Uncertainty in the estimation of drought risk due to soil-climate interactions in Scotland

Laura Poggio; Alessandro Gimona; Iain Brown; Marie Castellazzi

Uncertainty in the estimation of drought risk due to soil-climate interactions in Scotland

Laura Poggio (Lead / Corresponding author), Alessandro Gimona, Iain Brown, Marie Castellazzi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The impact of climate change on ecosystems is a global issue. As a result of the interaction between decreasing precipitation during the growth period and soil properties, the water available for plants and crops may become a limitation factor for crops or certain forest species in some areas in Scotland. The aim of this study was to estimate the uncertainty of a model predicting drought risk in the Dee catchment in the North East of Scotland. The model focuses on the fundamental interactions between soil and climate, which are the critical drivers for determining the available water capacity. Soil available water capacity was calculated, using pedotransfer functions, with data derived from the Scottish Soil Survey Database at ca. 100 profiles. We used a variation of regression kriging to interpolate the data. The preliminary results showed that the uncertainty related to soil modelling is higher in areas with rougher morphology and complex hydrology. A Bayesian framework for uncertainty integration of soil and climate interactions is briefly presented. The evaluated overall uncertainty is useful to underpin informed policy decisions, via risk assessment.

Original language	English
Title of host publication	Accuracy 2010
Subtitle of host publication	Proceedings of the 9th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences
Editors	Nicholas J. Tate, Peter F. Fisher
Publisher	International Spatial Accuracy Research Association
Pages	61-64
Number of pages	4
Publication status	Published - 2010
Event	9th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, Accuracy 2010 - Leicester, United Kingdom Duration: 20 Jul 2010 → 23 Jul 2010

Conference

Conference	9th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, Accuracy 2010
Country/Territory	United Kingdom
City	Leicester
Period	20/07/10 → 23/07/10

Keywords

Gaussian simulations
General additive model
Geostatistics
Spatial uncertainty
Stochastic modelling

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

http://www.spatial-accuracy.org/PoggioAccuracy2010

Cite this

Poggio, L., Gimona, A., Brown, I., & Castellazzi, M. (2010). Uncertainty in the estimation of drought risk due to soil-climate interactions in Scotland. In N. J. Tate, & P. F. Fisher (Eds.), Accuracy 2010: Proceedings of the 9th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences (pp. 61-64). International Spatial Accuracy Research Association. http://www.spatial-accuracy.org/PoggioAccuracy2010

Poggio, Laura ; Gimona, Alessandro ; Brown, Iain et al. / Uncertainty in the estimation of drought risk due to soil-climate interactions in Scotland. Accuracy 2010: Proceedings of the 9th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences. editor / Nicholas J. Tate ; Peter F. Fisher. International Spatial Accuracy Research Association, 2010. pp. 61-64

@inproceedings{7ab94ca750c14c7881f303a67b9fb39d,

title = "Uncertainty in the estimation of drought risk due to soil-climate interactions in Scotland",

abstract = "The impact of climate change on ecosystems is a global issue. As a result of the interaction between decreasing precipitation during the growth period and soil properties, the water available for plants and crops may become a limitation factor for crops or certain forest species in some areas in Scotland. The aim of this study was to estimate the uncertainty of a model predicting drought risk in the Dee catchment in the North East of Scotland. The model focuses on the fundamental interactions between soil and climate, which are the critical drivers for determining the available water capacity. Soil available water capacity was calculated, using pedotransfer functions, with data derived from the Scottish Soil Survey Database at ca. 100 profiles. We used a variation of regression kriging to interpolate the data. The preliminary results showed that the uncertainty related to soil modelling is higher in areas with rougher morphology and complex hydrology. A Bayesian framework for uncertainty integration of soil and climate interactions is briefly presented. The evaluated overall uncertainty is useful to underpin informed policy decisions, via risk assessment.",

keywords = "Gaussian simulations, General additive model, Geostatistics, Spatial uncertainty, Stochastic modelling",

author = "Laura Poggio and Alessandro Gimona and Iain Brown and Marie Castellazzi",

year = "2010",

language = "English",

pages = "61--64",

editor = "Tate, {Nicholas J.} and Fisher, {Peter F.}",

booktitle = "Accuracy 2010",

publisher = "International Spatial Accuracy Research Association",

note = "9th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, Accuracy 2010 ; Conference date: 20-07-2010 Through 23-07-2010",

}

Poggio, L, Gimona, A, Brown, I & Castellazzi, M 2010, Uncertainty in the estimation of drought risk due to soil-climate interactions in Scotland. in NJ Tate & PF Fisher (eds), Accuracy 2010: Proceedings of the 9th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences. International Spatial Accuracy Research Association, pp. 61-64, 9th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, Accuracy 2010, Leicester, United Kingdom, 20/07/10. <http://www.spatial-accuracy.org/PoggioAccuracy2010>

Uncertainty in the estimation of drought risk due to soil-climate interactions in Scotland. / Poggio, Laura (Lead / Corresponding author); Gimona, Alessandro; Brown, Iain et al.

Accuracy 2010: Proceedings of the 9th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences. ed. / Nicholas J. Tate; Peter F. Fisher. International Spatial Accuracy Research Association, 2010. p. 61-64.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Uncertainty in the estimation of drought risk due to soil-climate interactions in Scotland

AU - Poggio, Laura

AU - Gimona, Alessandro

AU - Brown, Iain

AU - Castellazzi, Marie

PY - 2010

Y1 - 2010

N2 - The impact of climate change on ecosystems is a global issue. As a result of the interaction between decreasing precipitation during the growth period and soil properties, the water available for plants and crops may become a limitation factor for crops or certain forest species in some areas in Scotland. The aim of this study was to estimate the uncertainty of a model predicting drought risk in the Dee catchment in the North East of Scotland. The model focuses on the fundamental interactions between soil and climate, which are the critical drivers for determining the available water capacity. Soil available water capacity was calculated, using pedotransfer functions, with data derived from the Scottish Soil Survey Database at ca. 100 profiles. We used a variation of regression kriging to interpolate the data. The preliminary results showed that the uncertainty related to soil modelling is higher in areas with rougher morphology and complex hydrology. A Bayesian framework for uncertainty integration of soil and climate interactions is briefly presented. The evaluated overall uncertainty is useful to underpin informed policy decisions, via risk assessment.

AB - The impact of climate change on ecosystems is a global issue. As a result of the interaction between decreasing precipitation during the growth period and soil properties, the water available for plants and crops may become a limitation factor for crops or certain forest species in some areas in Scotland. The aim of this study was to estimate the uncertainty of a model predicting drought risk in the Dee catchment in the North East of Scotland. The model focuses on the fundamental interactions between soil and climate, which are the critical drivers for determining the available water capacity. Soil available water capacity was calculated, using pedotransfer functions, with data derived from the Scottish Soil Survey Database at ca. 100 profiles. We used a variation of regression kriging to interpolate the data. The preliminary results showed that the uncertainty related to soil modelling is higher in areas with rougher morphology and complex hydrology. A Bayesian framework for uncertainty integration of soil and climate interactions is briefly presented. The evaluated overall uncertainty is useful to underpin informed policy decisions, via risk assessment.

KW - Gaussian simulations

KW - General additive model

KW - Geostatistics

KW - Spatial uncertainty

KW - Stochastic modelling

M3 - Conference contribution

AN - SCOPUS:84975706392

SP - 61

EP - 64

BT - Accuracy 2010

A2 - Tate, Nicholas J.

A2 - Fisher, Peter F.

PB - International Spatial Accuracy Research Association

T2 - 9th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, Accuracy 2010

Y2 - 20 July 2010 through 23 July 2010

ER -

Poggio L, Gimona A, Brown I, Castellazzi M. Uncertainty in the estimation of drought risk due to soil-climate interactions in Scotland. In Tate NJ, Fisher PF, editors, Accuracy 2010: Proceedings of the 9th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences. International Spatial Accuracy Research Association. 2010. p. 61-64

Uncertainty in the estimation of drought risk due to soil-climate interactions in Scotland

Abstract

Conference

Keywords

UN SDGs

Access to Document

Fingerprint

Cite this