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A Nonparametric Trend Test for Seasonal Data With Serial Dependence
Abstract
Statistical tests for monotonic trend in seasonal (e.g., monthly) hydrologic time series are commonly confounded by some of the following problems: nonnormal data, missing values, seasonality, censoring (detection limits), and serial dependence. An extension of the Mann‐Kendall test for trend (designed for such data) is presented here. Because the test is based entirely on ranks, it is robust against nonnormality and censoring. Seasonality and missing values present no theoretical or computational obstacles to its application. Monte Carlo experiments show that, in terms of type I error, it is robust against serial correlation except when the data have strong long‐term persistence (e.g., ARMA (1, 1) monthly processes with ϕ > 0.6) or short records (∼ 5 years). When there is no serial correlation, it is less powerful than a related simpler test which is not robust against serial correlation.
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Cited by
The influence of autocorrelation on the ability to detect trend in hydrological series
Yue, S., Pilon, P., Phinney, B., & Cavadias, G. (2002) · Hydrological Processes · doi:10.1002/hyp.1095 · Cited by 2,111
Kundzewicz, Z. W., & Robson, A. J. (2004) · Hydrological Sciences Journal · doi:10.1623/hysj.49.1.7.53993 · Cited by 580
Heat wave flash droughts in decline
Mo, K. C., & Lettenmaier, D. P. (2015) · Geophysical Research Letters · doi:10.1002/2015gl064018 · Cited by 330
Limits to detectability of land degradation by trend analysis of vegetation index data
Wessels, K. J., van den Bergh, F., & Scholes, R. J. (2012) · Remote Sensing of Environment · doi:10.1016/j.rse.2012.06.022 · Cited by 309
Khazaei, B., Khatami, S., Alemohammad, S. H., Rashidi, L., Wu, C., Madani, K., Kalantari, Z., Destouni, G., & Aghakouchak, A. (2019) · Journal of Hydrology · doi:10.1016/j.jhydrol.2018.12.004 · Cited by 245
Metadata
- Authors
- Hirsch, R. M., & Slack, J. R.
- Venue
- Water Resources Research
- Publisher
- American Geophysical Union (AGU)
- Published
- 1984-06
- Volume
- 20
- Issue
- 6
- Pages
- 727-732
- ISSN
- 0043-1397 (ISSN-L)
- 1944-7973
- OpenAlex
- W2029364683
- Cited by
- 1,658
- References
- 0
- FWCI
- 11.17
- Type
- journal article
- Language
- en
- Open access
- closed
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