Data Integration Issues in Research Supporting Sustainable Natural Resource Management

Herr, Alexander

doi:10.1111/j.1745-5871.2007.00476.x

Cited by 10 publications

(10 citation statements)

References 21 publications

(23 reference statements)

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“…Spatially-explicit social-ecological analyses are difficult because of the different scales at which socio-economic and biophysical data are collected and reported, the different units of measurement used for social and biophysical data, and the fact that the boundaries of biophysical and socio-economic variables do not coincide (Herr, 2007). Socio-economic data are generally reported at a coarse (administrative boundary) scale (even if data are collected at household level, these are normally aggregated) and tend not to be spatially referenced at finer scales.…”

Section: Introductionmentioning

confidence: 99%

Integrating socio-economic and biophysical data to support water allocations within river basins: An example from the Inkomati Water Management Area in South Africa

Lange

Wise

Forsyth

et al. 2010

Environmental Modelling & Software

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Sustainable natural resource management requires inputs from both the natural and the social sciences. Since natural and social systems are inter-related and inter-dependent, it is essential that these data can be integrated within a given analysis, which requires that they are spatially compatible. However, existing environmental and socio-economic monitoring networks tend to observe, collect and report socio-economic and biophysical data separately; with the result that much of these data are spatially incompatible, adding to the complexity of objective and consistent resource management. We present an approach for overcoming spatial incompatibilities between socio-economic and biophysical data; based on a meta-modelling approach using Geographical Information Systems and an application of a water-use simulation model. The method is developed and applied to the irrigation agriculture sector in the Inkomati Water Management Area in South Africa. Agricultural 2 census data, which is measured on a magisterial district scale, is integrated with georeferenced land cover data, which is independent of political boundaries. This allows us to increase the resolution at which data on the economic value derived from irrigation water is presented, from coarse magisterial district scale to a finer (49km 2 ) 'meso-zone' scale, enabling more efficient allocations of irrigation water within magisterial districts.

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Section: Introductionmentioning

confidence: 99%

Integrating socio-economic and biophysical data to support water allocations within river basins: An example from the Inkomati Water Management Area in South Africa

Lange

Wise

Forsyth

et al. 2010

Environmental Modelling & Software

View full text Add to dashboard Cite

show abstract

“…Spatial assessments are used to support the management of water resources and the environment [1][2][3][4][5][6][7][8]. Spatially varying distribution of population growth, changing water consumption, and changing climate have made water scarcity one of the key concerns in the world [4,9].…”

Section: Introductionmentioning

confidence: 99%

Exploring the Modifiable Areal Unit Problem in Spatial Water Assessments: A Case of Water Shortage in Monsoon Asia

Salmivaara

Porkka

Kummu

et al. 2015

Water

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Water shortage (availability per capita) is a key indicator of vulnerability to water scarcity. Spatial datasets enable the assessment of water shortage on multiple scales. The use of river basins and subbasins as analysis and management units is currently commonplace. An important but less acknowledged fact is that spatial assessments are strongly influenced by the choice of the unit of analysis due to the Modifiable Areal Unit Problem (MAUP). Climate conditions, agricultural activities, and access to groundwater also influence water availability and demand. In this study, a total of 21 different criteria were used to define areal units of analysis, i.e., zonings, for which water shortage was calculated. Focusing on Monsoon Asia, where water scarcity is a pressing problem, we found that zoning had a considerable impact, resulting in up to three-fold differences in the population under high water shortage (<1000 m 3 /cap/year), ranging from 782 million to 2.11 billion. In most zonings, however, the Indus and Yellow River Basins and northwest parts of India and China are under high water shortage. The study indicates that a multizonal and multiscale analysis is needed to minimize skewed or even misleading information that might be produced when using only one zoning.

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“…) can assist with the visualization of areas of high concentration for a widely distributed resource such as crop stubble. Further details on land use and methods for overlaying polygons of different size/shape to transfer values are described elsewhere (Herr, ; Herr & Dunlop, ).…”

Section: Methodsmentioning

confidence: 99%

A spatial assessment of potential biomass for bioenergy in Australia in 2010, and possible expansion by 2030 and 2050

et al. 2016

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This paper provides spatial estimates of potentially available biomass for bioenergy in Australia in 2010, 2030 and 2050 (under clearly stated assumptions) for the following biomass sources: crop stubble, native grasses, pulpwood and residues (created either during forest harvesting or wood processing) from plantations and native forests, bagasse, organic municipal solid waste and new short-rotation tree crops. For each biomass type, we estimated annual potential availability at the finest scale possible with readily accessible data, and then aggregated to make estimates for each of 60 Statistical Divisions (administrative areas) across Australia. The potentially available lignocellulosic biomass is estimated at approximately 80 Mt per year, with the major contributors of crop stubble (27.7 Mt per year), grasses (19.7 Mt per year) and forest plantations (10.9 Mt per year). Over the next 20-40 years, total potentially available biomass could increase to 100-115 Mt per year, with new plantings of short-rotation trees being the major source of the increase (14.7 Mt per year by 2030 and 29.3 Mt per year by 2050). We exclude oilseeds, algae and 'regrowth', that is woody vegetation naturally regenerating on previously cleared land, which may be important in several regions of Australia (Australian Forestry 77, 2014, 1; Global Change Biology Bioenergy 7, 2015, 497). We briefly discuss some of the challenges to providing a reliable and sustainable supply of the large amounts of biomass required to build a bioenergy industry of significant scale. More detailed regional analyses, including of the costs of delivered biomass, logistics and economics of harvest, transport and storage, competing markets for biomass and a full assessment of the sustainability of production are needed to underpin investment in specific conversion facilities (e.g. Opportunities for forest bioenergy: An assessment of the environmental and economic opportunities and constraints associated with bioenergy production from biomass resources in two prospective regions of Australia, 2011a).

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Data Integration Issues in Research Supporting Sustainable Natural Resource Management

Cited by 10 publications

References 21 publications

Integrating socio-economic and biophysical data to support water allocations within river basins: An example from the Inkomati Water Management Area in South Africa

Integrating socio-economic and biophysical data to support water allocations within river basins: An example from the Inkomati Water Management Area in South Africa

Exploring the Modifiable Areal Unit Problem in Spatial Water Assessments: A Case of Water Shortage in Monsoon Asia

A spatial assessment of potential biomass for bioenergy in Australia in 2010, and possible expansion by 2030 and 2050

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