واسنجی چندمنظوره مدل SWAT در برآورد رواناب، تبخیر و تعرق و عملکرد محصولات (مطالعه موردی: دشت مهاباد)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری، گروه مهندسی آبیاری و آبادانی، پردیس کشاورزی و منابع طبیعی، دانشگاه تهران، کرج، ایران

2 دانشیار، گروه مهندسی آبیاری و آبادانی، پردیس کشاورزی و منابع طبیعی، دانشگاه تهران، کرج، ایران.

3 استاد، دانشکده مهندسی عمران، دانشگاه صنعتی شریف، تهران، ایران.

چکیده

مدل SWAT به طور گسترده در مطالعات هیدرولوژیک بزرگ ‎مقیاس با توجه به کاربری زمین و شیوه‌‏های مدیریت کشاورزی استفاده می‌شود. در اغلب مطالعات عملکرد این مدل براساس داده‎‌های میدانی رواناب سطحی واسنجی می‏‌گردد و به دیگر مؤلفه‏‌های بیلان آب از جمله‏ تبخیروتعرق کمتر پرداخته شده است. هدف از این مطالعه واسنجی چندمنظوره مدل‏ SWAT با شاخص‌‏های تکمیلی از جمله تبخیروتعرق و عملکرد محصولات غالب در دشت مهاباد در استان آذربایجان غربی بود. واسنجی و اعتبار‏سنجی مدل براساس داده‏‌های ایستگاه هیدرومتری گردیعقوب واقع در خروجی محدوده مطالعه و داده‏‌های تبخیروتعرق و عملکرد محصولات غالب منطقه شامل گندم، جو، ذرت، چغندرقند، یونجه، سیب و انگور انجام شد. دوره‏‌های واسنجی و اعتبارسنجی به‌‏ترتیب 6 و 4 سال بود. با توجه به دقت داده‌‏ها در فرآیند واسنجی چندمنظوره، ضرایب 1، 0/9 و 0/8 به‏‌ترتیب برای داده‏‌های هیدرومتری، عملکرد و تبخیروتعرق در تابع هدف نرم‌‏افزار SWAT-CUP و روش SUFI2 درنظر گرفته شد. به طور کلی تحلیل حساسیت مدل منجر به انتخاب 43 مورد از حساس‌‏ترین پارامترها با توجه به حساسیت آن‏ها به دبی رودخانه، تبخیروتعرق و عملکرد گیاه شد به طوری که پتانسیل واحد گرمایی لازم برای رشد گیاه و شاخص LAI از مهم‏ترین پارامترها برای شبیه‌‎‏سازی عملکرد و تبخیروتعرق محصولات در فرآیند واسنجی مدل به‏دست آمد. نتایج نشان داد مدل SWAT به‏‌خوبی توانسته است جریان سطحی را در دوره‌‏های واسنجی (0/85=NSE؛ 0/87 =R2) و اعتبارسنجی (0/92=NSE؛ 0/89 =R2)  شبیه‌‏سازی کند. برآورد جریان سطحی دارای عدم قطعیت بالایی به‏‌خصوص در جریان کم در دوره واسنجی بود که منجر به بیش‌‏برآورد (%4/5 =PBIAS) جریان سطحی شده است. در ارزیابی عملکرد مدل SWAT در برآورد تبخیروتعرق واقعی، این مقادیر با خروجی مدل سنجش از دور WaPOR مورد مقایسه قرار گرفت. نتایج نشان داد معیار RMSE در دوره واسنجی بین 13/8 تا 66/4 میلی‏متر و در دوره اعتبار‏سنجی بین 23/9 تا 53/2 میلی‏متر متغیر است. در عین حال، مقادیر تبخیروتعرق واقعی برآورد شده مدل SWAT با برآورد نیاز آبی (پتانسیل) مدل CROPWAT مورد مقایسه قرار گرفت. در این بررسی معیار RMSE در دوره واسنجی بین 24/4 (%3/6) تا 49/4 (%6/5) میلی‏متر و در دوره اعتبار‏سنجی بین 21/7 (%6/2) تا 53/4 (%7/2) میلی‏متر برای محصولات مختلف به‏‌دست آمد. مقادیر معیار PBIAS نشان داد برآورد تبخیروتعرق مدل SWAT در هر دو دوره‏ واسنجی و اعتبارسنجی کمتر از برآورد نیاز آبی CROPWAT بوده است. به طور کلی برای اکثر محصولات، مقادیر تبخیروتعرق حاصل از مدل SWAT و WAPOR به مراتب کمتر از مقادیر تبخیروتعرق برآورد شده توسط مدل CROPWAT است که می‏‌تواند نشان دهنده کم‌‏آبیاری باشد. برآورد عملکرد محصولات توسط مدل SWAT با مقادیر عملکرد محصولات گزارش شده در منطقه مقایسه شد. نتایج حاکی از برآورد نسبی مدل برای عملکرد محصول بود، در عین این که مدل SWAT تا حدی عملکرد محصولات را بیش برآورد کرده است. بررسی حاضر نشان داد واسنجی چندمنظوره مدل هیدرولوژیکی بزرگ‎ مقیاس SWAT در یک منطقه تحت آبیاری علاوه‌‏بر استفاده از شاخص متداول جریان رودخانه، با درنظر گرفتن پارامترهای تکمیلی از قبیل تبخیروتعرق و عملکرد محصولات می­‌تواند منجر به افزایش دقت نتایج مدل شود.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Multipurpose Calibration of SWAT Model in Estimating Runoff, Evapotranspiration, and Crop Yield (A Case Study: Mahabad Plain)

نویسندگان [English]

  • Omid Raja 1
  • Masoud Parsinejad 2
  • Masoud Tajrishy 3
1 Ph.D. Candidate, Department of Irrigation and Reclamation Engineering, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran.
2 Associate Professor, Department of Irrigation and Reclamation Engineering, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran.
3 Professor, Department of Civil Engineering, Sharif University of Technology, Tehran, Iran.
چکیده [English]

In most studies, the SWAT model is calibrated based on surface runoff in hydrometric stations, and the evapotranspiration component, which has a great impact on the estimation of balance components, is not considered or less considered in the calibration process. Therefore, the aim of this study was to estimate the yield and evapotranspiration values of major crops in Mahabad plain in West Azerbaijan province, through multivariate calibration of SWAT model. Calibration and validation of the model based on the data of a hydrometric station (Gerdyaghoub station located at the exit of the plain), and crop yield and evapotranspiration of the major crops of the region including wheat, barley, corn, sugar beet, alfalfa, apple, and grape. A six year calibration period followed by a four-year validation period was used. In the multi-purpose calibration process, the coefficients of 1, 0.9, and 0.8, respectively, for hydrometric data, yield, and evapotranspiration were considered in the objective function of SWAT-CUP software and SUFI2 method. In general, the sensitivity analysis of the model led to the selection of 43 of the most sensitive parameters according to their sensitivity to river discharge, crop yield and evapotranspiration. Also, the heat unit potential required for full plant growth and Leaf area index (LAI) were the most important parameters to simulate the yield and evapotranspiration crops in the model calibration process. The results showed that the SWAT model was able to simulate the surface flow in the periods of calibration (NSE = 0.85; R2 = 0.87), and validation (NSE = 0.92; R2 = 0.89), as well. The model has high uncertainty in surface flow simulation, especially over-estimation in low flow during calibration period (PBIAS = 4.5%). In evaluating the performance of the SWAT model in estimating actual evapotranspiration, these values ​​were compared with the output of the WaPOR remote sensing model. The results showed that the RMSE criteria varies between 13.8 to 66.4 mm in the calibration period, and between 23.9 to 53.2 mm in the validation period. At the same time, the estimated actual evapotranspiration values ​​of the SWAT model were compared with the estimated crop evapotranspiration of the CROPWAT model. In this study, RMSE criteria in the calibration period between 24.4 (3.6%) to 49.4 (6.5%) mm, and in the validation period between 21.7 (6.2%) to 4.4 53 (7.2%) mm were obtained for different crops. PBIAS values ​​showed that the estimate of SWAT model evapotranspiration in both calibration and validation periods was lower than the estimate of CROPWAT crop evapotranspiration. In general, for most crops, the evapotranspiration values ​​obtained from the SWAT and WAPOR models are far less than the evapotranspiration values ​​estimated by the CROPWAT model that can indicate deficit-irrigation. Crops yield performance estimates were compared by SWAT model with crop yield performance values ​​reported in the region. The results showed a relative estimate of the model for crop performance, while the SWAT model somewhat over-estimated crop performance. The present study showed that multifunctional calibration of large-scale hydrological model SWAT in an irrigated area in addition to using the usual river flow index, taking into account additional parameters such as evapotranspiration and crop yield can increase the accuracy of model results.

کلیدواژه‌ها [English]

  • evaluation
  • Surface flow
  • actual water-use
  • Cultivation
  • WaPOR
Aalami MT, Abbasi H, Niksokhan MH (2018) Comparison of two calibration-uncertainty methods for soil and water assessment tool in stream flow and total suspended solids modeling. Water and Soil Science 28(3):53-64 (In Persian)
Abbaspour K C (2009) User manual for SWAT-CUP SWAT calibration and uncertainty analysis programs. Swiss Federal Institute of Aquatic Science and Technology, Eawag, Dübendorf, Switzerland
Abbaspour KC, Yang J, Maximov I, Siber R, Bogner K, Mieleitner J, Zobrist J (2007) Modelling hydrology and water quality in the pre-alpine/alpine Thur watershed using SWAT. Journal of Hydrology 333(2-4):413-430
Adeogun AG, Sule BF, Salami AW (2014) Validation of SWAT model for prediction of water yield and water balance: case study of upstream catchment of Jebba dam in Nigeria. International Journal Computer and Mathematical Science 8(2):264-270
Ahmadzadeh H, Morid S, Delavar M (2014) Assessment of changes in agricultural crop yields and inflows to Lake Urmia in Zarrinehrud River Basin due to changing irrigation systems from surface to pressure using SWAT model. Iranian Journal of Irrigation & Drainage 8(1):1-15 (In Persian)
Aizen V, Aizen E, Glazirin G, Loaiciga HA (2000) Simulation of daily runoff in Central Asian alpine watersheds. Journal Hydrology 238:15–34
Akhavana S, Abedi-Koupaia J, Mousavia SF, Eslamiana SS, Abbaspourc KC (2010) Application of SWAT model to investigate nitrate leaching in Hamadan–Bahar Watershed, Iran. Agriculture, Ecosystems and Environment 139(4):675-688
Aliyari F, Bailey RT, Tasdighi A, Dozier A, Arabi M, Zeiler K (2019) Coupled SWAT-MODFLOW model for large-scale mixed agro-urban river basins. Environmental Modelling and Software 115:200-210
Alizadeh A, Izady K, Davari K, Ziaei A N, Akhavan S, Hamidi Z (2013) Estimation of actual evapotranspiration at the basin year scale using SWAT. Iranian Journal of Irrigation and Drainage 2(7):258-243 (In Persian)
Allen RG, Periera LS, Raes D, Smith M (1998) Crop evapotranspiration (Guidelines for computing crop water requirements). Rome: Food and Agriculture Organization of the United Nations (FAO)
Amini MA, Torkan GH, Eslamian SS, Zareian MJ, Besalatpour AA (2019) Assessment of SWAT hydrological model in catchments' water balance simulation located in semi-arid regions (Case study: Zayandeh-Rud River Basin). Journal of Water and Soil 32(5):849-863 (In persian)
Anand J, Gosain AK, Khosa R (2018) Prediction of land use changes based on land change modeler and attribution of changes in the water balance of Ganga basin to land use change using the SWAT model. Science of the Total Environment 644:503-519
Arnold JG, Fohrer N (2005) SWAT2000: Current capabilities and research opportunities in applied watershed modelling. Hydrology Process 19:563-572
Arnold JG, Srinivasan R, Muttiah RS, Williams JR (1998) Large area hydrologic modeling and assessment-Part 1. Model development. Journal of the American Water Resources Association 34(1):73-89
Barlow JR, Clark BR (2011) Water use conservation scenarios for the Mississippi Delta using an existing regional groundwater flow model. In AGU Fall Meeting Abstracts, 14-56
Barlow PM, Leake SA (2012) Streamflow depletion by wells: Understanding and managing the effects of groundwater pumping on streamflow (p. 84). Reston, VA: US Geological Survey. Bear, J. and Cheng, A. H. D. 2010. Modeling groundwater flow and contaminant transport (Vol. 23). Springer Science & Business Media
Bastiaanssen W, Cheema M, Immerzeel W, Miltenburg, I Pelgrum H (2012) Surface energy balance and actual evapotranspiration of the transboundary Indus Basin estimated from satellite measurements and the ETLook model. Water Resources Research 48:100-120
Bejranonda W, Koontanakulvong S, Koch M (2007) Surface and groundwater dynamic interactions in the upper great Chao Phraya Plain of Thailand: Semi-Coupling of SWAT and MODFLOW. Groundwater and Ecosystems, IAH Selected Papers on Hydrogeolgy; International Association of Hydrology: Goring, UK, 17–21
Berihun ML, Tsunekawa A, Haregeweyn N, Dile YT, Tsubo M, Fenta AA, ... Srinivasan R (2020) Evaluating runoff and sediment responses to soil and water conservation practices by employing alternative modeling approaches. Science of The Total Environment 747:141118
Chu TW, Shirmohammadi A (2004) Evaluation of the SWAT model’s hydrology component in the piedmont physiographic region of Maryland. Transactions of the ASAE 47(4):1057
Chunn D, Faramarzi M, Smerdon B, Alessi DS (2019) Application of an integrated SWAT–MODFLOW Model to evaluate potential impacts of climate change and water withdrawals on groundwater–surface water interactions in west-central Alberta. Water 11(1):110
Dastjerdi E, Mojaradi B, Alizadeh H (2019) GIS-based identification and preparation of suitable climatological data sources for simulation using semi-distributed hydrological models. Iranian Journal of Soil and Water Research 50(7):1781-1791 (In Persian)
de Oliveira Serrão EA, Silva MT, Ferreira TR, da Silva VDPR, de Sousa FDS, de Lima AMM, ... Wanzeler RT S (2020) Land use change scenarios and their effects on hydropower energy in the Amazon. Science of The Total Environment 744:140981
Doorenbos J, Kasssam AH (1979) Yield response to water. Rome: Food and Agriculture Organization of the United Nations (FAO)
Dowlatabadi S, Zomorodian SA (2016) Conjunctive simulation of surface water and groundwater using SWAT and MODFLOW in Firoozabad watershed. KSCE Journal of Civil Engineering 20(1):485-496
Faramarzi M, Abbaspour KC, Schulin R, Yang H (2009) Modelling blue and green water resources availability in Iran. Hydrology Proceedings 23(3):486-501
Farokhnia A, Morid S, Delavar M, Abbaspour K (2018) Development of SWAT-LU model for simulation of urmia lake water level decrease and assessment of the proposed actions for its restoration; (Role of anthropogenic and climatic factors on hydrological change of the basin and lake). Iranian Journal of Irrigation & Drainage 12(5):1041-1058 (In persian)
Gao Y, Long D (2008) Intercomparison of remote sensing-based models for estimation of evapotranspiration and accuracy assessment based on SWAT. Hydrological Processes 22(25):4850-4869
Gassman PW, Reyes MR, Green CH, Arnold JG (2007) The soil and water assessment tool: Historical development, applications, and future research directions. Transactions of the ASABE 50(4):1211-1250
Green WH, Ampt GA (1911) Studies on soil physics 1: The flow of air and water through soils. Journal of Agricultural Science 4(1):1-24
Hargreaves GH, Samani ZA (1982) Estimating potential evapotranspiration. Journal of the Irrigation and Drainage Division 108(3):225-230
Hosseini M, Ghafouri M, Tabatabaei Z, Mokarian MR (2017) Estimation of water balance in watersheds led to west-south frontiers and Persian Gulf by semi distributed SWAT Model. Journal of Hydrology and Soil Science 20(4):183-194 (In Persian)
Hosseini SH, Memarian H, Memarian H (2019) Using SWAT and SWAT-CUP for hydrological simulation and uncertainty analysis in arid and semi-arid watersheds (Case study: Zoshk Watershed, Shandiz, Iran). Iranian Journal of Rainwater Catchment Systems 7(2):35-44 (In Persian)
Hu J, Ma J, Nie C, Xue L, Zhang Y, Ni F, ... Wang Z (2020) Attribution analysis of runoff change in min-tuo river basin based on SWAT model simulations, China. Scientific Reports 10(1):1-16
Izady A, Davary K, Alizadeh A, Ghahraman B, Sadeghi M, Moghaddamnia A (2012) Application of "panel-data" modeling to predict groundwater levels in the Neishaboor Plain, Iran”. Hydrogeology Journal 20(3):435-447
Jolejolea ME, Kimb BJ, Jeonb DJ, Cayetanoa M, Kimb JH (2018) Scenario study of the effect of different land use to a sub-basin in Yeongsan River basin using SWAT model. Desalination and Water Treatment 120:198-204
Kanishka G, Eldho TI (2020) Streamflow estimation in ungauged basins using watershed classification and regionalization techniques. Journal of Earth System Science 129(1):1-18
Kim NW, Chung IM, Won YS, Arnold JG (2008) Development and application of the integrated SWAT–MODFLOW model. Journal of Hydrology 356(1-2):1-16
Mo G, Zhang Y, Huang Y, Mo C, Yang Q (2020) Evaluation and hydrological impact of land-use changes in the Longtan basin. Journal of Earth System Science 129(1):1-11
Monteith JL (1965) Evaporation and environment. In the state and movement of water in living organisms, XIXth Symposium Society for Exp. Biol., Swansea, Cambridge University Press
Moriasi DN, Arnold JG, Van Liew MW, Bingner RL, Harmel RD, Veith TL (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE 50(3):885-900
Nair SS, King KW, Witter JD, Sohngen BL, Fausey NR (2011) Importance of crop yield in calibrating watershed water quality simulation tools. Journal American Water Resource Associate (JAWRA) 47(6):1285-1297
Näschen K, Diekkrüger B, Evers M, Höllermann B, Steinbach S, Thonfeld F (2019) The impact of Land Use/Land Cover Change (LULCC) on water resources in a tropical catchment in Tanzania under different climate change scenarios. Sustainability 11(24):7083
Naserabadi F, Esmali Ouri A, Akbari H, Rostamian R (2016) River flow Simulation using SWAT Model (Case study: Ghareh Su River in Ardabil Province-Iran). Journal of Watershed Management Research 7(13):50-59 (In Persian)
Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models: Part 1. A discussion of principles. Journal of Hydrology 10(3):282-290
Neitsch S, Arnold J, Kiniry J, Williams J (2011) Soil and water assessment tool: Theoretical documentation, version 2009, Texas Water Resource Institute, USA
Neitsch S, Arnold JG, Kiniry JR, Williams JR, King KW (2009) Soil and water assessment tool. in: theoretical documentation: version 2009. TWRI TR-191, College Station, TX
Neitsch SL, Arnold JG, Kiniry JR, Williams JR (2005) Soil and water assessment tool theoretical documentation: Version 2005. Temple, TX: Grassland, Soil and Water Research Laboratory, Agricultural Research Service. Available at: www.brc.tamus.edu/swat/doc.html. Accessed 1 November 2006
Patil NS, Nataraja M (2020) Effect of land use land cover changes on runoff using hydrological model: A case study in Hiranyakeshi watershed. Modeling Earth Systems and Environment 6(4):2345-2357
Payam Ebrahimi P, Salimi Kochi J, Mohseni Saravi M (2018) Calibration and validation of SWAT Model in runoff simulation, case study: Neka Watershed. Journal of Watershed Engineering and Management 10(3):266-279 (In Persian)
Pisinaras V, Petalas C, Gikas GD, Gemitzi A, Tsihrintzis, VA (2010) Hydrological and water quality modeling in a medium-sized basin using the Soil and Water Assessment Tool (SWAT). Desalination 250(1):274-286
Priestley CHB Taylor RJ (1972) On the assessment of surface heat flux and evaporation using large scale parameters. Monthly Weather Review 100(2):81-92
Rezaei Moghaddam MH, Hejazi MA, Behbody A (2019) Estimation of runoff catchment in east Azerbaijan Province: Comparative application of calibration methods and uncertainty analysis of SWAT Model. Journal of Geography and Environmental Hazards 8(31):59-75 (In persian)
Ritchie JT (1972) A model for predicting evaporation from a row crop with incomplete cover. Water Resources Research 8(5):1204-1213
Rostamian R, Jaleh A, Afyuni M, Mousavi SF, Heidarpour M, Jalalian A, Abbaspour KC (2008) Application of a SWAT model for estimating runoff and sediment in two mountainous basins in central Iran. Hydrological Sciences Journal 53(5):977-988
Saadatpour A, Alizadeh A, Ziaei A N, Izady A (2019) Estimation and comparison of blue and green water using SWAT and SWAT-MODFLOW models in the neishabour watershed. Iranian Journal of Irrigation & Drainage 13(4):1113-1129 (In persian)
Scanlon BR, Keese KE, Flint AL, Flint LE, Gaye CB, Edmunds WM, Simmers I (2006) Global synthesis of groundwater recharge in semiarid and arid regions. Hydrological Processes 20(15):3335-3370
Sedighi Hamidi P (2018) Investigating the effect of expansion of pressurized irrigation systems on water resources of Urmia Lake basin (Mahabad sub-basin). M.Sc. Thesis in Irrigation and Drainage Engineering, 131 p (In Persian)
Sophocleous MA (2005) Groundwater recharge and sustainability in the High Plains aquifer in Kansas, USA. Hydrogeology Journal 13(2):351-365
Spruill CA, Workman SR, Taraba JL (2000) Simulation of daily and monthly stream discharge from small watersheds using the SWAT model. Transactions of the ASAE 43(6):1431
Srivastava P, McNair JN, Johnson TE (2006) Comparison of process-based and artificial neural network approaches for streamflow modeling in an agricultural watershed. Journal of the American Water Resources Association 42(3):545-563
Thavhana MP, Savage MJ, Moeletsi ME (2018) SWAT model uncertainty analysis, calibration and validation for runoff simulation in the Luvuvhu River catchment, South Africa. Physics and Chemistry of the Earth, Parts A/B/C 105:115-124
Tuppad P, Douglas-Mankin KR, Lee T, Srinivasan R, Arnold JG (2011) Soil and Water Assessment Tool (SWAT) hydrologic/water quality model: Extended capability and wider adoption. Transactions of the ASABE 54(5):1677-1684
USDA Soil Conservation Service (1972) National engineering handbook. Section 4: Hydrology, Chapters 4-10
Vazquez-Amabile GG, Engel BA (2005) Use of SWAT to compute groundwater table depth and stream flow in the Muscatatuck River watershead. American Society of Agricultural Engineers 48(3):991-1003
Walker K, Thoms MC (1993) Environmental effects of flow regulation on the lower river Murray, Australia. Regulated Rivers: Research and Management 8:103-19
Water Consulting Engineers and Sustainable Development (2014) Update studies of water resources balance study areas of Urmia Lake catchment area leading to the water year of 2009-2010. Mahabad Study Area Water Balance Report 81p (In Persian)
Water Engineering Research Institute (2019) Collaborative land cover mapping of the Lake Urmia Basin, Iran. Tarbiat Modares University, GCP/IRA/066/JPN-18-003, 61p
Wei X, Bailey RT (2019) Assessment of system responses in intensively irrigated stream-aquifer systems using SWAT-MODFLOW. Water 11(8):1576
Wheater HS (2010) Hydrological processes, groundwater recharge and surface-water/groundwater interactions in arid and semi-arid areas. Groundwater Modeling in Arid and Semi-Arid Areas, 1st ed, Howard S. Wheater, Simon A. Mathias and Xin Li. Published by Cambridge University Press 5-37
White KL, Chaubey I (2005) Sensitivity analysis, calibration and validation for a malt sit and multivariable SWAT model. Journal of the American Water Resources Association 41(5):1077-1089
Wösten JHM, Pachepsky YA, Rawls WJ (2001) Pedotransfer functions: Bridging the gap between available basic soil data and missing soil hydraulic characteristics. Journal of Hydrology 251(3-4):123-150
Xu K, Peng HQ (2013) Estimating runoff and environment protection in Tao River Basin based on SWAT Model. In Applied Mechanics and Materials, Trans Tech Publications Ltd. 340:942-946
Yin l, Hu G, Huang J, Wen D, Dong J, Wang X, Li H (2011) Groundwater-recharge estimation in the Ordos Plateau, China: Comparison of methods. Hydrogeology Journal 19:1563-1575