Cultivated soil water dynamics with many Hydrus 1D simulations using R
Citation
Sigler, W. A., S. Ewing, R. Payn, C. A. Jones (2020). Cultivated soil water dynamics with many Hydrus 1D simulations using R, HydroShare,
https://doi.org/10.4211/hs.fd6cd94345f9420f97d63753fc850c41
Summary
Data and R code bundled here provide a framework to implement the open source Hydrus-1D soil water model to characterize influence of crop rotation, weather, and soils on root zone water flux in a non-irrigated annual cultivation agricultural system. Simulated water flux is combined with soil nitrate concentrations averaged by 2-year rotational sequence to produce nitrate leaching estimates. This framework and the associated results are the analytical underpinning of a paper in revision at the journal of Agricultural Ecosystems & Environment. Included are all data necessary to run the simulations, code to run the simulations (Hydrus 1D software required), code to aggregate/plot the results, and all of the results.
Software/Hardware
This code was successfully run in June 2020 using Hydrus-1D v4.16.0110 (Simunek et al., 2013) and R version 3.5.3, with a PC running Windows 10, 64-bit operating system with an Intel®Core ™ i7-6600U CPU@ 2.6 GHz processor, and 16.0 GB of RAM. R packages used in the analysis include: zoo, lubridate, reshape2, stringr, plyr, lattice, plotrix.
Contact
W. Adam Sigler
Check my ORCiD for my current email address
https://orcid.org/0000-0002-4815-0580
Rights
The original data presented here are available under CC-BY 4.0 https://creativecommons.org/licenses/by/4.0/legalcode
The code presented here is available under the MIT license.
https://opensource.org/licenses/MIT
The public domain HYDRUS 1-D Software carries a GNU General Public license as discussed on the HYDRUS 1-D website https://www.pc-progress.com/en/Default.aspx?H1D-description#k8
R packages used within the code (zoo; lubridate; reshape2; stringr; plyr; lattice; plotrix) all carry GPL-2, GPL-3, or MIT licenses.
Purpose
This framework supports assessment of the interaction between weather, soils, and management on flux of water and nitrogen through soils. Mean precipitation storage efficiency (PSE) in fallow is visually discernible in the precipitation partitioning plot (Figure 6B). PSE is zero in the plot for soil depths where partitioning bar height is approximately equal to mean annual precipitation (up to zf = 25 cm). While we focused on clay loam soil texture, additional soil textures were assessed in the sensitivity analysis and could be explored further to expand relevance of this work. Meteorological data from other weather stations could also be input to the model. Caution should be taken if applying the crop coefficients we derived for central Montana in areas with notably different climate conditions.
Related Resources
Sigler, W. Adam, Stephanie A. Ewing, Clain A Jones, Robert A. Payn, Perry Miller, Marco Maneta, In Revision. Water and nitrate loss from dryland agricultural soils is controlled by management, soils, and weather. Agriculture Ecosystems & Environment. (Primary publication this work is supporting)
Šimůnek, J., M. Šejna, M. T. van Genuchten (2020). Hydrus 1D - archive of version 4.16.0110, replicated from: Šimůnek, J., M. Šejna, and M. Th. van Genuchten. 2019. Hydrus-1D for Windows, Version 4.xx. https://www.pc-progress.com/en/Default.aspx?hydrus-1d, accessed 7/23/2020, replicated in HydroShare at: http://dx.doi.org/10.4211/hs.d24921ba081d431e80685bf177a0840f. (This is the exact version of the software used in this study, archived with source code and relevant manuals under a GNU GPLv3 license).
Simunek, J., Sejna, M., Saito, H., van Genuchten, M.Th., 2013. HYDRUS-1D Software Package for Simulating the Movement of Water, Heat, and Multiple Solutes in Variably Saturated Media, Version 4.16, HYDRUS Software Series 3, Department of Environmental Sciences, University of California Riverside, Riverside, California, USA, pp. 340, 2013.
Vick, E.S.K., Stoy, P.C., Tang, A.C.I., Gerken, T., 2016. The surface-atmosphere exchange of carbon dioxide, water, and sensible heat across a dryland wheat-fallow rotation. Agric. Ecosyst. Environ. 223, 129–140. https://doi.org/10.1016/j.agee.2016.07.018
Data References
The following are data listed in the “1_Input” section above which are from outside sources
agrimet_02to17_190717_1020.RData
• Meteorological data
• United States, Bureau of Reclamation, AgriMet network; Moccasin MT, Station Code MWSM; https://www.usbr.gov/gp/agrimet/station_mwsm_moccasin.html
carc_manual_190719.csv
• Precipitation data
• Montana State University, Central Agricultural Research Center (CARC); manual precipitation gage; Western Regional Climate Center station number 245761 https://wrcc.dri.edu/cgi-bin/cliMAIN.pl?mt5761
• The full daily precipitation dataset were not located on the website and the dataset was acquired from personnel at CARC.
daily.fa_191003_1928.RData
daily.sw_191003_1928.RData
daily.ww_191003_1928.RData
• Eddy covariance evapotranspiration data
• Paul C. Stoy (2013-2014) AmeriFlux US-Mj1 Montana Judith Basin wheat field, Dataset. https://doi.org/10.17190/AMF/1617715
• Paul C. Stoy (2014) AmeriFlux US-Mj2 Montana Judith Basin summer fallow field, Dataset. https://doi.org/10.17190/AMF/1617716
FieldC_NAIP_NDVI.csv
FieldC_ndvi.hist_181118_0816.RData
• Aerial imagery from 2011
• Four band, 1 meter resolution, aerial imagery, acquired by the National Agriculture Imagery Program (NAIP), and distributed by the Montana State Library; http://geoinfo.msl.mt.gov/data/Aerial_Photos/NAIP_2011
SCANdata_2017-04-20.csv
• Meteorological and soil moisture data
• United States, Natural Resources Conservation Service (NRCS), Soil Climate Analysis Network (SCAN); Moccasin station, Site Number 2119 https://wcc.sc.egov.usda.gov/nwcc/site?sitenum=2119&state=mt
Funding Agencies
This work was funded by the United States Department of Agriculture, National Institute of Food and Agriculture [grant number 2011-51130-31121, 2011] and USDA NIFA grant number 2016-67026-25067. Additional funding was provided by MSU Extension, Montana Fertilizer Advisory Committee, the Montana Agricultural Experiment Station and the Montana Institute on Ecosystems. This material is based upon work supported in part by the National Science Foundation EPSCoR Cooperative Agreement OIA-1757351, as well as NSF EPSCoR Track 1 award numbers OIA-1443108 and EPS-1101342
Contributors
Fordyce, Simon. Montana State University Central Agricultural Research Center
John, Andrew A.
Maneta, Marco P. University of Montana
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