Phosphorus budget in the water-agro-food system at nested scales in two contrasted regions of the world (ASEAN-8 and EU-27)

International audiencePhosphorus (P) plays a strategic role in agricultural production as well as in the occurrence of freshwater and marine eutrophication episodes throughout the world. Moreover, the scarcity and uneven distribution of minable P resources is raising concerns about the sustainability of long-term exploitation. In this paper we analyze the P cycle in anthropic systems with an original multiscale approach (world region, country, and large basin scales) in two contrasting world regions representative of different trajectories in socioeconomic development for the 1961-2009 period: Europe (EU-27)/France and the Seine River Basin, and Asia (ASEAN-8)/Vietnam and the Red River Basin. Our approach highlights different trends in the agricultural and food production systems of the two regions. Whereas crop production increased until the 1980s in Europe and France and has stabilized thereafter, in ASEAN-8 and Vietnam it began to increase in the 1980s and it is still rising today. These trends are related to the increasing use of fertilizers, although in European countries the amount of fertilizers sharply decreased after the 1980s. On average, the total P delivered from rivers to the sea is 3 times higher for ASEAN-8 (300kgPkm(-2)yr(-1)) than for EU-27 countries (100kgPkm(-2)yr(-1)) and is twice as high in the Red River (200kgPkm(-2)yr(-1)) than in the Seine River (110kgPkm(-2)yr(-1)), with agricultural losses to water in ASEAN-8 3 times higher than in EU-27. Based on the P flux budgets, this study discusses early warnings and management options according to the particularities of the two world regions, newly integrating the perspective of surface water quality with agricultural issues (fertilizers, crop production, and surplus), food/feed exchanges, and diet, defining the so-called water-agro-food system

How can water quality be improved when the urban waste water directive has been fulfilled? A case study of the Lot river (France)

International audienceThe Lot river, a major tributary of the downstream Garonne river, the largest river on the Northern side of the Pyrenees Mountains, was intensively studied in the 1970s. A pioneering program called “Lot Rivière Claire” provided a diagnosis of water quality at the scale of the whole watershed and proposed an ambitious program to manage nutrient pollution and eutrophication largely caused by urban wastewater releases. Later on, the implementation of European directives from 1991 to 2000 resulted in the nearly complete treatment of point sources of pollution in spite of a doubling of the basin’s population. At the outlet of the Lot river, ammonium and phosphate contamination which respectively peaked to 1 mg N-NH4 L−1 and 0.3 mg P-PO4 L−1 in the 1980s returned to much lower levels in recent years (0.06 mg N-NH4 L−1 and 0.02 mg P-PO4 L−1), a reduction by a factor 15. However, during this time, nitrate contamination has regularly increased since the 1980s, from 0.5 to 1.2 mg N-NO3 L−1 in average, owing to the intensification of agriculture and livestock farming. Application of the Riverstrahler model allowed us to simulate the water quality of the Lot drainage network for the 2002–2014 period. We showed that, with respect to algal requirements, phosphorus and silica are well balanced, but nitrogen remains largely in excess over phosphorus and silica. This imbalance can be problematic for the ecological status of the water bodies. Using the model, for simulating various scenarios of watershed management, we showed that improvement of urban wastewater treatment would not result in any significant change in the river’s water quality. Even though arable land occupies a rather limited fraction of the watershed area, only the adoption of better farming practices or more radical changes in the agro-food system could reverse the trend of increasing nitrate contamination

Ecological Functioning of the Seine River: From Long-Term Modelling Approaches to High-Frequency Data Analysis

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