scholarly journals Describing and locating cropping systems on a regional scale. A review

2010 ◽  
Vol 30 (1) ◽  
pp. 131-138 ◽  
Author(s):  
Delphine Leenhardt ◽  
Frédérique Angevin ◽  
Anne Biarnès ◽  
Nathalie Colbach ◽  
Catherine Mignolet
Soil Research ◽  
2014 ◽  
Vol 52 (5) ◽  
pp. 463 ◽  
Author(s):  
Zhongkui Luo ◽  
Enli Wang ◽  
Jeff Baldock ◽  
Hongtao Xing

The diversity of cropping systems and its variation could lead to great uncertainty in the estimation of soil organic carbon (SOC) stock across time and space. Using the pre-validated Agricultural Production Systems Simulator, we simulated the long-term (1022 years) SOC dynamics in the top 0.3 m of soil at 613 reference sites under 59 representative cropping systems across Australia’s cereal-growing regions. The point simulation results were upscaled to the entire cereal-growing region using a Monte Carlo approach to quantify the spatial pattern of SOC stock and its uncertainty caused by cropping system and environment. The predicted potential SOC stocks at equilibrium state ranged from 10 to 140 t ha–1, with the majority in a range 30–70 t ha–1, averaged across all the representative cropping systems. Cropping system accounted for ~10% of the total variance in predicted SOC stocks. The type of cropping system that determined the carbon input into soil had significant effects on SOC sequestration potential. On average, the potential SOC stock in the top 0.3 m of soil was 30, 50 and 60 t ha–1 under low-, medium- and high-input cropping systems in terms of carbon input, corresponding to –2, 18 and 26 t ha–1 of SOC change. Across the entire region, the Monte Carlo simulations showed that the potential SOC stock was 51 t ha–1, with a 95% confidence interval ranging from 38 to 64 t ha–1 under the identified representative cropping systems. Overall, predicted SOC stock could increase by 0.99 Pg in Australian cropland under the identified representative cropping systems with optimal management. Uncertainty varied depending on cropping system, climate and soil conditions. Detailed information on cropping system and soil and climate characteristics is needed to obtain reliable estimates of potential SOC stock at regional scale, particularly in cooler and/or wetter regions.


2019 ◽  
Vol 173 ◽  
pp. 491-503 ◽  
Author(s):  
Davide Rizzo ◽  
Olivier Therond ◽  
Romain Lardy ◽  
Clément Murgue ◽  
Delphine Leenhardt

2021 ◽  
Author(s):  
Shannon de Roos ◽  
Gabrielle De Lannoy ◽  
Dirk Raes

<p>A shift to more sustainable land cultivation practices is necessary to meet the future crop demand, which faces a vastly growing population and changing climatic conditions. To assess which management practices can be effectively applied at a regional scale, good spatial monitoring techniques are required. With a regional version of the AquaCrop model v6.1, we simulate crop biomass production and soil moisture at a 1-km resolution over Europe. Biomass productivity is compared against the Dry Matter Productivity of the Copernicus Global Land Service, derived from optical satellite sensors, while surface moisture content is evaluated with Sentinel-1 and SMAP microwave satellite retrieval products and inter-compared with in situ data. We show that the AquaCrop model can successfully be applied at a relatively fine resolution over a large scale, using global input data.</p><p>This research is part of a H2020 project, named SHui. SHui is a collaborative effort between Universities from Europe and China, with the overall aim of managing water scarcity in cropping systems for individuals as well as stakeholder organizations.</p>


2020 ◽  
Author(s):  
Shannon de Roos ◽  
Gabriëlle de Lannoy ◽  
Dirk Raes

<p>The pressure on soil and water resources to support the demand for crop production calls for effective water management at the regional scale and a need for regional crop models.</p><p>In our study, the field-based Aquacrop v.6.1 is modified to a gridded crop model that is run spatially over the main part of Europe at 1-km resolution.</p><p>The gridded model simulates spatially distributed soil moisture, crop biomass and yield, given spatial input of meteorological forcings extracted from the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) and 1-km soil texture information from the Harmonized World Soil Database v1.2 (HWSD v1.2). For the first model evaluation, a hypothetical and uniform crop is implemented, and field management and irrigation practices are not included. We will present preliminary results over Europe by comparing the spatial soil moisture and biomass simulations with remote sensing data.</p><p>This work is part of the SHui project, a H2020 project that aims at improving stakeholder decision-making for water scarcity management in European and Chinese cropping systems.</p>


Author(s):  
Delphine Leenhardt ◽  
Frédérique Angevin ◽  
Anne Biarnès ◽  
Nathalie Colbach ◽  
Catherine Mignolet

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