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Best one step ahead prediction in hydrology
Author(s) -
Wallis James R.
Publication year - 1972
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/wr008i002p00529
Subject(s) - autoregressive integrated moving average , autoregressive model , box–jenkins , mathematics , statistics , econometrics , set (abstract data type) , sample (material) , hydrology (agriculture) , computer science , time series , engineering , geotechnical engineering , chemistry , chromatography , programming language
Recent papers suggest that stochastic one step ahead prediction is an important growth field in hydrology; two examples of this viewpoint are papers by Rao and Kashyap [1971] and Carlson et al . [1970]. More specifically, it is beginning to appear that ‘best one step ahead prediction’ is to be equated to the quasi objective procedure developed by Box and Jenkins for other purposes. For the uninitiated let me state that the Box and Jenkins procedure is a recipe that one can follow if one wishes to choose a specific model from the domain of autoregressive integrated moving average models (ARIMA) ( p , d , q ). Even if we are to set aside all of the technical problems relative to selecting objective criteria, small sample biases, seasonal and diurnal variability, and what might best be called the type 2 error fitting problem, there are still philosophical and evaluation problems connected with applying this approach to short‐term hydrologic forecasting.