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published an article in November 2018.
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Adriano Camps

217 shared publications

CommSensLab, Unidad de Excelencia María de Maeztu, Department of Signal Theory and Communications, Universitat Politècnica de Catalunya, E-08034 Barcelona, Spain

Hyuk Park

108 shared publications

CommSensLab, Unidad de Excelencia María de Maeztu, Department of Signal Theory and Communications, Universitat Politècnica de Catalunya, E-08034 Barcelona, Spain

Jose A. Marengo

17 shared publications

CEMADEN-National Center for Monitoring and Early Warning of Natural Disasters, Brazil

Mercedes Vall·llossera

11 shared publications

CommSensLab, Unidad de Excelencia María de Maeztu, Department of Signal Theory and Communications, Universitat Politècnica de Catalunya, E-08034 Barcelona, Spain

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Article 0 Reads 0 Citations Sensitivity of TDS-1 GNSS-R Reflectivity to Soil Moisture: Global and Regional Differences and Impact of Different Spati... Adriano Camps, Mercedes Vall·llossera, Hyuk Park, Gerard Por... Published: 21 November 2018
Remote Sensing, doi: 10.3390/rs10111856
DOI See at publisher website ABS Show/hide abstract
The potential of Global Navigation Satellite Systems-Reflectometry (GNSS-R) techniques to estimate land surface parameters such as soil moisture (SM) is experimentally studied using 2014–2017 global data from the UK TechDemoSat-1 (TDS-1) mission. The approach is based on the analysis of the sensitivity to SM of different observables extracted from the Delay Doppler Maps (DDM) computed by the Space GNSS Receiver–Remote Sensing Instrument (SGR-ReSI) instrument using the L1 (1575.42 MHz) left-hand circularly-polarized (LHCP) reflected signals emitted by the Global Positioning System (GPS) navigation satellites. The sensitivity of different GNSS-R observables to SM and its dependence on the incidence angle is analyzed. It is found that the sensitivity of the calibrated GNSS-R reflectivity to surface soil moisture is ~0.09 dB/% up to 30° incidence angle, and it decreases with increasing incidence angles, although differences are found depending on the spatial scale used for the ground-truth, and the region. The sensitivity to subsurface soil moisture has been also analyzed using a network of subsurface probes and hydrological models, apparently showing some dependence, but so far results are not conclusive.
Article 0 Reads 3 Citations Impact of soil moisture over Palmer Drought Severity Index and its future projections in Brazil Luciana Rossato, José Antônio Marengo, Carlos Frederico De A... Published: 01 January 2017
RBRH, doi: 10.1590/2318-0331.0117160045
DOI See at publisher website ABS Show/hide abstract
Soil moisture is a main factor for the study of drought impacts on vegetation. Drought is a regional phenomenon and affects the food security more than any other natural disaster. Currently, the monitoring of different types of drought is based on indexes that standardize in temporal and regional level allowing, thus, comparison of water conditions in different areas. Therefore, in order to assess the impact of soil moisture during periods of drought, drought Palmer Severity Index was estimated for the entire region of the territory. For this were used meteorological data (rainfall and evapotranspiration) and soil (field capacity, permanent wilting point and water storage in the soil). The data field capacity and wilting point were obtained from the physical properties of soil; while the water storage in soil was calculated considering the water balance model. The results of the PSDI were evaluated during the years 2000 to 2015, which correspond to periods with and without occurrence of drought. In order to assess the future drought projections, considering the set of the Coupled Model Intercomparison rainfall data Project Phase 5 (CMIP5). Climate projections precipitation in CMIP5 for the period 2071-2100 was extracted generating entitled forcing scenarios Representative Concentration Pathways - RCPs, and referred to as RCOP 8.5, corresponding to an approximate radiative forcing the end the twenty-first century of 8.5 Wm -2 . The results showed that the PDSI is directly associated with climatological patterns of precipitation and soil moisture in any spatial and temporal scale (including future projections). Therefore, it is concluded that the PDSI is an important index to assess soil moisture different water conditions, as well as the association with economic and social information to create risk maps for subsidies to decision makers. Keywords: Soil moisture; Palmer Drought Severity Index; Future projections; Brazil
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