Top co-authors See all
S. M. White
166 shared publications
School of Engineering, University of Durham, Science Park, Durham DH1 3LE, UK
159 shared publications
Czech Hydrometeorological Institute, Brno, Czech Republic
95 shared publications
93 shared publications
Jesús Julio Camarero
77 shared publications
Distribution of Articles published per year
(2000 - 2018)
(2000 - 2018)
Total number of journals
Publications See all
Article 0 Reads 0 Citations Comparison of precipitation measurements by OTT Parsivel2 and Thies LPM optical disdrometers Published: 08 May 2018
Hydrology and Earth System Sciences, doi: 10.5194/hess-22-2811-2018
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 100 000 min of data and up to 30 000 min with rain in more than 200 rainfall events, with intensities peaking at 277 mm h−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 0 Reads 0 Citations Regional Crop Gross Primary Productivity and Yield Estimation Using Fused Landsat-MODIS Data Published: 28 February 2018
Remote Sensing, doi: 10.3390/rs10030372
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 0 Citations Comparison of precipitation measurements by Ott Parsivel2 and Thies LPM optical disdrometers Published: 14 November 2017
Hydrology and Earth System Sciences Discussions, doi: 10.5194/hess-2017-652
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 mm h−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 mm h−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.
Article 0 Reads 0 Citations SPREAD: A high-resolution daily gridded precipitation dataset for Spain Published: 07 June 2017
Earth System Science Data Discussions, doi: 10.5194/essd-2017-35
A high-resolution daily gridded precipitation dataset was built from raw data of 12,858 observatories covering a period from 1950 to 2012 in peninsular Spain and 1971 to 2012 in Balearic and Canary Islands. The original data were quality controlled and gaps were filled on each day and location independently. Using the serially-complete dataset, a grid with a 5 x 5 kilometres spatial resolution was constructed by estimating daily precipitation amounts and their corresponding uncertainty at each grid node. Daily precipitation estimations were compared to original observations to assess the quality of the gridded dataset. Four daily precipitation indices were computed to characterize the spatial distribution of daily precipitation and nine extreme precipitation indices were used to describe the frequency and intensity of extreme precipitation events. The use of the total available data in Spain, the independent estimation of precipitation for each day and the high spatial resolution of the grid allowed for a precise spatial and temporal assessment of daily precipitation that are difficult to achieve when using other methods, pre- selected long-term stations or global gridded datasets. SPREAD dataset is publicly available at http://dx.doi.org/10.20350/digitalCSIC/7393.
Article 0 Reads 10 Citations Ongoing and Emerging Questions in Water Erosion Studies Published: 12 December 2016
Land Degradation & Development, doi: 10.1002/ldr.2641
Soil erosion is a threat to food security, especially in regions where the area of arable land is shrinking dramatically because of soil degradation. Research on soil erosion expanded progressively throughout the 20th century, although a number of unresolved problems persist despite this issue being crucial for the environment and the welfare of society. Some basic unresolved issues, including the absence of a universally accepted definition of soil erosion and disagreement about how to measure it have contributed to a degree of scientific stagnation. Accurate prediction of the response of soils to disturbance is hampered by the dependence of the erosion process on the spatial scale involved, the time lag between the disturbance and the erosion response, and the short periods for which data are typically available. We argue that devoting increased attention to the following environmental, demographic, political, and societal issues will reinvigorate progress in the field. i) The relationships between on-site and off-site consequences of soil erosion need to be elucidated if the economic and environmental costs are to be adequately assessed. ii) Effective measures for soil conservation need to focus on spatial patterns of plant cover that reduce sediment connectivity, and most importantly on the relationships between hillslopes and sediment transfer in eroded channels. iii) The scientific community must be able to identify early warning signs of critical transitions, if irreversible soil degradation is to be prevented. iv) Consensus needs to be reached concerning the contribution of soil erosion to the carbon cycle. v) The consequences of climate change on erosion and sediment transport should be investigated in depth. vi) The general society needs to perceive soil erosion as a critical matter requiring an urgent response. This article is protected by copyright. All rights reserved.
Article 1 Read 2 Citations Estimating erosion rates using 137Cs measurements and WATEM/SEDEM in a Mediterranean cultivated field Published: 01 March 2016
CATENA, doi: 10.1016/j.catena.2015.11.009
Highlights•Similar soil redistribution patterns obtained by 137Cs and WATEM/SEDEM•Water erosion dominates soil redistribution over tillage erosion for the study period.•Spatially 137Cs redistribution rates are useful to calibrate WATEM/SEDEM.•Water erosion affects the distribution and export of soil fine components.•Topographic changes by human activity are not well captured by WATEM/SEDEM. ABSTRACTThe loss of fertile topsoil is one of the principal soil degradation problems in agricultural landscapes worldwide. Mediterranean agroecosystems are particularly threatened to soil degradation because of the climate, a higher sensitivity to soil erosion and the intensification of human activities and agricultural practices during centuries. The severity of this problem and the expected increasing risk of soil erosion in Mediterranean cultivated landscapes as a consequence of climate change have generated a demand for estimations of soil redistribution rates and soil loss monitoring.In this study, a representative cultivated field of mountain Mediterranean agroecosystems was selected to estimate 137Cs derived soil redistribution rates using a 137Cs mass balance model. Besides numeric simulation was performed using the WATEM/SEDEM model to estimate spatially-distributed soil redistribution rates. A detailed topographic survey was done to obtain a high-resolution digital elevation model (2.5 m) of the study field and 137Cs derived soil redistribution rates were used to calibrate the model. In the study field, soil erosion predominated over soil deposition. Mean values of 137Cs derived soil erosion and deposition rates were 19.7 Mg ha− 1 yr− 1 and 12.6 Mg ha− 1 yr− 1, respectively. Water erosion was the predominant process of soil redistribution whereas tillage erosion was not significant. The rates obtained with WATEM/SEDEM model were lower; mean erosion was 3.9 Mg ha− 1 yr− 1 and mean deposition rates that occurred in 35% of the grid cells was of 5.8 Mg ha− 1 yr− 1. The use of spatially-distributed models is required to better quantify soil redistribution processes and to evaluate superficial soil distribution. However, point-estimates of soil redistribution such as those provided by 137Cs are required to allow calibration of the models. The knowledge about the spatial distribution of erosion processes is a useful tool for the application of effective soil erosion control and prevention strategies on water and tillage erosion on agroecosystems.