Information on sediment sources in river catchments is required for effective sediment control strategies, to understand sediment, nutrient and pollutant transport, and for developing soil erosion management plans. Sediment fingerprinting procedures are employed to quantify sediment source contributions and have become a widely used tool. As fingerprinting procedures are naturally variable and locally dependant, there are different applications of the procedure. Here, the auto-evaluation of different fingerprinting procedures using virtual sample mixtures is proposed to support the selection of the fingerprinting procedure with the best capacity for source discrimination and apportionment. Surface samples from four land uses from a Central Spanish Pyrenean catchment were used i) as sources to generate the virtual sample mixtures and ii) to characterise the sources for the fingerprinting procedures. The auto-evaluation approach involved comparing fingerprinting procedures based on four optimum composite fingerprints selected by three statistical tests, three source characterisations (mean, median and corrected mean) and two types of objective functions for the mixing model. A total of 24 fingerprinting procedures were assessed by this new approach which were solved by Monte Carlo simulations and compared using the root mean squared error (RMSE) between known and assessed source ascriptions for the virtual sample mixtures. It was found that the source ascriptions with the highest accuracy were achieved using the corrected mean source characterisations for the composite fingerprints selected by the Kruskal Wallis H-test and principal components analysis. Based on the RMSE results, high goodness of fit (GOF) values were not always indicative of accurate source apportionment results, and care should be taken when using GOF to assess mixing model performance. The proposed approach to test different fingerprinting procedures using virtual sample mixtures provides an enhanced basis for selecting procedures that can deliver optimum source discrimination and apportionment.

Mountain wetlands in Mediterranean regions are particularly threatened in agricultural environments due to anthropogenic activity. An integrated study of source-to-sink sediment fluxes was carried out in an agricultural catchment that holds a small permanent lake included in the European NATURA 2000 Network. More than 1000 yrs of human intervention and the variety of land uses pose a substantial challenge when attempting to estimate sediment fluxes which is the first requirement to protect fragile wetlands. To date, there have been few similar studies and those that have been carried out have not addressed such complex terrain. Geostatistical interpolation and GIS tools were used to derive the soil spatial redistribution from point (137)Cs inventories, and to establish the sediment budget in a catchment located in the Southern Pyrenees. The soil redistribution was intense and soil erosion predominated over soil deposition. On the areas that maintained natural vegetation the median soil erosion and deposition rates were moderate, ranging from 2.6 to 6 Mg ha yr(-1) and 1.5 to 2.1 Mg ha yr(-1), respectively. However, in cultivated fields both erosion and deposition were significantly higher (ca. 20 Mg ha yr(-1)), and the maximum rates were always associated with tillage practices. Farming activities in the last part of the 20th century intensified soil erosion, as evidenced by the 1963 (137)Cs peaks in the lake cores and estimates from the sediment budget indicated a net deposition of 671 Mg yr(-1). Results confirm a siltation risk for the lake and provide a foundation for designing management plans to preserve this threatened wetland. This comprehensive approach provides information useful for understanding processes that influence the patterns and rates of soil transfer and deposition within fragile Mediterranean mountain wetlands subjected to climate and anthropogenic stresses.

In the Mediterranean region, the long history of cultivation is associated with significant changes in the original landscape. Agricultural intensification and subsequent land abandonment and reforestation have significantly affected the hydrological behaviour and connectivity patterns of hydrological systems. Thus, information on the spatial distribution of land use/cover is essential for monitoring the runoff response to interpret catchment hydrology. A medium-size catchment of the central part of the Ebro Basin (NE Spain), representative of Mediterranean mountain agroecosystems, was selected to assess the effect of land use/cover changes during the last few decades on the hydrological network of the catchment. To this end, a topography-based index, the -index of connectivity‖ (IC), was applied to assess the effects of land use changes from 1957-2010. The sediment connectivity was estimated using a geomorphometric approach to simulate how connectivity changes due This article is protected by copyright. All rights reserved.to the different land covers. To improve this index, we used a combination of C-factor, rugosity index and the novel application of a total aerial biomass equation (TAB) over pine reforested areas as a weight factor. A high-resolution (1 x 1 m) DEM (Digital Elevation Model) was created by filtering and applying a multiscale curvature classification algorithm.The connectivity values show a decrease directly related to the ~71% decrease of agricultural land. Understanding landscape patterns, changes and interactions of human activities is essential for land management in Mediterranean agroecosystems.

ABSTRACT. The study and quantification of soil redistribution is a complex and difficult task and even a non-solved question at catchment scale both in field and numerical simulation studies. In this study we tackle this topic by coupling two different predicting models and a sound field-based dataset to assess the potential soil redistribution in a Mediterranean rain-fed agricultural and mountainous catchment (La Reina gully catchment, Cinco Villas region, NE Spain): the enhanced Modified-RMMF-2014 version of the "Modified Revised Morgan, Morgan and Finney" model (Morgan, 2001;López-Vicente and Navas, 2010)

No abstract