Trends in Maximum Daily Rainfall in Marginal Desert Environment: Signs of Climate Change
Abstract
Problem statement: Change in intense precipitation has been used as an indicator for anticipated climate change. The trend in maximum daily rainfall in 10 rainfall stations distributed in the north and north east of Jordan has been investigated. Based on mean annual rainfall and geographic location, rainfall stations were divided into subhumid, semi-arid and arid stations. Approach: The regression approach T-test and Mann-Kendall test were used to investigate significant trends in maximum daily rainfall. Logistic regression model used to test the trends in the frequency of heavy rainfall. Based on p-vales, significant trends were determined. Results: The results show that pronounced significant decreasing trend is observed in three out of four semi-arid stations used in this study. In arid stations, only one station out of three show significant increasing trend. However, none of the three subhumid stations used in the study show any significant trend. Logistic regression test for readings above 90th percentile among the maximum daily rainfall shows significant downward trend only in the semi-arid stations. Conclusion: The results of this study confirm that semi-arid zone is more vulnerable to climate change. Serious actions to mitigate and adapt to climate changes should be given a priority in the semi-arid zone. Redistribution of daily rainfall intensity will have a significant impact on water resources management.
DOI: https://doi.org/10.3844/ajessp.2011.331.337
Copyright: © 2011 Khaldoun A. Al-Qudah and Abdullah A. Smadi. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Maximum daily rainfall
- climate change
- trend analysis
- semi-arid
- global warming
- Generalized Linear Model (GLM)
- Odds Ratio (OR)
- semi-arid zone
- regression model