Supporting the Sustainable Development Goals: A context sensitive indicator for sustainable use of water at the facility level

SUSTAINABLE DEVELOPMENT(2022)

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摘要
This paper presents a low-cost and scalable method for providing a sustainable water allocation for enterprises based on the hydrological, economic, and demographic contexts of their facilities. Context-based performance indicators are vital for effectively monitoring and achieving the Sustainable Development Goals (SDGs). Currently, the SDGs consist of 17 goals that are associated with 169 targets and 232 indicators. Making valid and objective measurements of the 232 indicators represents a significant challenge for scientists and policy makers. Achieving the SDGs will likely involve significant efforts in developing and sustaining systems for monitoring status and progress, providing incentives, and conducting enforcement. Provision of low-cost Sustainable Development Performance Indicators (SDPIs) of progress at high spatial and temporal resolution is essential for effective management by governments and businesses. The water allocations we produce are based on a facility's total and consumptive use of water, their contribution to gross domestic product (GDP), their number of full-time employees, the population and GDP of several geographic contexts, and the annually specific hydrological balance (i.e., precipitation minus evapotranspiration) of those contexts. The allocations and related sustainability assessments are determined for a range of geographic contexts (circular regions centered on the facility with radii of 10, 50, 100, 200, and 300 km respectively). From the hydrological data we give priority to 'Water for Nature' and allocate a proportion of the remaining 'Water for Economy' to the facility based on their contribution to GDP and the number of full-time employees they have. This allocation is compared to their actual water withdrawals to provide an indication of the sustainability of their economic activity.
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关键词
context-based SDGs, earth observation data for SDGs, SDPI, water allocation, water for environment
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