JOURNAL ARTICLE

SHORT‐TERM FORECASTING OF SNOWMELT RUNOFF USING ARMAX MODELS1

Jeffrey P. HaltinerJosé D. Salas

Year: 1988 Journal:   JAWRA Journal of the American Water Resources Association Vol: 24 (5)Pages: 1083-1089   Publisher: Wiley

Abstract

ABSTRACT: Time series models of the ARMAX class were investigated for use in forecasting daily riverflow resulting from combined snowmelt/rainfall. The Snowmelt Runoff Model (Martinec‐Rango Model) is shown to have a form similar to the ARMAX model. The advantage of the ARMAX approach is that analytical model identification and parameter estimation techniques are available. In addition, previous forecast errors can be included to improve forecasts and confidence limits can be estimated for the forecasts. Diagnostic checks are available to determine if the model is performing properly. Finally, Kalman filtering can be used to allow the model parameters to vary continuously to reflect changing basin runoff conditions. The above advantages result in improved flow forecasts with fewer model parameters.

Keywords:
Snowmelt Kalman filter Surface runoff Environmental science Identification (biology) Term (time) Econometrics Computer science Meteorology Statistics Mathematics Snow Geography

Metrics

40
Cited By
0.88
FWCI (Field Weighted Citation Impact)
6
Refs
0.75
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Hydrology and Watershed Management Studies
Physical Sciences →  Environmental Science →  Water Science and Technology
Hydrological Forecasting Using AI
Physical Sciences →  Environmental Science →  Environmental Engineering
Flood Risk Assessment and Management
Physical Sciences →  Environmental Science →  Global and Planetary Change

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