Under the same perspective of the Sustainable Development Goal (SDG) 15.3 aiming to restore degraded land and soil, one of the current priorities of the new Common Agriculture Policy (CAP) is to overcome the serious environmental problems raised by intensive agriculture. Despite the steps forward guaranteed by new technologies and innovations (e.g., IoT, precision agriculture), the availability of real operational tools, which could help the member states fulfil the high requirements and expectations of the new CAP and SDGs, is still lacking. To fill this gap, in the H2020 LandSupport project, the web-based best practice tool was developed to identify, on-the-fly, optimized agronomic solutions to help achieve land-degradation neutrality. The tool's core is the ARMOSA process-based model, which dynamically simulates the continuum soil–plant–atmosphere, combining several cropping systems, crops, nitrogen fertilization rates, tillage solutions, and crop residue management for specific regions of interest. It provides a synthetic “Best Practice index” to identify the optimized local solutions, which combines the production, nitrate leaching, and SOC_change, according to the end-user dynamic requests. The tool was implemented for three case studies: Marchfeld Region in Austria, Zala County in Hungary, and Campania Region in Italy, which are representative of a variety of different pedoclimatic conditions. In the present work, we report three possible cases of use in supporting best practices aiming toward soil and water conservation: (i) crop production optimization; (ii) impact of management practices (i.e., cover crops) over soil carbon; (iii) lowering the impact of nitrate leaching.

中文翻译：

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一种基于网络的操作工具，用于识别欧洲农业系统的最佳实践


在旨在恢复退化土地和土壤的可持续发展目标（SDG）15.3的同一视角下，新的共同农业政策（CAP）当前的优先事项之一是克服集约农业带来的严重环境问题。尽管新技术和创新（例如物联网、精准农业）保证了前进的步伐，但仍然缺乏可以帮助成员国满足新的 CAP 和 SDG 的高要求和期望的实际操作工具。为了填补这一空白，在 H2020 土地支持项目中，开发了基于网络的最佳实践工具，以识别即时、优化的农艺解决方案，以帮助实现土地退化零增长。该工具的核心是基于 ARMOSA 流程的模型，该模型动态模拟连续的土壤-植物-大气，结合了特定感兴趣区域的多种耕作系统、作物、氮肥施肥率、耕作解决方案和作物残茬管理。它提供了一个综合的“最佳实践指数”来识别优化的本地解决方案，根据最终用户的动态请求，将生产、硝酸盐浸出和 SOC_change 结合起来。该工具针对三个案例研究进行了实施：奥地利的马奇菲尔德地区、匈牙利的佐拉县和意大利的坎帕尼亚地区，这些地区代表了各种不同的土壤气候条件。在目前的工作中，我们报告了支持水土保持最佳实践的三种可能的使用案例：（i）作物生产优化； (ii) 管理实践（即覆盖作物）对土壤碳的影响； (iii) 降低硝酸盐浸出的影响。