Abstract
Reservoir systems need the forecast of rainfall and inflow on daily time scale for planning of water allocation to different users. Prediction of daily rainfall or daily reservoir inflow is a challenging task in water resource management. This study aims at forecasting the daily reservoir inflow using the projections of atmospheric variables extracted from the global climatic models as input. Daily rainfall series for the future period is simulated using a calibrated weather generator based on generalized linear models. The simulated daily rainfall series are compared with the monthly predictions obtained from local polynomial regression model, and the best correlated daily rainfall simulation is transformed into stream flow using a calibrated and validated soil and water assessment tool to generate the daily inflow series. The modelling procedure was applied to a typical reservoir catchment in India. Diagnostic checks carried out to assess the performance of the rainfall simulations revealed that the simulated series are having the same statistical characteristics as that of the observed series. The simulated inflow was found to be acceptable with respect to the performance indicators evaluated in the study. The methodology adopted is data driven, flexible and easy to implement.
Similar content being viewed by others
References
Arnold JG, Srinivasan R, Muttiah RS, Williams JR (1998) Large area hydrologic modeling and assessment part I: model development. J Am Water Resour Assoc 34(1):73–89
Arnold JG, Kiniry JR, Srinivasan R, Williams JR, Haney EB, Neitsch SL (2012) Soil and water assessment tool input/output documentation version 2012. In: Texas Water Resources Institute Technical Report No. 439; Texas A&M University System: College Station, TX
Bai Y, ChenZ Xie J, Li C (2016) Daily reservoir inflow forecasting using multiscale deep feature learning with hybrid models. J Hydrol 532:193–206
Bardossy A, Plate EJ (1992) Space time model for daily rainfall using atmospheric circulation patterns. Water Resour Res 28(5):1247–1259
Barkotula MAB (2010) Stochastic generation of occurrence and amount of daily rainfall. Pak J Stat Oper Res 6(1):61–73
Beven KJ (2012) Rainfall-runoff modelling: the primer. Wiley, Chichester
Block P, Rajagopalan B (2009) Statistical—dynamical approach for stream flow modeling at Malakal Sudan on the White Nile river. J Hydraul Eng 14(2):185–196
Block P, Filho FAS, Liqiang S, Hyun-Han K (2009) A Stream flow forecasting framework using multiple climate and hydrological models. J Am Water Resour Assoc 45(4):828–843
Chandler RE (2014) Stochastic weather generators. Third value training workshop, Trieste, Italy
Chandler RE, Wheater HS (2002) Analysis of rainfall variability using generalized linear models—a case study from the West of Ireland. Water Resour Res 38:10
Dhar S, Mazumdar A (2009) Hydrological modelling of the Kangsabati River under changed climate scenario: case study in India. Hydrol Process 23(16):2394–2406
Fahrmeir L, Tutz G (1994) Multivariate statistical modelling based on generalized linear models. Springer, New York
Ghosh S, Mujumdar PP (2008) Statistical downscaling of GCM simulations to stream flow using relevance vector machine. Adv Water Resour 31:132–146
Gosain AK, Rao S, Basuray D (2006) Climate change impact assessment on hydrology of Indian river basins. Curr Sci 90(3):346–353
Jany G, Letha J, Jairaj PG (2015) Statistical downscaling using local polynomial regression for rainfall predictions—a case study. Water Resour Manag 30:183–193
Johnston R, Smakhtin V (2014) Hydrological modeling of large river basins: how much is enough? Water Resour Manag 28:2695–2730. https://doi.org/10.1007/s11269-014-0637-8
Kalnay E, Kanamitsu M, Kistler R, Collins W, Deaven D, Gandin L, Iredell M, Saha S, White G, Woollen J, Zhu Y, Chelliah M, Ebisuzaki W, Higgins W, Janowiak J, Mo KC, Ropelewski C, Wang J, Leetmaa A, Reynolds R, Jenne R, Joseph D (1996) The NCEP/NCAR reanalysis 40-year project. Bull Am Meteorol Soc 77:437–471
Kusre BC, Baruah DC, Bordoloi PK, Patra SC (2010) Assessment of hydropower potential using GIS and hydrological modeling technique in Kopili River basin in Assam (India). Appl Energy 87(1):298–309
Li C, Bai Y, Zeng B (2016) Deep feature learning architectures for daily reservoir inflow forecasting. Water Resour Manag 30:14
Nash JE, Sutcliff JV (1970) River flow forecasting through conceptual models part-1 a discussion of principles. J Hydrol 10(3):282–290
Pai DS, Sredhar L, Rajeevan M, Sreejith OP, Satbhai NS, Mikopadhyay B (2013) Development and Analysis of a new spatial resolution (0.25°×0.25°) long period (1901–2010) daily gridded rainfall set over India. Research Report 1/2013, National Climate Centre, IMD, Pune
Panagoulia D, Bardossy A, Lourmas G (2008) Multivariate stochastic downscaling models for generating precipitation and temperature scenarios of climate change based on atmospheric circulation. J Glob NEST 10(2):263–272
Prasanth AP (2008) Studies on the role of tropospheric biennial oscillation in the inter annual variability of Indian summer monsoon. Research report, Department of Atmospheric science, CUSAT
Sloan PG, Moore ID (1984) Modeling subsurface storm flow on steeply sloping forested watersheds. Water Resour Res 20(12):1815–1822
Stehlik J, Bardossy A (2002) Multivariate stochastic downscaling model for generating daily precipitation series based on atmospheric circulation. J Hydrol 256:120–141
USDA Soil Conservation Service (1972) Section 4: hydrology. National Engineering Handbook, Washington, DC
Wheater HS, Jakeman AJ, Beven KJ (1993) Progress and directions in rainfall-runoff modelling. In: Modelling change in environmental systems, pp 101–132
Wilks DS (1992) Adapting stochastic weather generation algorithms for climate change studies. Clim Change 22:67–84
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
George, J., Janaki, L. & Gomathy, J.P. Prediction of daily reservoir inflow using atmospheric predictors. Sustain. Water Resour. Manag. 5, 1745–1754 (2019). https://doi.org/10.1007/s40899-019-00323-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40899-019-00323-4