SENSITIVITY OF LINEAR AND NONLINEAR SURFACE RUNOFF MODELS TO INPUT ERRORS

The relationship is examined between errors in runoff peak predictions by linear and nonlinear surface runoff models and errors in input intensity. It is shown that if input intensity errors are sufficiently large, a linear model optimally identified according to a least-squares criterion may perform better than a nonlinear model even though the system is truly nonlinear.

• Corporate Authors:

  Elsevier

  Radarweg 29
  Amsterdam,   Netherlands  1043 NX
• Authors:
  • Singh, V P
  • Woolhiser, D A
• Publication Date: 1976-4

Media Info

• Features: Figures; References; Tables;
• Pagination: p. 243-249
• Serial:
  • Journal of Hydrology
  • Volume: 29
  • Issue Number: 3/4

Subject/Index Terms

• TRT Terms: Drainage; Errors; Linear equations; Linearity; Mathematical models; Nonlinear systems; Runoff; Weather forecasting
• Uncontrolled Terms: Input; Models; Nonlinearity
• Subject Areas: Highways; Hydraulics and Hydrology;

Filing Info

• Accession Number: 00136336
• Record Type: Publication
• Files: TRIS
• Created Date: Jul 13 1976 12:00AM