Beginning Of Time Series Research Articles

REFINEMENT OF CONIFER GROWTH MODELS BASED ON TREE-RING CHRONOLOGIES OF THE NORTH OF WESTERN SIBERIA

The subject of this research is conifer growth model based on time-series of annual rings width. The article addresses processing of data and model update in respect of forest dendrology. The purpose of study is to update the conifer growth model due to expansion of time-series of tree-rings width in regards to conifer forests in Western Siberia. The method represents expansion of time-series due to the fact that some growth phases had not been taken into account. When measurements were taken at the height of 1.3 meters, the following phases were not considered: seedling, juvenile, immature and beginning of virginile phase. The authors carried out examination of a number of scans and core samples, as well as time-series received by other scientists and which are contained in the International Tree-Ring Data Bank. Based on the results of field studies, the authors recommend to add some zeroes to the beginning of time-series within the range of 10-15 years for pine-trees in the south of Western Siberia, depending on growth conditions; the range of 15-30 years in the north for larch-trees and pine-trees depending on soil and climate conditions and latitude. The sequence of data pre-processing operations for time-series, received by means of core sampling, is as follows: averaging out of radius gain in 2 (3) mutually perpendicular directions for one specimen, graphing of radius gain curve, adding to the beginning of time-series, its normalization, approximation by specified growth function. It is possible to build area growth function for the scans. For averaging out a group of model trees, the sequence of operations is as follows: synchronization of time-series by cross-correlation method, approximation by specified growth function. Methods and results of studies can be applied in forest sectors and oil and gas industries for monitoring of forest health conditions. The proposed method of curve growth model update will allow to define more precisely time intervals for efficient forest exploitation as well as to reconstruct digital models of conifer populations in the north of Western Siberia.

Evaluating persistence and identifying trends and abrupt changes in monthly and annual rainfalls of a semi-arid region in Western India

In this study, 43-year (1965–2007) monthly and annual rainfall time series of ten rainfall stations in a semi-arid region of western India are analyzed by adopting three tests for testing normality and by applying autoregressive technique for exploring persistence. Gradual trends are identified by three tests, and their magnitudes are assessed by the Sen’s slope estimator. Also, abrupt changes are detected by using four tests and they are further confirmed by two tests. Box-whisker plots revealed that the rainfalls of June and September are right skewed for all the stations. The annual rainfalls of Bhinder, Dhariawad, and Gogunda stations are found considerably right skewed. The normality tests indicated that the rainfall of July does not deviate from the normal distribution at all the stations. However, the annual rainfall is found non-normal at five stations. The monthly rainfalls of June, July, and August have persistence respectively at three (Mavli, Salumber, and Sarada), two (Kherwara and Sarada), and one (Mavli) stations, whereas the annual rainfall has persistence at Girwa and Mavli stations. Significantly increasing trend is detected at Mavli in the rainfall of July and in the annual rainfall (p value > 0.05), while the negative trend in August rainfall at Dhariawad is found significant (p value > 0.10). This study revealed that the presence of serial correlation does not affect the performance of the Mann-Kendall test. Mean values of trend magnitudes for the rainfalls of June, July, August, and September are 0.3, 0.8, −0.4, and 0.4 mm year−1, respectively, and the overall mean value for the annual rainfall is 0.9 mm year−1. It is found that the standard normal homogeneity test and the Pettitt test are biased towards the end of the series to locate a change point. Conversely, the Bayesian test has a tendency to look for a change point in the beginning of time series. Confirmed abrupt changes in the rainfall time series are found in the year 2003 (Bhinder) in June; years 1974 (Mavli) and 1989 (Dhariawad and Salumber) in July; years 1972 (Sarada), 1990 (Dhariawad), and 2003 (Mavli) in August; years 1977 (Dhariawad), 1991 (Sarada), and 2004 (Kotra) in September; and in the year 1972 (Mavli and Sarada stations) in the annual series. It is emphasized that the significantly increasing trend of rainfall may have linkages with climate change and/or variability. Finally, this study recommends use of multiple statistical tests for analyzing hydrologic time series in order to ensure reliable decisions.