Regional probability distribution of the annual reference evapotranspiration and its effective parameters in Iran-Reference-Cited by-同舟云学术

Regional probability distribution of the annual reference evapotranspiration and its effective parameters in Iran

Published:2017-10-11 Issue:1-2 Volume:134 Page:411-422
ISSN:0177-798X
Container-title:Theoretical and Applied Climatology
language:en
Short-container-title:Theor Appl Climatol

Author:

Khanmohammadi Neda,Rezaie Hossein,Montaseri Majid,Behmanesh Javad

Publisher

Springer Science and Business Media LLC

Subject

Atmospheric Science

Link

http://link.springer.com/article/10.1007/s00704-017-2283-6/fulltext.html

Reference46 articles.

1. Akritas MG (1988) Pearson-type goodness-of-fit tests: the univariate case. J Am Stat Assoc 83:222–230. https://doi.org/10.2307/2288944

2. Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration—guidelines for computing crop water requirements, FAO Irrigation and Drainage Paper 56. Food and Agriculture Organization of the United Nations, Rome

3. Balldassarre GD, Castellarin A, Brath A (2006) Relationships between statistics of rainfall extremes and mean annual precipitation: an application for design-storm estimation in northern central Italy. J Hydrol Earth Sys Sci 10:589–601

4. Bhagat AD, Patil MA (2014) Probability distribution functions of weekly reference crop evapotranspiration for Solapur district of Maharashtra. Int J Agric Eng 7(2):399–401. https://doi.org/10.15740/HAS/IJAE/7.2/399-401

5. Blain GC (2011) Standardized precipitation index based on Pearson type III distribution. J Revista Brasileira de Meteorologia 26:167–180

Cited by 7 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. Harnessing the runoff reduction potential of urban bioswales as an adaptation response to climate change;Scientific Reports;2024-05-28

2. Trivariate Stochastic Weather Model for Predicting Maize Yield;Journal of Applied Mathematics;2022-11-15

3. Stochastic Analysis of Hourly to Monthly Potential Evapotranspiration with a Focus on the Long-Range Dependence and Application with Reanalysis and Ground-Station Data;Hydrology;2021-12-01

4. A Global-Scale Investigation of Stochastic Similarities in Marginal Distribution and Dependence Structure of Key Hydrological-Cycle Processes;Hydrology;2021-03-31

5. Seasonal Hydropower Planning for Data‐Scarce Regions Using Multimodel Ensemble Forecasts, Remote Sensing Data, and Stochastic Programming;Water Resources Research;2019-11