Assessment of a Precipitation Data Network for Design of an Irrigation Scheme

  1. AGU Hydrology Section
  1. I. Simmers

Published Online: 19 MAR 2013

DOI: 10.1029/SP004p0038

Precipitation Analysis for Hydrologic Modeling

Precipitation Analysis for Hydrologic Modeling

How to Cite

Simmers, I. (1975) Assessment of a Precipitation Data Network for Design of an Irrigation Scheme, in Precipitation Analysis for Hydrologic Modeling (ed AGU Hydrology Section), American Geophysical Union, Washington, D. C.. doi: 10.1029/SP004p0038

Author Information

  1. Department of Earth Sciences, University of Waikato, Hamilton, New Zealand

Publication History

  1. Published Online: 19 MAR 2013
  2. Published Print: 1 JAN 1975

ISBN Information

Print ISBN: 9781118656037

Online ISBN: 9781118668993



  • Annual mean rainfall;
  • Correlation coefficients;
  • Covariance function;
  • Gauge density;
  • Maniototo Plains;
  • Taieri basin


To plan a data collection programme it is vital to first establish the purposes for which the gathered data are to be used, and the degree of precision of the information at a particular confidence level that will be adequate.

This study forms part of a larger project which is concerned with the data requirements and analyses for the planning of an irrigation scheme in the Maniototo Plains and Styx Basin, Central Otago. Ten percent is chosen as the standard error allowed for rainfall population parameter estimation.

Precipitation records to 1966 were insufficient for a water resources appraisal of the area and necessitated extension of the data collection network. It is thus essential to be able to determine the network density required to assess rainfall over an area to the given precision level. Earlier techniques used to estimate the errors, and thus the optimum network density, are rejected in favour of the structural function method described by Gandin (1970) and by Cislerova and Hutchinson (1973).

The results here suggest that the established precipitation gauges are within the bounds of acceptable density and location to satisfy the allowable error criterion for annual data. Between gauge distances of up to 50 km could be tolerated.

Results for the monthly data are less promising. Analysis shows that in no month does the present network allow mean areal rainfall estimation to within 20 percent of actual at the 95 percent confidence level. Further, in only five months is it possible to estimate values with standard errors of less than 10 percent, no matter how dense the network. The allowable error for parameter estimation thus appears too stringent a criterion for the study area, though a higher value may be unacceptable for engineering design purposes.

It is further deduced that the errors associated with individual station catch will determine the limit of estimated parameter precision. All station records from the post-1966 network thus require extension if areal population parameters are to be estimated to within the allowable total error, even though the present network design is theoretically acceptable for many purposes.