EconPapers    
Economics at your fingertips  
 

A two‐field geostatistical model combining point and areal observations—A case study of annual runoff predictions in the Voss area

Thea Roksvåg, Ingelin Steinsland and Kolbjørn Engeland

Journal of the Royal Statistical Society Series C, 2021, vol. 70, issue 4, 934-960

Abstract: We estimate annual runoff by using a Bayesian geostatistical model for interpolation of hydrological data of different spatial support: streamflow observations from catchments (areal data), and precipitation and evaporation data (point data). The model contains one climatic spatial effect that is common for all years under study, and 1 year specific spatial effect. Hence, the framework enables a quantification of the spatial variability caused by long‐term weather patterns and processes. This can contribute to a better understanding of biases and uncertainties in environmental modelling. The suggested model is evaluated by predicting annual runoff for catchments around Voss in Norway and through a simulation study. We find that on average we benefit from combining point and areal data compared to using only one of the data types, and that the interaction between nested areal data and point data gives a spatial model that takes us beyond smoothing. Another finding is that when climatic effects dominate over annual effects, systematic under‐ and overestimation of runoff can be expected over time. However, a dominating climatic spatial effect also implies that short records of runoff from an otherwise ungauged catchment can lead to large improvements in the predictive performance.

Date: 2021
References: Add references at CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
https://doi.org/10.1111/rssc.12492

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssc:v:70:y:2021:i:4:p:934-960

Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-9876

Access Statistics for this article

Journal of the Royal Statistical Society Series C is currently edited by R. Chandler and P. W. F. Smith

More articles in Journal of the Royal Statistical Society Series C from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().

 
Page updated 2021-08-08
Handle: RePEc:bla:jorssc:v:70:y:2021:i:4:p:934-960