Extreme climate events, such as extreme daily temperatures, extreme daily rainfall amounts, large areas experiencing unusually warm temperatures, or storms, are predicted to increase in frequency and duration with ongoing climate change (1).
The results demonstrate that the methods and the time scales used for bias correction of RCM rainfall data have a larger impact on the accuracy of the daily rainfall and consequently the simulated streamflow.
This paper presents a case study of rainwater tank evaluation and design for large roof areas, located in Melbourne, Australia, based on observed daily rainfall data representing three different climatic regimes (i.e. dry average, and wet years).
We used daily rainfall and streamflow time series from two large catchments in the seasonal tropics of Queensland, Australia to investigate the hydrological impacts of woodland clearing.
Despite increases in daily rainfall and the number of days with large rainfall events increasing with MAR, there was a decline in daily SS yield possibly due to the exhaustion of sediment supply by frequent runoff events in high MAR watersheds.
Significant lag effects were observed at 38, 40, 43, and 45 days, with the largest percent change at 58 days (19.1% increase with a 10-mm increase in daily rainfall ≤ 50 mm; 95% CI: 2.1, 39.0%).
Daily rainfall records and major flooding.
2 30 a.m.: New daily rainfall record in Fayetteville, N.C.
Both today and Friday, daily rainfall records could fall.
A rainfall monitoring product based on daily rainfall estimates from the Climate Prediction Center.
