Cloud Transform Algorithm based Approach for Hydrological Series
Frequency Analysis
- Chengguo Wu,
- Juliang Jin,
- Liyang Zhou,
- Xia Bai,
- Yuliang Zhou,
- Libing Zhang,
- Yi Cui
Liyang Zhou
China Water Northeastern Investigation, Design and Research Co., Ltd.
Author ProfileAbstract
Hydrological series frequency analysis is a fundamental task for water
resources management and water conservancy project design. Given the
deficiencies of higher distribution for the upper tail section of
hydrological frequency curve and safer designing result of water
conservancy project utilizing empirical frequency formula and
Pearson-III type function based curve fitting method, the normal cloud
transform algorithm based approach for hydrological series frequency
analysis was proposed through estimating sample empirical frequency by
normal cloud transform algorithm, and determining the cumulative
probability distribution curve by overlapping calculation of multiple
cloud distribution patterns. It can be revealed from its application
result in norther Anhui province, China that, the varying trend of
cumulative probability distribution curve of annual precipitation
derived from the cloud transform algorithm based method was basically
consistent with the result obtained through traditional empirical
frequency formula. Meanwhile, the upper tail section of annual
precipitation frequency curve derived from cloud transform algorithm was
distributing below the calculation result utilizing traditional
empirical frequency formula, which indicated that the annual
precipitation frequency calculation result utilizing cloud transform
algorithm was more optimal than the corresponding result obtained by
traditional empirical frequency formula. Therefore, the proposed cloud
transform algorithm based approach was reliable and effective for
hydrological series frequency analysis, which can be further applied in
the related research field of hydrological process analysis.07 Sep 2020Submitted to Hydrological Processes 11 Sep 2020Submission Checks Completed
11 Sep 2020Assigned to Editor
11 Sep 2020Reviewer(s) Assigned
11 Sep 2020Review(s) Completed, Editorial Evaluation Pending