Preprints
https://doi.org/10.5194/gmd-2021-98
https://doi.org/10.5194/gmd-2021-98

Submitted as: development and technical paper 17 May 2021

Submitted as: development and technical paper | 17 May 2021

Review status: this preprint is currently under review for the journal GMD.

Performance analysis of regional AquaCrop (v6.1) biomass and surface soil moisture simulations using satellite and in situ observations

Shannon de Roos, Gabriëlle J. M. De Lannoy, and Dirk Raes Shannon de Roos et al.
  • Department of Earth and Environmental Sciences, KU Leuven, Heverlee, B-3001, Belgium

Abstract. 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 good insight in land cultivation practices at the field to global scale.

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 arcseconds (~1 km). 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. 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 correlation of 0.8 (CGLS-DMP), 0.74 (SMAP-SSM) and 0.52 (CGLS-SSM), respectively. 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 interannual 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 proves to be useful in assessing crop production and soil moisture at various scales and could serve as a bridge between point-based and global models.

Shannon de Roos et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CEC1: 'Comment on gmd-2021-98', Juan Antonio Añel, 17 May 2021
    • AC1: 'Reply on CEC1', Shannon de Roos, 18 May 2021
  • RC1: 'Comment on gmd-2021-98', Christoph Müller, 11 Jun 2021
    • AC2: 'Reply on RC1', Shannon de Roos, 25 Jun 2021
  • RC2: 'Comment on gmd-2021-98', Anonymous Referee #2, 26 Jul 2021
    • AC3: 'Reply on RC2', Shannon de Roos, 30 Jul 2021

Shannon de Roos et al.

Shannon de Roos et al.

Viewed

Total article views: 312 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
230 71 11 312 3 1
  • HTML: 230
  • PDF: 71
  • XML: 11
  • Total: 312
  • BibTeX: 3
  • EndNote: 1
Views and downloads (calculated since 17 May 2021)
Cumulative views and downloads (calculated since 17 May 2021)

Viewed (geographical distribution)

Total article views: 305 (including HTML, PDF, and XML) Thereof 305 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 30 Jul 2021
Download
Short summary
A spatially distributed version of the field-scale crop model AquaCrop v6.1 was developed for applications at various spatial scales. Multi-year 1-km simulations over Europe were evaluated against biomass and surface soil moisture products derived from optical and microwave satellite missions, and in situ observations of soil moisture. Even when using easily accessible global input data, the model is able to capture the temporal and spatial variability at the field to regional scale.