Search

As watersheds are urbanized, the amount of impervious surfaces will be increased. As such, water infiltration will be reduced, and the volume of surface runoff will be increased. By retaining stormwater, best management practices (BMPs) are used to mitigate the hydrologic effects of urbanization. Using the Ludlow watershed in northern Kentucky as a case study, the main objective of this paper was to identify the most cost-effective arrangement of BMPs in reducing surface runoff. A simulation program was employed to model the hydrologic conditions in the Ludlow watershed under the current and future climate conditions and to identify the most cost-effective BMP arrangement. The results show that the simulation program is an effective tool in simulating a small watershed. Indeed, BMPs are instrumental in reducing surface runoff even when the future climate becomes drier. The most cost-effective BMP arrangement is to install two infiltration trenches and one bioretention in the watershed. These findings can be useful in watershed management in areas with similar hydroclimatic conditions. [ABSTRACT FROM AUTHOR]

The development of watershed models with minimal quantified uncertainty under nonstationary conditions is a major challenge in the field of hydrology. This is especially problematic in data-poor areas where values for model inputs are lacking or measured on temporally and/or spatially sparse scales. The objective of this work is to conduct a global sensitivity and uncertainty analysis (GSA/UA) of the Pitman semidistributed hydrologic model for the data-poor Okavango Basin in southern Africa under both stationary and climate change scenarios. The Morris GSA method allowed qualitative ranking of important model inputs whereas the variance-based Fourier amplitude sensitivity test (FAST) method quantitatively identified the parametric uncertainty and sensitivity to these inputs. Results showed that the most important model inputs determining mean annual flow and model fit to observed data were the infiltration rate and the temporal rainfall distribution. In addition, the wetter western headwaters region was shown to be the most important region in determining the flow at the outlet of the basin. Parameter equifinality was significant in this study, and hence the evaluation of the relationships between mechanisms was not straightforward. Analysis of model results under climate change scenarios showed that a hot and wet scenario introduced more change in mean annual flow than a hot and dry scenario. The climate change scenarios also altered model sensitivity. For example, the parameter that controls the rate of infiltration decreased in importance and the parameter that controls soil moisture storage gained importance under the dry scenario. These results are useful when determining the applicability of model predictions under stationary and nonstationary conditions and when focusing watershed monitoring efforts. [ABSTRACT FROM AUTHOR]

The head region of the Yellow River is the key area where climate change would affect the hydrological process, since it is in a high elevation and cold area. Temperature and precipitation are two important meteorologic factors influencing the hydrological process. In this study, runoff change was evaluated as a result of the hydrological process change and an evaluation of runoff response to the two factors was made. Data derived from the results of seven general circulation models (GCMs) under two intergovernmental panel on climate change scenarios (A2 and B2) were used as future climate scenarios. First, factual and future climate change is analyzed according to data observed and obtained from GCMs. It was found that temperature has been increasing since 1961 and would continue in the future. The change in future precipitation also showed an increasing tendency. Then, a distributed hydrologic model, taking into account the effect of snow and frozen soil, was developed based on observed data in order to investigate the impact of temperature and precipitation change on runoff. Simulated runoff corresponding to climate scenarios indicates that the runoff amount would change lightly before 2020 and then would decrease approximately 5% per year. Analysis of runoff characteristics showed that runoff would increase in the dry season, resulting in relatively uniform distribution of seasonal runoff. Large variablility in annual runoff in the future implies a high probability and severity of flooding as well as droughts. [ABSTRACT FROM AUTHOR]

We examine the response of streamflow to long-term rainfall variability under climate change by coupling downscaled global climate model precipitation to a distributed hydrologic model. We use daily output of the coupled global climate model (CGCM2) of the Canadian Centre for Climate Modelling and Analysis corresponding to the Intergovernmental Panel on Climate Change Special Report on Emission Scenarios B2 scenario. The B2 scenario envisions slower population growth (10.4 billion by 2100) with a more rapidly evolving economy and more emphasis on environmental protection. We use the Hydrologic Modeling System of the Hydrologic Engineering Center for distributed hydrologic modeling. Because of the incongruence between the spatial scale of the CGCM2 output and that of the hydrologic model, a new space-time stochastic random cascade model was implemented in order to downscale the CGCM2 precipitation. The downscaling model accounts for the observed spatial intermittency of precipitation as well as for the self-similar scaling structure of its spatial distribution. For the South Platte basin, results show that the distribution of peak flow rate is more sensitive to the spatial variability of rainfall than total runoff volume. Results also show that the relative impact of long-term rainfall variation associated with climate change on total runoff and peak flow can be much greater than the magnitude of the rainfall variation itself, and that the magnitude of the impact depends strongly on the magnitude of the associated change in evapotranspiration. [ABSTRACT FROM AUTHOR]