Use of average data of 181 synoptic stations for estimation of reference crop evapotranspiration by temperature-based methods-Reference-Cited by-同舟云学术

Use of average data of 181 synoptic stations for estimation of reference crop evapotranspiration by temperature-based methods

Published:2014-07-09 Issue:12 Volume:28 Page:4237-4255
ISSN:0920-4741
Container-title:Water Resources Management
language:en
Short-container-title:Water Resour Manage

Author:

Valipour Mohammad

Publisher

Springer Science and Business Media LLC

Subject

Water Science and Technology,Civil and Structural Engineering

Link

http://link.springer.com/content/pdf/10.1007/s11269-014-0741-9.pdf

Reference47 articles.

1. Abbaspour KC (1991) A comparison of different methods of estimating energy-limited evapotranspiration in the peace river region of British Columbia. Atmos Ocean 29(4):686–698

2. Acheampong PK (1986) Evaluation of potential evapotranspiration methods for Ghana. Geol J 12(4):409–415

3. Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration. Guidelines for computing crop water requirements. FAO Irrigation and Drainage. Paper no. 56. FAO, Rome.

4. Baier W (1971) Evaluation of latent evaporation estimates and their conversion to potential evaporation. Canad J Plant Sci 51:255–266

5. Baier W, Robertson GW (1965) Estimation of latent evaporation from simple weather observations. Canad J Plant Sci 45:276–284

Cited by 70 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Reference evapotranspiration estimation using reanalysis and WaPOR products in dryland Croplands;Heliyon;2024-02

2. Standardized precipitation evapotranspiration index (SPEI) estimated using variant long short-term memory network at four climatic zones of China;Computers and Electronics in Agriculture;2023-10

3. Comparative study of reference evapotranspiration estimation models based on machine learning algorithm: a case study of Zhengzhou City;Hydrology Research;2023-07-20

4. Estimating daily reference evapotranspiration using a novel hybrid deep learning model;Journal of Hydrology;2022-11

5. Prediction of diffuse solar radiation using machine learning models based on sunshine period and sky‐clearness index for the humid‐subtropical climate of India;Environmental Progress & Sustainable Energy;2022-08-29