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Title: Effect of temporal averaging of meteorological data on predictions of groundwater recharge

Abstract

Accurate estimates of infiltration and groundwater recharge are critical for many hydrologic, agricultural and environmental applications. Anticipated climate change in many regions of the world, especially in tropical areas, is expected to increase the frequency of high-intensity, short-duration precipitation events, which in turn will affect the groundwater recharge rate. Estimates of recharge are often obtained using monthly or even annually averaged meteorological time series data. In this study we employed the HYDRUS-1D software package to assess the sensitivity of groundwater recharge calculations to using meteorological time series of different temporal resolutions (i.e., hourly, daily, weekly, monthly and yearly averaged precipitation and potential evaporation rates). Calculations were applied to three sites in Brazil having different climatological conditions: a tropical savanna (the Cerrado), a humid subtropical area (the temperate southern part of Brazil), and a very wet tropical area (Amazonia). To simplify our current analysis, we did not consider any land use effects by ignoring root water uptake. Temporal averaging of meteorological data was found to lead to significant bias in predictions of groundwater recharge, with much greater estimated recharge rates in case of very uneven temporal rainfall distributions during the year involving distinct wet and dry seasons. For example, at themore » Cerrado site, using daily averaged data produced recharge rates of up to 9 times greater than using yearly averaged data. In all cases, an increase in the time of averaging of meteorological data led to lower estimates of groundwater recharge, especially at sites having coarse-textured soils. Lastly, our results show that temporal averaging limits the ability of simulations to predict deep penetration of moisture in response to precipitation, so that water remains in the upper part of the vadose zone subject to upward flow and evaporation.« less

Authors:
 [1];  [1];  [2];  [3]
  1. Univ. of Rio de Janeiro, Rio de Janeiro (Brazil)
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  3. Sao Paulo State Univ., Rio Claro (Brazil); Utrecht Univ., Utrecht (Netherlands)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
OSTI Identifier:
1461160
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Hydrology and Hydromechanics
Additional Journal Information:
Journal Volume: 66; Journal Issue: 2; Journal ID: ISSN 0042-790X
Publisher:
de Gruyter
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; Groundwater recharge; Meteorological data; Temporal averaging; HYDRUS-1D; Infiltration; Evaporation

Citation Formats

Batalha, Marcia S., Barbosa, Maria C., Faybishenko, Boris, and van Genuchten, Martinus Th. Effect of temporal averaging of meteorological data on predictions of groundwater recharge. United States: N. p., 2018. Web. doi:10.1515/johh-2017-0051.
Batalha, Marcia S., Barbosa, Maria C., Faybishenko, Boris, & van Genuchten, Martinus Th. Effect of temporal averaging of meteorological data on predictions of groundwater recharge. United States. https://doi.org/10.1515/johh-2017-0051
Batalha, Marcia S., Barbosa, Maria C., Faybishenko, Boris, and van Genuchten, Martinus Th. Tue . "Effect of temporal averaging of meteorological data on predictions of groundwater recharge". United States. https://doi.org/10.1515/johh-2017-0051. https://www.osti.gov/servlets/purl/1461160.
@article{osti_1461160,
title = {Effect of temporal averaging of meteorological data on predictions of groundwater recharge},
author = {Batalha, Marcia S. and Barbosa, Maria C. and Faybishenko, Boris and van Genuchten, Martinus Th.},
abstractNote = {Accurate estimates of infiltration and groundwater recharge are critical for many hydrologic, agricultural and environmental applications. Anticipated climate change in many regions of the world, especially in tropical areas, is expected to increase the frequency of high-intensity, short-duration precipitation events, which in turn will affect the groundwater recharge rate. Estimates of recharge are often obtained using monthly or even annually averaged meteorological time series data. In this study we employed the HYDRUS-1D software package to assess the sensitivity of groundwater recharge calculations to using meteorological time series of different temporal resolutions (i.e., hourly, daily, weekly, monthly and yearly averaged precipitation and potential evaporation rates). Calculations were applied to three sites in Brazil having different climatological conditions: a tropical savanna (the Cerrado), a humid subtropical area (the temperate southern part of Brazil), and a very wet tropical area (Amazonia). To simplify our current analysis, we did not consider any land use effects by ignoring root water uptake. Temporal averaging of meteorological data was found to lead to significant bias in predictions of groundwater recharge, with much greater estimated recharge rates in case of very uneven temporal rainfall distributions during the year involving distinct wet and dry seasons. For example, at the Cerrado site, using daily averaged data produced recharge rates of up to 9 times greater than using yearly averaged data. In all cases, an increase in the time of averaging of meteorological data led to lower estimates of groundwater recharge, especially at sites having coarse-textured soils. Lastly, our results show that temporal averaging limits the ability of simulations to predict deep penetration of moisture in response to precipitation, so that water remains in the upper part of the vadose zone subject to upward flow and evaporation.},
doi = {10.1515/johh-2017-0051},
journal = {Journal of Hydrology and Hydromechanics},
number = 2,
volume = 66,
place = {United States},
year = {Tue Feb 06 00:00:00 EST 2018},
month = {Tue Feb 06 00:00:00 EST 2018}
}

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Works referencing / citing this record:

Groundwater recharge estimation using HYDRUS 1D model in Alaşehir sub-basin of Gediz Basin in Turkey
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