Indian summer monsoon rainfall is strongly influenced by various large-scale atmosphere-ocean oscillations including Pacific Decadal Oscillation (PDO), and El Niño-Southern Oscillation (ENSO). Researchers have shown that the negative phase of PDO or La Niña episodes of ENSO produce higher magnitude rainfall and hence relatively wetter years. So, it is imperative to have better knowledge of flood characteristics in the Indian watersheds for optimal planning and design of various infrastructure, and for optimal planning and management of reservoir operations. Traditionally, such information is estimated using flood frequency analysis (FFA) for small and medium sized projects. However, the adequacy of traditionally accepted assumption that the annual peak flows are independent and identically distributed (i.i.d.) is questioned globally \cite{Gurrapu_2016,Milly_2008}. This study evaluates the influence of PDO and ENSO and flood characteristics in Godavari River, India. The results indicate that the flood magnitude and frequency at majority of the selected gauges in Godavari River Basin is significantly influenced by PDO and ENSO, higher magnitude floods are associated with negative phase of PDO and La Niña episodes of ENSO. A few gauges are inversely related to these teleconnections. The influence of these teleconnections on regional climate is spatially variable across India and so are the contrasting results. The results from this study benefits the design engineers for efficient design of water resources infrastructures and water managers for optimal planning and management of reservoir operations. 

Flood frequency analysis assumes that annual peak flood events occur independently of each other, regardless of previous flood events (the independent and identically distributed (i.i.d.) assumption); however, annual peak flood records do not necessarily appear to conform to these assumptions. We tested the i.i.d assumption by analyzing the effects of the Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO) on 250 naturally flowing annual peak flood records across the entire western North American margin. Using permutation tests on quantile-quantile (Q-Q) plots, we found that the PDO has a greater impact on the magnitude of annual peak floods than the AMO. Twenty-six percent of the gauges have higher magnitude annual floods depending on the PDO phase (p < 0.1). Next, we examined the interacting effects of the PDO and AMO on the frequencies of lower and upper quartile annual peak floods, and found reinforcing, cancelling, and dominating effects. Lastly, we used permutation t-tests on the Julian dates of seasonal maximum and minimum streamflows to assess the impact of the PDO and AMO. We found that the PDO and AMO have substantial effects on the dates of winter maximum and summer minimum streamflow dates across the coastal margin. Since these two climate oscillations have significant effects on the magnitudes of annual peak floods, the i.i.d. assumption does not hold. Hence, we advocate for the need to re-assess baseline flood analysis in western North America to improve flood management strategies.