Abstract. The impact of implementing different best management practices (BMPs) at the 1 small watershed scale were examined for the Petzenkirchen catchment in Austria and Lake 2 Vico in Italy, in terms of data needs, hydrological processes, tools and models involved.

Nitrogen loading to the Bassin d'Arcachon coastal lagoon (SW France) was evaluated by studying land-use and nitrogen output in its 3001 km2 catchment. At present, the catchment is dominated by forestry (79%), while intensive agriculture occupies 9% of the surface. The N-output of two hydrological subunits, i.e. the Tagon subunit dominated by pine forestry and the Arriou II subunit comprising both forestry and intensive agriculture, were monitored for a seven year period (1996)(1997)(1998)(1999)(2000)(2001)(2002). From these observations it was calculated that forestry contributes on average 1.6 kg total N ha−1 yr−1, which is dominated by organic nitrogen (DON + PON are 70% of N). On an areal basis, intensive agriculture contributes 26 times more than forestry, i.e. 41.6 kg total N ha−1 yr−1, which is mainly in the form of nitrate (65% of N). These data were upscaled to the catchment and the upscaling was validated by comparison to gauged nitrogen throughputs for the catchment of the Leyre river that is the major tributary to the system. Taking into account the other known N sources and the interannual variability in the catchment it was estimated that nitrogen loading to the lagoon was on average 90 kg ha−1 yr−1 (range from 54 to 126 kg ha−1 yr−1). The sandy soils of the catchment have a clear potential for denitrification, but anoxic conditions (waterlogged) and input of organic matter to fuel this process are required. Currently, agricultural practices and spatial planning do not make use of this potential. Nitrogen loading in the Bassin d'Arcachon is reflected by 10-40 μM nitrate concentrations in winter, which became depleted during spring as a result of uptake by vegetation. Short-term uptake experiments showed that the macroalga Monostroma obscurum is well adapted to temperatures between 10 to 20 °C and competitive with respect to the seagrass Zostera noltii when the nitrate concentrations are above 10 μM. Spring conditions with high nitrate and high insolation are therefore favourable for M. obscurum and this species presents a high risk for algal blooming. In contrast, the macroalga Enteromorpha clathrata well adapted to summertime temperatures around 25 °C, forms occasionally blooms in the lagoon. This phenomenon is limited due to the low DIN concentrations in summer.

No abstract

Two spatial optimization approaches, developed from the opposing perspectives of ecological economics and landscape planning and aimed at the definition of new distributions of farming systems and of land use elements, are compared and integrated into a general framework. The first approach, applied to a small river catchment in southwestern France, uses SWAT (Soil and Water Assessment Tool) and a weighted goal programming model in combination with a geographical information system (GIS) for the determination of optimal farming system patterns, based on selected objective functions to minimize deviations from the goals of reducing nitrogen and maintaining income. The second approach, demonstrated in a suburban landscape near Leipzig, Germany, defines a GIS-based predictive habitat model for the search of unfragmented regions suitable for hare populations (Lepus europaeus), followed by compromise optimization with the aim of planning a new habitat structure distribution for the hare. The multifunctional problem is solved by the integration of the three landscape functions ("production of cereals," "resistance to soil erosion by water," and "landscape water retention"). Through the comparison, we propose a framework for the definition of optimal land use patterns based on optimization techniques. The framework includes the main aspects to solve land use distribution problems with the aim of finding the optimal or best land use decisions. It integrates indicators, goals of spatial developments and stakeholders, including weighting, and model tools for the prediction of objective functions and risk assessments. Methodological limits of the uncertainty of data and model outcomes are stressed. The framework clarifies the use of optimization techniques in spatial planning.

No abstract