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1. Introduction Understanding the climatic forcing of river flow represents a major research challenge of practical relevance, due to high socioeconomic and ecological dependence on water resources. This relevance is further enhanced in light of the pressing need to predict future water stress and risk within the context of climate change ( Houghton et al. 2001 ). Hydrologists have long been aware of the influence of climate on river flow, although traditional analyses rarely extended beyond
1. Introduction Understanding the climatic forcing of river flow represents a major research challenge of practical relevance, due to high socioeconomic and ecological dependence on water resources. This relevance is further enhanced in light of the pressing need to predict future water stress and risk within the context of climate change ( Houghton et al. 2001 ). Hydrologists have long been aware of the influence of climate on river flow, although traditional analyses rarely extended beyond
1. Introduction Land surface models (LSMs) have been developed by the atmospheric science community to provide atmospheric models with bottom boundary conditions (water and energy balance) and to serve as the land base for hydrologic modeling. Over the past two decades, overland and subsurface runoff calculations done by LSMs have extensively been used to provide water inflow to river routing models that calculate river discharge ( De Roo et al. 2003 ; Habets et al. 1999a – c , 2008
1. Introduction Land surface models (LSMs) have been developed by the atmospheric science community to provide atmospheric models with bottom boundary conditions (water and energy balance) and to serve as the land base for hydrologic modeling. Over the past two decades, overland and subsurface runoff calculations done by LSMs have extensively been used to provide water inflow to river routing models that calculate river discharge ( De Roo et al. 2003 ; Habets et al. 1999a – c , 2008
basin). The temperature of the water in streams is more and more being influenced by human activities within basins—mainly due to the construction of water reservoirs, the erection of thermal and nuclear power plants, and the diversion of sewage into surface waters ( Stancikova and Capekova 1993 ). The first daily measurements of water temperatures of Slovakian streams and rivers were made in 1925. Measurements of water temperature in the Danube River at the Bratislava gauging station for a period
basin). The temperature of the water in streams is more and more being influenced by human activities within basins—mainly due to the construction of water reservoirs, the erection of thermal and nuclear power plants, and the diversion of sewage into surface waters ( Stancikova and Capekova 1993 ). The first daily measurements of water temperatures of Slovakian streams and rivers were made in 1925. Measurements of water temperature in the Danube River at the Bratislava gauging station for a period
observed only over very limited areas (e.g., Robock et al. 2000 ). This deficiency exists primarily because in situ measurement of soil moisture (as well as snow mass and soil heat content) is difficult to accomplish, and remote sensing techniques are not always effective ( Dirmeyer et al. 2006 ). However, many observational datasets are available for river discharge, which represent the final stage of the land surface water cycle before draining into the oceans. Consequently, river routing schemes
observed only over very limited areas (e.g., Robock et al. 2000 ). This deficiency exists primarily because in situ measurement of soil moisture (as well as snow mass and soil heat content) is difficult to accomplish, and remote sensing techniques are not always effective ( Dirmeyer et al. 2006 ). However, many observational datasets are available for river discharge, which represent the final stage of the land surface water cycle before draining into the oceans. Consequently, river routing schemes
1. Introduction Recently, Welles et al. (2007) evaluated National Weather Service (NWS) river stage forecasts. They found the forecast skill may not have improved as much as expected because, as they suggested, forecast system updates were not driven by objective measures of forecast skill. Many people have studied elements of the forecast process—calibration, state updating, and precipitation forecasts—but the forecast process itself with the various elements linked together has not been
1. Introduction Recently, Welles et al. (2007) evaluated National Weather Service (NWS) river stage forecasts. They found the forecast skill may not have improved as much as expected because, as they suggested, forecast system updates were not driven by objective measures of forecast skill. Many people have studied elements of the forecast process—calibration, state updating, and precipitation forecasts—but the forecast process itself with the various elements linked together has not been
1. Introduction Anthropogenic climate change is intensifying the variability of the water cycle ( Douville et al. 2021 ), increasing the frequency and intensity of floods ( Hirabayashi et al. 2013 ) and droughts ( Trenberth et al. 2014 ) and threatening water availability around the world ( Konapala et al. 2020 ). Global trends in observed mean and extreme river flow have been detected and attributed to anthropogenic climate change, emphasizing the pervasive effects of climate change on
1. Introduction Anthropogenic climate change is intensifying the variability of the water cycle ( Douville et al. 2021 ), increasing the frequency and intensity of floods ( Hirabayashi et al. 2013 ) and droughts ( Trenberth et al. 2014 ) and threatening water availability around the world ( Konapala et al. 2020 ). Global trends in observed mean and extreme river flow have been detected and attributed to anthropogenic climate change, emphasizing the pervasive effects of climate change on
, and topographical characteristics. For instance, Abdulla et al. (1996) and Abdulla and Lettenmaier (1997a , b ) used a family of regression equations that relate the two-layer VIC (VIC-2L) model parameters to local land surface and climatological characteristics to derive the spatial distribution of vegetation and hydrological parameters over the Arkansas–Red River basin and obtained good simulation results. In principle, one would assume that the model parameters are closely related to basin
, and topographical characteristics. For instance, Abdulla et al. (1996) and Abdulla and Lettenmaier (1997a , b ) used a family of regression equations that relate the two-layer VIC (VIC-2L) model parameters to local land surface and climatological characteristics to derive the spatial distribution of vegetation and hydrological parameters over the Arkansas–Red River basin and obtained good simulation results. In principle, one would assume that the model parameters are closely related to basin
1. Introduction River flow is a useful indicator of freshwater availability, and can thus be used to evaluate likely impacts of climate change on water resources and flooding. There have been a number of studies of changes in river flow at the global scale (e.g., Arora and Boer 1999 ; Arnell 1999b , 2003 ; Hagemann and Dumenil 1998 ; Hirabayashi et al. 2008 ; Milly et al. 2005 ; Nijssen et al. 2001a , b ) using either stand-alone hydrological models driven by climate data output from
1. Introduction River flow is a useful indicator of freshwater availability, and can thus be used to evaluate likely impacts of climate change on water resources and flooding. There have been a number of studies of changes in river flow at the global scale (e.g., Arora and Boer 1999 ; Arnell 1999b , 2003 ; Hagemann and Dumenil 1998 ; Hirabayashi et al. 2008 ; Milly et al. 2005 ; Nijssen et al. 2001a , b ) using either stand-alone hydrological models driven by climate data output from
1. Introduction Projections of precipitation and river runoff associated with climate change are important sources of information for utilization of global water resources and prevention of floods and drought ( Seckler et al. 1999 ; Vörösmarty et al. 2000 ; McCarthy et al. 2001 ; Milly et al. 2002 ; Oki et al. 2003 ; Arnell 2004 ). The development of coupled atmosphere–ocean general circulation models (AOGCMs) has enabled us to project future changes in precipitation and river runoff
1. Introduction Projections of precipitation and river runoff associated with climate change are important sources of information for utilization of global water resources and prevention of floods and drought ( Seckler et al. 1999 ; Vörösmarty et al. 2000 ; McCarthy et al. 2001 ; Milly et al. 2002 ; Oki et al. 2003 ; Arnell 2004 ). The development of coupled atmosphere–ocean general circulation models (AOGCMs) has enabled us to project future changes in precipitation and river runoff
1. Introduction River water temperature T w is one of the most important parameters affecting freshwater biogeochemistry and the physical properties of surface water in rivers and lakes. The heating and cooling processes of T w in rivers are greatly influenced by meteorological and hydrological conditions over a wide range of spatial and temporal scales. The Arctic rivers are mostly ice covered during winter, with relatively stable T w values, and T w varies significantly during the ice
1. Introduction River water temperature T w is one of the most important parameters affecting freshwater biogeochemistry and the physical properties of surface water in rivers and lakes. The heating and cooling processes of T w in rivers are greatly influenced by meteorological and hydrological conditions over a wide range of spatial and temporal scales. The Arctic rivers are mostly ice covered during winter, with relatively stable T w values, and T w varies significantly during the ice
