EUSEDcollab: a network of data from European catchments to monitor net soil erosion by water.

As a network of researchers we release an open-access database (EUSEDcollab) of water discharge and suspended sediment yield time series records collected in small to medium sized catchments in Europe. EUSEDcollab is compiled to overcome the scarcity of open-access data at relevant spatial scales for studies on runoff, soil loss by water erosion and sediment delivery. Multi-source measurement data from numerous researchers and institutions were harmonised into a common time series and metadata structure. Data reuse is facilitated through accompanying metadata descriptors providing background technical information for each monitoring station setup. Across ten European countries, EUSEDcollab covers over 1600 catchment years of data from 245 catchments at event (11 catchments), daily (22 catchments) and monthly (212 catchments) temporal resolution, and is unique in its focus on small to medium catchment drainage areas (median = 43 km2, min = 0.04 km2, max = 817 km2) with applicability for soil erosion research. We release this database with the aim of uniting people, knowledge and data through the European Union Soil Observatory (EUSO).

Challenges and progresses in the detailed estimation of sediment export in agricultural watersheds in Navarra (Spain) after two decades of experience.

Soil erosion is a very serious environmental problem worldwide, with agriculture considered the main source of sediment in inland waters. In order to determine the extent and importance of soil erosion in the Spanish region of Navarra, in 1995 the Government of Navarra established the Network of Experimental Agricultural Watersheds (NEAWGN), which consists of five small watersheds representative of local conditions. In each watershed, key hydrometeorological variables, including turbidity, were recorded every 10 min, and daily samples were taken to determine suspended sediment concentration. In 2006, the frequency of suspended sediment sampling was increased during hydrologically relevant events. The main objective of this study is to explore the possibility of obtaining long and accurate time series of suspended sediment concentration in the NEAWGN. To this end, simple linear regressions between sediment concentration and turbidity are proposed. In addition, supervised learning models incorporating a larger number of predictive variables are used for the same purpose. A series of indicators are proposed to objectively characterize the intensity and timing of sampling. It was not possible to obtain a satisfactory model for estimating the concentration of suspended sediment. This would be mainly due to the large temporal variability found of the physical and mineralogical characteristics of the sediment, which would be affecting the turbidity value, independently of the sediment concentration, per se. This fact would be particularly important in small river watersheds such as those of this study, and especially if their physical conditions are spatially and temporally radically disturbed by agricultural tillage and by a constant modification of the vegetation cover, as is the case in cereal basins. Our findings suggest that better results could be obtained by including in the analysis variables such as soil texture and exported sediment texture, rainfall erosivity, and the state of vegetation cover and riparian vegetation.

Evaluation of Nitrate Soil Probes for a More Sustainable Agriculture.

Synthetic nitrogen (N) fertilizers and their increased production and utilization have played a great role in increasing crop yield and in meeting the food demands resulting from population growth. Nitrate (NO3-) is the common form of nitrogen absorbed by plants. It has high water solubility and low retention by soil particles, making it prone to leaching and mobilization by surface water, which can seriously contaminate biological environments and affect human health. Few methods exist to measure nitrate in the soil. The development of ion selective sensors provides knowledge about the dynamics of nitrate in the soil in real time, which can be very useful for nitrate management. The objective of this study is to analyze the performance of three commercial probes (Nutrisens, RIKA and JXCT) under the same conditions. The performance was analyzed with respect to electrical conductivity (EC) (0-50 mS/cm) and nitrate concentration in aqueous solution and in sand (0-180 ppm NO3-) at 35% volumetric soil moisture. Differences were shown among probes when studying their response to variations of the EC and, notably, only the Nutrisens probe provided coherent accurate measurements. In the evaluation of nitrate concentration in liquid solution, all probes proved to be highly sensitive. Finally, in the evaluation of all probes' response to modifications in nitrate concentration in sand, the sensitivity decreased for all probes, with the Nutrisens probe the most sensitive and the other two probes almost insensitive.

Influence of Surface Roughness Spatial Variability and Temporal Dynamics on the Retrieval of Soil Moisture from SAR Observations.

Radar-based surface soil moisture retrieval has been subject of intense research during the last decades. However, several difficulties hamper the operational estimation of soil moisture based on currently available spaceborne sensors. The main difficulty experienced so far results from the strong influence of other surface characteristics, mainly roughness, on the backscattering coefficient, which hinders the soil moisture inversion. This is especially true for single configuration observations where the solution to the surface backscattering problem is ill-posed. Over agricultural areas cultivated with winter cereal crops, roughness can be assumed to remain constant along the growing cycle allowing the use of simplified approaches that facilitate the estimation of the moisture content of soils. However, the field scale spatial variability and temporal variations of roughness can introduce errors in the estimation of soil moisture that are difficult to evaluate. The objective of this study is to assess the impact of roughness spatial variability and roughness temporal variations on the retrieval of soil moisture from radar observations. A series of laser profilometer measurements were performed over several fields in an experimental watershed from September 2004 to March 2005. The influence of the observed roughness variability and its temporal variations on the retrieval of soil moisture is studied using simulations performed with the Integral Equation Model, considering different sensor configurations. Results show that both field scale roughness spatial variability and its temporal variations are aspects that need to be taken into account, since they can introduce large errors on the retrieved soil moisture values.