使用机器学习模型评估土壤水分不足和补充灌溉方案对俄亥俄州玉米和大豆产量的影响

IF 6.5 1区 农林科学 Q1 AGRONOMY
Rajveer Dhillon , Susanta Das , Vinayak S. Shedekar , Vivek Sharma
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引用次数: 0

摘要

为了了解气候变量和灌溉需求与作物产量之间的关系,本研究评估了月降水量、温度、土壤水分亏缺(SWD)和补充灌溉对俄亥俄州县域玉米和大豆产量时空变异的影响。我们将土壤水分平衡方法与机器学习相结合,以确定影响补灌对县级玉米和大豆产量影响的关键气候和土壤水文变量。为了模拟SWD和天气参数对产量变异的影响,随机森林模型对玉米产量的RMSE为0.60 Mt/ha, R²为0.77,对大豆产量的RMSE为0.21 Mt/ha, R²为0.64。玉米产量受7月土壤水分亏缺、9月最高温度和8月降水影响最大,而大豆产量主要受5月和8月降水影响。夏季补充灌溉50.8 毫米/月,玉米产量比大豆产量提高更多,与旱作条件相比,玉米产量平均增加598 公斤/公顷(约0.6公吨/公顷)。然而,在所有条件下,对两种作物进行补充灌溉,在统计上显著降低了年际产量变异性。灌溉超过50.8 毫米/月没有产生进一步的显著收益。产量的提高在不同年份有所不同,干旱年份的产量提高幅度较大,特别是玉米,在9月份较凉爽的年份产量提高幅度更大。俄亥俄州西南部的玉米平均产量(1991-2022年)增幅较高,平均增幅高达22.6% %,相当于增加1224 公斤/公顷(约120万吨/公顷)。大豆的平均产量增幅高达9.2 %,相当于207.5 kg/ha (~ 0.21 Mt/ha)的增幅,俄亥俄州不同地区的平均产量增幅较高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessing the impact of soil water deficit and supplemental irrigation scenarios on Ohio’s maize and soybean yields using machine learning models
To understand the relationship between climate variables and irrigation requirements with crop yield, this study evaluates the role of monthly precipitation, temperature, soil water deficit (SWD), and supplemental irrigation on the spatio-temporal variability of county-level maize and soybean yields across Ohio. We combined a soil water balance approach with machine learning to identify key climatic and soil hydrological variables influencing the effects of supplemental irrigation on county-level maize and soybean yields. To model the effect of SWD and weather parameters on yield variability, the Random Forest model performed best with an RMSE of 0.60 Mt/ha and an R² of 0.77 for maize, and with an RMSE of 0.21 Mt/ha and an R² of 0.64 for soybean yields. Maize yields were most influenced by July soil water deficit, September maximum temperature, and August precipitation, whereas soybean yields were primarily affected by precipitation in May and August. Supplemental irrigation of 50.8 mm/month during the summer improved maize yields more than soybean yields, with an average maize yield increase of 598 kg/ha (∼0.6 Mt/ha) relative to rainfed conditions. However, a statistically significant reduction in inter-annual yield variability was found with supplemental irrigation under all conditions for both crops. Irrigation beyond 50.8 mm/month did not yield further significant gains. Yield improvement varied over the years, with higher improvement seen during dry years, particularly for maize and it was more pronounced in years with cooler September months. Southwest Ohio showed a higher average yield (1991–2022) increase for maize, with an average increase of up to 22.6 %, which corresponds to an increase of 1224 kg/ha (∼1.2 Mt/ha). For soybeans, an average yield increase of up to 9.2 % was found, which corresponds to an increase of 207.5 kg/ha (∼0.21 Mt/ha), and counties with higher average yield increases were found in different regions of Ohio.
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来源期刊
Agricultural Water Management
Agricultural Water Management 农林科学-农艺学
CiteScore
12.10
自引率
14.90%
发文量
648
审稿时长
4.9 months
期刊介绍: Agricultural Water Management publishes papers of international significance relating to the science, economics, and policy of agricultural water management. In all cases, manuscripts must address implications and provide insight regarding agricultural water management.
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