Hydrological models have been developed to estimate snow accumulation, snowmelt and snowmelt runoff on the Canadian Prairies; however, their proper scale of application is unknown in the Prairie environment. The first objective of this thesis is to examine the proper scale for pre-melt snow accumulation as snow water equivalent (SWE) and snowmelt in a Prairie first order basin. Spatially distributed and spatially aggregated approaches were used to calculate SWE and snowmelt at St. Denis National Wildlife Area (SDNWA). Both approaches used models with similar physics, but differed in the model scale at which calculations were carried out. The simulated pre-melt SWE, cumulative seasonal SWE, and daily snowmelt from the two modelling approaches were compared to field observations of pre-melt SWE, cumulative seasonal SWE, and daily snowmelt; comparisons of areal cumulative seasonal SWE, areal snowmelt, snowmelt duration, and snow-covered area were also conducted between two modelling approaches. Results from these comparisons showed that both approaches had reasonable and similar accuracy in estimation of SWE and snowmelt. The spatially aggregated approach was more computationally efficient and was selected as a modelling scale for small-sized prairie basins. <p>Another objective of this thesis is to derive a snow hydrology model for the Canadian Prairies. Physically-based hydrological models were assembled in the Cold Regions Hydrological Model Platform (CRHM) using the aggregated approach. Tests of pre-melt SWE and surface snowmelt runoff were conducted at two basins in Saskatchewan Creighton Tributary of Bad Lake and Wetland 109, St. Denis. Results showed that the snow hydrology model had a reasonable capability to simulate SWE and snowmelt runoff to the stream and wetland. <p>Droughts are natural hazards that develop frequently on the Canadian Prairies. Analyzing the impact of drought on hydrological processes and water supply is another objective of this thesis. Synthetic drought scenarios were proposed for the Creighton Tributary of Bad Lake and the corresponding impacts on the snowmelt runoff-related processes were examined. Results indicated that wind redistribution of snow was very sensitive to drought conditions, sublimation of blowing snow and snow-covered period were sensitive to drought, but winter evaporation and infiltration did not show strong trend. The results also showed that drought conditions had magnified effects on the snowmelt runoff and could cause cessation of streamflow. Also, the impacts of the recent 1999-2005 drought on the snowmelt hydrology were investigated at St. Denis. Results illustrated that three-years (1999-2002) of severe winter drought were followed by a normal year (2002-03) and then a two-year (2003-05) recovery period, and then returning to normal (2005-06). Results showed that both snowfall and rainfall during hydrological winter were consistently low for severe drought and surface snowmelt runoff was very much lower during severe drought, about 45-65 mm less compared to that in the normal periods.

Hydrological models have been developed to estimate snow accumulation, snowmelt and snowmelt runoff on the Canadian Prairies; however, their proper scale of application is unknown in the Prairie environment. The first objective of this thesis is to examine the proper scale for pre-melt snow accumulation as snow water equivalent (SWE) and snowmelt in a Prairie first order basin. Spatially distributed and spatially aggregated approaches were used to calculate SWE and snowmelt at St. Denis National Wildlife Area (SDNWA). Both approaches used models with similar physics, but differed in the model scale at which calculations were carried out. The simulated pre-melt SWE, cumulative seasonal SWE, and daily snowmelt from the two modelling approaches were compared to field observations of pre-melt SWE, cumulative seasonal SWE, and daily snowmelt; comparisons of areal cumulative seasonal SWE, areal snowmelt, snowmelt duration, and snow-covered area were also conducted between two modelling approaches. Results from these comparisons showed that both approaches had reasonable and similar accuracy in estimation of SWE and snowmelt. The spatially aggregated approach was more computationally efficient and was selected as a modelling scale for small-sized prairie basins. <p>Another objective of this thesis is to derive a snow hydrology model for the Canadian Prairies. Physically-based hydrological models were assembled in the Cold Regions Hydrological Model Platform (CRHM) using the aggregated approach. Tests of pre-melt SWE and surface snowmelt runoff were conducted at two basins in Saskatchewan Creighton Tributary of Bad Lake and Wetland 109, St. Denis. Results showed that the snow hydrology model had a reasonable capability to simulate SWE and snowmelt runoff to the stream and wetland. <p>Droughts are natural hazards that develop frequently on the Canadian Prairies. Analyzing the impact of drought on hydrological processes and water supply is another objective of this thesis. Synthetic drought scenarios were proposed for the Creighton Tributary of Bad Lake and the corresponding impacts on the snowmelt runoff-related processes were examined. Results indicated that wind redistribution of snow was very sensitive to drought conditions, sublimation of blowing snow and snow-covered period were sensitive to drought, but winter evaporation and infiltration did not show strong trend. The results also showed that drought conditions had magnified effects on the snowmelt runoff and could cause cessation of streamflow. Also, the impacts of the recent 1999-2005 drought on the snowmelt hydrology were investigated at St. Denis. Results illustrated that three-years (1999-2002) of severe winter drought were followed by a normal year (2002-03) and then a two-year (2003-05) recovery period, and then returning to normal (2005-06). Results showed that both snowfall and rainfall during hydrological winter were consistently low for severe drought and surface snowmelt runoff was very much lower during severe drought, about 45-65 mm less compared to that in the normal periods.

Magíster en Ciencias de la Ingeniería, Mención Recursos y Medio Ambiente Hídrico. Ingeniero Civil / La representación del ciclo hidrológico es, hasta el día de hoy, difícil de modelar producto de diversos desafíos entre los que se encuentran la heterogeneidad de la cuenca, la representación de procesos físicos, las observaciones disponibles, la incertidumbre en las forzantes del modelo y la incertidumbre estructural, entre otros. Sin embargo, en los últimos años se ha puesto a dis-posición de la comunidad diversos productos e imágenes satelitales que buscan aumentar la disponibilidad de información mediante percepción remota. Algunas de las variables hidroló-gicas de interés que hay disponibles son la fracción de área cubierta por nieve, la humedad de suelo, la evapotranspiración, el equivalente en agua de nieve, índices de vegetación, precipita-ción, temperatura del suelo y el albedo. En este trabajo se busca incorporar información de percepción remota para analizar si su inclusión mejora la modelación hidrológica tradicional que se basa, principalmente, en el contraste de caudales modelados con los observados. La zona de estudio corresponde a tres sub-cuencas del río Elqui, en la Región de Coquimbo, que están definidas por estaciones fluviométricas pertenecientes a la DGA: río Cochiguaz en el Peñón, estero Derecho en Alcohuaz y río Toro antes junta río La Laguna. En estas cuencas se intenta (1) estimar los caudales usando el modelo CRHM (Cold Regions Hydrological Model) considerando que no existe información fluviométrica, bajo la hipótesis que es posible estimar el caudal de manera razonable si se calibran parámetros asociados a otros procesos del ciclo hidrológico, (2) calibrar el modelo usando sólo caudales y (3) incorporar la información de percepción remota junto con la fluviométrica para representar el ciclo hidrológico. Todo esto a una escala temporal horaria, con forzantes que se construyen a partir de información de la red meteorológica DGA en conjunto con la red CEAZA. Los resultados muestran que estimar la escorrentía en cuencas sin información fluvio-métrica sigue siendo un desafío, pues los caudales estimados a partir de la calibración de otros procesos entregan, para distintos sets de parámetros, índices NSE que, en promedio, son 0,56, 0,26 y -0,29 para Cochiguaz, Derecho y Toro respectivamente. No obstante, la modelación que considera percepción remota y caudales mejora los índices de 0,74 a 0,89 y de 0,75 a 0,8 para las cuencas Cochiguaz y Derecho respectivamente. En el caso del río Toro, el NSE se mantiene en 0,74.