Mathematical models describing the surface runoff hydrograph from a watershed can be classified as either linear or nonlinear. Linear models are routinely used because of their mathematical tractability although it is generally recognized that watersheds are inherently nonlinear. This paper examines the sensitivity of predictions of runoff peak and its time by five linear and nonlinear surface runoff models to errors in rainfall excess. It is shown that if rainfall excess errors are sufficiently large, a perfectly identified nonlinear model does not perform always as well as an optimally identified linear model in predicting runoff peak, according to an objective function based upon fitting of runoff peaks. Thus, if one is not very confident in estimates of watershed infiltration then in some circumstances linear models may have an advantage over nonlinear models in runoff peak predictions because they do not amplify the input errors. /Author/

  • Corporate Authors:

    Elsevier Science

    Radarweg 29, P.O. Box 211
    1043NX AE Amsterdam,   Netherlands 
  • Authors:
    • Singh, V P
  • Publication Date: 1977-5

Media Info

  • Features: Figures; References; Tables;
  • Pagination: p. 301-318
  • Serial:

Subject/Index Terms

Filing Info

  • Accession Number: 00157760
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Oct 13 1977 12:00AM