The results show a high probability of not meeting the groundwater quality standards when 25 deriving a policy from just a deterministic analysis. To increase the reliability several 26 realizations can be optimized at the same time. By using a mixed-integer stochastic 27 formulation, the desired reliability level of the strategy can be fixed in advance. The approach 28 allows deriving the trade-offs between the reliability of meeting the standard and the net 29 benefits from agricultural production. In a risk-averse decision-making, not only the reliability 30 of meeting the standards counts, but also the probability distribution of the maximum pollutant 31 concentrations.A sensitivity analysis was carried out to assess the influence of the variance of 32 the hydraulic conductivity fields on the strategies.The results have shown that larger the 33 variance, greater the range of maximum nitrate concentrations and the worst-case (or maximum 34 value) that could be reached for the same level of reliability. 35

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Among the difficulties and uncertainties that arise when determining water balance is the calculation of groundwater abstraction. This factor is particularly important in aquifers whose extension and heavy agricultural use make direct quantification methods unfeasible (i.e. flow meters and power consumption data). This study presents a method of quantifying groundwater abstractions for irrigation based on the analysis of multitemporal and multispectral satellite images. The process begins with a highly detailed classification of irrigated crops; these data are entered in a Geographic Information System, overlain with a correct estimate of the irrigation requirements of the crop, and corrected in accordance with the agricultural practices of the area. The results reveal the spatial and temporal distribution of the groundwater volume abstracted and used for agriculture. This methodology has been applied in the Mancha Oriental Hydrogeological System (Spain, 7,260 km 2 ), where abstractions for agriculture comprise more than 90% of the hydrological resources consumed. In this context, accuracies of over 95% have been obtained with a cost sixty times lower than that of traditional methods.

Wildland fires are one of the major causes of ecosystem degradation, especially in semiarid climates, where the erosion hazard is high. The identification of potential erosion zones is typically difficult as it requires expensive field and laboratory work. This paper proposes a methodology based on remote sensing and GIS techniques, which permits speedy identification of erosional areas in a semi-automatic way, tested in a large burn scar in south-eastern Spain. Inputs were slope, aspect, and fire severity. In order to obtain the latter a new method has been proposed, based on the difference in NDVI between two images (acquired before and after the fire event). Combining these maps in a GIS, a Forest Intervention Priority map (FIP) is produced, which identifies areas of high erosion potential. Field work was conducted to assess the method. Results indicate that the applied methodology reliably predicted the extent of very severe fire and, further, was generally useful for identifying sites of significant erosion. Additional work is required to refine: (1) remotely sensed fire severity thresholds, particularly for other Mediterranean forest systems and substrate conditions; and (2) associated mapping tools for informing post-fire management applications.

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