Performance analysis of regional AquaCrop (v6.1) biomass and surface soil moisture simulations using satellite and in situ observations
<p>The current intensive use of agricultural land is affecting the land quality and contributes to climate change. Feeding the world's growing population under changing climatic conditions demands a global transition to more sustainable agricultural systems. This requires efficient models...
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Copernicus Publications
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/6279ad74594847e38396eab3837bee54 |
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| Sumario: | <p>The current intensive use of agricultural land is affecting the land quality
and contributes to climate change. Feeding the world's growing population
under changing climatic conditions demands a global transition to more
sustainable agricultural systems. This requires efficient models and data to
monitor land cultivation practices at the field to global scale.</p>
<p>This study outlines a spatially distributed version of the field-scale crop
model AquaCrop version 6.1 to simulate agricultural biomass production and
soil moisture variability over Europe at a relatively fine resolution of 30 arcsec (<span class="inline-formula">∼1</span> <span class="inline-formula">km</span>). A highly efficient parallel processing
system is implemented to run the model regionally with global meteorological
input data from the Modern-Era Retrospective analysis for Research and
Applications version 2 (MERRA-2), soil textural information from the
Harmonized World Soil Database version 1.2 (HWSDv1.2), and generic crop
information. The setup with a generic crop is chosen as a baseline for a
future satellite-based data assimilation system. The relative temporal
variability in daily crop biomass production is evaluated with the Copernicus
Global Land Service dry matter productivity (CGLS-DMP) data. Surface soil
moisture is compared against NASA Soil Moisture Active–Passive surface soil
moisture (SMAP-SSM) retrievals, the Copernicus Global Land Service surface
soil moisture (CGLS-SSM) product derived from Sentinel-1, and in situ data
from the International Soil Moisture Network (ISMN). Over central Europe, the
regional AquaCrop model is able to capture the temporal variability in both
biomass production and soil moisture, with a spatial mean temporal correlation
of 0.8 (CGLS-DMP), 0.74 (SMAP-SSM), and 0.52 (CGLS-SSM). The
higher performance when evaluating with SMAP-SSM compared to Sentinel-1
CGLS-SSM is largely due to the lower quality of CGLS-SSM satellite retrievals
under growing vegetation. The regional model further captures the short-term
and inter-annual variability, with a mean anomaly correlation of 0.46 for daily
biomass and mean anomaly correlations of 0.65 (SMAP-SSM) and 0.50 (CGLS-SSM)
for soil moisture. It is shown that soil textural characteristics and
irrigated areas influence the model performance. Overall, the regional
AquaCrop model adequately simulates crop production and soil moisture and
provides a suitable setup for subsequent satellite-based data assimilation.</p> |
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