Determining the Minimum Number of Stochastically Generated Point Precipitation Records Required to Model Basinwide Precipitation
Publication: Journal of Hydrologic Engineering
Volume 16, Issue 5
Abstract
This paper presents a general expression that may be used to determine the minimum number of locations in a river basin at which cross-correlated point precipitation time series must be stochastically generated to adequately capture the temporal variance of precipitation over large areas, based on the spatial correlation structure of the precipitation field. Using fewer precipitation time series than necessary leads to an overestimate of the variance of the areal precipitation. Application of the derived expression is demonstrated by using the Anseba River basin in Eritrea, East Africa, as an example. This test case is validated using a series of stochastic precipitation fields that are generated at different spatial scales. The expression was derived by expanding the method of moments equation for the variance at the field scale.
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Acknowledgments
The work presented in this paper was inspired by the work performed by Natural Resources Consulting Engineers, Inc., of Fort Collins, Colorado, under a contract with the government of Eritrea. Dr. Marijan Babić, who is now with the Civil Engineering Institute of Croatia in Zagreb, provided key contributions during the early stages of this work.
References
Bras, R., and Rodríguez-Iturbe, I. (1976). “Evaluation of mean square error involved in approximating the areal average of a rainfall event by a discrete simulation.” Water Resour. Res., 12(2), 181–184.
Carney, M. C., Babić, M., and Mesghinna, W. (2008). “On the importance of spatial correlation in stochastic precipitation used in water supply modeling.” Proc., AGU Hydrology Days, Colorado State Univ., Fort Collins, CO.
Euroconsult. (1998). “Sector study on national water resources and irrigation potential, stage I report,” Component 1 Rep., Surface Water Resources, Arnhem, The Netherlands.
Habib, E., Krajewski, W. F., and Ciach, G. J. (2001). “Estimation of rainfall interstation correlation.” J. Hydrometeorol., 2(6), 621–629.
Huff, F. A. (1970). “Spatial distribution of rainfall rates.” Water Resour. Res., 6(1), 254–260.
Huff, F. A., and Shipp, W. L. (1969). “Spatial correlations of storm, monthly, and seasonal precipitation.” J. Appl. Meteorol., 8(4), 542–550.
Neitsch, S. L., Arnold, J. G., Kiniry, J. R., and Williams, J. R. (2005). Soil and water assessment tool theoretical documentation version 2005, USDA-ARS Grassland, Soil, and Water Research Laboratory, Temple, TX.
Richardson, C. W. (1981). “Stochastic simulation of daily precipitation, temperature, and solar radiation.” Water Resour. Res., 17(1), 182–190.
Rodríguez-Iturbe, I., and, J. M., and Mejia, J. M. (1974). “The design of rainfall networks in time and space.” Water Resour. Res., 10(4), 713–728.
Rodríguez-Puebla, C., Encinas, A. H., Nieto, S., and Garmendia, J. (1998). “Spatial and temporal patterns of annual precipitation variability over the Iberian Peninsula.” Int. J. Climatol., 18(3), 299–316.
Salas, J. D. (1993). “Analysis and modeling of hydrologic time series.” Handbook of hydrology, D. R. Maidment, eds., McGraw-Hill, New York.
Şen, Z., and Habib, Z. (2001). “Monthly spatial rainfall correlation functions and interpretations for Turkey.” Hydrol. Sci. J., 46(4), 525–535.
Sharpley, A. N., and Williams, J. R. (1990). EPIC-Erosion Productivity Impact Calculator, 1. Model documentation, USDA-ARS Tech. Bull. 1768, Temple, TX.
Weber, R. O., and Talkner, P., (1993). “Some remarks on spatial correlation functions.” Mon. Weather Rev., 121(9), 2611–2617.
Wilks, D. S. (1998). “Multisite generalization of a daily stochastic precipitation generation model.” J. Hydrol. (Amsterdam), 210, 178–91.
Wilks, D. S., and Wilby, R. L., (1999). “The weather generation game: A review of stochastic weather models, Prog. Phys. Geogr., 23(3), 329–357.
Zawadzki, I. I., (1973). “Statistical properties of precipitation patterns.” J. Appl. Meteorol., 12(3), 459–472.
Information & Authors
Information
Published In
Journal of Hydrologic Engineering
Volume 16 • Issue 5 • May 2011
Pages: 484 - 492
Copyright
© 2011 American Society of Civil Engineers.
History
Received: Jan 4, 2010
Accepted: Sep 16, 2010
Published online: Oct 7, 2010
Published in print: May 1, 2011
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