Geoscience Reference
In-Depth Information
studies. Unfortunately, remaining trend detection tests and other important
properties of the time series (i.e., stationarity, homogeneity, periodicity and
persistence) are often ignored. The main reason behind this ignorance seems
to be lack of scientists'/researchers' knowledge about the availability of
appropriate statistical tests for time series analysis as well as the lack of easy-
to-use guidelines/book for their effective application. It is expected that the
application of time series analysis to hydrological/hydrogeological variables
will expand considerably in the future with gradual advancements in
computation technology and increasing availability of software packages for
time series analysis. More and more studies encompassing a wide variety of
hydrological/hydrogeological variables, together with innovative studies are
needed to bring the time series analysis techniques to maturity.
References
Abaurrea, J. and Cebrian, A. (2003). Trend analysis of daily rainfall extremes.
http://www.isi-eh.usc.es/resumenes/127_52_abstract.pdf (accessed on 27 July 2003).
Adamowski, K. and Bocci, C. (2001). Geostatistical regional trend detection in river
flow data. Hydrological Processes , 15: 3331-3341.
Adamowski, K. and Bougadis, J. (2003). Detection of trends in annual extreme rainfall.
Hydrological Processes , 17(18): 3547-3560.
Adeloye, A.J. and Montaseri, M. (2002). Preliminary streamflow data analyses prior
to water resources planning study. Hydrological Sciences Journal , 47(5): 679-692.
Alemaw, B.F. and Chaoka, T.R. (2002). Trends in the flow regime of the southern
African rivers as visualized from rescaled adjusted partial sums (RAPS). African
Journal of Science and Technology , Science and Engineering Series , 3(1): 69-78.
Anderson, P.L., Meerschaert, M.M. and Vecchia, A.V. (1999). Innovations algorithm
for periodically stationary time series. Stochastic Processes and their Applications ,
83(1): 149-169.
Angel, J.R. and Huff, F.A. (1997). Changes in heavy rainfall in Midwestern United
States. Journal of Water Resources Planning and Management, ASCE , 123(4):
246-249.
Anh, V., Lunney, K. and Peiris, S. (1997). Stochastic models for characterisation and
prediction of time series with long-range dependence and fractality. Environmental
Modelling and Software , 12(1): 67-73.
Antonopoulos, V.Z., Papamichail, D.M. and Mitsiou, K.A. (2001). Statistical and
trend analysis of water quality and quantity data for the Strymon River in Greece.
Hydrology and Earth System Sciences , 5(4): 679-691.
Astatkie, T., Yiridoe, E.K. and Clark, J.S. (2003). Testing for trend in variability of
climate data: Measures and temporal aggregation with applications to Canadian
data. Theoretical and Applied Climatology , 76(3-4): 235-247.
Astel, A., Mazerski, J., Polkowska, Z . . and NamieĀ“nik, J. (2004). Application of PCA
and time series analysis in studies of precipitation in Tricity (Poland). Advances in
Environmental Research , 8(3-4): 337-349.
Search WWH ::




Custom Search