Streamflow

Abstract: We present TerraClimate, a dataset of high-spatial resolution (1/24°, ~4-km) monthly climate and climatic water balance for global terrestrial surfaces from 1958-2015. TerraClimate uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim dataset, with coarser resolution time varying (i.e., monthly) data from other sources to produce a monthly dataset of precipitation, maximum and minimum temperature, wind speed, vapor pressure, and solar radiation. TerraClimate additionally produces monthly surface water balance datasets using a water balance model that incorporates reference evapotranspiration, precipitation, temperature, and interpolated plant extractable soil water capacity. These data provide important inputs for ecological and hydrological studies at global scales that require high spatial resolution and time varying climate and climatic water balance data. We validated spatiotemporal aspects of TerraClimate using annual temperature, precipitation, and calculated reference evapotranspiration from station data, as well as annual runoff from streamflow gauges. TerraClimate datasets showed noted improvement in overall mean absolute error and increased spatial realism relative to coarser resolution gridded datasets.

Abstract: Radiative effects of anthropogenic changes in atmospheric composition are expected to cause climate changes, in particular an intensification of the global water cycle with a consequent increase in flood risk. But the detection of anthropogenically forced changes in flooding is difficult because of the substantial natural variability; the dependence of streamflow trends on flow regime further complicates the issue. Here we investigate the changes in risk of great floods--that is, floods with discharges exceeding 100-year levels from basins larger than 200,000 km(2)--using both streamflow measurements and numerical simulations of the anthropogenic climate change associated with greenhouse gases and direct radiative effects of sulphate aerosols. We find that the frequency of great floods increased substantially during the twentieth century. The recent emergence of a statistically significant positive trend in risk of great floods is consistent with results from the climate model, and the model suggests that the trend will continue.

Abstract: > * SUMMARY 1. This paper introduces a new approach for setting streamflow-based river ecosystem management targets and this method is called the 'Range of Variability Approach' (RVA). The proposed approach derives from aquatic ecology theory concerning the critical role of hydrological variability, and associated characteristics of timing, frequency, duration, and rates of change, in sustaining aquatic ecosystems. The method is intended for application on rivers wherein the conservation of native aquatic biodiversity and protection of natural ecosystem functions are primary river management objectives. 2. The RVA uses as its starting point either measured or synthesized daily streamflow values from a period during which human perturbations to the hydrological regime were negligible. This streamflow record is then characterized using thirty-two different hydrological parameters, using methods defined in Richter et al. (1996). Using the RVA, a range of variation in each of the thirty-two parameters, e.g. the values at t 1 standard deviation from the mean or the twenty-fifth to seventy-fifth percentile range, are selected as initial flow management targets. 3. The RVA targets are intended to guide the design of river management strategies (e.g. reservoir operations rules, catchment restoration) that will lead to attainment of these targets on an annual basis. The RVA will enable river managers to define and adopt readily interim management targets before conclusive, long-term ecosystem research results are available. The RVA targets and management strategies should be adaptively refined as suggested by research results and as needed to sustain native aquatic ecosystem biodiversity and integrity.