CONTEXT

Crop rotations considerably affect the hydrological regime of river basins used for agricultural production and are key for sustainable land and water management. However, eco-hydrological modelling usually neglects crop rotations.

OBJECTIVE

In this paper, we present a Crop Generator to reproduce the stochastic characteristics of crop rotations at regional scale.

METHODS

The Crop Generator emulates farmers’ decision making on crop rotation planning. We combined the Crop Generator with the eco-hydrological Soil and Water Integrated Model to show the hydrological relevance of considering crop rotations in a study region in central Europe including the Elbe River basin.

RESULTS AND CONCLUSIONS

A spatial validation showed that the Crop Generator reproduced the given cropping patterns well. Higher daily discharge, runoff and groundwater seepage and lower evapotranspiration were simulated based on crop rotations compared with a simplified representation of cropping patterns. The Crop Generator is a solution to simulate more realistic cropping patterns in large-scale eco-hydrological modelling. It closes the gap between aggregated agricultural statistics and the requirement of representing crop rotations in a realistic way in eco-hydrological modelling.

SIGNIFICANCE

The Crop Generator enables smart projections of future adjustments in crop rotations in view of climate and socio-economic changes as a basis for improving eco-hydrological projections and designing more sustainable agricultural systems.

中文翻译：

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作物生成器：实施轮作以有效推进生态水文建模

语境

作物轮作对用于农业生产的河流流域的水文状况有很大影响，是可持续土地和水资源管理的关键。然而，生态水文模型通常会忽略轮作。

客观的

在本文中，我们提出了一个作物生成器来重现区域范围内作物轮作的随机特征。

方法

Crop Generator 模拟农民对轮作计划的决策。我们将作物生成器与生态水文土壤和水综合模型相结合，以展示在包括易北河流域在内的中欧研究地区考虑作物轮作的水文相关性。

结果和结论

空间验证表明，作物生成器很好地再现了给定的作物模式。与种植模式的简化表示相比，基于轮作模拟了更高的日排放量、径流和地下水渗漏以及更低的蒸散量。Crop Generator 是一种在大规模生态水文建模中模拟更逼真的种植模式的解决方案。它缩小了汇总农业统计数据与在生态水文建模中以现实方式表示作物轮作的要求之间的差距。

意义

Crop Generator 能够根据气候和社会经济变化对未来作物轮作的调整进行智能预测，以此作为改进生态水文预测和设计更可持续的农业系统的基础。