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The paper presents potential impacts of climate change on rainwater tanks outcomes such as water savings, reliability and water savings efficiency under two projected climate change scenarios; RCP4.5 and RCP8.5 utilising a case study using rainfall data from four stations within the city of Brisbane, Australia. Historical rainfall data were collected from the Australian Bureau of Meteorology website for the selected stations. Projected daily rainfall data were collected from Australian government data portal for the same stations within Brisbane. Using an earlier developed daily water balance model, eTank potential annual water savings were calculated for several weather and climate change scenarios with varied roof areas and rainwater demandValues of 'Seasonality Index (SI)', a commonly used factor representing rainfall variability within a year, were explored to validate earlier developed relationships between SI and water savings efficiency through rainwater tanks. It is found that in most cases water savings in future periods are expected to decrease and such decrease is not necessarily attributed to the expected decrease in rainfall amounts in future, rather also affected by future reductions in rainwater tank reliability. Linear relationships between potential future water savings and reliabilities for all the stations are found. Relationship between SI and water savings efficiency was established, and it is found that the relationship slightly varies with an earlier developed relationship using historical data. Compared to earlier established relationship, for lower SI values water savings efficiency is expected to become better, while for higher SI values the water savings efficiency is expected to become worse. Also, an increase of roof area from 100 m2 to 200 m2 will cause an average increase of water savings efficiency by 25% and an increase of rainwater usage from 200 L/day to 300 L/day will cause an average increase of water savings efficiency by 20%. [ABSTRACT FROM AUTHOR]

ABSTRACT Water infrastructure and flood mitigation projects are currently designed assuming a stationary climate. However, increased frequency and magnitude of extreme rainfall events questions the stationary climate assumption. The reality of non-stationary rainfall extremes should be properly considered in the design of water infrastructure and flood mitigation projects, because the extreme value distribution models with constant parameters may no longer be valid under non-stationary climate conditions. In this study, first extreme rainfall frequency analysis in Victoria (Australia) was conducted through generalized extreme value ( GEV) models under non-stationary and stationary climate conditions, and superiority of non-stationary GEV models over stationary models was investigated. High quality extreme rainfall data (i.e. annual maximums) from 23 stations in Victoria for storm durations ranging from 10 min to 48 h were used for frequency analysis. In developing the non-stationary extreme rainfall models, both the time dependency and the dependency to indices of climate oscillations affecting Australian rainfall variability were investigated. It was found that none of the non-stationary GEV models was superior to stationary GEV models. Therefore, the stationary GEV models were used to determine the spatial variability of rainfall intensity-frequency-duration relationships in Victoria. In general, low rainfall intensity estimates in the Western Region (except southern portion for long storm durations) were found in Victoria, whereas high rainfall intensity estimates were detected mostly in the Central and Northern Regions for short storm durations and in the Gippsland Region for long storm durations. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The increased frequency and magnitude of extreme rainfall events due to anthropogenic climate change, and decadal and multi-decadal climate variability question the stationary climate assumption. The possible violation of stationarity in climate can cause erroneous estimation of design rainfalls derived from extreme rainfall frequency analysis. This may result in significant consequences for infrastructure and flood protection projects since design rainfalls are essential input for design of these projects. Therefore, there is a need to conduct frequency analysis of extreme rainfall events in the context of non-stationarity, when nonstationarity is present in extreme rainfall events. A methodology consisting of threshold selection, extreme rainfall data (peaks over threshold data) construction, trend and nonstationarity analysis, and stationary and non-stationary generalised Pareto distribution (GPD) models was developed in this paper to investigate trends and non-stationarity in extreme rainfall events, and potential impacts of climate change and variability on intensity--frequency--duration (IFD) relationships. The methodology developed was successfully implemented using rainfall data from an observation station in Melbourne (Australia) for storm durations ranging from 6 min to 72 h. Although statistically significant trends were detected in extreme rainfall data for storm durations of 30min, 3 h and 48 h, statistical non-stationarity tests and non-stationary GPD models did not indicate non-stationarity for these storm durations and other storm durations. It was also found that the stationary GPD models were capable of fitting extreme rainfall data for all storm durations. Furthermore, the IFD analysis showed that urban flash flood producing hourly rainfall intensities have increased over time. [ABSTRACT FROM AUTHOR]

Recent climate change impact studies suggest that current rainfall intensity-frequency- duration (IFD) curves are likely to change as a result of climate change. In this paper, an effort was made to quantify the changing character of storm IFD curves using data of four consecutive 30-year time slices from 1880 to 2010. The Melbourne Regional Office rainfall data were used for the purposes of the study. Annual maximum series and generalised extreme value distribution were employed to derive the IFD curves using the data of different time slices and the whole period. Results of IFD curves produced from data for the whole period and the current IFD procedure in Australia, described in Australian Rainfall and Runoff (ARR), showed that the former had produced higher intensities for all sub-hourly storms of return periods of 10 to 100 years compared to the latter, and vice versa for return periods below 10 years. For all other storm durations (ie. 1-72 hours) and for short return periods (<10 years), the current ARR method had generated more intense storms. The above results demonstrate that there is a need to conduct further analysis to investigate changing character of storm IFD curves using rainfall data at several stations. [ABSTRACT FROM AUTHOR]

Among the processes most affected by global warming are the hydrological cycle and water resources. Regions where the majority of runoff consists of snowmelt are very sensitive to climate change. It is significant to express the relationship between climate change and snow hydrology and it is imperative to perform climate change impact studies on snow hydrology at global and regional scales. Climate change impacts on the mountainous Upper Euphrates Basin were investigated in this paper. First, historical data trend analysis of significant hydro-meteorological data is presented. Available future climate data are then explained, and, finally, future climate data are used in hydrological models, which are calibrated and validated using historical hydro-meteorological data, and future streamflow is projected for the period 2070–2100. The hydrological model outcomes indicate substantial runoff decreases in summer and spring season runoff, which will have significant consequences on water sectors in the Euphrates Basin. Citation Yilmaz, A.G. & Imteaz, M.A. (2011) Impact of climate change on runoff in the upper part of the Euphrates basin. Hydrol. Sci. J. 56(7), 1265–1279. [ABSTRACT FROM AUTHOR]