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–Č Type Year Authors Title Venue/Journal DOI Research type Water System Technical Focus Abstract Link with Projects Link with Tools Related policies ID
publications-1581 PEER REVIEWED ARTICLE 2017 Pere Quintana-Seguí , Marco Turco , Sixto Herrera , Gonzalo Miguez-Macho Validation of a new SAFRAN-based gridded precipitation product for Spain and comparisons to Spain02 and ERA-Interim 10.5194/hess-21-2187-2017 Uncategorized Uncategorized Abstract. Offline land surface model (LSM) simulations are useful for studying the continental hydrological cycle. Because of the nonlinearities in the models, the results are very sensitive to the quality of the meteorological forcing; thus, high-quality gridded datasets of screen-level meteorological variables are needed. Precipitation datasets are particularly difficult to produce due to the inherent spatial and temporal heterogeneity of that variable. They do, however, have a large impact on the simulations, and it is thus necessary to carefully evaluate their quality in great detail. This paper reports the quality of two high-resolution precipitation datasets for Spain at the daily time scale: the new SAFRAN-based dataset and Spain02. SAFRAN is a meteorological analysis system that was designed to force LSMs and has recently been extended to the entirety of Spain for a long period of time (1979/1980–2013/2014). Spain02 is a daily precipitation dataset for Spain and was created mainly to validate regional climate models. In addition, ERA-Interim is included in the comparison to show the differences between local high-resolution and global low-resolution products. The study compares the different precipitation analyses with rain gauge data and assesses their temporal and spatial similarities to the observations. The validation of SAFRAN with independent data shows that this is a robust product. SAFRAN and Spain02 have very similar scores, although the latter slightly surpasses the former. The scores are robust with altitude and throughout the year, save perhaps in summer when a diminished skill is observed. As expected, SAFRAN and Spain02 perform better than ERA-Interim, which has difficulty capturing the effects of the relief on precipitation due to its low resolution. However, ERA-Interim reproduces spells remarkably well in contrast to the low skill shown by the high-resolution products. The high-resolution gridded products overestimate the number of precipitation days, which is a problem that affects SAFRAN more than Spain02 and is likely caused by the interpolation method. Both SAFRAN and Spain02 underestimate high precipitation events, but SAFRAN does so more than Spain02. The overestimation of low precipitation events and the underestimation of intense episodes will probably have hydrological consequences once the data are used to force a land surface or hydrological model. 603608
publications-1582 PEER REVIEWED ARTICLE 2016 J. Alejandro Martinez , Francina Dominguez , Gonzalo Miguez-Macho Effects of a Groundwater Scheme on the Simulation of Soil Moisture and Evapotranspiration over Southern South America 10.1175/jhm-d-16-0051.1 Simulation & Modeling Natural Water Bodies Abstract The effects of groundwater dynamics on the representation of water storage and evapotranspiration (ET) over southern South America are studied from simulations with the Noah-MP land surface model. The model is run with three different configurations: one including the Miguez-Macho and Fan groundwater scheme, another with the Simple Groundwater Model (SIMGM), and the other with free drainage at the bottom of the soil column. The first objective is to assess the effects of the groundwater schemes using a grid size typical of regional climate model simulations at the continental scale (20 km). The phase and amplitude of the fluctuations in the terrestrial water storage over the southern Amazon are improved with one of the groundwater schemes. An increase in the moisture in the top 2 m of the soil is found in those regions where the water table is closer to the land surface, including the western and southern Amazon and the La Plata basin. This induces an increase in ET over the southern La Plata basin, where ET is water limited. There is also a seasonal increase in ET during the dry season over parts of the southern Amazon. The second objective is to assess the role of the horizontal resolution on the effects induced by the Miguez-Macho and Fan groundwater scheme using simulations with grid sizes of 5 and 20 km. Over the La Plata basin, the effect of groundwater on ET is amplified at the 5-km resolution. Notably, over parts of the Amazon, the groundwater scheme increases ET only at the higher 5-km resolution. 603608
publications-1583 PEER REVIEWED ARTICLE 2016 J. Alejandro Martinez , Francina Dominguez , Gonzalo Miguez-Macho Impacts of a Groundwater Scheme on Hydroclimatological Conditions over Southern South America 10.1175/jhm-d-16-0052.1 IoT & Sensors Natural Water Bodies Abstract A sensitivity study of the impact of a groundwater scheme on hydrometeorological variables in coupled land–atmosphere simulations over southern South America is presented. It is found that shallow water tables in the groundwater scheme lead to reduced drainage and even upward capillary fluxes over parts of the central and southern La Plata basin. This leads to an increase in the simulated moisture in the root zone, which in turn produces an increase in evapotranspiration (ET) over the southern part of the domain, where ET is water limited. There is also a decrease in the near-surface temperature, in the range 0.5°–1.0°C. During the dry season, the increases in ET and relative humidity over the central La Plata coincide with an increase in precipitation downstream. Including groundwater leads to an increase in precipitation over parts of the central and southern La Plata basin during the early rainy season (October–December). The overall increase in ET and precipitation over the southern La Plata basin during the early rainy season is 13% and 10%, respectively. The additional precipitation comes from both an increase in the availability of atmospheric moisture when the groundwater scheme is used and its effect on the atmospheric instability. In the La Plata basin, including a representation of groundwater increases simulated precipitation and partially alleviates a warm and dry bias present in simulations without realistic subsurface hydrology. 603608
publications-1584 PEER REVIEWED ARTICLE 2016 Jorge Eiras-Barca , Swen Brands , Gonzalo Miguez-Macho Seasonal variations in North Atlantic atmospheric river activity and associations with anomalous precipitation over the Iberian Atlantic Margin 10.1002/2015jd023379 Simulation & Modeling River Basins AbstractIn the present study, a novel atmospheric river (AR) detection scheme based on column‐integrated water vapor and column‐integrated water vapor flux is presented and applied for the Iberian Atlantic Margin (IAM) and a wider area covering the North Atlantic Ocean for the period 1979–2013. The seasonal cycle in AR frequency over the North Atlantic exhibits a relatively small amplitude, being more pronounced toward the east and south of the oceanic basin, as it is increasingly related to the seasonal cycle in storm activity and the meridional displacement of the subtropical high. In the eastern North Atlantic, downwind of the North American continent, it shows a more complex behavior. The interannual variability of AR frequency is weak across the entire North Atlantic, and it does not present consistent long‐term spatiotemporal patterns. For the southern IAM, AR occurrence is slightly enhanced by the negative phase of the North Atlantic Oscillation during the previous days. Up to 80% of the anomalous precipitation events (above the 95th percentile) in the IAM are associated with ARs; these values exceed 90% in winter and decrease to 75% in spring when convection not related to ARs becomes a significant precipitation mechanism. Moisture advection within ARs is thus a very important contributor to anomalous precipitation. Likewise, the strength of the associated storm systems and the characteristics of the ARs themselves are also very relevant factors. The percentage of total ARs linked to anomalous precipitation is relatively low, only reaching 20% where topographic features are favorable. 603608
publications-1585 PEER REVIEWED ARTICLE 2014 Luca Pulvirenti , Frank Silvio Marzano , Nazzareno Pierdicca , Saverio Mori , Marco Chini Discrimination of Water Surfaces, Heavy Rainfall, and Wet Snow Using COSMO-SkyMed Observations of Severe Weather Events 10.1109/tgrs.2013.2244606 Simulation & Modeling Precipitation & Ecological Systems No abstract available 603608
publications-1586 PEER REVIEWED ARTICLE 2017 Alexander Gruber , Wouter Arnoud Dorigo , Wade Crow , Wolfgang Wagner Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals 10.1109/tgrs.2017.2734070 Simulation & Modeling Precipitation & Ecological Systems No abstract available 603608
publications-1587 PEER REVIEWED ARTICLE 2017 Wouter Dorigo , Wolfgang Wagner , Clement Albergel , Franziska Albrecht , Gianpaolo Balsamo , Luca Brocca , Daniel Chung , Martin Ertl , Matthias Fork ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions 10.1016/j.rse.2017.07.001 Simulation & Modeling Natural Water Bodies No abstract available 603608
publications-1588 PEER REVIEWED ARTICLE 2017 Brecht Martens , Diego G. Miralles , Hans Lievens , Robin van der Schalie , Richard A. M. de Jeu , Diego Fernández-Prieto , Hylke E. Beck , Wouter A. GLEAM v3: satellite-based land evaporation and root-zone soil moisture 10.5194/gmd-10-1903-2017 IoT & Sensors Natural Water Bodies Abstract. The Global Land Evaporation Amsterdam Model (GLEAM) is a set of algorithms dedicated to the estimation of terrestrial evaporation and root-zone soil moisture from satellite data. Ever since its development in 2011, the model has been regularly revised, aiming at the optimal incorporation of new satellite-observed geophysical variables, and improving the representation of physical processes. In this study, the next version of this model (v3) is presented. Key changes relative to the previous version include (1) a revised formulation of the evaporative stress, (2) an optimized drainage algorithm, and (3) a new soil moisture data assimilation system. GLEAM v3 is used to produce three new data sets of terrestrial evaporation and root-zone soil moisture, including a 36-year data set spanning 1980–2015, referred to as v3a (based on satellite-observed soil moisture, vegetation optical depth and snow-water equivalent, reanalysis air temperature and radiation, and a multi-source precipitation product), and two satellite-based data sets. The latter share most of their forcing, except for the vegetation optical depth and soil moisture, which are based on observations from different passive and active C- and L-band microwave sensors (European Space Agency Climate Change Initiative, ESA CCI) for the v3b data set (spanning 2003–2015) and observations from the Soil Moisture and Ocean Salinity (SMOS) satellite in the v3c data set (spanning 2011–2015). Here, these three data sets are described in detail, compared against analogous data sets generated using the previous version of GLEAM (v2), and validated against measurements from 91 eddy-covariance towers and 2325 soil moisture sensors across a broad range of ecosystems. Results indicate that the quality of the v3 soil moisture is consistently better than the one from v2: average correlations against in situ surface soil moisture measurements increase from 0.61 to 0.64 in the case of the v3a data set and the representation of soil moisture in the second layer improves as well, with correlations increasing from 0.47 to 0.53. Similar improvements are observed for the v3b and c data sets. Despite regional differences, the quality of the evaporation fluxes remains overall similar to the one obtained using the previous version of GLEAM, with average correlations against eddy-covariance measurements ranging between 0.78 and 0.81 for the different data sets. These global data sets of terrestrial evaporation and root-zone soil moisture are now openly available at www.GLEAM.eu and may be used for large-scale hydrological applications, climate studies, or research on land–atmosphere feedbacks. 603608
publications-1589 PEER REVIEWED ARTICLE 2017 Alexander Loew , William Bell , Luca Brocca , Claire E. Bulgin , Jörg Burdanowitz , Xavier Calbet , Reik V. Donner , Darren Ghent , Alexander Gruber Validation practices for satellite-based Earth observation data across communities 10.1002/2017rg000562 Data Management & Analytics Natural Water Bodies AbstractAssessing the inherent uncertainties in satellite data products is a challenging task. Different technical approaches have been developed in the Earth Observation (EO) communities to address the validation problem which results in a large variety of methods as well as terminology. This paper reviews state‐of‐the‐art methods of satellite validation and documents their similarities and differences. First, the overall validation objectives and terminologies are specified, followed by a generic mathematical formulation of the validation problem. Metrics currently used as well as more advanced EO validation approaches are introduced thereafter. An outlook on the applicability and requirements of current EO validation approaches and targets is given. 603608
publications-1590 PEER REVIEWED ARTICLE 2017 Kengo Miyaoka , Alexander Gruber , Francesca Ticconi , Sebastian Hahn , Wolfgang Wagner , Julia Figa-Saldana , Craig Anderson Triple Collocation Analysis of Soil Moisture From Metop-A ASCAT and SMOS Against JRA-55 and ERA-Interim 10.1109/jstars.2016.2632306 Data Management & Analytics Natural Water Bodies No abstract available 603608