Please login first
Santiago Beguería-Portugés  - - - 
Top co-authors See all
Ana Navas

227 shared publications

Soil and Water Department, Estación Experimental de Aula Dei (EEAD-CSIC), Zaragoza, Spain

R. M. Trigo

217 shared publications

Instituto Dom Luiz, Faculdade de Ciências, Universidade de Lisboa; Lisboa Portugal

Steven M. White

204 shared publications

European Synchrotron Radiation Facility, BP 220, 38043 Grenoble CEDEX, France

Petr Štěpánek

193 shared publications

Global Change Research Institute of the Czech Academy of Sciences, Bělidla 986/4a, 603 00 Brno, Czech Republic

J. Julio Camarero

179 shared publications

Instituto Pirenaico de Ecología (IPE-CSIC), 50192 Zaragoza, Spain

70
Publications
0
Reads
0
Downloads
1449
Citations
Publication Record
Distribution of Articles published per year 
(2000 - 2018)
Publications See all
Article 0 Reads 0 Citations Computation of rainfall erosivity from daily precipitation amounts Santiago Beguería, Roberto Serrano-Notivoli, Miquel Tomás-Bu... Published: 01 October 2018
Science of The Total Environment, doi: 10.1016/j.scitotenv.2018.04.400
DOI See at publisher website
Article 0 Reads 0 Citations Drought Sensitiveness on Forest Growth in Peninsular Spain and the Balearic Islands Marina Peña-Gallardo, Sergio M. Vicente-Serrano, J. Julio Ca... Published: 30 August 2018
Forests, doi: 10.3390/f9090524
DOI See at publisher website
ABS Show/hide abstract
Drought is one of the key natural hazards impacting net primary production and tree growth in forest ecosystems. Nonetheless, tree species show different responses to drought events, which make it difficult to adopt fixed tools for monitoring drought impacts under contrasting environmental and climatic conditions. In this study, we assess the response of forest growth and a satellite proxy of the net primary production (NPP) to drought in peninsular Spain and the Balearic Islands, a region characterized by complex climatological, topographical, and environmental characteristics. Herein, we employed three different indicators based on in situ measurements and satellite image-derived vegetation information (i.e., tree-ring width, maximum annual greenness, and an indicator of NPP). We used seven different climate drought indices to assess drought impacts on the tree variables analyzed. The selected drought indices include four versions of the Palmer Drought Severity Index (PDSI, Palmer Hydrological Drought Index (PHDI), Z-index, and Palmer Modified Drought Index (PMDI)) and three multi-scalar indices (Standardized Precipitation Evapotranspiration Index (SPEI), Standardized Precipitation Index (SPI), and Standardized Precipitation Drought Index (SPDI)). Our results suggest that—irrespective of drought index and tree species—tree-ring width shows a stronger response to interannual variability of drought, compared to the greenness and the NPP. In comparison to other drought indices (e.g., PDSI), and our results demonstrate that multi-scalar drought indices (e.g., SPI, SPEI) are more advantageous in monitoring drought impacts on tree-ring growth, maximum greenness, and NPP. This finding suggests that multi-scalar indices are more appropriate for monitoring and modelling forest drought in peninsular Spain and the Balearic Islands.
Article 0 Reads 1 Citation Recent trends reveal decreasing intensity of daily precipitation in Spain Roberto Serrano-Notivoli, Santiago Beguería, Miguel Ángel Sa... Published: 18 July 2018
International Journal of Climatology, doi: 10.1002/joc.5562
DOI See at publisher website
Article 0 Reads 0 Citations Comparison of precipitation measurements by OTT Parsivel2 and Thies LPM optical disdrometers Marta Angulo-Martínez, Santiago Beguería, Borja Latorre, Mar... Published: 08 May 2018
Hydrology and Earth System Sciences, doi: 10.5194/hess-22-2811-2018
DOI See at publisher website
ABS Show/hide abstract
Optical disdrometers are present weather sensors with the ability of providing detailed information on precipitation such as rain intensity, radar reflectivity or kinetic energy, together with discrete information on the particle size and fall velocity distribution (PSVD) of the hydrometeors. Disdrometers constitute a step forward towards a more complete characterization of precipitation, being useful in several research fields and applications. In this article the performance of two extensively used optical disdrometers, the most recent version of OTT Parsivel2 disdrometer and Thies Clima Laser Precipitation Monitor (LPM), is evaluated. During 2 years, four collocated optical disdrometers, two Thies Clima LPM and two OTT Parsivel2, collected up to 100000min of data and up to 30000min with rain in more than 200 rainfall events, with intensities peaking at 277mmh−1 in 1 minute. The analysis of these records shows significant differences between both disdrometer types for all integrated precipitation parameters, which can be explained by differences in the raw PSVD estimated by the two sensors. Thies LPM recorded a larger number of particles than Parsivel2 and a higher proportion of small particles than OTT Parsivel2, resulting in higher rain rates and totals and differences in radar reflectivity and kinetic energy. These differences increased greatly with rainfall intensity. Possible causes of these differences, and their practical consequences, are discussed in order to help researchers and users in the choice of sensor, and at the same time pointing out limitations to be addressed in future studies.
Article 1 Read 1 Citation Regional Crop Gross Primary Productivity and Yield Estimation Using Fused Landsat-MODIS Data Mingzhu He, John Kimball, Marco Maneta, Bruce Maxwell, Alvar... Published: 28 February 2018
Remote Sensing, doi: 10.3390/rs10030372
DOI See at publisher website
ABS Show/hide abstract
Accurate crop yield assessments using satellite remote sensing-based methods are of interest for regional monitoring and the design of policies that promote agricultural resiliency and food security. However, the application of current vegetation productivity algorithms derived from global satellite observations is generally too coarse to capture cropland heterogeneity. The fusion of data from different sensors can provide enhanced information and overcome many of the limitations of individual sensors. In thitables study, we estimate annual crop yields for seven important crop types across Montana in the continental USA from 2008–2015, including alfalfa, barley, maize, peas, durum wheat, spring wheat and winter wheat. We used a satellite data-driven light use efficiency (LUE) model to estimate gross primary productivity (GPP) over croplands at 30-m spatial resolution and eight-day time steps using a fused NDVI dataset constructed by blending Landsat (5 or 7) and Terra MODIS reflectance data. The fused 30-m NDVI record showed good consistency with the original Landsat and MODIS data, but provides better spatiotemporal delineations of cropland vegetation growth. Crop yields were estimated at 30-m resolution as the product of estimated GPP accumulated over the growing season and a crop-specific harvest index (HIGPP). The resulting GPP estimates capture characteristic cropland productivity patterns and seasonal variations, while the estimated annual crop production results correspond favorably with reported county-level crop production data (r = 0.96, relative RMSE = 37.0%, p < 0.05) from the U.S. Department of Agriculture (USDA). The performance of estimated crop yields at a finer (field) scale was generally lower, but still meaningful (r = 0.42, relative RMSE = 50.8%, p < 0.05). Our methods and results are suitable for operational applications of crop yield monitoring at regional scales, suggesting the potential of using global satellite observations to improve agricultural management, policy decisions and regional/global food security.
Article 0 Reads 1 Citation Comparison of precipitation measurements by Ott Parsivel2 and Thies LPM optical disdrometers Marta Angulo-Martínez, Santiago Beguería, Borja Latorre, Mar... Published: 14 November 2017
Hydrology and Earth System Sciences Discussions, doi: 10.5194/hess-2017-652
DOI See at publisher website
ABS Show/hide abstract
Optical disdrometers are present weather sensors with the ability of providing detailed information of precipitation such as rain intensity, kinetic energy or radar reflectivity, together with discrete information on the distribution of particle sizes and fall velocities (PSVD) of the hydrometeors. Disdrometers constitute a step forward towards a more complete characterisation of precipitation, being highly useful in several research fields and applications. In this article the performance of the two optical disdrometer most extensively used, the most recent version of Ott PARSIVEL2 disdrometer and Thies Clima Laser Precipitation Monitor, is evaluated. During a two years precipitation observation experiment, four collocated optical disdrometers, two Thies Clima LPM and two Ott PARSIVEL2, recorded 58761 common one-minute precipitation observations, totalling 221 natural rainfall events, with intensities peaking at 220&thinsp;mm&thinsp;h&minus;1. The results show significant differences between both disdrometer types for all integrated precipitation parameters, which can be explained by differences in the raw particle size and velocity distribution (PSVD). Thies LPM recorded in average double number of particles than PARSIVEL2. PSVD percentile comparison showed Thies LPM measuring more small particles than Ott Parsivel2, resulting in higher rain rates and totals. These differences increased greatly with rainfall intensity. At rain rates above 10&thinsp;mm&thinsp;h&minus;1 Thies LPM recorded nine times the number of particles of PARSIVEL2, affecting all precipitation variables. The practical consequences of these differences, and possible reasons, are discussed, in order to help researchers and users in the election of the sensor, pointing out at the same time limitations to be fixed in future versions.
Top