Data Test and Pre-Treatment for Hydrological Modelling and Applications
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Date
2022
Authors
Kibe, L.J
Kilonzo, F. N
Journal Title
Journal ISSN
Volume Title
Publisher
Kenya Society of Environmental, Biological and Agricultural Engineers
Abstract
The proper application of meaningful hydrological model output must be preceded by use of reliable model
inputs, the quality and behaviour, which must be ascertained by evaluating for any intrinsic quality problems.
Long term (>40 years) rainfall hydrological data for the 5 rainfall stations situated in a catchment supplying
part of the larger Nairobi metropolitan and its environs are used to demonstrate the need for data quality
check. Tests for outlier analysis, trends analysis, autocorrelation and homogeneity are performed on the data.
Results indicate that one station had an outlier data point. The trends analysis using the Mann-Kendal method
with the Sen slope analysis using the raw data show general non statistically significant declining rainfall over
the period for both annual and seasonal rainfall and significant increase in maximum temperature at 95%
confidence level. Homogeneity test using the Pettit test identified break points. Trend analysis after removal of
change points returns significant trends in annual rainfall for three of the five stations and several seasonal
datasets at 95% confidence level. There is therefore need to pre-treat data appropriately before application in
modeling and decision support simulations. Pre-treatment of data prior to use in hydrological modelling is
expected to yield more reliable/accurate model predictions by reducing errors associated with model inputs
Description
Article
Keywords
Quality, analysis, outlier, confidence level, hydrological data
Citation
Kilonzo, F. N., & Kibet, L. J. (2022). Data Test and Pre-Treatment for Hydrological Modelling and Applications. Journal of Engineering in Agriculture and the Environment, 8(1), 14-14.