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Hydrologic Modelling (hydrologic + modelling)
Selected AbstractsEstimation of rainfall from infrared-microwave satellite data for basin-scale hydrologic modellingHYDROLOGICAL PROCESSES, Issue 15 2010Oscar Anthony Kalinga Abstract The infrared-microwave rainfall algorithm (IMRA) was developed for retrieving spatial rainfall from infrared (IR) brightness temperatures (TBs) of satellite sensors to provide supplementary information to the rainfall field, and to decrease the traditional dependency on limited rain gauge data that are point measurements. In IMRA, a SLOPE technique (ST) was developed for discriminating rain/no-rain pixels through IR image cloud-top temperature gradient, and 243K as the IR threshold temperature for minimum detectable rainfall rate. IMRA also allows for the adjustment of rainfall derived from IR-TB using microwave (MW) TBs. In this study, IMRA rainfall estimates were assessed on hourly and daily basis for different spatial scales (4, 12, 20, and 100 km) using NCEP stage IV gauge-adjusted radar rainfall data, and daily rain gauge data. IMRA was assessed in terms of the accuracy of the rainfall estimates and the basin streamflow simulated by the hydrologic model, Sacramento soil moisture accounting (SAC-SMA), driven by the rainfall data. The results show that the ST option of IMRA gave accurate satellite rainfall estimates for both light and heavy rainfall systems while the Hessian technique only gave accurate estimates for the convective systems. At daily time step, there was no improvement in IR-satellite rainfall estimates adjusted with MW TBs. The basin-scale streamflow simulated by SAC-SMA driven by satellite rainfall data was marginally better than when SAC-SMA was driven by rain gauge data, and was similar to the case using radar data, reflecting the potential applications of satellite rainfall in basin-scale hydrologic modelling. Copyright © 2010 John Wiley & Sons, Ltd. [source] Improving interpolation of daily precipitation for hydrologic modelling: spatial patterns of preferred interpolatorsHYDROLOGICAL PROCESSES, Issue 23 2009Daniel Kurtzman Abstract Detailed hydrologic models require high-resolution spatial and temporal data. This study aims at improving the spatial interpolation of daily precipitation for hydrologic models. Different parameterizations of (1) inverse distance weighted (IDW) interpolation and (2) A local weighted regression (LWR) method in which elevation is the explanatory variable and distance, elevation difference and aspect difference are weighting factors, were tested at a hilly setting in the eastern Mediterranean, using 16 years of daily data. The preferred IDW interpolation was better than the preferred LWR scheme in 27 out of 31 validation gauges (VGs) according to a criteria aimed at minimizing the absolute bias and the mean absolute error (MAE) of estimations. The choice of the IDW exponent was found to be more important than the choice of whether or not to use elevation as explanatory data in most cases. The rank of preferred interpolators in a specific VG was found to be a stable local characteristic if a sufficient number of rainy days are averaged. A spatial pattern of the preferred IDW exponents was revealed. Large exponents (3) were more effective closer to the coast line whereas small exponents (1) were more effective closer to the mountain crest. This spatial variability is consistent with previous studies that showed smaller correlation distances of daily precipitation closer to the Mediterranean coast than at the hills, attributed mainly to relatively warm sea-surface temperature resulting in more cellular convection coastward. These results suggest that spatially variable, physically based parameterization of the distance weighting function can improve the spatial interpolation of daily precipitation. Copyright © 2009 John Wiley & Sons, Ltd. [source] The more things change, the more they stay the same: the state of hydrologic modellingHYDROLOGICAL PROCESSES, Issue 21 2008Bellie Sivakumar No Abstracts. [source] Stream network modelling using lidar and photogrammetric digital elevation models: a comparison and field verificationHYDROLOGICAL PROCESSES, Issue 12 2008Paul N. C. Murphy Abstract A conventional, photogrammetrically derived digital elevation model (DEM; 10 m resolution) and a light detection and ranging (lidar)-derived DEM (1 m resolution) were used to model the stream network of a 193 ha watershed in the Swan Hills of Alberta, Canada. Stream networks, modelled using both hydrologically corrected and uncorrected versions of the DEMs and derived from aerial photographs, were compared. The actual network, mapped in the field, was used as verification. The lidar DEM-derived network was the most accurate representation of the field-mapped network, being more accurate even than the photo-derived network. This was likely due to the greater initial point density, accuracy and resolution of the lidar DEM compared with the conventional DEM. Lidar DEMs have great potential for application in land-use planning and management and hydrologic modelling. The network derived from the hydrologically corrected conventional DEM was more accurate than that derived from the uncorrected one, but this was not the case with the lidar DEM. Copyright © 2007 John Wiley & Sons, Ltd. [source] Advances in the application of the SWAT model for water resources managementHYDROLOGICAL PROCESSES, Issue 3 2005R. Jayakrishnan Abstract Developments in computer technology have revolutionized the study of hydrologic systems and water resources management. Several computer-based hydrologic/water quality models have been developed for applications in hydrologic modelling and water resources studies. Distributed parameter models, necessary for basin-scale studies, have large input data requirements. Geographic information systems (GIS) and model,GIS interfaces aid the efficient creation of input data files required by such models. One such model available for the water resources professional is the Soil and Water Assessment Tool (SWAT), a distributed parameter model developed by the United States Department of Agriculture. This paper describes some recent advances made in the application of SWAT and the SWAT,GIS interface for water resources management. Four case studies are presented. The Hydrologic Unit Model for the United States (HUMUS) project used SWAT to conduct a national-scale analysis of the effect of management scenarios on water quantity and quality. Integration of the SWAT model with rainfall data available from the WSR-88D radar network helps us to incorporate the spatial variability of rainfall into the modelling process. This study demonstrates the usefulness of radar rainfall data in distributed hydrologic studies and the potential of SWAT for application in flood analysis and prediction. A hydrologic modelling study of the Sondu river basin in Kenya using SWAT indicates the potential for application of the model in African watersheds and points to the need for development of better model input data sets in Africa, which are critical for detailed water resources studies. The application of SWAT for water quality analysis in the Bosque river basin, Texas demonstrates the strength of the model for analysing different management scenarios to minimize point and non-point pollution, and its potential for application in total maximum daily load (TMDL) studies. Copyright © 2005 John Wiley & Sons, Ltd. [source] Topographic parameterization in continental hydrology: a study in scaleHYDROLOGICAL PROCESSES, Issue 18 2003Robert N. Armstrong Abstract Digital elevation models (DEMs) are useful and popular tools from which topographic parameters can be quickly and efficiently extracted for various hydrologic applications. DEMs coupled with automated methods for extracting topographic information provide a powerful means of parameterizing hydrologic models over a wide range of scales. However, choosing appropriate DEM scales for particular hydrologic modelling applications is limited by a lack of understanding of the effects of scale and grid resolution on land-surface representation. The scale effects of aggregation on square-grid DEMs of two continental-scale basins are examined. Base DEMs of the Mackenzie and Missouri River basins are extracted from the HYDRO1k DEM of North America. Successively coarser grids of 2, 4, 8, , 64 km were generated from the ,base' DEMs using simple linear averaging. TOPAZ (Topographic Parameterization) was applied to the base and aggregated DEMs using constant critical source area and minimum source channel length values to extract topographic variables at varying scales or resolutions. The effects of changing DEM resolution are examined by considering changes in the spatial distribution and statistical properties of selected topographic variables of hydrological importance. The effects of increasing grid size on basin and drainage network delineation, and derived topographic variables, tends to be non-linear. In particular, changes in overall basin extent and drainage network configuration make it impractical to apply a simple scaling function to estimate variable values for fine-resolution DEMs from those derived from coarse-resolution DEMs. Results also suggest the resolution to which a DEM can be reduced by aggregation and still provide useful topographic information for continental-scale hydrologic modelling is that at which the mean hydraulic slope falls to approximately 1%. In this study, that generally occurred at a resolution of about 10 km. Copyright © 2003 John Wiley & Sons, Ltd. [source] Downscaling simulations of future global climate with application to hydrologic modellingINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 4 2005Eric P. Salathé Jr Abstract This study approaches the problem of downscaling global climate model simulations with an emphasis on validating and selecting global models. The downscaling method makes minimal, physically based corrections to the global simulation while preserving much of the statistics of interannual variability in the climate model. Differences among the downscaled results for simulations of present-day climate form a basis for model evaluation. The downscaled results are used to simulate streamflow in the Yakima River, a mountainous basin in Washington, USA, to illustrate how model differences affect streamflow simulations. The downscaling is applied to the output of three models (ECHAM4, HADCM3, and NCAR-PCM) for simulations of historic conditions (1900,2000) and two future emissions scenarios (A2 and B2 for 2000,2100) from the IPCC assessment. The ECHAM4 simulation closely reproduces the observed statistics of temperature and precipitation for the 42 year period 1949,90. Streamflow computed from this climate simulation likewise produces similar statistics to streamflow computed from the observed data. Downscaled climate-change scenarios from these models are examined in light of the differences in the present-day simulations. Streamflows simulated from the ECHAM4 results show the greatest sensitivity to climate change, with the peak in summertime flow occurring 2 months earlier by the end of the 21st century. Copyright © 2005 Royal Meteorological Society. [source] Application of GIS for processing and establishing the correlation between weather radar reflectivity and precipitation dataMETEOROLOGICAL APPLICATIONS, Issue 1 2005Y. Gorokhovich Correlation between weather radar reflectivity and precipitation data collected by rain gauges allows empirical formulae to be obtained that can be used to create continuous rainfall surfaces from discrete data. Such surfaces are useful in distributed hydrologic modelling and early warning systems in flood management. Because of the spatial relationship between rain gauge locations and radar coverage area, GIS provides the basis for data analysis and manipulation. A database of 82 radar stations and more than 1500 rain gauges in continental USA was compiled and used for the continuous downloading of radar images and rain data. Image sequences corresponding to rain events were extracted for two randomly selected radar stations in South and North Carolina. Rainfall data from multiple gauges within the radar zone of 124 nautical miles (nm) (,230 km) were extracted and combined with corresponding reflectivity values for each time interval of the selected rain event. Data were normalised to one-hour intervals and then statistical analysis was applied to study the potential correlation. Results of regression analysis showed a significant correlation between rain gauge data and radar reflectivity values and allowed derivation of empirical formulae. Copyright © 2005 Royal Meteorological Society. [source] | ||||||||||