The wavelet analysis clearly shows a noticeable

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ning and end of the time-series which is not real. The wavelet analysis clearly shows a noticeable change in the rainfall pattern after 1960’. That means periodic component are responsible for producing increasing trend in the annual rainfall series of all stations and change in rainfall pattern after 1960. This fact might be due to climate change as larger anthro- pogenic trends are recorded during the period of 1960-1990 [46] [47] . 5. Conclusion This study reveals significant changes in seasonal and annual rainfall in Nira river basin of Maharashtra, Central
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A. R. Murumkar, D. S. Arya 67 Table 4. t-test significance for linear equation. Series Station Linear Equation t-test statistics Annual Akluj y = 0.805x + 427.9 1.345 Baramati y = 1.126x + 437.9 1.915 * Bhor y = 2.749x + 880.0 3.224 * Malsiras y = 1.415x + 464.6 1.916 * Monsoon Akluj y = 0.270x + 240.6 0.696 Baramati y = 0.270x + 177.0 0.858 Bhor y = 2.374x + 613.1 3.104 * Malsiras y = 1.283x + 159.8 2.649 * Post-Monsoon Akluj y = 2.065x + 51.93 5.337 * Baramati y = 1.093x + 204.9 2.476 * Bhor y = 0.618x + 207.0 1.533 Malsiras y = 0.483x + 239.6 0.99 Summer Akluj y = 1.038x + 127.4 4.716 * Baramati y = 0.180x + 41.65 1.457 Bhor y = 0.174x + 50.77 1.297 Malsiras y = 0.205x + 42.46 1.883 * Winter Akluj y = 0.049x + 7.953 0.643 Baramati y = 0.069x + 13.10 1.095 Bhor y = 0.005x + 7.094 0108 Malsiras y = 0.149x + 21.67 1.524 ( * 10% significance level). Table 5. Homogeneity of stations by Chi-square statistic. Null Hypothesis: Stations are homogeneous with respect to trends Trend 2 hom og χ Annual 35.653 * Monsoon 7.690 * Post-Monsoon 43.18 * Summer 99.19 * Winter 27.98 * * null hypothesis accepted at 10% significance level
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