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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Soil water balance models for determining crop water and irrigation requirements and irrigation scheduling focusing on the FAO56 method and the dual Kc approach
L. S. Pereira, Paula Paredes, Nebo Jovanovic
Agricultural Water Management (2020) Vol. 241, pp. 106357-106357
Open Access | Times Cited: 183

Showing 1-25 of 183 citing articles:

A Systematic Review on Monitoring and Advanced Control Strategies in Smart Agriculture
Syeda Iqra Hassan, Muhammad Mansoor Alam, Usman Illahi, et al.
IEEE Access (2021) Vol. 9, pp. 32517-32548
Open Access | Times Cited: 129
Two stage Stochastic Energy Scheduling for Multi Energy Rural Microgrids With Irrigation Systems and Biomass Fermentation
W. D. Li, Yunyang Zou, Hongming Yang, et al.
IEEE Transactions on Smart Grid (2024) Vol. 16, Iss. 2, pp. 1075-1087
Closed Access | Times Cited: 16
Standard single and basal crop coefficients for field crops. Updates and advances to the FAO56 crop water requirements method
L. S. Pereira, Paula Paredes, D. J. Hunsaker, et al.
Agricultural Water Management (2020) Vol. 243, pp. 106466-106466
Closed Access | Times Cited: 132
Standard single and basal crop coefficients for vegetable crops, an update of FAO56 crop water requirements approach
L. S. Pereira, Paula Paredes, R. López-Urrea, et al.
Agricultural Water Management (2020) Vol. 243, pp. 106196-106196
Closed Access | Times Cited: 106
Updated single and dual crop coefficients for tree and vine fruit crops
Giovanni Rallo, Teresa A. Paço, Paula Paredes, et al.
Agricultural Water Management (2021) Vol. 250, pp. 106645-106645
Closed Access | Times Cited: 76
An integrated strategy for improving water use efficiency by understanding physiological mechanisms of crops responding to water deficit: Present and prospect
Jian Kang, Xinmei Hao, Huiping Zhou, et al.
Agricultural Water Management (2021) Vol. 255, pp. 107008-107008
Closed Access | Times Cited: 72
Mapping maize crop coefficient Kc using random forest algorithm based on leaf area index and UAV-based multispectral vegetation indices
Guomin Shao, Wenting Han, Huihui Zhang, et al.
Agricultural Water Management (2021) Vol. 252, pp. 106906-106906
Closed Access | Times Cited: 66
A review on smart irrigation management strategies and their effect on water savings and crop yield
Sami Touil, Amina Richa, Meriem Fizir, et al.
Irrigation and Drainage (2022) Vol. 71, Iss. 5, pp. 1396-1416
Closed Access | Times Cited: 62
Evapotranspiration partitioning, water use efficiency, and maize yield under different film mulching and nitrogen application in northwest China
Heng Fang, Yuannong Li, Xiaobo Gu, et al.
Field Crops Research (2021) Vol. 264, pp. 108103-108103
Closed Access | Times Cited: 56
Soil moisture forecast for smart irrigation: The primetime for machine learning
Rodrigo Togneri, Diego Felipe dos Santos, Glauber Camponogara, et al.
Expert Systems with Applications (2022) Vol. 207, pp. 117653-117653
Closed Access | Times Cited: 52
Water Use and Soil Water Balance of Mediterranean Vineyards under Rainfed and Drip Irrigation Management: Evapotranspiration Partition and Soil Management Modelling for Resource Conservation
Hanaa Darouich, Tiago B. Ramos, L. S. Pereira, et al.
Water (2022) Vol. 14, Iss. 4, pp. 554-554
Open Access | Times Cited: 39
Water use and soil water balance of Mediterranean tree crops assessed with the SIMDualKc model in orchards of southern Portugal
Tiago B. Ramos, Hanaa Darouich, Ana R. Oliveira, et al.
Agricultural Water Management (2023) Vol. 279, pp. 108209-108209
Open Access | Times Cited: 24
AI and machine learning for soil analysis: an assessment of sustainable agricultural practices
Muhammad Awais, Syed Muhammad Zaigham Abbas Naqvi, Hao Zhang, et al.
Bioresources and Bioprocessing (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 24
Data-driven water need estimation for IoT-based smart irrigation: A survey
Rodrigo Togneri, Ronaldo C. Prati, Hitoshi Nagano, et al.
Expert Systems with Applications (2023) Vol. 225, pp. 120194-120194
Closed Access | Times Cited: 23
Machine learning models to predict daily actual evapotranspiration of citrus orchards under regulated deficit irrigation
Antonino Pagano, Federico Amato, Matteo Ippolito, et al.
Ecological Informatics (2023) Vol. 76, pp. 102133-102133
Open Access | Times Cited: 23
Spatio-temporal changes and its driving forces of irrigation water requirements for cotton in Xinjiang, China
Qingling Geng, Yongkun Zhao, Shikun Sun, et al.
Agricultural Water Management (2023) Vol. 280, pp. 108218-108218
Open Access | Times Cited: 22
Mulching effects on soil evaporation, crop evapotranspiration and crop coefficients: a review aimed at improved irrigation management
Tiago B. Ramos, Hanaa Darouich, L. S. Pereira
Irrigation Science (2024) Vol. 42, Iss. 3, pp. 525-539
Open Access | Times Cited: 9
Updates and advances to the FAO56 crop water requirements method
L. S. Pereira, Paula Paredes, Douglas J. Hunsaker, et al.
Agricultural Water Management (2021) Vol. 248, pp. 106697-106697
Open Access | Times Cited: 54
Prediction of maize crop coefficient from UAV multisensor remote sensing using machine learning methods
Guomin Shao, Wenting Han, Huihui Zhang, et al.
Agricultural Water Management (2022) Vol. 276, pp. 108064-108064
Open Access | Times Cited: 31
Evapotranspiration estimation using a modified crop coefficient model in a rotated rice-winter wheat system
Rangjian Qiu, Longan Li, Chunwei Liu, et al.
Agricultural Water Management (2022) Vol. 264, pp. 107501-107501
Closed Access | Times Cited: 29
Short-term daily reference evapotranspiration forecasting using temperature-based deep learning models in different climate zones in China
Lei Zhang, Xin Zhao, Ge Zhu, et al.
Agricultural Water Management (2023) Vol. 289, pp. 108498-108498
Open Access | Times Cited: 17
Assessing water-nitrogen use, crop growth and economic benefits for maize in upper Yellow River basin: Feasibility analysis for border and drip irrigation
Zhi Qi, Ya Gao, Chen Sun, et al.
Agricultural Water Management (2024) Vol. 295, pp. 108771-108771
Open Access | Times Cited: 6
Microtensiometers Accurately Measure Stem Water Potential in Woody Perennials
Víctor Blanco, Lee Kalcsits
Plants (2021) Vol. 10, Iss. 12, pp. 2780-2780
Open Access | Times Cited: 37
Impacts of a shallow saline water table on maize evapotranspiration and groundwater contribution using static water table lysimeters and the dual Kc water balance model SIMDualKc
Meihan Liu, Paula Paredes, Haibin Shi, et al.
Agricultural Water Management (2022) Vol. 273, pp. 107887-107887
Closed Access | Times Cited: 23
Data-Driven Modelling of Soil Moisture Dynamics for Smart Irrigation Scheduling
Erion Bwambale, Felix K. Abagale, Geophrey K. Anornu
Smart Agricultural Technology (2023) Vol. 5, pp. 100251-100251
Open Access | Times Cited: 14
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