Prediction of Monthly Potential Evapotranspiration under RCP Scenarios in Future Periods (Case Study: Golpayegan Basin)

Document Type : Research Article

Authors

1 PhD Student of Watershed Management Sciences and Engineering, Faculty of Natural Resources and Earth Sciences, University of Kashan

2 Associate Professor, Department of Rangeland and Watershed Management, Faculty of natural Resources and Earth Sciences, University of Kashan

3 Assistant Professor, Department of Watershed Management, Faculty of Natural Resources and Earth Sciences, Shahrekord University

Abstract

Evapotranspiration is the transfer of energy between the Earth's surface and the atmosphere and it is the most productive mechanism of communication between the hydrosphere, lithosphere and biosphere. This study focuses on predicting potential evapotranspiration in Golpayegan basin as a response to climate change. For this purpose, six algorithms including Hargreaves-Samani, Thornthwaite, Romanenko, Oudin, Kharrufa and Blaney-Criddle and also, Penman- Monteith- FAO as a standard algorithm, were used for estimating the potential evapotranspiration. The results showed that the Hargreaves-Samani algorithm performed closer to the Penman-Monteith-FAO standard algorithm compared to other algorithms. Therefore, this algorithm was used to evaluate the potential impact of climate change in future periods on the rate of potential evapotranspiration. After that, the amount of potential evapotranspiration using general circulation models (GCM) was estimated under RCP scenarios 2.6,4.5,8.5 for near, middle and far periods of 2021-2040, 2041-2060 and 2061-2080 by the LARS-WG6 model using the HadGEM2-ES climatic model. Finally, the predicted evapotranspiration values in future periods were compared with the evapotranspiration results in the baseline period of 1992-2017 to investigate the impact of climate change on potential evapotranspiration. The results showed an increase in potential evapotranspiration under all RCP scenarios in future periods. Increase under scenarios of RCP2.6, RCP4.5 and RCP8.5 in the near future were obtained 6.31, 7.5 and 7.10 percent, In the middle future period, 9.69, 9.84 and 11.82 percent and in the distant future period, 8.17, 13.79 and 18.15 percent, respectively.

Keywords

References

[1]. Dey P, Mishra A. Separating the impacts of climate change and human activities on stream flow: A review of methodologies and critical assumptions. Journal of Hydrology. 2017; 548: 278-90.
[2]. Stocker TF, Qin D, Plattner GK, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM. Climate change 2013: The physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. United Kingdom and New York, NY, USA: Cambridge University Press, Cambridge; 2013.
[3]. Schubert SD, Lim YK. Climate variability and weather extremes: Model-simulated and historical data. In Extremes in a Changing Climate. Netherlands: Springer; 2013 (pp. 239-285).
[4]. Miao C, Duan Q, Sun Q, Li J. Evaluation and application of Bayesian multi-model estimation in temperature simulations. Progress in physical geography. 2013; 37(6):727-44.
[5]. Hargreaves GH, Allen RG. History and evaluation of Hargreaves evapotranspiration equation. Journal of Irrigation and Drainage Engineering. 2003; 129(1):53-63.
[6]. Vanderlinden K, Giraldez JV, Van Meirvenne M. Assessing reference evapotranspiration by the Hargreaves method in southern Spain. Journal of Irrigation and Drainage Engineering. 2004; 130(3):184-91.
[7]. Samani Z. Estimating solar radiation and evapotranspiration using minimum climatological data. Journal of irrigation and drainage engineering. 2000; 126(4):265-7.
[8]. Liang L, Li L, Liu Q. Temporal variation of reference evapotranspiration during 1961–2005 in the Taoer River basin of Northeast China. Agricultural and Forest Meteorology. 2010; 150(2):298-306.
[9]. Guo B, Zhang J, Gong H, Cheng X. Future climate change impacts on the ecohydrology of Guishui River Basin, China. Ecohydrology & Hydrobiology. 2014; 14(1):55-67.
[10].            Li S, Kang S, Zhang L, Zhang J, Du T, Tong L, Ding R. Evaluation of six potential evapotranspiration models for estimating crop potential and actual evapotranspiration in arid regions. Journal of Hydrology. 2016; 543:450-61.
[11].            Gharbia SS, Smullen T, Gill L, Johnston P, Pilla F. Spatially distributed potential evapotranspiration modeling and climate projections. Science of the Total Environment. 2018; 633:571-92.
[12].            Babaeian I, Kouhi M. Agroclimatic indices assessment over some selected weather stations of Khorasan Razavi Province under climate change scenarios. Journal of Water and Soil. 2012; 26(4): 953-967. (In Persian).
[13].            Gharbia S, Smullon T, Gill L, Johnston P, Pilla F. Spatially distributed potential evapotranspiration modeling and climate projections. Science of The Total Environment. 2018; 571:592-633.
[14].            Goudarzi M, Salahi B, Hosseini SA. Estimation of evapotranspiration rate due to climate change in the Urmia Lake basin. Iranian Journal of Watershed Management Science and Engineering. 2018; 13(41):1-2.
[15].            Javaherian M, Ebrahimi H, Aminnejad B. Prediction of changes in climatic parameters using CanESM2 model based on RCP scenarios (case study): Lar dam basin. Ain Shams Engineering Journal. 2020; https://doi.org/10.1016/j.asej.2020.04.012.
[16].            Liu Y, Chon J, Pan T. Spatial and temporal patterns of drought hazard for China under different RCP scenarios in the 21st century. International Journal of Disaster Risk Reduction. 2020.
 
[17].            Salarian M, Najafi M, Davari K, Eslamiyan SS, Heidari M. The most Appropriate Method to Estimate Potential Evapotranspiration in Meteorological Data Scarce Condition in the Warm and Cold Months of the Year (Case Study of Isfahan). Iranian Journal of Irrigation and Drainage. 2012; 1(8):62-73. (In Persian).
[18].            Ojwang G, Agatsiva J, Situma C. Analysis of climate change and variability risks in the smallholder sector. Environment and Natural Resources Management working paper; 2010.
[19].            Kouhi M, Sanaei- Nejad H. Evaluation of Climate Change Scenarios based on Two Statistical Downscaling Methods for Reference Evapotranspiration in Urmia Region. Iranian Journal of lrrigation and Drainage. 2014; 4(7): 559-574. (In Persian).
[20].            Chong-Hai XU, Ying X. The projection of temperature and precipitation over China under RCP scenarios using a CMIP5 multi-model ensemble. Atmospheric and Oceanic Science Letters. 2012; 5(6):527-33.
[21].            Chattopadhyay N, Hulme M. Evaporation and potential evapotranspiration in India under conditions of recent and future climate change. Agricultural and Forest Meteorology. 1997; 87(1):55-73.
[22].            Xu CY, Singh VP. Cross comparison of empirical equations for calculating potential evapotranspiration with data from Switzerland. Water Resources Management. 2002; 16(3):197-219.
[23].            Allen RG, Pereira LS, Raes D, Smith M. Crop evapotranspiration Guidelines for computing crop water requirements FAO irrigation and drainage paper 56, Rome, Italy: FAO; 1998.
[24].            Hargreaves GH. Moisture availability and crop production. Trans. ASAE. 1975; 18 (5): 980–984.
[25].            Hargreaves GH, Samani ZA. Estimating potential evapotranspiration. J. Irrig. Drain. Div. 1982; 108: 225–230.
[26].            Hargreaves GH, Samani ZA. Reference crop evapotranspiration from temperature. Appl. Eng. Agric. 1985; 1: 96–99.
 
[27].            Oudin L, Hervieu F, Michel C, Perrin C, Andréassian V, Anctil F, Loumagne C. Which potential evapotranspiration input for a lumped rainfall–runoff model?: Part 2—Towards a simple and efficient potential evapotranspiration model for rainfall–runoff modelling. Journal of hydrology. 2005; 303(1-4):290-306.
[28].            Thornthwaite CW. An approach toward a rational classification of climate. Geogr. Rev. 1948; 38: 55–94.
[29].            Blaney HF, Criddle WD. Determining Water Requirements in Irrigated Area from Climatological Irrigation Data, US Department of Agriculture, Soil Conservation Service, Technical Paper; 1950.
[30].            Pruitt W, Doorenbos J. Empirical Calibration: A Requisite for Evapotranspiration Formulae Based on Daily or Longer Mean Climate Data?. The Committee; 1977.
[31].            Kharrufa N. Simplified equation for evapotranspiration in arid regions. Beiträge zur Hydrologie. 1985; 5: 39–47.
[32].            Romanenko VA. Computation of the autumn soil moisture using a universal relationship for a large area. Proc. of Ukrainian Hydrometeorological Research Institute. 1961;3:12-25.
[33].            Dinpashoh Y. Study of Reference Crop Evapotranspiration in I.R. of Iran. Agricultural Water Management, 2003; 84, 123-129. (In Persian).
[34].            Kouchakzadeh M. Nikbakht J. Comparison of different methods to estimate reference evapotranspiration in Iran different climate with PMFAO Standard Method, Agricultural Sciences. 2004;10(3): 43-57.
[35].            Heydari Tasheh Kaboud Sh, Khoshkhoo T. Projection and prediction of the annual and seasonal future reference evapotranspiration time scales in the West of Iran under RCP emission scenarios, 2019; 19 (53): 157-176.
[36].            Jalalkamali N, Rajabi M, Naghizade M. Evaluation of Climate Change Effect on Estimation of Reference Evapotranspiration and Comparison with Lysimetric Data (case study, Bardsir plain), 2020; 14 (2): 605-615.
Iranian journal of Ecohydrology
Volume 8, Issue 1
April 2021
Pages 205-220

Files

History

  • Receive Date: 25 September 2020
  • Revise Date: 18 February 2021
  • Accept Date: 18 February 2021

Share

How to cite

Statistics