UAV-Based Remote Sensing to Evaluate Daily Water Demand Characteristics of Maize: A Case Study from Yuci Lifang Organic Dry Farming Experimental Base in Jinzhong City, China

Author:

Li Yaoyu1,Qu Tengteng2,Wang Yuzhi2,Zhao Qixin2,Jia Shujie2,Yin Zhe2,Guo Zhaodong2,Wang Guofang3,Li Fuzhong2,Zhang Wuping2

Affiliation:

1. College of Agricultural Engineering, Shanxi Agricultural University, Taigu 030801, China

2. College of Software, Shanxi Agricultural University, Taigu 030801, China

3. College of Resources and Environment, Shanxi Agricultural University, Taigu 030801, China

Abstract

Soil moisture critically influences crop growth, especially in dryland environments. Precise agricultural management requires real-time monitoring of stratified soil moisture and assessment of crops’ daily water needs. We aim to provide low-cost, high-throughput information acquisition services for dryland regions with underdeveloped infrastructure and offer scientific support for sustainable water resource management. We used UAVs (Unmanned Aerial Vehicles) with multi-spectral sensors for routine maize monitoring, capturing leaf reflectance. Constructing vegetation indices, we quantified the relationship between leaf water content and surface soil moisture, using the Biswas model to predict deep soil moisture distribution. We used UVAs to monitor crop height and calculated the daily water demand for the entire growth period of corn using the Penman Montes equation. We found an R2 of 0.8603, RMSE of 2.455%, and MAE of 2.099% between NDVI and canopy leaf water content. A strong linear correlation (R2 = 0.7510) between canopy leaf water content and soil moisture was observed in the top 20 cm of soil. Deep soil moisture inversion from the top 20 cm soil moisture showed an R2 of 0.9984, with RE mostly under 10%, but exceeding 20% at 120 cm depth. We also constructed a maize height model aligning with a sigmoidal growth curve (R2 = 0.9724). Maize’s daily water demand varied from 0.7121 to 9.4263 mm, exhibiting a downward-opening parabolic trend. Integration of rainfall and soil water data allowed for dynamic irrigation adjustments, mitigating drought and water stress effects on crops. We highlighted UAV multi-spectral imaging’s effectiveness in monitoring crop water needs, facilitating quick daily water requirement estimations. Our work offers a scientific foundation for managing maize cultivation in drylands, enhancing water resource utilization.

Funder

The National Key Research and Development Program Project

Key Research and Development Project in Shanxi Province

Basic Research Project of Shanxi Provincial Department of Science and Technology

Publisher

MDPI AG

Reference68 articles.

1. Does Soil Moisture Influence Climate Variability and Predictability over Australia?;Timbal;J. Clim.,2002

2. Impacts of radiation, temperature and soil moisture on hidden heat of transpiration and leaf temperature of Quercus variabilis seedlings;Jingling;Sci. Soil Water Conserv.,2017

3. An overview of soil moisture drought research in China:Progress and perspective;Wang;Atmos. Ocean. Sci. Lett.,2023

4. The International Soil Moisture Network: Serving Earth system science for over a decade;Dorigo;Hydrol. Earth Syst. Sci.,2021

5. Soil Salinization Monitoring Method Based on UAV-Satellite Remote Sensing Scale-up;Junying;Trans. Chin. Soc. Agric. Mach.,2019

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