Abstract. The feasibility of synthesizing distributed fields of soil moisture by the novel application of four-dimensional data assimilation (4DDA) applied in a hydrological model is explored. Six 160-km 2 push broom microwave radiometer (PBMR) images gathered over the Walnut Gulch experimental watershed in southeast Arizona were assimilated into the Topmodel-based Land-Atmosphere Transfer Scheme (TOPLATS) using several alternative assimilation procedures. Modification of traditional assimilation methods was required to use these high-density PBMR observations. The images were found to contain horizontal correlations that imply length scales of several tens of kilometers, thus allowing information to be advected beyond the area of the image. Information on surface soil moisture also was assimilated into the subsurface using knowledge of the surfacesubsurface correlation. Newtonian nudging assimilation procedures are preferable to other techniques because they nearly preserve the observed patterns within the sampled region but also yield plausible patterns in unmeasured regions and allow information to be advected in time. IntroductionSoil moisture is most often described as the water in the root zone that can interact with the atmosphere through evapotranspiration and precipitation. Because soil moisture links the hydrologic cycle and the energy budget of land surfaces by regulating latent heat fluxes, accurate assessment of the spatial and temporal variation of soil moisture is important for the study, understanding, and management of surface biogeophysical processes. Given the crucial role of soil moisture in land surface processes, it should be monitored with the same accuracy and frequency as other important environmental variables. However, because in situ soil moisture measurements are generally expensive and often problematic, no large-area soil moisture networks exist to measure soil moisture at the high frequency, multiple depths, and fine spatial resolution that is required for various applications. Remote sensing of soil moisture is limited by errors introduced by soil type, landscape roughness, vegetation cover, and inadequate coverage in both space and time. Alternatively, many reliable hydrologic models are available for calculating soil moisture, but these are prone to error in both structure and parameterization. It has been suggested [Wei, 1995] In the "statistical correction" data assimilation technique, = F(O, x, t) + GoWo(x, t)•o(x)(O•,-O) OtThe model's forcing terms are represented by F, 0•, is the observation at the model grid, and t is time. G 0 is the nudging factor that determines the magnitude of the nudging term relative to all other model processes, while the fourdimensional weighting function Wo specifies its spatial and temporal variation. The analysis quality factor • varies between 0 and 1 and is based on the quality and distribution of the observations. Equation (6) is implemented for all three TOPLATS soil layers, with the weighting factor decreasing with depth and time using...

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The main aim of this study was to assess the ability of simple geometric measures of thunderstorm rainfall in explaining the runoff response from the watershed. For calculation of storm geometric properties (e.g. areal coverage of storm, areal coverage of the high-intensity portion of the storm, position of storm centroid and the movement of storm centroid in time), spatial information of rainfall is needed. However, generally the rainfall data consists of rainfall depth values over an unevenly spaced network of raingauges. For this study, rainfall depth values were available for 91 raingauges in a watershed of about 148 km 2. There was a question about which interpolation method should be used for obtaining uniformly gridded data. Therefore, a small study was undertaken to compare cross-validation statistics and computed geometric parameters using two interpolation methods (kriging and multiquadric). These interpolation methods were used to estimate precipitation over a uniform 100 m £ 100 m grid. The cross-validation results from the two methods were generally similar and neither method consistently performed better than the other did. In view of these results we decided to use multiquadric interpolation method for the rest of the study. Several geometric measures were then computed from interpolated surfaces for about 300 storm events occurring in a 17-year period. The correlation of these computed measures with basin runoff were then observed in an attempt to assess their relative importance in basin runoff response. It was observed that the majority of the storms (observed in the study) covered the entire watershed. Therefore, it was concluded that the areal coverage of storm was not a good indicator of the amount of runoff produced. The areal coverage of the storm core (10-min intensity greater than 25 mm/h), however, was found to be a much better predictor of runoff volume and peak rate. The most important variable in runoff production was found to be the volume of the storm core. It was also observed that the position of the storm core relative to the watershed outlet becomes more important as the catchment size increases, with storms positioned in the central portion of the watershed producing more runoff than those positioned near the outlet or near the head of the watershed. This observation indicates the importance of interaction of catchment size and shape with the spatial storm structure in runoff generation. Antecedent channel wetness was found to be of some importance in explaining runoff for the largest of the three

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Peatland ecosystems have been consistent carbon (C) sinks for millennia, but it has been predicted that exposure to warmer temperatures and drier conditions associated with climate change will shift the balance between ecosystem photosynthesis and respiration providing a positive feedback to atmospheric CO 2 concentration. Our main objective was to determine the sensitivity of ecosystem photosynthesis, respiration and net ecosystem production (NEP) measured by eddy covariance, to variation in temperature and water table depth associated with interannual shifts in weather during 2004-2009. Our study was conducted in a moderately rich treed fen, the most abundant peatland type in western Canada, in a region (northern Alberta) where peatland ecosystems are a significant landscape component. During the study, the average growing season (May-October) water depth declined approximately 38 cm, and temperature [expressed as cumulative growing degree days (GDD, March-October)] varied approximately 370 GDD. Contrary to previous predictions, both ecosystem photosynthesis and respiration showed similar increases in response to warmer and drier conditions. The ecosystem remained a strong net sink for CO 2 with an average NEP ( AE SD) of 189 AE 47 g C m À2 yr À1 . The current net CO 2 uptake rates were much higher than C accumulation in peat determined from analyses of the relationship between peat age and cumulative C stock. The balance between C addition to, and total loss from, the top 0-30 cm depth (peat age range 0-70 years) of shallow peat cores averaged 43 AE 12 g C m À2 yr À1 . The apparent long-term average rate of net C accumulation in basal peat samples was 19-24 g C m À2 yr À1 . The difference between current rates of net C uptake and historical rates of peat accumulation is likely a result of vegetation succession and recent increases in tree establishment and productivity.