Snow indicates the potential stored water volume that is an important source of water supply, which has been the most valuable and indispensable natural resource throughout the history of the world. Euphrates and Tigris, having the biggest dams of Turkey, are the two largest trans-boundary rivers that originate in Turkey and pass throughout the water deficit nations Syria, Iran, Iraq and Saudi Arabia bringing life as well as water all their way. Snowmelt runoff originating from the mountains of Eastern Turkey accounts for 60 to 70 % of total annual discharge observed in Euphrates and Tigris. For an optimum operation of the dams, maximizing energy production, mitigation of floods and satisfying water rights, hydrological models which can both simulate and forecast the river discharges of Euphrates and Tigris are needed. In this study a hydrological model, snowmelt runoff model (SRM), is used in conjunction with remote sensing and geographic information systems to forecast the river discharges in the headwaters of Euphrates River, Upper Euphrates Basin. NOAA and MODIS satellite images were used to derive the snow covered area (SCA) information required by SRM. Linear reduction methodologies based on accumulated air temperature, with constant or varying gradient, were developed to get the continuous daily SCA values from the discrete daily satellite images. Temperature and precipitation forecasts were gathered from two different numerical weather prediction models, namely European Center for Medium Range Weather Forecasts (ECMWF) and Mesoscale Model Version 5 (MM5) from Turkish State Meteorological Services. These data sets provided t+24 hour forecasts of both temperature and precipitation. Temperature, precipitation and SCA information are fed into SRM. Discharge forecasts obtained from the model outputs are compared with the observed values. The overall performance of the model was seen as promising. Possible reasons of the mismatches between the forecasted and observed values are searched. Experiences gained throughout the study are summarized and recommendations on further forecast studies are mentioned.

Snowmelt runoff in the mountainous eastern part of Turkey is of great importance as it constitutes 60-70% in volume of the total yearly runoff during spring and early summer months. Therefore, forecasting the amount and timing of snowmelt runoff especially in the Euphrates Basin, where large dams are located, is an important task in order to use the water resources of the country in an optimum manner. The HBV model, being one of the well-known conceptual hydrological models used more than 45 countries over the world, is applied for the first time in Turkey to a small basin of 242 km2 on the headwaters of Euphrates River for 2002-2004 water years. The input data are provided from the automatic snow-meteorological stations installed at various locations and altitudes in Upper Euphrates Basin operating in real-time. Since ground based observations can only represent a small part of the region of interest, spatially and temporally distributed snow cover data are acquired through the use of MODIS optical satellite. Automatic model parameter estimation methods, GML and SCE_UA, are utilized to calibrate the HBV model parameters with a multi-objective criteria using runoff as well as snow covered area to ensure the internal validity of the model and to generate a Pareto front. Model simulations show that the choice of study years and timing of satellite images affect the results and further suggest that more study catchments and years should be included to achieve more comprehensible conclusions. In the second part of the study, the calibrated HBV model is applied to forecast runoff with a 1-day lead time using gridded input data from numerical weather prediction models of ECMWF and MM5 for the 2004 snowmelt period. Promising results indicate the possible operational use of runoff forecasting using numerical weather prediction models in order to prevent or at least take precautions before flooding ahead of time.

The purpose of this dissertation is to develop and evaluate techniques for improvement of seasonal streamflow forecasts in the Upper Rio Grande (URG) basin in the U.S. Southwest. Three techniques are investigated. The first technique is an investigation of the effects of the El Ni??o/Southern Oscillation (ENSO) on temperature, precipitation, snow water equivalent (SWE), and the resulting streamflow at a monthly time scale, using data from 1952 to 1999 (WY). It was seen that the effects of ENSO on temperature and precipitation were confined to certain months, predominantly at the beginning and end of the winter season, and that the effect of these modulations of temperature and precipitation by ENSO can be seen in the magnitude and time variation of SWE and streamflow. The second part is a comparison of the use for snowmelt-runoff modeling of the newly available snowcover product based on imagery from the satellite-borne Moderate Resolution Imaging Spectroradiometer (MODIS) with the long-time standard snowcover product from the National Hydrological Remote Sensing Center (NOHRSC). This comparison is made using the Snowmelt Runoff Model (SRM) in two watersheds located inside the URG basin. This comparison is important because the MODIS snowcover product could greatly improve the availability of snowcover information because of its high spatial (500m) and temporal (daily) resolutions and extensive (global) coverage. Based on the results of this comparison, the MODIS snowcover product gives comparable snowcover information compared to that from NOHRSC. The final part is an investigation of streamflow forecasting using mass-balance models. Two watersheds used in the comparison of MODIS and NOHRSC snowcover products were again used. The parameters of the mass-balance models are obtained in two different ways and streamflow forecasts are made on January 1st, February 1st, March 1st and April 1st. The first means of parameter estimation is to use the parameter values from 1990 to 2001 SRM streamflow simulations and the second means is by optimization. The results of this investigation show that mass-balance models show potential to improve the long-term streamflow forecasts in snowmelt-dominated watersheds if dependable precipitation forecasts can be provided.

L'économie du Pakistan, fondée sur l'agriculture, est hautement dépendante de l'approvisionnement en eau issu de la fonte de la neige et des glaciers du Haut Bassin de l'Indus (UIB) qui s'étend sur les chaînes de l'Himalaya, du Karakoram et de l'Hindukush. Il est par conséquent essentiel pour la gestion des ressources en eau d'appréhender la dynamique de la cryosphère (neige et glace), ainsi que les régimes hydrologiques de cette région dans le contexte de scénarios de changement climatique. La base de données satellitaire du produit de couverture neigeuse MODIS MOD10A2 a été utilisée de mars 2000 à décembre 2009 pour analyser la dynamique du couvert neigeux de l'UIB. Les données journalières de débits à 13 stations hydrométriques et de précipitation et température à 18 postes météorologiques ont été exploitées sur des périodes variables selon les stations pour étudier le régime hydro-climatique de la région. Les analyses satellitaires de la couverture neigeuse et glaciaire suggèrent une très légère extension de la cryosphère au cours de la dernière décade (2000‒2009) en contradiction avec la rapide fonte des glaciers observée dans la plupart des régions du monde. Le modèle « Snowmelt Runoff » (SRM), associé aux produits neige du capteur MODIS a été utilisé avec succès pour simuler les débits journaliers et étudier les impacts du changement climatique sur ces débits dans les sous-bassins à contribution nivo-glaciaire de l'UIB. L'application de SRM pour différents scénarios futurs de changement climatique indique un doublement des débits pour le milieu du siècle actuel. La variation des écoulement de l'UIB, la capacité décroissante des réservoirs existants (barrage de Tarbela) à cause de la sédimentation, ainsi que la demande croissante pour les différents usages de l'eau, laissent penser que de nouveaux réservoirs sont à envisager pour stocker les écoulements d'été et répondre aux nécessités de l'irrigation, de la production hydro-électrique, de la prévention des crues et de l'alimentation en eau domestique. / Agriculture based economy of Pakistan is highly dependent on the snow and glacier melt water supplies from the Upper Indus River Basin (UIB), situated in the Himalaya, Karakoram and Hindukush ranges. It is therefore essential to understand the cryosphere (snow and ice) dynamics and hydrological regime of this area under changed climate scenarios, for water resource management. The MODIS MOD10A2 remote-sensing database of snow cover products from March 2000 to December 2009 was selected to analyse the snow cover dynamics in the UIB. A database of daily flows from 13 hydrometric stations and climate data (precipitation and temperature) from 18 gauging stations, over different time periods for different stations, was made available to investigate the hydro-climatological regime in the area. Analysis of remotely sensed cryosphere (snow and ice cover) data during the last decade (2000‒2009) suggest a rather slight expansion of cryosphere in the area in contrast to most of the regions in the world where glaciers are melting rapidly. The Snowmelt Runoff Model (SRM) integrated with MODIS remote-sensing snow cover products was successfully used to simulate the daily discharges and to study the climate change impact on these discharges in the snow and glacier fed sub-catchments of UIB. The application of the SRM under future climate change scenarios indicates a doubling of summer runoff until the middle of this century. This variation in the Upper Indus River flow, decreasing capacity of existing reservoirs (Tarbela Dam) by sedimentation and the increasing demand of water uses suggests that new reservoirs shall be planned for summer flow storage to meet with the needs of irrigation supply, increasing power generation demand, flood control and water supply.

Rain-on-snow events represent one of the basic mechanisms causing floods. Rain falling on the snow cover causes enhanced melting and the resulting runoff often exceeds the runoff caused by rain. During the winter seasons 2018 and 2019, water samples from the stream, snowpack and precipitation were repeatedly taken in the the Ptačí Brook catchment in the Šumava mountains, and the concentrations of 2 H and 18 O were measured in the laboratory. Based on the observed isotope ratios 18 O/16 O and 2 H/1 H in combination with other variables measured in the catchment, the two ROS events from 2019 were reconstructed. The ratio of heavy isotopes increased in the snowpack due to ROS events. Using the end member mixing equation, a hydrograph separation was performed for both investigated events. For the first event, it was not possible to clearly separate groundwater from rainfall, and thus the range of snow in the total runoff was determined by its separation from rainfall and subsequent separation from groundwater. The second event examined was separated directly into three components: rainfall, groundwater and snow. According to the analyses, the total runoff during ROS events in both cases was mostly formed by event water (a combination of rainfall and melt water). The melting water from the snow cover...