Hashemi, H., Ahmadi, K., Kalantar, B., & Pradhan, B. (2019). Groundwater potential mapping using a novel data-mining ensemble model. Hydrogeology Journal, 27(1), 211-224.

Lee, S., & Min, K. (2001). Statistical analysis of landslide susceptibility at Youngin, Korea. Environmental Geology, 40, 1095–1113.

Li, X., Zhao, S., Yang, H., Cong, D., & Zhang, Z. (2017). Abi-band binary mask-based land-use change detection using Landsat 8 OLI imagery. Sustainability, 9(3), 479.

Liu, X., He, J., Yao, Y., Zhang, J., Liang, H., Wang, H., & Hong, Y. (2017). Classifying urban land use by integrating remote sensing and social media data. International Journal of Geographical Information Science, 31(8), 1675-1696.

Lorestan Regional Water Company, (2001). Feasibility studies for soil protection and watershed management in the Marbareh watershed and a small part of the Tireh River in the north of Dorud (in Persian).

Marker, M., Pelacani, S., & Schroder, B. (2012). A functional entity approach to predict soil erosion processes in a small Plio-Pleistocene Mediterranean catchment in Northern Chianti, Italy. Geomorphology, 125(4), 530-540.

Messenzehl, K., Meyer, H., Otto, J.C., Hoffmann, T., & Dikau, R. (2017). Regional-scale controls on the spatial activity of rockfalls (Turtmann Valley, Swiss Alps)—A multivariate modeling approach. Geomorphology, 287, 29-45.

Miraki, S., Zanganeh, S.H., Chapi, K., Singh, V.P., Shirzadi, A., Shahabi, H., & Pham, B.T. (2019). Mapping groundwater potential using a novel hybrid intelligence approach. Water resources management, 33(1), 281-302.

Mogaji, K.A., Omosuyi, G.O., Adelusi, A.O., & Lim, H.S. (2016). Application of GIS-based evidential belief function model to regional groundwater recharge potential zones mapping in hardrock geologic terrain. Environmental Processes, 3(1), 93-123.

Mokarram, M., Saber, A., Mohammadizadeh, P., & Abdolali, A. (2020). Determination of artificial recharge location using analytic hierarchy process and Dempster–Shafer theory. Environmental Earth Sciences, 79(10), 1-15.

Mukherjee, S. (1996). Targeting saline aquifer by remote sensing and geophysical methods in a part of Hamirpur-Kanpur, India. Hydrogeology Journal, 19, 53-64.

Naghibi, S.A., Moghaddam, D.D., Kalantar, B., Pradhan, B., & Kisi, O. (2017). A comparative assessment of GIS-based data mining models and a novel ensemble model in groundwater well potential mapping. Journal of Hydrology, 548, 471-483.

Norouzi, H., Nadiri, A., Asghari Moghaddam,, A., & Gharekhani, M. (2017). Prediction of Transmissivity of Malikan Plain Aquifer Using Random Forest Method. Water and Soil Science, 27(2), 61-75 (in Persian).

Pars Ray Ab Consulting Engineering Company, (2012). Azna Aligudarz Comprehensive Report, Chapters 2, 3, 6 and 16 (in Persian).

Pourghasemi, H.R., Mohammady, M., & Pradhan, B. (2012). Landslide susceptibility mapping using index of entropy and conditional probability models in GIS: Safarood Basin. Iran. Catena 97, 71–84.

Qureshi, M.E., Reeson, A., Reinelt, P., Brozović, N., & Whitten, S. (2012). Factors determining the economic value of groundwater. Hydrogeology Journal, 21(3), 1-9.

Reggiani, P., & Weerts, A. (2008). Bayesian approach to decision-making under uncertainty: An application to real time forecasting in the river Rhine. Journal of Hydrology, 356, 56-69.

Rittel, H.W., & Webber, M.M. (1973). Dilemmas in a general theory of planning. Policy sciences, 4(2), 155-169.

Rojas, R., Feyen, L., & Dassargues, A. (2008). Conceptual model uncertainty in groundwater modeling: Combining generalized likelihood uncertainty estimation and Bayesian model averaging. Water Resources Research, 44, W12418.

Rukundo, E., & Doğan, A. (2019). Dominant Influencing Factors of Groundwater Recharge Spatial Patterns in Ergene River Catchment, Turkey. Water, 11(4), 653.

Rwanga, S.S., & Ndambuki, J.M. (2017). Accuracy assessment of land use/land cover classification using remote sensing and GIS. International Journal of Geosciences, 8(04), 611.

Sadoddin, A., Letcher, R.A., Jakeman, A.J., & Newham, L.T. (2005). A Bayesian decision network approach for assessing the ecological impacts of salinity management. Mathematics and Computers in Simulation, 69(1-2), 162-176.

Saha, A.K., Gupta, R.P., Sarkar, I., Arora, M.K., & Csaplovics, E. (2005). An approach for GIS-based statistical landslide susceptibility zonation with a case study in the Himalayas. Landslides, 2, 61–69.

Seiler, K.P., & Gat, J.R. (2007). Groundwater Recharge from Run-Off, Infiltration and Percolation. Water Science and Technology Library, Springer Dordrecht, New York, USA, 248 pages.

Sekertekin, A., Marangoz, M., & Akcin, H. (2017). pixel-based classification analysis of land use land cover using sentinel-2 and landsat-8 data. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-4/W6, 91-93.

Shah, T., Burke, J., Villholth, K., Angelica, M., Custodio, E., Daibes, F., Hoogesteger, J., Giordano, M., Girman, J., van der Gun, J. Kendy, E., Kijne, J., Llamas, R., Masiyandima, M., Margat, J., Marin, L., Peck, J., Rozelle, S., Sharma, B.R., Vincent, L., & Wang, J. (2007). Groundwater: a global assessment of scale and significance. Pp.395-423, In: Molden, David (Ed.), Water for food, water for life: a Comprehensive Assessment of Water Management in Agriculture, London, UK: Earthscan; Colombo, Sri Lanka: International Water Management Institute (IWMI).

Sihag, P., Angelaki, A., & Chaplot, B. (2020). Estimation of the recharging rate of groundwater using random forest technique. Applied Water Science, 10(7), 1-11.

Simmers, I., Hendrickx, J.M.H., Kruseman, G.P., & Rushton, K.R. (1997). Recharge of phreatic aquifers in (semi-)arid areas. IAH International Contributions to hydrogeology 19, 1^st Edition: CRC Press, 240 pages.

Vrugt, J.A., & Sadegh, M. (2013). Toward diagnostic model calibration and evaluation: Approximate Bayesian computation. Water Resources Research, 49(7), 4335-4345.

Wada, Y., Van Beek, L.P.H., Van Kempen, C.M., Reckman, J.W.T.M., Vasak, S., & Bierkens, M.F.P. (2010). Global depletion of groundwater resources. Geophysical Research Letters, 37(20), L20402.

Yeh, H.F., Cheng, Y.S., Lin, H.I., & Lee, C.H. (2016). Mapping groundwater recharge potential zone using a GIS approach in Hualian River, Taiwan. Sustainable Environment Research, 26(1), 33-43.

Yenehun, A., Walraevens, K., & Batelaan, O. (2017). Spatial and temporal variability of groundwater recharge in Geba bain. Northern Ethiopia. Journal of African Earth Sciences,134, 198–212.

Zektser, I.S. (2012). Investigation of Transboundary Aquifers in Russia: Modern State and Main Tasks, Proceedings of NATO Advanced Research Workshop on Sustainable Use and Protection of Groundwater Resources. Transboundary Water Management, 79-85.

Zhang, K., Wu, X., Niu, R., Yang, K., & Zhao, L. (2017). The assessment of landslide susceptibility mapping using random forest and decision tree methods in the Three Gorges Reservoir area, China. Environmental Earth Sciences, 76(11), 1-20.