The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Detection of hydrologic trends and variability
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Citations
Cites
Nonparametric Tests Against Trend
Mann, H. B. (1945) · Econometrica · doi:10.2307/1907187 · Cited by 17,144
Robust Locally Weighted Regression and Smoothing Scatterplots
Cleveland, W. S. (1979) · Journal of the American Statistical Association · doi:10.1080/01621459.1979.10481038 · Cited by 11,594
Techniques of trend analysis for monthly water quality data
Hirsch, R. M., Slack, J. R., & Smith, R. A. (1982) · Water Resources Research · doi:10.1029/wr018i001p00107 · Cited by 2,934
Statistical Field Significance and its Determination by Monte Carlo Techniques
Livezey, R. E., & Chen, W. Y. (1983) · Monthly Weather Review · doi:10.1175/1520-0493(1983)111<0046:sfsaid>2.0.co;2 · Cited by 1,153
Trends in floods and low flows in the United States: impact of spatial correlation
Douglas, E., Vogel, R. M., & Kroll, C. N. (2000) · Journal of Hydrology · doi:10.1016/s0022-1694(00)00336-x · Cited by 1,071
Streamflow trends in the United States
Lins, H. F., & Slack, J. R. (1999) · Geophysical Research Letters · doi:10.1029/1998gl900291 · Cited by 744
Analysis of Climate Variability
(1995) · Springer eBooks · doi:10.1007/978-3-662-03167-4 · Cited by 439
Climate change, hydrology, and water resources
Gleick, P. H. (1989) · Reviews of Geophysics · doi:10.1029/rg027i003p00329 · Cited by 328
Climate change effects on the hydrologic regime within the Churchill-Nelson River Basin
Westmacott, J. R., & Burn, D. H. (1997) · Journal of Hydrology · doi:10.1016/s0022-1694(97)00073-5 · Cited by 196
Self-citationIncreasing U.S. streamflow linked to greenhouse forcing
Lins, H. F., & Michaels, P. J. (1994) · Eos · doi:10.1029/94eo00947 · Cited by 66
Cited by
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
Rice, J. S., Emanuel, R. E., Vose, J. M., & Nelson, S. A. C. (2015) · Water Resources Research · doi:10.1002/2014wr016367 · Cited by 95
Long-term trends of precipitation in the North China Plain
Fan, L., Lu, C., Yang, B., & Chen, Z. (2012) · Journal of Geographical Sciences · doi:10.1007/s11442-012-0978-2 · Cited by 71
Bouwer, L. M., Aerts, J. C. J. H., Droogers, P., & Dolman, A. J. (2006) · Hydrology and Earth System Sciences · doi:10.5194/hess-10-703-2006 · Cited by 69
Yang, T., Chen, X., Xu, C.-Y., & Zhang, Z.-C. (2009) · Stochastic Environmental Research and Risk Assessment · doi:10.1007/s00477-008-0278-7 · Cited by 49
Metadata
- Authors
- Burn, D. H., & Hag Elnur, M. A.
- Venue
- Journal of Hydrology
- Publisher
- Elsevier BV
- Published
- 2002-01
- Volume
- 255
- Issue
- 1-4
- Pages
- 107-122
- ISSN
- 0022-1694 (ISSN-L)
- OpenAlex
- W1973609976
- Cited by
- 1,162
- References
- 11
- FWCI
- 32.71
- Type
- journal article
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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- CoChat. (2026). Citation check: Detection of hydrologic trends and variability. https://app.cochat.ai/papers/10.1016/s0022-1694(01)00514-5
- The paper
- Burn, D. H., & Hag Elnur, M. A. (2002). Detection of hydrologic trends and variability. Journal of Hydrology. https://doi.org/10.1016/s0022-1694(01)00514-5
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
