For the purpose of hydrological forecasting on mountains' and sub-mountains' rivers is important knowledge of distribution of snow water equivalent in the watershed. Submitted thesis therefore deals with comparison of 9 interpolation methods in terms of quality of their forecasting when predicting snow depth and snow water equivalent in watershed Bystřice (127,6 km2 ), which is situated in the northwest of Bohemia in the Ore mountains. Point data of snow depth and snow water equivalent used in interpolation were sampled during an off- road measuring in 17. 2. 2010 at the 14 snow sampling locations. The interpolation methods were: (1) Thiessen's polygons, (2) inverse distance weighting, (3) global polynomial (4) local polynomial (5) radial basis functions, (6) ordinary kriging, (7) cokriging, (8) residual kriging and (9) orographic interpolation. Independent variable-altitude used in the calculation of snow depth and snow water equivalent was used only in the last three listed methods. Predictive ability of interpolation methods was evaluated by using cross-validation and visual comparison of predicted maps. The best prediction ability was provided by residual kriging and orographic interpolation. The geostatistical methods were next in the order. The method of Thiessen's polygons and inverse distance...

This work deals with the evaluation of snow cover and snow spatial distribution in experimental Zbytinský and Tetřivči stream basin. Snow mesaurements were focused on snow depth and a snow water equivalent. Interpolation metods and detailed monitoring of rainfall-flow process were applied in the period of the winter half-year 2009 - 2011. The effects of geografic factors on spatial distribution of snow cover in the accumulation period and in the snow melting period were analysed. The analysis of physical geografic factors effect was focused on vegetation, exposure, slope, wind flow and shading. Results confirmed the strong effect of vegetation in the accumulation and snow melting period. Other physical geografic effects on spatial distribution of snow cover were not so significant. The model HEC-HMS was applied to determine the runoff in both stream basins. Simulations result in the winter half-year period reached good agreement between observed and simulated hydrographs. Effects of snow cover contribution to runoff in the snow melting period in wooded Tetřívčí stream basin and also in antropogenic Zbytinský stream basin were proved based on simulations of outflow and snow water equivalent. Key words: snow depth, snow water equivalent, HEC-HMS, Blanice River basin, Zbytinský stream, Tetřívčí stream

Water stored in snow is a critical contribution to the world’s available freshwater supply and is fundamental to the sustenance of natural ecosystems, agriculture and human societies. The importance of snow for the natural environment and for many socio-economic sectors in several mid‐ to high‐latitude mountain regions around the world, leads scientists to continuously develop new approaches to monitor and study snow and its properties. The need to develop new monitoring methods arises from the limitations of in situ measurements, which are pointwise, only possible in accessible and safe locations and do not allow for a continuous monitoring of the evolution of the snowpack and its characteristics. These limitations have been overcome by the increasingly used methods of remote monitoring with space-borne sensors that allow monitoring the wide spatial and temporal variability of the snowpack. Snow models, based on modeling the physical processes that occur in the snowpack, are an alternative to remote sensing for studying snow characteristics. However, from literature it is evident that both remote sensing and snow models suffer from limitations as well as have significant strengths that it would be worth jointly exploiting to achieve improved snow products. Accordingly, the main objective of this thesis is the development of novel methods for the estimation of snow parameters by exploiting the different properties of remote sensing and snow model data. In particular, the following specific novel contributions are presented in this thesis: i. A novel data fusion technique for improving the snow cover mapping. The proposed method is based on the exploitation of the snow cover maps derived from the AMUNDSEN snow model and the MODIS product together with their quality layer in a decision level fusion approach by mean of a machine learning technique, namely the Support Vector Machine (SVM). ii. A new approach has been developed for improving the snow water equivalent (SWE) product obtained from AMUNDSEN model simulations. The proposed method exploits some auxiliary information from optical remote sensing and from topographic characteristics of the study area in a new approach that differs from the classical data assimilation approaches and is based on the estimation of AMUNDSEN error with respect to the ground data through a k-NN algorithm. The new product has been validated with ground measurement data and by a comparison with MODIS snow cover maps. In a second step, the contribution of information derived from X-band SAR imagery acquired by COSMO-SkyMed constellation has been evaluated, by exploiting simulations from a theoretical model to enlarge the dataset.

Master thesis is concerned with the subject of a snow cover dynamics (focused on snow melting) and of the detailed analysis of each physical-geographic factors effect on its character. Knowledges published in the domestic and foreign scientific literature are confronted with the data acquired within a number of expeditionary snow monitoring campaignes carried out during winter periods 2011/2012 a 2012/2013 in headwaters of rivers of Šumava (Šumava Mts., southwestern Czechia). Mobile field survey was done in a number of time horizons within the broadly conceived research in the upper Otava River basin concentrated on the assessment of the retention potential in headstream areas.

Ce travail de thèse propose une méthodologie d’instrumentation reposant sur plusieurs outils hydrologiques, géophysiques et géochimiques afin de quantifier l’apport nival dans les débits du Lignon. Cette instrumentation consiste en un suivi des échanges aux différents compartiments/interfaces hydrologiques que forment l’atmosphère, la neige, le sol et les cours d’eau au cours des saisons. La neige, et surtout l’équivalent en eau liquide qu’elle représente, est fondamentale pour la compréhension du fonctionnement des sources du Lignon, situées à l’aval direct d’une congère de grand volume. Ce volume d’eau est stocké durant la saison froide pour être restitué lors de la fonte printanière. Cette restitution est loin d’être homogène dans le Haut Lignon, en raison de la forte variabilité spatio-temporelle des paramètres qui la pilotent.L’infiltration de l’eau alors produite est une étape clef dans le comportement hydrologique du Lignon au printemps. La structure du sol à proximité des sources explique également la forte dépendance des sources du Lignon par rapport aux précipitations neigeuses. Cette dépendance est particulièrement visible lors de la fonte de la neige, qui modifie à très court terme les débits aux sources. Cette relation neige-pluie-débit met en évidence une alimentation superficielle pluvio-neigeuse prépondérante par rapport aux débits issus d’eau plus profonde, mais variable au cours de l’année.La méthode d’instrumentation employée, adaptée à l’hydrologie locale employée, permet de corroborer les résultats obtenus avec une précision appréciable, tout en ouvrant de nouvelles perspectives d’application à d’autres bassins versants d’altitude. / This work proposes a methodology for an instrumentation based on several hydrological, geophysical and geochemical tools, to quantify the contribution of snowmelting proportions in the Lignon. This instrumentation is a monitoring of the different compartments / hydrological interfaces made up by atmosphere, snow, soil and rivers throughout the seasons.Snow, and especially the snow water equivalent, is fundamental to a better hydrological understanding of the sources of the Lignon, located directly downstream of a large snowdrift. This amount of water is stored during the cold season, to be returned during the spring melting. This return is heterogeneous in the top of the Lignon, due to the high spatial and temporal variability of parameters leading the melting.The infiltration of water therefore produced is a key step in the hydrological behavior of the Lignon during the spring time, which can be potentially more affected by the freezing of the ground, which significantly increases surface runoff.Soil structure near sources also explains the strong dependence of the sources of the Lignon towards snowfalls and rains. This dependence is especially noticeable at the snow melting that changes with very short term the flows at the sources.This snow-rainfall-runoff relationship highlights a predominant rain-snow surface supply, in comparison with the deeper water flows, and variable during the year.This instrumentation method, adapted to the local scale hydrology, allows corroborating the results obtained with a good accuracy, while opening new opportunities for application to other altitude watersheds.

From the Proceedings of the 1974 Meetings of the Arizona Section - American Water Resources Assn. and the Hydrology Section - Arizona Academy of Science - April 19-20, 1974, Flagstaff, Arizona / Profiles of snowpack build-up in openings in forest overstories have been widely observed; however, a quantitative characterization of such a snowpack profile would aid in developing empirical guidelines for improving water yields from snowpacks. A technique is outlined that illustrates (a) evaluating snowpack profiles in and adjacent to individual forest openings in terms of increase or decrease in water equivalent, and (b) defining trade-offs between the estimated increase or decrease in snowpack water equivalent and the forest resource removed. Snowpack water equivalent during peak seasonal accumulation was measured in and adjacent to a clearcut strip in a ponderosa pine stand in north-central Arizona. A 4-degree polynomial, which defines the snowpack profile in terms of deposition, redistribution, and ablation characteristics, was empirically selected to describe snowpack water equivalent data points. An increase of 60 percent in snowpack water equivalent was realized by removing 46 percent of the ponderosa pine in the zone of influence, using a strip equal to one and one-half the height of the adjacent overstory.

Vid gruvdrift genereras stora mängder gråberg (sprängsten) som lagras i deponier på markytan. Dessa deponier kan innehålla kväveföreningar, härstammande från odetonerade sprängämnen. Under senvintern/våren bidrar snösmältningen till att stora mängder vatten frigörs och infiltrerar i gråbergsmassorna. Lakvattnet som bildas från dessa deponier kan innehålla förhöjda halter av kväve vilket bl.a. kan leda till övergödning av närliggande sjöar och vattendrag. I denna studie har två snöinventeringar utförts på två gråbergshögar vid LKAB:s gruvområde i Kiruna. Syftet med rapporten har varit att beräkna snötäckets vattenekvivalent samt undersöka hur mycket vatten som potentiellt kan infiltrera deponierna och bilda lakvatten. Snötaxeringarna utfördes under februari och april 2015. Vid dessa tillfällen uppmättes snö- djups variationer mellan 8-100 cm beroende på slutningsriktning, samt snömassa variationer mellan 10-430 g. Med hjälp av dessa variabler beräknades snötäckets totala vattenekvivalent för de båda högarna till 100 m3 och 90m3. Utifrån en porositetlaboration uppskattades gråbergsdeponiernas totala porvolym till 968m3 och 725m3. Då den totala porvolymen är större än den vattenmängd som potentiellt kan infiltrera deponierna, bör majoriteten av vattnet lagras i porerna istället för att bidra till lakvattenproduktionen.

L’estimation de l’équivalent en eau de la neige (ÉEN) en temps quasi-réel est un enjeu important pour Hydro-Québec. Le réseau de mesure au sol étant non homogène et de faible densité, ne permet pas un suivi adéquat de l’ÉEN. L’imagerie satellitaire pourrait être une alternative à ce problème. Le modèle HUT (Helsinki University of Technology) permet l’estimation de l’ÉEN à partir des données micro-ondes passives. Le premier objectif de ce projet était de comparer deux produits qui estiment l’ÉEN à partir du modèle HUT, mais avec deux procédures d’inversion différentes. Il s’agit du produit Grille Neige du Québec (GNQ) et le produit GlobSnow. Deuxièmement, l’étude a évalué le produit GNQ en fonction de la végétation, du climat et de la topographie. L’étude s’est portée sur la région des bassins versants de la Grande et du Manicouagan situés au nord du Québec, sur une période allant du 1er janvier au 31 mars des années 2006 à 2010. Les données in-situ utilisées sont les lignes de neige d’Hydro-Québec et les mesures d’ÉEN de l’Année Polaire Internationale (février 2008), qui concernaient les sites de Sept-Iles et Schefferville. Il s’agissait de calculer l’erreur quadratique moyenne, le biais et le R2 pour chaque produit par rapport aux données in-situ, puis d’analyser ces paramètres en fonction des valeurs de fraction forestière, de volume des tiges, des moyennes de température et des précipitations, ainsi que de l’ÉEN moyen mesuré et de la pente du terrain. L’analyse a été faite d’abord à l’échelle du bassin, puis à l’échelle de cinq bandes latitudinales de 1° de latitude du nord vers le sud. Pour toute la zone, cette étude a démontré la supériorité de GNQ (RMSE=31%) par rapport à GlobSnow (RMSE=43%) pour un ÉEN moyen de 215 mm. Cependant cette supériorité décroit du nord vers le sud, où les produits deviennent similaires avec une RMSE = 45% et un biais de -90 mm pour un ÉEN moyen de 253 mm. Ceci pourrait être expliqué par l’effet de la densité de végétation caractéristique de la forêt boréale (fraction forestière > 45%), qui agit comme un masque au signal, et par l’effet d’un ÉEN > 250mm qui le sature. Pour le GNQ, l’effet combiné de la température et des précipitations joue un impact sur l’estimation de l’ÉEN, alors que le relief, plat en général, n’a pas montré un impact significatif. Pour conclure, le produit GNQ montre de meilleurs résultats que le produit GlobSnow, mais cette efficacité est limitée pour les régions ayant une végétation dense et un ÉEN très élevé. / Abstract : The monitoring of snow water equivalent (SWE) in near real time is an important challenge for Hydro-Quebec. Measurement networks do not allow adequate monitoring of the SWE. Passive microwave remote sensing could be an alternative to overcome this problem. The HUT (Helsinki University of Technology) model allows the estimation of the SWE from passive microwave data. The first purpose of this project was to compare two products that estimate the SWE using the HUT model, but with different inversion approaches. The first product is Quebec Snow Grid (GNQ) produced by Hydro-Quebec, and the second product is GlobSnow. The second objective of this study was to evaluate the GNQ product with regards to environmental variables (vegetation cover fraction, stem volume, climate and topography). The study area is located at La Grande and Manicouagan watersheds in northern Quebec. The study period was from 1 st January to 31 March of the years 2006 to 2010. The SWE data estimated by the two products were compared to Hydro-Quebec's insitu snow line data and to 2008 International Polar Year field campaign’s SWE measurements in Sept-Iles and Schefferville. The methodology of this work consisted in calculating the RMSE (Root Mean Square Error), bias and R2 for each product, relative to the in-situ data; and then analyze these parameters according to forest fraction, stem volume, mean temperatures, precipitation, as well as the mean measured SWE and the slope of the terrain. This was done, first for the study area, and then at the scale of five latitudinal bands of one degree latitude from north to south, which divide the study area. This study demonstrated the superiority of GNQ (RMSE = 31%) compared to GlobSnow (RMSE = 43%) for an average SWE of 215 mm over the entire study area. However, the performance decreases from north to south, where both products become quite similar, with RMSE = 45% and a bias of -90 mm for an average SWE of 253 mm. This could be explained by the effect of the vegetation density characteristic of the boreal forest (forest fraction> 45%), which acts like a mask for the signal, and by the higher SWE values (> 250 mm) which saturates it, hence the underestimation of the SWE. A combined effect of temperature and precipitation that had an impact on the SWE estimate was found for GNQ product. The relatively flat relief did not have a significant impact on the estimation of the SWE. Globally, GNQ shows better results than GlobSnow, but its capacity is limited for dense vegetation and thick snowpack.

From the Proceedings of the 1972 Meetings of the Arizona Section - American Water Resources Assn. and the Hydrology Section - Arizona Academy of Science - May 5-6, 1972, Prescott, Arizona / Inventory-prediction relationships between snowpack conditions and forest attributes may be useful in estimating water yields derived from snow, but such relationships are developed usually from source data collected over a short time period. Analyses of long-term data suggest inventory-prediction relationships developed from limited data may have more general application, however. Available records from 18 snow courses in the ponderosa pine type in Arizona provided source data in this study, which was designed to empirically analyze inventory-prediction relationships developed from long-term snow survey records. The primary hypothesis tested and evaluated by statistically analyzing the family of regression equations representing a snow course, was that, given a precipitation input, the distribution of snowpack water equivalent at peak seasonal accumulation is determined by the spatial arrangement of the forest cover, e.g. basal area. Generally 12 of the 18 snow courses evaluated appeared to support the hypothesis, three courses did not, and three courses were considered inconclusive.

From the Proceedings of the 1973 Meetings of the Arizona Section - American Water Resources Assn. and the Hydrology Section - Arizona Academy of Science - May 4-5, 1973, Tucson, Arizona / A preliminary study of probability distributions for use on snowpack accumulation in the central Arizona highlands was made from 22 snow courses selected as having 10 or more years of available records. Due to the frequent occurrence of zero water equivalent value, application of a single continuous probability distribution is precluded. By means of two distributions, however, the snowpack water equivalent can be assessed by a binomial distribution describing the probability of snow, and a lognormal distribution describing the probability of water equivalent. The area chosen for detailed analysis is where the headwaters of many of Arizona's major river systems occur.