The relationship between time series models for water table depth and physical information
The relationship between parameters of autoregressive moving average exogenous variable (ARMAX) models and physical information that can be derived from databases such as digital topographical maps, digital elevation maps and soil profile descriptionswas investigated at 51 sites with open sandy soils in the Pleistocene part of the Netherlands, The ARMAX parameters appeared to be weakly related with physical information. Water-table depth predicted with ARMAX models which were guessed using physical information have large systematic errors but relatively small random errors. It is concluded tha... Mehr ...
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| Dokumenttyp: | report |
| Erscheinungsdatum: | 1998 |
| Verlag/Hrsg.: |
DLO Winand Staring Centre
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| Schlagwörter: | data analysis / evaluation / models / netherlands / soil / time series / topography / water table / bodem / evaluatie / gegevensanalyse / grondwaterspiegel / modellen / nederland / tijdreeksen / topografie |
| Sprache: | Englisch |
| Permalink: | https://search.fid-benelux.de/Record/base-26776209 |
| Datenquelle: | BASE; Originalkatalog |
| Powered By: | BASE |
| Link(s) : | https://research.wur.nl/en/publications/the-relationship-between-time-series-models-for-water-table-depth |
The relationship between parameters of autoregressive moving average exogenous variable (ARMAX) models and physical information that can be derived from databases such as digital topographical maps, digital elevation maps and soil profile descriptionswas investigated at 51 sites with open sandy soils in the Pleistocene part of the Netherlands, The ARMAX parameters appeared to be weakly related with physical information. Water-table depth predicted with ARMAX models which were guessed using physical information have large systematic errors but relatively small random errors. It is concluded that the relationships between time series model paremters and physical information can be improved with respect to the modelling as well as the quality of the data used.