Evapotranspiration evaluation models based on machine learning algorithms—A comparative study
Author
Abstract
Suggested Citation
DOI: 10.1016/j.agwat.2019.03.015
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Torres, Alfonso F. & Walker, Wynn R. & McKee, Mac, 2011. "Forecasting daily potential evapotranspiration using machine learning and limited climatic data," Agricultural Water Management, Elsevier, vol. 98(4), pages 553-562, February.
- Anapalli, Saseendran S. & Fisher, Daniel K. & Reddy, Krishna N. & Wagle, Pradeep & Gowda, Prasanna H. & Sui, Ruixiu, 2018. "Quantifying soybean evapotranspiration using an eddy covariance approach," Agricultural Water Management, Elsevier, vol. 209(C), pages 228-239.
- Valipour, Mohammad & Gholami Sefidkouhi, Mohammad Ali & Raeini−Sarjaz, Mahmoud, 2017. "Selecting the best model to estimate potential evapotranspiration with respect to climate change and magnitudes of extreme events," Agricultural Water Management, Elsevier, vol. 180(PA), pages 50-60.
- Krishna Singh & Mahesh Pal & V. Singh, 2010. "Estimation of Mean Annual Flood in Indian Catchments Using Backpropagation Neural Network and M5 Model Tree," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(10), pages 2007-2019, August.
- Manish Goyal, 2014. "Modeling of Sediment Yield Prediction Using M5 Model Tree Algorithm and Wavelet Regression," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(7), pages 1991-2003, May.
- Feng, Yu & Jia, Yue & Cui, Ningbo & Zhao, Lu & Li, Chen & Gong, Daozhi, 2017. "Calibration of Hargreaves model for reference evapotranspiration estimation in Sichuan basin of southwest China," Agricultural Water Management, Elsevier, vol. 181(C), pages 1-9.
- Negm, Amro & Minacapilli, Mario & Provenzano, Giuseppe, 2018. "Downscaling of American National Aeronautics and Space Administration (NASA) daily air temperature in Sicily, Italy, and effects on crop reference evapotranspiration," Agricultural Water Management, Elsevier, vol. 209(C), pages 151-162.
- Pozníková, Gabriela & Fischer, Milan & van Kesteren, Bram & Orság, Matěj & Hlavinka, Petr & Žalud, Zdeněk & Trnka, Miroslav, 2018. "Quantifying turbulent energy fluxes and evapotranspiration in agricultural field conditions: A comparison of micrometeorological methods," Agricultural Water Management, Elsevier, vol. 209(C), pages 249-263.
- Zhang, Zixiong & Gong, Yicheng & Wang, Zhongjing, 2018. "Accessible remote sensing data based reference evapotranspiration estimation modelling," Agricultural Water Management, Elsevier, vol. 210(C), pages 59-69.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Yan, Shicheng & Wu, Lifeng & Fan, Junliang & Zhang, Fucang & Zou, Yufeng & Wu, You, 2021. "A novel hybrid WOA-XGB model for estimating daily reference evapotranspiration using local and external meteorological data: Applications in arid and humid regions of China," Agricultural Water Management, Elsevier, vol. 244(C).
- Granata, Francesco & Di Nunno, Fabio, 2021. "Forecasting evapotranspiration in different climates using ensembles of recurrent neural networks," Agricultural Water Management, Elsevier, vol. 255(C).
- Wu, Lifeng & Peng, Youwen & Fan, Junliang & Wang, Yicheng & Huang, Guomin, 2021. "A novel kernel extreme learning machine model coupled with K-means clustering and firefly algorithm for estimating monthly reference evapotranspiration in parallel computation," Agricultural Water Management, Elsevier, vol. 245(C).
- Xiang, Keyu & Li, Yi & Horton, Robert & Feng, Hao, 2020. "Similarity and difference of potential evapotranspiration and reference crop evapotranspiration – a review," Agricultural Water Management, Elsevier, vol. 232(C).
- Rana Muhammad Adnan & Xiaohui Yuan & Ozgur Kisi & Muhammad Adnan & Asif Mehmood, 2018. "Stream Flow Forecasting of Poorly Gauged Mountainous Watershed by Least Square Support Vector Machine, Fuzzy Genetic Algorithm and M5 Model Tree Using Climatic Data from Nearby Station," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(14), pages 4469-4486, November.
- Zhang, Lei & Zhao, Xin & Zhu, Ge & He, Jun & Chen, Jian & Chen, Zhicheng & Traore, Seydou & Liu, Junguo & Singh, Vijay P., 2023. "Short-term daily reference evapotranspiration forecasting using temperature-based deep learning models in different climate zones in China," Agricultural Water Management, Elsevier, vol. 289(C).
- Feng, Yu & Gong, Daozhi & Mei, Xurong & Hao, Weiping & Tang, Dahua & Cui, Ningbo, 2017. "Energy balance and partitioning in partial plastic mulched and non-mulched maize fields on the Loess Plateau of China," Agricultural Water Management, Elsevier, vol. 191(C), pages 193-206.
- Xueping Zhu & Chi Zhang & Guangtao Fu & Yu Li & Wei Ding, 2017. "Bi-Level Optimization for Determining Operating Strategies for Inter-Basin Water Transfer-Supply Reservoirs," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(14), pages 4415-4432, November.
- Rana Muhammad Adnan & Zhongmin Liang & Xiaohui Yuan & Ozgur Kisi & Muhammad Akhlaq & Binquan Li, 2019. "Comparison of LSSVR, M5RT, NF-GP, and NF-SC Models for Predictions of Hourly Wind Speed and Wind Power Based on Cross-Validation," Energies, MDPI, vol. 12(2), pages 1-22, January.
- Fuentes, Sigfredo & Ortega-Farías, Samuel & Carrasco-Benavides, Marcos & Tongson, Eden & Gonzalez Viejo, Claudia, 2024. "Actual evapotranspiration and energy balance estimation from vineyards using micro-meteorological data and machine learning modeling," Agricultural Water Management, Elsevier, vol. 297(C).
- Jamil, Basharat & Akhtar, Naiem, 2017. "Comparison of empirical models to estimate monthly mean diffuse solar radiation from measured data: Case study for humid-subtropical climatic region of India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 1326-1342.
- Sen Guo & Haoran Zhao & Huiru Zhao, 2017. "A New Hybrid Wind Power Forecaster Using the Beveridge-Nelson Decomposition Method and a Relevance Vector Machine Optimized by the Ant Lion Optimizer," Energies, MDPI, vol. 10(7), pages 1-20, July.
- Rana Muhammad Adnan & Kulwinder Singh Parmar & Salim Heddam & Shamsuddin Shahid & Ozgur Kisi, 2021. "Suspended Sediment Modeling Using a Heuristic Regression Method Hybridized with Kmeans Clustering," Sustainability, MDPI, vol. 13(9), pages 1-21, April.
- Feng, Jiaojiao & Wang, Weizhen & Xu, Feinan & Wang, Shengtang, 2024. "Evaluating the ability of deep learning on actual daily evapotranspiration estimation over the heterogeneous surfaces," Agricultural Water Management, Elsevier, vol. 291(C).
- Feng, Yu & Hao, Weiping & Li, Haoru & Cui, Ningbo & Gong, Daozhi & Gao, Lili, 2020. "Machine learning models to quantify and map daily global solar radiation and photovoltaic power," Renewable and Sustainable Energy Reviews, Elsevier, vol. 118(C).
- Manish Goyal & C. Ojha, 2011. "Estimation of Scour Downstream of a Ski-Jump Bucket Using Support Vector and M5 Model Tree," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(9), pages 2177-2195, July.
- Xiao, Chunan & Cai, Jiabing & Zhang, Baozhong & Chang, Hongfang & Wei, Zheng, 2023. "Evaluation and verification of two evapotranspiration models based on precision screening and partitioning of field temperature data," Agricultural Water Management, Elsevier, vol. 278(C).
- Yan, Haofang & Li, Mi & Zhang, Chuan & Zhang, Jianyun & Wang, Guoqing & Yu, Jianjun & Ma, Jiamin & Zhao, Shuang, 2022. "Comparison of evapotranspiration upscaling methods from instantaneous to daytime scale for tea and wheat in southeast China," Agricultural Water Management, Elsevier, vol. 264(C).
- Ouyang, Ying & Yang, Jia & Huang, Yanbo & Leininger, Theodor D. & Chastain, Daryl, 2024. "Evidence of higher evapotranspiration in croplands than in forestlands in four Mississippi watersheds over the past decade," Agricultural Water Management, Elsevier, vol. 302(C).
- Anas Mahmood Al-Juboori, 2019. "Generating Monthly Stream Flow Using Nearest River Data: Assessing Different Trees Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(9), pages 3257-3270, July.
More about this item
Keywords
Actual evapotranspiration; Machine learning; Regression tree; Ensemble methods; Support vector regression; Irrigation;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:agiwat:v:217:y:2019:i:c:p:303-315. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agwat .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.