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Donghai Zheng, Rogier van der Velde, Zhongbo Su, Martijn J. Booij, Arjen Y. Hoekstra, and Jun Wen

1. Introduction High-altitude regions, such as the source region of the Yellow River (SRYR) in the northeastern part of the Tibetan Plateau, have seen recently a striking air and ground surface warming ( Zhao et al. 2004 ; Wang et al. 2008 ; Qin et al. 2009 ; Yang et al. 2011a ; Wu et al. 2012 ), accompanied with noticeable ecological and hydrological changes ( Wang et al. 2003 ; Yang et al. 2007 ; Yang et al. 2011b ; Zhou and Huang 2012 ). Heat flux exchanges at the land

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Junchao Shi, Massimo Menenti, and Roderik Lindenbergh

1. Introduction Recent meteorological and glaciological studies show that a significant proportion of the total energy absorbed by glacier surfaces comes from turbulent fluxes ( Munro 1989 ; Oerlemans 2000 ; Denby and Greuell 2000 ; Brock et al. 2000 ). When evaluating the energy exchange over glaciers, the atmospheric boundary layer (ABL) is generally supposed to be stratified ( Arya 1973 , 1975 ). This energy transfer process is commonly parameterized by the “bulk eddy” aerodynamic method

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Chiara Corbari and Marco Mancini

evapotranspiration fluxes (ET)]. In this way there is the opportunity to increase control points of evapotranspiration so that its accuracy can be improved. Satellite data for their intrinsic nature of spatially distributed information can be used for the internal calibration/validation of distributed hydrological models in each pixel of the domain. This can be achieved with hydrologic modeling based on energy and water balance algorithms in conjunction with remote sensing data, in particular of land surface

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Mustafa Gokmen, Zoltan Vekerdy, Maciek W. Lubczynski, Joris Timmermans, Okke Batelaan, and Wouter Verhoef

abstraction.” The semiarid Konya basin in central Anatolia (Turkey), which is one of the biggest endorheic basins in the world, is a typical example of groundwater resources under strong anthropogenic pressure. Over the last few decades, the basin experienced huge groundwater abstraction for irrigation, which caused a hydraulic head decline of ~1 m yr −1 ( Bayari et al. 2009 ). Establishing the spatial and temporal distribution of hydrological fluxes using remote sensing (RS) methods has been the focus

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Rafael Pimentel, Javier Herrero, Yijian Zeng, Zhongbo Su, and María J. Polo

evolution is made by using simple empirical relationships between the snowmelt flux and selected meteorological variables ( Kustas et al. 1994 ). However, in these areas, the marked annual, seasonal, and even weekly variability of temperature, wind, and rainfall make this a difficult approach to apply in practice, and energy and mass balance equations are usually needed to capture these highly variable conditions ( Anderson 1976 ). Many physically based point models for the mass and energy balance in

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Gift Dumedah and Jeffrey P. Walker

surface model used in this study to simulate soil moisture is the JULES model—a widely used tiled model of subgrid heterogeneity that simulates water and energy fluxes between a vertical profile of soil layers, vegetation, and the atmosphere ( Best et al. 2011 ). The JULES model uses meteorological forcing data, surface land cover data, soil properties data, and values for prognostic variables. The soil properties data were derived from the Digital Atlas of Australian Soils ( McKenzie et al. 2000

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