A first global and spatially explicit emergy database of rivers and streams based on high-resolution GIS-maps

In emergy evaluation (EME), water is often identified as the main renewable resource input of a natural or human system. Water flows in EME have been generally examined with a global perspective, i.e. without considering topographical and climatic differences at regional or local scales. Hence, spatial differentiation in water flows characterization is essential to improve the quality of EME results. This paper introduces the first global, spatially explicit emergy dataset of freshwater flows, developed following the rationale found in prior EMEs of rivers. The unit emergy value (UEV) of a stream was calculated as the highest value between rain chemical potential emergy and rain geopotential emergy over the streamʹs catchment area, divided by the stream flow rate. This approach was applied with a high resolution and a global coverage, using Geographic Information System (GIS) software and, notably, world maps of precipitation, evapotranspiration and elevation, to estimate accumulation patterns of rainfall emergy value and flow rates. Preliminary results are compared with available data on riverʹs UEVs retrieved from previous studies and with the actual stream flow of major rivers in the world and in France. While flow rates modeled in the database show important differences as compared to actual data, the comparison of the modeled emergy value of rivers with prior studies was made difficult by the heterogeneity in calculation details observed previously. Therefore, it is highly recommended for the emergy community to foster the use and improvement of such high-resolution, spatially explicit dataset instead of using regional or global UEV averages, which should only be used when reliable local values are not available. Hence, territorial averages were computed in order to characterize background processes in the hybrid lifecycle-emergy accounting framework, as this approach can complement and enrich the conventional EME with the inclusion of detailed information on supply chain processes. To this aim, data were aggregated over major watersheds and administrative regions, and weighted with a proxy for urban surface water consumption. The next steps identified to enhance our prospective work include: (1) the characterization of water reservoirs (glaciers, lakes, groundwater, soil moisture), (2) the improvement of runoff modeling and stream flows, (3) the spatial assessment of atmospheric processes to refine transformities of rain (chemical potential and geopotential), and (4) the inclusion of additional elements such as sediments, minerals and particulate matter as a flow of emergy in rivers.