مقایسه مدل‌های هوشمند در پیش‌بینی نوسانات تراز سطح آب دریاچه زریوار با درنظرگیری تراز آب زیرزمینی

نوع مقاله: یادداشت فنی (5 صفحه)

نویسندگان

1 دانشجو/پردیس ابوریحان - دانشگاه تهران

2 دانشگاه تهران - پردیس ابوریحان

3 دانشیار / دانشگاه تهران

4 استادیار/ گروه مهندسی منابع آب دانشگاه کردستان

چکیده

همواره پیش‌بینی سطح آب دریاچه‌ها در سطح دنیا از مهم‌ترین و پیچیده‌ترین فرایندهای هیدرولوژیکی است که برآورد آن می‌تواند در راستای جلوگیری از بروز وضعیت نامطلوب و مدیریت صحیح این اکوسیستم ارزشمند بکار گرفته شود. از اینرو در این پژوهش از چهار تکنیک محاسبات نرم موجک-شبکه عصبی مصنوعی (WANN)، شبکه عصبی مصنوعی (ANN)، مدل استنتاج عصبی-فازی تطبیقی (ANFIS) و برنامه‌ریزی بیان ژن (GEP) در محاسبه مقادیر پیش‌بینی شده دو ماه آینده تراز سطح آب دریاچه زریوار استفاده شد. نتایج سری زمانی پیش‌بینی با استفاده از نمودارهای سری زمانی پیش‌بینی شده توسط انواع مدل‌های هوشمند و همچنین شاخص‌های آماری RMSE، R2 و MAE مقایسه شدند. نتایج این تحقیق نشان داد از چهار مدل مذکور به صورت قابل ملاحظه‌ای عملکرد مدل WANN از مدل‌های دیگر در پیش بینی سطح آب دریاچه بهتر بود. پس از مدل WANN به لحاظ صحت مقادیر شبیه‌سازی شده به ترتیب مدل‌های ANFIS، GEP و ANN تعیین شدند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Comparison of intelligent models to predict water level fluctuations of Zarival Lake using groundwater level

نویسندگان [English]

  • Siavash Gavili 1
  • Saman Javadi 2
  • M. E Banihabib 3
  • Hadi Sanikhani 4
3 Associate professor, University of Tehran
4 Department of Water engineering, University of Kordestan
چکیده [English]

In recent decades, drought and lack of water resources management has caused many lakes and wetlands to be in critical conditions. Surface water level prediction is an important and complex hydrological process but it is required for better management and improvement of their ecosystem. In this research, four soft-computing techniques including wavelet artificial neural network (WANN), artificial neural network (ANN), adaptive-neuro-fuzzy inference system (ANFIS) and gene expression programming (GEP) were used to predict 2-month water level fluctuations of Zarivar Lake. The predicted water levels in each technique were compared with observed data and statistical indicators, RMSE, MAE and R2 were used to evaluate the performance of each method. The results proved that WANN performed considerably better and its prediction was more accurate. After WANN, the accuracy of ANFIS, GEO and ANN, respectively, were better and closer to observed data. The selected technique in this research can be recommended to predict the water levels in lakes and wetlands with enough accuracy.

کلیدواژه‌ها [English]

  • Soft Computing
  • Zarivar lake
  • predicting water level
  • wavelet-neural network model

Albrecht F (1950) Die methoden zur Bestimmung Verdunstung der natürlichen Erdoberflache. Arch Meteor Geoph Biokl Ser B.2:1–38

Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration: Guidelines for computing crop water requirements. FAO Irrigation and Drainage Paper, 56, Rome, Italy, 300 p

Azhar A, Perera B (2011) Evaluation of reference evapotranspiration estimation methods under southeast Australian conditions. J Irrig Drain Eng. 137:268–279

Babamiri O, Dinpazhoh Y (2016) Comparison and evaluation of twenty methods for estimating reference evapotranspiration based on three general categories: air temperature, solar radiation and mass Transfer in the basin of lake Urmia. Journal of Water and Soil Sci. (Sci. & Technol. Agric. & Natur. Resour) 20 (77):145-161(In Persian)

Bolhasani k, Zarei H (2016) Estimation of location and zoning of reference evapotranspiration using statistical methods and geographic information systems. Journal of Aquatic Sciences and Engineering, Ahwaz Islamic Azad University 11(13):7-21 (In Persian)

Brockamp B,Wenner H (1963) Verdunstungsmessungen aufden Steiner See bei Münster. Dt Gewasserkundl Mitt 7:149–154

Dalton J (1802) Experimental essays on the constitution of mixed gases; on the force of steam of vapour from waters and other liquids in different temperatures, both in a torricellian vacuum and in air on evaporation and on the expansion of gases by heat. Mem Manch Lit Philos Soc. 5:535–602

Ganjizadeh R, Boromand Nasab S, Soltani Mahmoudi A, Ganjizadeh H (2013) Determination of reference evapotranspiration by using interpolation methods and comparing it with empirical methods (Case study: Golestan). In:Proc. First Conference-National Water Crisis, Isfahan (In Persian)

Grismer M, Orang M, Matyac S (2002) Pan evaporation to evapotranspiration conversion methods.J. Irrig. Drain. Eng. 128(3):180–184

Hargreaves GH (1994) Defining and using reference evapotranspiration. Journal of Irrig. and Drain Eng., ASCE 120(6):1132-1139

Hayati H, Haghighatjou P, Samiee M (2012) Evaluation mass transfer methods for calculating evaporation in Sistan plain .In: Proc. Third National Conference on Integrated Water Resources Management, 10p (In Persian)

Jacovides CP (1997) Reply to comment on statistical procedures for the evaluation of evapotranspiraiton models. Journal of Agricultural water management 3:95-97

Kouchakzadeh M, and Bahmani A (2005) Assessment of artificial neural networks revenue in reducing required parameters for estimation of reference evapotranspiration. Journal of Agricultural sciences Islamic Azad University 4:87-97

Mahringer W (1970) Verdunstungsstudien am neusiedler see. Arch Met Geoph Biokl Ser B .18:1–20

Mardikis MG, Kalives DP, Kollias V J (2005) Comparison of interpolatiob methods for the prediction of referenceevapotranspiration-An application in Greece. Journal Water Resources Management, Publisher Springer Netherlands 19(3)

Martinez-Cob A (1996) Multivariate geostatistical analysis of evaporation and precipitation in mountainous terrain. Journal of Hydrology 174(1–2):19–35

Meyer A (1926) Uber einige Zusammenhnge zwischen Klima und Boden in Europa. Chemie der Erde. 2:209–347

Nazarifar M, Seifi K, Momeni R (2007) Estimation of geostatistical and Tissen methods in estimating regional variations of potential evapotranspiration (Case study: Hamadan). In: Proc. Ninth Irrigation Seminar and Evaporation Reduction, Kerman: Shahid Bahonar Kerman University (In Persian)

Penman HC (1948) Natural evaporation from open water, bare soil and grass. Proc R Soc Lond Ser A. 193:120–145

Rohwer C (1931) Evaporation from free water surface. USDA Tech Null. 217:1–96

Romanenko VA (1961) Computation of the autumn soil moisture using a universal relationship for a large area. Proceedings, Ukrainian Hydrometeorological Research Institute, no. 3.Kiev

Sabziparvar AA, Bayatvarkeshi M, Ghasemi A (2008) Evaluation of different methods for estimating evapotranspiration in two different climates (Case study: Hamadan, Karaj, Gorgan). In: Proc.Third National Conference on Integrated Water Resources Management.Tabriz.7p. https://www.civilica.com/ Paper-WRM03-WRM03_178.html (In Persian)

Sharghi T, Bari Abarghuei H, Asadi MA, Kousari MR (2010) Estimation of reference evapotranspiration using FAO-Penman-Monteith method and its zonation in Yazd province. Journal of Arid Biom Scientific and Research 1(1):25-32 (In Persian)

Tabari HM, Grismer E, Trajkovic S (2011) Comparative analysis of 31 reference evapotranspiration methods under humid conditions. Irrig. Sci. 31(2):107-117

Trabert W (1896) Neue Beobachtungen u¨ber Verdampfungsgeschwindigkeiten. meteorol Z, 13:261–263

Tomar AS (2015) Performance evaluation of mass transfer-based reference evapotranspiration equations with FAO-56 pm model as index at tarairegion of uttarakhand, India. International Journal of Agricultural Sciences and Veterinary Medicine 3(4) 12p

Valipour M (2014) Application of new Mass transfer formulae for Computation of Evapotranspiration. Journal of Applied Water Engineering and Research 2(1):33-46

WMO (1966) Measurement and estimation of evaporation and evapotranspiration. Tech Pap. (CIMO-Rep) 83

Xu C Y, singhV P (1997) Sensitivity of mass transfer-based evaporation equations to errors in daily and monthly input data. Hydrological Process 11:1465-1473

Xu CY, Singh VP (2002) Cross comparison of empirical equations for calculating potential evapotranspiration with data from Switzerland. Water Resources Manage 16:197-219

Zareabayneh H, Bayat Varkeshi M, Sabziparvar AA, Marofi S, Ghasemi A (2010) Evaluation of different reference evapotranspiration methods and their zonings in Iran. Journal of Physical Geography Research Quarterly 42(74):95-109 (In Persian)

Zhai LQ, Feng Q Li, Xu CY (2010) Comparison and modification of equations for calculating evapotranspiration (ET) with data from Gansu province, northwest China. Irrig. Drain 59:477-490