seasons have been studied. Salinity varied spatially and temporally and seasonally during ebb and flood tide conditions. Water temperature showed a difference of 10 • C in winter to summer. Temperature did not vary much vertically as it is a well-mixed estuary. Strong currents exceeding 100 cm s −1 were observed during peak ebb and flood tide conditions irrespective of the season. Longitudinal eddy diffusion coefficient (K x) was estimated as 757 m s −1 and 811 m 2 s −1 during summer and post-monsoon seasons, respectively. The vertical eddy diffusion coefficient (ε v) was estimated as 0.0337 m 2 s −1 during post-monsoon season. The salinity and current observations are compared with those obtained from models reported earlier. Values of pH, Dissolved Oxygen and Biological Oxygen Demand are within the threshold limits of the estuarine environment. Nutrients show seasonal variation in the estuarine environment. High values (160-2686 mg l −1) of total suspended matter were noticed both at surface and bottom in the study region showing the impact of fresh water and sediment transportation.

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The relationship between the Indian Ocean Sea-Surface Temperature Anomalies (SSTA) and the Indian Summer Monsoon Rainfall (ISMR) have been examined for the period, 1983-2006. High and positive correlation (0.51; significant at > 99% level) is noticed between ISMR and SSTA over southeastern Arabian Sea (AS) in the preceding January. Significant and positive correlation (0.61: significant at > 99% level) is also observed with the SSTA over northwest of Australia (NWA) in the preceding February. The combined SSTA index (AS þ NWA) showed a very high correlation of 0.71 with the ISMR. The correlation between East Asia sea-level pressure (average during February and March in the region, 35 N-45 N; 120 E-130 E) and ISMR is found to be 0.62. The multiple correlation using the above two parameters is 0.85 which explains 72% variance in ISMR. Using the above two parameters a linear multiple regression model to predict ISMR is developed. Our results are comparable with those obtained from the power regression (developed with 16, 8 and 10 parameters) and ensemble models (using 3 to 6 parameters) of the Indian Meteorological Department (IMD) (Rajeevan et al. 2004;2006). The rainfall during 2002 and 2004 could be predicted accurately from the present model. It is well known fact that most of the dynamical=statistical methods failed to predict the rainfall in 2002. However, as for associations between SST and ISMR, the index is quite susceptible to inter decadal fluctuations and markedly reduced skill is found in the decades preceding 1983. The RMS error for 24 years is 5.56 (% of long period average, LPA) and the correlation between the predicted and observed rainfall is 0.79.

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