Scientific Results

This catalogue is obtained by conducting a systematic literature review of scientific studies and reviews related to monitoring, forecasting, and simulating the inland water cycle. The analysis maps scientific expertise across research groups and classifies findings by the type of inland water studied, application focus, and geographical scope. A gap analysis will identify missing research areas and assess their relevance to policymaking.

ID â–² Type Year Authors Title Venue/Journal DOI Research type Water System Technical Focus Abstract Link with Projects Link with Tools Related policies ID
publications-2251 Peer reviewed articles 2022 José L. J. Ledesma, Anna Lupon, Eugènia Martí, Susana Bernal Hydrology and riparian forests drive carbon and nitrogen supply and DOC:NO3- stoichiometry along a headwater Mediterranean stream Hydrology and Earth System Sciences 10.5194/hess-26-4209-2022 Simulation & Modeling Irrigation Systems Abstract. In forest headwater streams, metabolic processes are predominately heterotrophic and depend on both the availability of carbon (C) and nitrogen (N) and a favourable C:N stoichiometry. In this context, hydrological conditions and the presence of riparian forests adjacent to streams can play an important, yet understudied role in determining dissolved organic carbon (DOC) and nitrate (NO3-) concentrations and DOC:NO3- molar ratios. Here, we aimed to investigate how the interplay between hydrological conditions and riparian forest coverage drives DOC and NO3- supply and DOC:NO3- stoichiometry in an oligotrophic headwater Mediterranean stream. We analysed DOC and NO3- concentrations and DOC:NO3- molar ratios during both base flow and storm flow conditions at three stream locations along a longitudinal gradient of increased riparian forest coverage. Further, we performed an event analysis to examine the hydroclimatic conditions that favour the transfer of DOC and NO3- from riparian soils to the stream during storms. Stream DOC and NO3- concentrations were generally low (overall averages ± SD were 1.0±0.6 mg C L−1 and 0.20±0.09 mg N L−1), although significantly higher during storm flow compared to base flow conditions in all three stream sites. Optimal DOC:NO3- stoichiometry for stream heterotrophic microorganisms (corresponding to DOC:NO3- molar ratios between 4.8 and 11.7) was prevalent at the midstream and downstream sites under both flow conditions, whereas C-limited conditions were prevalent at the upstream site, which had no surrounding riparian forest. The hydroclimatic analysis of storms suggested that large and medium storm events display a distinct mechanism of DOC and NO3- mobilization. In comparison to large storms, medium storm events showed limited hydrological responses that led to significantly lower increases in stream DOC and NO3- concentrations. During large storm events, different patterns of DOC and NO3- mobilization arise, depending on antecedent soil moisture conditions: drier antecedent conditions promoted rapid elevations of the riparian groundwater table, hydrologically activating a wider and shallower soil layer, and leading to relatively higher increases in stream DOC and NO3- concentrations compared to large storm events preceded by wet conditions. Our results suggest that (i) increased supply of limited resources during storms can potentially sustain in-stream heterotrophic activity during high flows, especially during large storm events preceded by dry conditions, and (ii) C-limited conditions upstream were overcome downstream, likely due to higher C inputs from riparian forests present at lower elevations. The contrasting spatiotemporal patterns in DOC and NO3- availability and DOC:NO3- stoichiometry observed at the studied stream suggest that groundwater inputs from riparian forests are essential for maintaining in-stream heterotrophic activity in oligotrophic, forest headwater catchments. 834363
publications-2252 Peer reviewed articles 2016 Fabienne Trolard, Guilhem Bourrié, Antoine Baillieux, Samuel Buis, André Chanzy, Philippe Clastre, Jean-François Closet, Dominique Courault, Marie-Lorraine Dangeard, Nicola Di Virgilio, Philippe Dussouilliez, Jules Fleury, Jérémy Gasc, Ghislain Géniaux, Rachel Jouan, Catherine Keller, Patrice Lecharpentier, Jean Lecroart, Claude Napoleone, Gihan Mohammed, Albert Olioso, Suzanne Reynders, Fed The PRECOS framework: Measuring the impacts of the global changes on soils, water, agriculture on territories to better anticipate the future Journal of Environmental Management 10.1016/j.jenvman.2016.07.002 Uncategorized Irrigation Systems No abstract available 633945
publications-2253 Peer reviewed articles 2016 Isidro Campos, Jose González-Piqueras, Arnaud Carrara, Julio Villodre, Alfonso Calera Estimation of total available water in the soil layer by integrating actual evapotranspiration data in a remote sensing-driven soil water balance Journal of Hydrology Simulation & Modeling River Basins No abstract available 633945
publications-2254 Peer reviewed articles 2016 Isidro Campos, Claudio Balbontín, Jose González-Piqueras, Maria P González-Dugo, Christopher MU Neale, Alfonso Calera Combining a water balance model with evapotranspiration measurements to estimate total available soil water in irrigated and rainfed vineyards Agricultural Water Management Simulation & Modeling River Basins No abstract available 633945
publications-2255 Peer reviewed articles 2016 Dalezios N.R, Spyropoulos N.V Very high resolution satellite based monitoring of crop evapotranspiration in precision agriculture Remote Sensing Journal. MDPI Simulation & Modeling Irrigation Systems No abstract available 633945
publications-2256 Peer reviewed articles 2017 J. González-Piqueras, H. Lopez-Corcoles, S. Sánchez, J. Villodre, V. Bodas, I. Campos, A. Osann, A. Calera Monitoring crop N status by using red edge-based indices Advances in Animal Biosciences 10.1017/S2040470017000243 Uncategorized Precipitation & Ecological Systems No abstract available 633945
publications-2257 Peer reviewed articles 2014 Lukas, V., Smutný, V., Novák, J., Neudert, L., Dryšlová, T., Kren, J. Variable rate application of fertilizers based on the Mehlich 3 methodology Növénytermelés 10.12666/Novenyterm.63.2014.Suppl Uncategorized River Basins No abstract available 633945
publications-2258 Peer reviewed articles 2015 J. González-Piqueras, J. Villodre, I. Campos Rodríguez, A. Calera Belmonte, C. Balbontín Nesvara Seguimiento de los flujos de calor sensible y calor latente en vid mediante la aplicación del balance de energía METRIC Revista de Teledetección 10.4995/raet.2015.2310 Uncategorized Precipitation & Ecological Systems <p>En este trabajo se presenta el seguimiento de los flujos de energía en un cultivo de vid bajo riego, obtenidos a partir del modelo de balance de energía METRIC (Allen et al., 2007b). Este modelo resulta operativo al utilizar un método de calibración interna definido a partir de la selección de píxeles con valores extremos dentro de la escena. De esta manera se obtuvieron mapas de radiación neta (Rn), flujo de calor en suelo (G), calor sensible (H), calor latente (LE), evapotranspiración (ET) y coeficiente de cultivo (Kc). Estos valores fueron validados con registros obtenidos en el sitio, utilizando una torre de flujos turbulentos (covarianza de torbellinos). El RMSE fue 43 W m<sup>-2</sup>,33 W m<sup>-2</sup>, 55 W m<sup>-2</sup> y 40 W m<sup>-2</sup> en Rn, G, H y LE, los cuales en términos relativos representan un 8%, 29 %, 21% y 20% respectivamente. A escala diaria el RMSE para la ET fue de 0,58 mm día<sup>-1</sup>, con un valor de Kc máximo y estable de 0,42±0,08. Estos resultados permiten considerar que el método es adecuado y operativo para el seguimiento de la evapotranspiración y cálculo de las necesidades hídricas del viñedo evaluado.</p> 633945
publications-2259 Peer reviewed articles 2017 Isidro Campos, Christopher M.U. Neale, Andrew E. Suyker, Timothy J. Arkebauer, Ivo Z. Gonçalves Reflectance-based crop coefficients REDUX: For operational evapotranspiration estimates in the age of high producing hybrid varieties Agricultural Water Management 10.1016/j.agwat.2017.03.022 AI & Machine Learning River Basins No abstract available 633945
publications-2260 Peer reviewed articles 2016 Francesco Vuolo, Mateusz Żółtak, Claudia Pipitone, Luca Zappa, Hannah Wenng, Markus Immitzer, Marie Weiss, Frederic Baret, Clement Atzberger Data Service Platform for Sentinel-2 Surface Reflectance and Value-Added Products: System Use and Examples Remote Sensing 10.3390/rs8110938 Uncategorized Precipitation & Ecological Systems This technical note presents the first Sentinel-2 data service platform for obtaining atmospherically-corrected images and generating the corresponding value-added products for any land surface on Earth. Using the European Space Agency’s (ESA) Sen2Cor algorithm, the platform processes ESA’s Level-1C top-of-atmosphere reflectance to atmospherically-corrected bottom-of-atmosphere (BoA) reflectance (Level-2A). The processing runs on-demand, with a global coverage, on the Earth Observation Data Centre (EODC), which is a public-private collaborative IT infrastructure in Vienna (Austria) for archiving, processing, and distributing Earth observation (EO) data. Using the data service platform, users can submit processing requests and access the results via a user-friendly web page or using a dedicated application programming interface (API). Building on the processed Level-2A data, the platform also creates value-added products with a particular focus on agricultural vegetation monitoring, such as leaf area index (LAI) and broadband hemispherical-directional reflectance factor (HDRF). An analysis of the performance of the data service platform, along with processing capacity, is presented. Some preliminary consistency checks of the algorithm implementation are included to demonstrate the expected product quality. In particular, Sentinel-2 data were compared to atmospherically-corrected Landsat-8 data for six test sites achieving a R2 = 0.90 and Root Mean Square Error (RMSE) = 0.031. LAI was validated for one test site using ground estimations. Results show a very good agreement (R2 = 0.83) and a RMSE of 0.32 m2/m2 (12% of mean value). 633945