In:
Geoscientific Model Development, Copernicus GmbH, Vol. 14, No. 1 ( 2021-01-28), p. 573-601
Abstract:
Abstract. The incorporation of a comprehensive crop module in land
surface models offers the possibility to study the effect of agricultural
land use and land management changes on the terrestrial water, energy, and
biogeochemical cycles. It may help to improve the simulation of
biogeophysical and biogeochemical processes on regional and global scales in
the framework of climate and land use change. In this study, the performance
of the crop module of the Community Land Model version 5 (CLM5) was
evaluated at point scale with site-specific field data focusing on the
simulation of seasonal and inter-annual variations in crop growth, planting
and harvesting cycles, and crop yields, as well as water, energy, and carbon
fluxes. In order to better represent agricultural sites, the model was
modified by (1) implementing the winter wheat subroutines following Lu et al. (2017) in CLM5; (2) implementing plant-specific parameters for sugar beet,
potatoes, and winter wheat, thereby adding the two crop functional types
(CFTs) for sugar beet and potatoes to the list of actively managed crops in
CLM5; and (3) introducing a cover-cropping subroutine that allows multiple crop
types on the same column within 1 year. The latter modification allows the
simulation of cropping during winter months before usual cash crop planting
begins in spring, which is an agricultural management technique with a long
history that is regaining popularity as it reduces erosion and improves soil
health and carbon storage and is commonly used in the regions evaluated in
this study. We compared simulation results with field data and found that
both the new crop-specific parameterization and the winter wheat
subroutines led to a significant simulation improvement in terms of energy
fluxes (root-mean-square error, RMSE, reduction for latent and sensible heat by up to 57 % and 59 %, respectively), leaf area index (LAI), net ecosystem exchange, and crop
yield (up to 87 % improvement in winter wheat yield prediction) compared
with default model results. The cover-cropping subroutine yielded a
substantial improvement in representation of field conditions after harvest
of the main cash crop (winter season) in terms of LAI magnitudes,
seasonal cycle of LAI, and latent heat flux (reduction of wintertime RMSE
for latent heat flux by 42 %). Our modifications significantly improved
model simulations and should therefore be applied in future studies with
CLM5 to improve regional yield predictions and to better understand
large-scale impacts of agricultural management on carbon, water, and energy
fluxes.
Type of Medium:
Online Resource
ISSN:
1991-9603
DOI:
10.5194/gmd-14-573-2021
DOI:
10.5194/gmd-14-573-2021-supplement
Language:
English
Publisher:
Copernicus GmbH
Publication Date:
2021
detail.hit.zdb_id:
2456725-5
Bookmarklink
