Mapping crop evapotranspiration with high-resolution imagery and meteorological data: insights into sustainable agriculture in Prince Edward Island

Fatima Imtiaz, Aitazaz Farooque, Xander Wang, Farhat Abbas, Hassan Afzaal, Travis Esau, Bishnu Acharya, Qamar Zaman
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Abstract

Soil moisture variability caused by soil erosion, weather extremes, and spatial variations in soil health is a limiting factor for crop growth and productivity. Crop evapotranspiration (ET) is significant for irrigation water management systems. The variability in crop water requirements at various growth stages is a common concern at a global level. In Canada’s Prince Edward Island (PEI), where agriculture is particularly prominent, this concern is predominantly evident. The island’s most prominent business, agriculture, finds it challenging to predict agricultural water needs due to shifting climate extremes, weather patterns, and precipitation patterns. Thus, accurate estimations for irrigation water requirements are essential for water conservation and precision farming. This work used a satellite-based normalized difference vegetation index (NDVI) technique to simulate the crop coefficient (K c ) and crop evapotranspiration (ET c ) for field-scale potato cultivation at various crop growth stages for the growing seasons of 2021 and 2022. The standard FAO Penman–Monteith equation was used to estimate the reference evapotranspiration (ET r ) using weather data from the nearest weather stations. The findings showed a statistically significant ( p < 0.05) positive association between NDVI and tabulated K c values extracted from all three satellites (Landsat 8, Sentinel-2A, and Planet) for the 2021 season. However, the correlation weakened in the subsequent year, particularly for Sentinel-2A and Planet data, while the association with Landsat 8 data became statistically insignificant ( p > 0.05). Sentinel-2A outperformed Landsat 8 and Planet overall. The K c values peaked at the halfway stage, fell before the maturity period, and were at their lowest at the start of the season. A similar pattern was observed for ET c (mm/day), which peaked at midseason and decreased with each developmental stage of the potato crop. Similar trends were observed for ET c (mm/day), which peaked at the mid-stage with mean values of 4.0 (2021) and 3.7 (2022), was the lowest in the initial phase with mean values of 1.8 (2021) and 1.5 (2022), and grew with each developmental stage of the potato crop. The study’s ET maps show how agricultural water use varies throughout a growing season. Farmers in Prince Edward Island may find the applied technique helpful in creating sustainable growth plans at different phases of crop development. Integrating high-resolution imagery with soil health, yield mapping, and crop growth parameters can help develop a decision support system to tailor sustainable management practices to improve profit margins, crop yield, and quality.
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利用高分辨率图像和气象数据绘制作物蒸散量图:对爱德华王子岛可持续农业的见解
土壤侵蚀、极端天气和土壤健康的空间变化引起的土壤水分变异是作物生长和生产力的限制因素。作物蒸散发(ET)对灌溉水管理系统具有重要意义。作物在不同生长阶段需水量的变化是全球普遍关注的问题。在农业特别突出的加拿大爱德华王子岛(PEI),这种担忧尤为明显。由于极端气候、天气模式和降水模式的变化,该岛最重要的商业——农业发现,预测农业用水需求是一项挑战。因此,准确估计灌溉需水量对节水和精准农业至关重要。本研究采用基于卫星的归一化植被指数(NDVI)技术,模拟了2021年和2022年不同作物生长阶段马铃薯大田种植的作物系数(kc)和作物蒸散量(ET c)。利用最近气象站的气象数据,使用FAO标准Penman-Monteith方程估计参考蒸散量(ET r)。研究结果显示了统计学上显著的(p <从所有三颗卫星(Landsat 8、Sentinel-2A和Planet)提取的2021年季节NDVI与表中K - c值呈正相关。然而,在接下来的一年里,相关性减弱了,特别是对于Sentinel-2A和Planet数据,而与Landsat 8数据的关联在统计上变得微不足道(p >0.05)。哨兵- 2a整体表现优于陆地卫星8号和行星。K - c值在中期达到峰值,在成熟期之前下降,在季初达到最低。蒸散发量(mm/day)也有类似的规律,在季中达到峰值,并随着马铃薯作物的各个发育阶段而下降。ET c (mm/d)的变化趋势与此类似,在中期达到峰值,平均值为4.0(2021年)和3.7(2022年),在初始阶段最低,平均值为1.8(2021年)和1.5(2022年),并且随着马铃薯作物的各个发育阶段而增长。该研究的ET地图显示了农业用水在整个生长季节的变化情况。爱德华王子岛的农民可能会发现,这项应用技术有助于在作物生长的不同阶段制定可持续的生长计划。将高分辨率图像与土壤健康、产量测绘和作物生长参数相结合,可以帮助开发决策支持系统,以定制可持续管理实践,从而提高利润率、作物产量和质量。
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