Performance evaluation of daily Weather Generator ClimGen model in a mountainous watershed of Himalayan foothills
DOI:
https://doi.org/10.53550/Keywords:
Crop growth models, Hydrological, Mountainous, Watershed, Weather generationAbstract
Long-term series of daily weather data are required for the analysis of weatherimpacted systems such as cropping management systems, hydrologic studies, environmental studies etc. Weather generators are used to produce long series of synthetic daily climatic data using existing weather records where observed climate data are limited. But before evaluating any hydrological, crop growth and other models, it is first required to evaluate the weather generator in-built in the model for its better efficiency. Therefore, in this study, mostly used weather data generator, ClimGen, was evaluated for generating daily information taking daily precipitation (1970-2008), maximum and minimum temperatures of two existing weather stations of a hilly watershed, located in Uttarakhand i.e. Tamadhaun (1989-2008) and Kedar (1989-2003). After doing parameterization, ClimGen was used to generate daily series of rainfall from 2004-2008, maximum and minimum temperature data for Tamadhaun from 2006-2008 and for Kedar from 2001-2003. The generated data then used to evaluate the performance of ClimGen model using minimum root mean square error (RMSE), maximum correlation coefficient (r) and coefficient of efficiency (CE). ClimGen performed well in generating the minimum and maximum temperatures. However, for precipitation, it clearly underestimated the daily rainfall in all two locations. Therefore, based on actual and generated rainfall, system response models may be evaluated very carefully for the hilly watersheds.
References
Abedinpour, M., Sarangi, A., Rajput, T.B.S. and Singh, Man. 2014. Prediction of maize yield under future water availability scenarios using AquaC rop model. J. Agric. Sc., 152(4): 558-574 DOI: http://dx.doi.org/10.1017/S0021859614000094
Acutis, M, Donatelli, M. and Stockle, C.O. 1999. Performance of two weather generators as a function of the number of available years of measured climatic data. Proceedings First International Symposium on Modelling Cropping Systems, Lleida, Spain, 21-23 June. pp.129-130.
Arnold, C.D. and Elliot, W.J. 1996. CLIGEN Weather Generator Predictions of Seasonal Wet and Dry Spells in Uganda. Trans. of ASAE., 39(3): 969-972.
Castellvi, F. and Stockle, C.O. 2001. Comparing the performance of WGEN and ClimGen in the generation of temperature and solar radiation. Trans. of ASAE. 44: 1683-1687.
Danuso, F. and Della, M.V. 1997. CLIMAK reference manual. DPVTA, University of Udine, Italy, 36 p.
Jalota, S.K., Singh, G.B., Ray, S.S., Sood, Anil and Panigrahy, S. 2006. Performance of Cropsyst Model in Rice-Wheat cropping system. Jour. Agric. Physics., 6(1): 7-13.
Johnson, G.L., Hanson, C.L., Hardegree, S.P. and Ballard, E.B. 1996. Stochastic Weather Simulation: Overview and analysis of two commonly used models. J. Applied Met., 35: 1878-1896.
McKague, K., Rudra, R., Ogilvie, J., Ahmed, I. and Gharabaghi, B. 2005. Evaluation of weather generator ClimGen for Southern Ontario. Can. Water Resour. J., 30(4): 315-330.
Matalas, N.C. 1967. Mathematical assessment of synthetic hydrology. Water Resour. Res., 3(4): 937-945.
Murray, S.J. 2013. Present and future water resources in India: Insights from satellite remote sensing and a dynamic global vegetation model. J. Earth Syst. Sci., 122(1):1 13.
Nash, J.E. and Sutcliffe, J.V. 1970. River flow forecasting through conceptual models. J. Hydrol., 10: 282-290.
Reddy, K.S., Kumar, M., Marithi, V., Umesha, B., Vijaylaxmi and Nageswar Rao, C.V.K. 2014. Climate change analysis in southern Telangana region, Andhra Pradesh using LARS-WG model. Curr. Sci. 107(1): 54-62.
Reddy, K.S., Kumar, M., Nagarjuna Kumar, R., Umesha, B., Vijayalakshmi and Venkateswarlu, B. 2012. Long term rainfall and temperature analysis through ClimGen model in Ranga Reddy district of Andhra Pradesh. J.Agrometeorol. (Spec. Issue-I). 15: 45-50.
Richardson, C.W. andWright, D.A. 1984. WGEN:Amodel for generating daily weather variables. USDA-ARS, 235 p.
Safeeq, M. and Fares, A. 2011. Accuracy evaluation of ClimGen weather generator and daily to hourly disaggregation methods in tropical conditions. Theor. Appl. Climatol 106: 321-341.
Sharpley, A.N. and Williams, J.R. 1990. EPIC-Erosion/Productivity Impact Calculator: 1. Model Documentation. US Department of Agriculture Technical Bulletin No. 1768: 235 p.
Stockle, C.O., Campbell, G.S. and Nelson, R. 1999. ClimGen manual. Biological Systems Engineering Department, Washington State University, Pullman,WA, 28 p.
Tao, F., Hayashi, Y., Zhang, Z., Sakamoto, T. and Yokozawa, M. 2008. Global warming, rice production, and water use in China: Developing a probabilistic assessment. Agril. Forest Met., 148: 94-110.
Waichler, S.R. and Wigmosta, M.S. 2003. Development of hourly meteorological values from daily data and significance to hydrological modeling at H. J. Andrews Experimental Forest. J. Hydrometeor . 4: 251-263.



