Stochastic Integral Equations and Rainfall-Runoff Models

  • Theodore V. HromadkaII
  • Robert J. Whitley

Table of contents

  1. Front Matter
    Pages I-XVIII
  2. Theodore V. Hromadka II, Robert J. Whitley
    Pages 1-116
  3. Theodore V. Hromadka II, Robert J. Whitley
    Pages 117-168
  4. Theodore V. Hromadka II, Robert J. Whitley
    Pages 169-214
  5. Theodore V. Hromadka II, Robert J. Whitley
    Pages 215-261
  6. Theodore V. Hromadka II, Robert J. Whitley
    Pages 262-325
  7. Theodore V. Hromadka II, Robert J. Whitley
    Pages 326-367
  8. Back Matter
    Pages 368-384

About this book


The subject of rainfall-runoff modeling involves a wide spectrum of topics. Fundamental to each topic is the problem of accurately computing runoff at a point given rainfall data at another point. The fact that there is currently no one universally accepted approach to computing runoff, given rainfall data, indicates that a purely deter­ ministic solution to the problem has not yet been found. The technology employed in the modern rainfall-runoff models has evolved substantially over the last two decades, with computer models becoming increasingly more complex in their detail of describing the hydrologic and hydraulic processes which occur in the catchment. But despite the advances in including this additional detail, the level of error in runoff estimates (given rainfall) does not seem to be significantly changed with increasing model complexity; in fact it is not uncommon for the model's level of accuracy to deteriorate with increasing complexity. In a latter section of this chapter, a literature review of the state-of-the-art in rainfall-runoff modeling is compiled which includes many of the concerns noted by rainfall-runoff modelers. The review indicates that there is still no deterministic solution to the rainfall-runoff modeling problem, and that the error in runoff estimates produced from rainfall-runoff models is of such magnitude that they should not be simply ignored.


Integral equation calculus floods model modeling operator statistics uncertainty

Authors and affiliations

  • Theodore V. HromadkaII
    • 1
  • Robert J. Whitley
    • 2
  1. 1.Williamson & SchmidIrvineUSA
  2. 2.Dept. of MathematicsUniversity of CaliforniaIrvineUSA

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 1989
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-642-49311-9
  • Online ISBN 978-3-642-49309-6
  • Buy this book on publisher's site