An integrated approach to linking economic valuation and catchment modelling

被引:84
作者
Kragt, M. E. [1 ,2 ]
Newham, L. T. H. [2 ]
Bennett, J. [1 ]
Jakeman, A. J. [2 ,3 ]
机构
[1] Australian Natl Univ, Crawford Sch Econ & Govt, Canberra, ACT 2600, Australia
[2] Australian Natl Univ, Fenner Sch Environm & Soc, Integrated Catchment Assessment & Management ICAM, Canberra, ACT 2600, Australia
[3] Australian Natl Univ, Natl Ctr Groundwater Res & Training, Canberra, ACT 0200, Australia
关键词
Bayesian networks; Catchment scale modelling; Choice experiments; Environmental values; Integrated water resources management; Knowledge integration; Model development; BAYESIAN BELIEF NETWORKS; 10 ITERATIVE STEPS; NEW-SOUTH-WALES; DECISION-SUPPORT; SOURCE POLLUTION; RIVER-BASIN; MANAGEMENT; FRAMEWORK; CHOICE; QUEENSLAND;
D O I
10.1016/j.envsoft.2010.04.002
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
An increased emphasis on integrated water management at a catchment scale has led to the development of numerous modelling tools. To support efficient decision making and to better target investment in management actions, such modelling tools need to link socioeconomic information with biophysical data. However, there is still limited experience in developing catchment models that consider environmental changes and economic values in a single framework. We describe a model development process where biophysical modelling is integrated with economic information on the non-market environmental costs and benefits of catchment management changes for a study of the George catchment in northeast Tasmania, Australia. An integrated assessment approach and Bayesian network modelling techniques were used to integrate knowledge about hydrological, ecological and economic systems. Rather than coupling existing information and models, synchronous data collection and model development ensured tailored information exchange between the different components. The approach is largely transferable to the development of integrated hydro-economic models in other river catchments. Our experiences highlight the challenges in synchronizing economic and scientific modelling. These include the selection of common attributes and definition of their levels suitable for the catchment modelling and economic valuation. The lessons from the model development process are useful for future studies that aim to integrate scientific and economic knowledge. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码:92 / 102
页数:11
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