Effect of temporal resolution of wind data on wind erosion prediction with the revised wind erosion equation (RWEQ)

In wind erosion modelling and assessment, wind speed is a crucial variable. Available records for large regions of the world generally show relatively low temporal resolution. The effect of using wind data of different temporal resolutions in RWEQ discrete and continuous versions was assessed. Wind...

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Main Authors: Juan E Panebianco, Daniel E Buschiazzo
Format: Article
Language:English
Published: Asociación Argentina de la Ciencia del Suelo
Series:Ciencia del Suelo
Subjects:
Online Access:http://www.scielo.org.ar/scielo.php?script=sci_arttext&pid=S1850-20672013000200005&lng=en&tlng=en
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author Juan E Panebianco
Daniel E Buschiazzo
author_facet Juan E Panebianco
Daniel E Buschiazzo
author_sort Juan E Panebianco
collection DOAJ
description In wind erosion modelling and assessment, wind speed is a crucial variable. Available records for large regions of the world generally show relatively low temporal resolution. The effect of using wind data of different temporal resolutions in RWEQ discrete and continuous versions was assessed. Wind erosion was measured during 82 high-wind events occurring between 2005 and 2008. Simulated and measured erosion values were compared. For wind erosion simulation during discrete periods, the model was loaded with wind speeds averaged in 5 minutes and 1 hour- intervals. For continuous simulation, a weather file for RWEQ/ 97 was developed and Weibull factors were calculated using both hourly and daily wind speeds. When the discrete version of RWEQ was used with hourly wind speeds instead of five-minute averages, the total simulated soil loss was reduced by 44%. The model efficiency was not significantly affected by wind speed data resolution. RWEQ continuous version, loaded with monthly Weibull parameters using hourly wind speeds, calculated zero erosion. Monthly Weibull distribution scale factors calculated using daily wind speeds were reduced by 32% on average with respect to hourly data. Increasing the Weibull scale parameter by up to 50% slightly improved the monthly simulated erosion rates. Using low resolution wind speed data reduces the model outputs. This may be corrected but a large amount of field information is needed.
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spelling doaj.art-6a9676c8fbb044d09f769b1cf923a6a42022-12-21T22:11:46ZengAsociación Argentina de la Ciencia del SueloCiencia del Suelo0326-31691850-2067312189199S1850-20672013000200005Effect of temporal resolution of wind data on wind erosion prediction with the revised wind erosion equation (RWEQ)Juan E Panebianco0Daniel E Buschiazzo1Consejo Nacional de Investigaciones Científicas y TécnicasConsejo Nacional de Investigaciones Científicas y TécnicasIn wind erosion modelling and assessment, wind speed is a crucial variable. Available records for large regions of the world generally show relatively low temporal resolution. The effect of using wind data of different temporal resolutions in RWEQ discrete and continuous versions was assessed. Wind erosion was measured during 82 high-wind events occurring between 2005 and 2008. Simulated and measured erosion values were compared. For wind erosion simulation during discrete periods, the model was loaded with wind speeds averaged in 5 minutes and 1 hour- intervals. For continuous simulation, a weather file for RWEQ/ 97 was developed and Weibull factors were calculated using both hourly and daily wind speeds. When the discrete version of RWEQ was used with hourly wind speeds instead of five-minute averages, the total simulated soil loss was reduced by 44%. The model efficiency was not significantly affected by wind speed data resolution. RWEQ continuous version, loaded with monthly Weibull parameters using hourly wind speeds, calculated zero erosion. Monthly Weibull distribution scale factors calculated using daily wind speeds were reduced by 32% on average with respect to hourly data. Increasing the Weibull scale parameter by up to 50% slightly improved the monthly simulated erosion rates. Using low resolution wind speed data reduces the model outputs. This may be corrected but a large amount of field information is needed.http://www.scielo.org.ar/scielo.php?script=sci_arttext&pid=S1850-20672013000200005&lng=en&tlng=enpredicción de la erosión eólicadatos de vientoenergía eólicarweq
spellingShingle Juan E Panebianco
Daniel E Buschiazzo
Effect of temporal resolution of wind data on wind erosion prediction with the revised wind erosion equation (RWEQ)
Ciencia del Suelo
predicción de la erosión eólica
datos de viento
energía eólica
rweq
title Effect of temporal resolution of wind data on wind erosion prediction with the revised wind erosion equation (RWEQ)
title_full Effect of temporal resolution of wind data on wind erosion prediction with the revised wind erosion equation (RWEQ)
title_fullStr Effect of temporal resolution of wind data on wind erosion prediction with the revised wind erosion equation (RWEQ)
title_full_unstemmed Effect of temporal resolution of wind data on wind erosion prediction with the revised wind erosion equation (RWEQ)
title_short Effect of temporal resolution of wind data on wind erosion prediction with the revised wind erosion equation (RWEQ)
title_sort effect of temporal resolution of wind data on wind erosion prediction with the revised wind erosion equation rweq
topic predicción de la erosión eólica
datos de viento
energía eólica
rweq
url http://www.scielo.org.ar/scielo.php?script=sci_arttext&pid=S1850-20672013000200005&lng=en&tlng=en
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AT danielebuschiazzo effectoftemporalresolutionofwinddataonwinderosionpredictionwiththerevisedwinderosionequationrweq