This study is focused on the evaluation of selected rainfall-runoff episodes in terms of temporal and spatial distribution of rainfall and runoff in the upper basin of the Blanice River. HEC - HMS model with two variants of spatial discretization was used to achieve the results of the holistic approach. The main input data was quantitative precipitation estimation, which better assessed the spatial variability of rainfall fields than interpolated ground measurements. The model simulated five episodes. Contrary to expectations, southern headstream area of the basin showed lower coefficient of runoff in comparison with its northern part. Precipitation cores of epizods occurred over the northern part of the basin at the outlet. Outputs from the model were evaluated in relation to measurements carried out in the experimental basin Zbytiny. Key words: Blanice River, HEC-HMS, hydrologic modeling, quantitative precipitation estimation

A challenge in hydrological studies in the Canadian Prairie region is to find good-quality meteorological data because many basins are located in remote regions where few stations are available, and existing stations typically have short records and often contain a high number of missing data. The recently released North American Regional Reanalysis (NARR) data set appears to have potential for hydrological studies in data-scarce central Canada. The main objectives of this study are: (1) to evaluate and utilize NARR data for hydrologic modelling and statistical downscaling, (2) to develop methods for estimating missing precipitation data using NARR data, and (3) to investigate and correct NARR precipitation bias in the Canadian Prairie region. Prior to applying NARR for hydrological modelling, the NARR surface data were evaluated by comparison with observed meteorological data over the Canadian Prairie region. The comparison results indicated that NARR is a suitable alternative to observed surface meteorological data and thus useful for hydrological modelling. After evaluation of NARR surface climate data, the SLURP model was set up with input data from NARR and calibrated for several watersheds. The results indicated that the hydrological model can be reasonably calibrated using NARR data as input. The relatively good agreement between precipitation from NARR and observed station data suggests that NARR information may be used in the estimation of missing precipitation records at weather stations. Several traditional methods for estimating missing data were compared with three NARR-based estimation methods. The results show that NARR-based methods significantly improved the estimation of precipitation compared to the traditional methods. The existence of NARR bias is a critical issue that must be addressed prior to the use of the data. Using observed weather station data, a statistical interpolation technique (also known as Optimum Interpolation) was employed to correct gridded NARR precipitation for bias. The results suggest that the method significantly reduces NARR bias over the selected study area.

A challenge in hydrological studies in the Canadian Prairie region is to find good-quality meteorological data because many basins are located in remote regions where few stations are available, and existing stations typically have short records and often contain a high number of missing data. The recently released North American Regional Reanalysis (NARR) data set appears to have potential for hydrological studies in data-scarce central Canada. The main objectives of this study are: (1) to evaluate and utilize NARR data for hydrologic modelling and statistical downscaling, (2) to develop methods for estimating missing precipitation data using NARR data, and (3) to investigate and correct NARR precipitation bias in the Canadian Prairie region. Prior to applying NARR for hydrological modelling, the NARR surface data were evaluated by comparison with observed meteorological data over the Canadian Prairie region. The comparison results indicated that NARR is a suitable alternative to observed surface meteorological data and thus useful for hydrological modelling. After evaluation of NARR surface climate data, the SLURP model was set up with input data from NARR and calibrated for several watersheds. The results indicated that the hydrological model can be reasonably calibrated using NARR data as input. The relatively good agreement between precipitation from NARR and observed station data suggests that NARR information may be used in the estimation of missing precipitation records at weather stations. Several traditional methods for estimating missing data were compared with three NARR-based estimation methods. The results show that NARR-based methods significantly improved the estimation of precipitation compared to the traditional methods. The existence of NARR bias is a critical issue that must be addressed prior to the use of the data. Using observed weather station data, a statistical interpolation technique (also known as Optimum Interpolation) was employed to correct gridded NARR precipitation for bias. The results suggest that the method significantly reduces NARR bias over the selected study area.

El Instituto Geofísico del Perú ha desarrollado un proyecto, financiado por INNOVATE Perú, llamado “Diseño e implementación de un radar perfilador de vientos que opera en UHF para estudios de turbulencias y precipitación en el territorio peruano”, este proyecto es la propuesta de solución a una limitación presentada por la comunidad científica del Perú y otras entidades para hacer estudios climáticos de vientos y precipitación. Parte del desarrollo de este radar, es el procesamiento de los datos recibidos. En esta tesis se ha hecho un análisis del diseño, frecuencia y tipo de radar que fue diseñado para luego seleccionar los algoritmos de procesamiento necesarios. Los algoritmos que se desarrollaron para el procesamiento del radar UHF permiten estimar vientos troposféricos y turbulencia con la técnica de análisis espectral total. Además de medir la intensidad de precipitación y el factor de reflectividad obtenido de las lluvias con la relación del diámetro de gotas y el factor de reflectividad. Los resultados de estas estimaciones, posteriormente son comparados con otros instrumentos para su validación y su posterior aplicación. / The Geophysical Institute of Peru (IGP) has developed a project called "Design and implementation of a radar profiler that operates in UHF for studies of turbulence and precipitation in the Peruvian territory", this project is the proposed solution to a limitation presented by the scientific community of Peru and other entities to conduct climate studies of winds and precipitation. Part of the development of this radar is the processing of received data. In this thesis an analysis of the design, frequency and type of the designed radar was done to then select the appropriate processing algorithms. The algorithms that were developed for the UHF radar processing allows the estimation of tropospheric winds and turbulence with the full spectral analysis technique. In addition to measuring the intensity of precipitation and the reflectivity factor obtained from rainfall related to the diameter of drops and the reflectivity factor. The results of these estimates are then compared with other instruments for validation and subsequent application. / Tesis