Historical Climate Variability Research Articles

Impacts of climate variability on the operational forecast and management of the Upper Des Moines River Basin

Data from the regulated 14,000 km2 upper Des Moines River basin and a coupled forecast‐control model are used to study the sensitivity of flow forecasts and reservoir management to climatic variability over scales ranging from daily to interdecadal. Robust coupled forecast‐control methodologies are employed to minimize reservoir system sensitivity to climate variability and change. Large‐scale hydrologic‐hydraulic prediction models, models for forecast uncertainty, and models for reservoir control are the building blocks of the methodology. The case study concerns the 833.8 × 106 m3 Saylorville reservoir on the upper Des Moines River. The reservoir is operated by the U.S. Corps of Engineers for flood control, low‐flow augmentation, and water supply. The total record of 64 years of daily data is divided into three periods, each with distinct characteristics of atmospheric forcing. For each climatic period the coupled forecast‐control methodology is simulated with a maximum forecast lead time of 4 months and daily resolution. For comparison, the results of operation using current reservoir control practices were obtained for the historical periods of study. Large differences are found to exist between the probabilistic long‐term predictions of the forecast component when using warm or cool and wet or dry initial conditions in the spring and late summer. Using ensemble input corresponding to warm or cool and wet or dry years increases these differences. Current reservoir management practices cannot accommodate historical climate variability. Substantial gain in resilience to climate variability is shown to result when the reservoir is operated by a control scheme which uses reliable forecasts and accounts for their uncertainty. This study shows that such coupled forecast‐control decision systems can mitigate adverse effects of climatic forcing on regional water resources.

Historic climate variability of wetness in East China (960–1992): a wavelet analysis

In this paper, a dataset of historic wetness is analyzed with the wavelet transform technique. A previous dataset was derived from historic documents, and consists of annual dryness/wetness grades from 1 to 5 at 120 stations in the China mainland for the period from 1470 to 1979. This dataset was extended back to AD 960 for six regions in East China in a previous study, and the extended dataset is used in this paper. The Mexican Hat wavelet transform technique and descriptive statistical analysis were used to analyze each of the six regional time series. The wavelet analysis of climatic fluctuation displayed variations of different time scales at particular time points, as well as persistent anomalies. The climatic variations occuring on longer time scales may cover a larger area; these are the outstanding persistent dry and wet stages during the last 1033 years. The variations on longer time scales coincide roughly with those previously identified. On shorter time scales, some synchronous fluctations are also observed but in fewer years. 8 refs., 4 figs.

Historic climate variability of wetness in East China (960–1992): a wavelet analysis

Historic climate variability of wetness in East China (960–1992): a wavelet analysis

Estimation of possible climate change impacts on water availability, extreme flow events and soil moisture in the Goulburn and Ovens Basins, Victoria

A rainfall-runoff model (IHACRES) is applied on a daily timestep to a large area of the state of Victoria, Australia. Successful calibrations of this dynamic lumped parameter model were performed for 5 rivers contributing streamflow to the Ovens Basin, and for 9 rivers of the Goulburn Basin. This is the first application of the model on such a scale, involving two basins where the total drainage area of the catchments modelled is about 6,500 km2. The models were tested by simulation over the entire common period of observation for the 14 catchments under consideration. The results show that the models closely simulate the observed streamflow. The effect of historical climate variability on streamflow was investigated. The models were used for estimation of the potential impact of climatic change on water availability for irrigation for different climate scenarios developed in the Division of Atmospheric Research, CSIRO. This allows conditional estimates to be made of water supply in these basins for the periods 2030 and 2070 under current vegetation conditions. Projecting the future hydrologic regime in this region is extremely important, in particular for supporting irrigation management of the Basin. The problem of estimating the impact of climate change on the probability of extreme events of the hydrological regime was analysed. Flood frequency was found to increase for the scenarios providing the maximum amount of water; to 50% at 2030 and 100% at 2070. The probability of flood events for the ‘dry’ scenarios rapidly decreases for these dates. Drought frequency, as defined by a soil wetness index, increased 35% for the ‘dry’ scenario at 2030 and 80% for this scenario at 2070.