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1.
A land surface hydrology parameterization for use in atmospheric GCMs is presented. The parameterization incorporates subgrid scale variability in topography, soils, soil moisture and precipitation. The framework of the model is the statistical distribution of a topography-soils index, which controls the local water balance fluxes, and is therefore taken to represent the large land area. Spatially variable water balance fluxes are integrated with respect to the topography-soils index to yield our large scale parameterizations: water balance calculations are performed for a number of intervals of the topography-soils distribution, and interval responses are weighted by the probability of occurrence of the interval. Grid square averaged land surface fluxes result. The model functions independently as a macroscale water balance model. Runoff ratio and evapotranspiration efficiency parameterizations are derived and are shown to depend on the spatial variability of the above mentioned properties and processes, as well at the dynamics of land surface-atmosphere interactions.  相似文献   

2.
It is commonly assumed that biophysically based soil-vegetation-atmosphere transfer (SVAT) models are scale-invariant with respect to the initial boundary conditions of topography, vegetation condition and soil moisture. In practice, SVAT models that have been developed and tested at the local scale (a few meters or a few tens of meters) are applied almost unmodified within general circulation models (GCMs) of the atmosphere, which have grid areas of 50–500 km2. This study, which draws much of its substantive material from the papers of Sellers et al. (1992c, J. Geophys. Res., 97(D17): 19033–19060) and Sellers et al. (1995, J. Geophys. Res., 100(D12): 25607–25629), explores the validity of doing this. The work makes use of the FIFE-89 data set which was collected over a 2 km × 15 km grassland area in Kansas. The site was characterized by high variability in soil moisture and vegetation condition during the late growing season of 1989. The area also has moderate topography.

The 2 km × 15 km ‘testbed’ area was divided into 68 × 501 pixels of 30 m × 30 m spatial resolution, each of which could be assigned topographic, vegetation condition and soil moisture parameters from satellite and in situ observations gathered in FIFE-89. One or more of these surface fields was area-averaged in a series of simulation runs to determine the impact of using large-area means of these initial or boundary conditions on the area-integrated (aggregated) surface fluxes. The results of the study can be summarized as follows:

1. 1. analyses and some of the simulations indicated that the relationships describing the effects of moderate topography on the surface radiation budget are near-linear and thus largely scale-invariant. The relationships linking the simple ratio vegetation index (SR), the canopy conductance parameter (F) and the canopy transpiration flux are also near-linear and similarly scale-invariant to first order. Because of this, it appears that simple area-averaging operations can be applied to these fields with relatively little impact on the calculated surface heat flux.
2. 2. The relationships linking surface and root-zone soil wetness to the soil surface and canopy transpiration rates are non-linear. However, simulation results and observations indicate that soil moisture variability decreases significantly as an area dries out, which partially cancels out the effects of these non-linear functions.In conclusion, it appears that simple averages of topographic slope and vegetation parameters can be used to calculate surface energy and heat fluxes over a wide range of spatial scales, from a few meters up to many kilometers at least for grassland sites and areas with moderate topography. Although the relationships between soil moisture and evapotranspiration are non-linear for intermediate soil wetnesses, the dynamics of soil drying act to progressively reduce soil moisture variability and thus the impacts of these non-linearities on the area-averaged surface fluxes. These findings indicate that we may be able to use mean values of topography, vegetation condition and soil moisture to calculate the surface-atmosphere fluxes of energy, heat and moisture at larger length scales, to within an acceptable accuracy for climate modeling work. However, further tests over areas with different vegetation types, soils and more extreme topography are required to improve our confidence in this approach.
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3.
The variation in soil texture, surface moisture or vertical soil moisture gradient in larger scale atmospheric models may lead to significant variations in simulated surface fluxes of water and heat. The parameterization of soil moisture fluxes at spatial scales compatible with the grid size of distributed hydrological models and mesoscale atmospheric models ( 100 km2) faces principal problems which relate to the underlying microscopic or field scale heterogeneity in soil characteristics.

The most widely used parameterization in soil hydrology, the Darcy-Richards (DR) equation, is gaining increasing importance in mesoscale and climate modelling. This is mainly due to the need to introduce plant-interactive soil water depletion and stomatal conductance parameterizations and to improve the calculation of deep percolation and runoff. Covering a grid of several hundreds of square kilometres, the DR parameterization in soil-vegetation-atmosphere-transfer schemes (SVATs) is assumed to be scale-invariant. The parameters describing the non-linear, area-average soil hydraulic functions in this scale-invariant DR-equation should be treated as calibration-parameters, which do not necessarily have a physical meaning. The saturated hydraulic conductivity is one of the soil parameters to which the models show very high sensitivity. It is shown that saturated hydraulic conductivity can be scaled in both vertical and horizontal directions for large flow domains.

In this paper, a distinction is made between effective and aggregated soil parameters. Effective parameters are defined as area-average values or distributions over a domain with a single, distinct textural soil type. They can be obtained by scaling or inverse modelling. Aggregated soil parameters represent grid-domains with several textural soil types. In soil science dimensional methods have been developed to scale up soil hydraulic characteristics. With some specific assumptions, these techniques can be extrapolated from classical field-scale problems in soil heterogeneity to larger domains, compatible with the grid-size of large scale models. Particularly promising is the estimation of effective soil hydraulic parameters from area averaging measurements through inverse modelling of the unsaturated flow.

Techniques to scale and aggregate the soil characteristics presented in this paper qualify for direct or indirect use in large scale meteorological models. One of the interesting results is the effective behaviour of the reference curve, which can be obtained from similar media scaling. If the conclusions of this paper survive further studies, a relatively simple method will become available to parameterize soil variability at large scales. The inverse technique is found to provide effective soil parameters which perform well in predicting both the area-average evaporation and the area-average soil moisture fluxes, such as subsurface runoff. This is not the case for aggregated soil parameters. Obtained from regression relationships between soil textural composition and hydraulic characteristics, these aggregated parameters predict evaporation fluxes well, but fail to predict water balance terms such as percolation and runoff. This is a serious drawback which could eventually hamper the improvement of the representation of the hydrological cycle in mesoscale atmospheric models and in GCMs.  相似文献   


4.
The spatial variation of soil moisture over very small areas (<100 m2) can have nonlinear impacts on cycling and flux rates resulting in bias if it is not considered, but measuring this variation is difficult over extensive temporal and spatial scales. Most studies examining spatial variation of soil moisture were conducted at hillslope (0.01 km2) to multi-catchment spatial scales (1000 km2). They found the greatest variation at mid wetness levels and the smallest variation at wet and dry wetness levels forming a concave down relationship. There is growing evidence that concave down relationships formed between spatial variation of soil moisture and average soil moisture are consistent across spatial scales spanning several orders of magnitude, but more research is needed at very small, plot scales (<100 m2). The goal of this study was to characterise spatial variation in shallow soil moisture at the plot scale by relating the mean of measurements collected in a plot to the standard deviation (SD). We combined data from a previous study with thousands of new soil moisture measurements from 212 plots in eight catchments distributed across the US Mid-Atlantic Region to (1) test for a generalisable mean–SD relationship at plot scales, (2) characterise how landcover, land use, season, and hillslope position contribute to differences in mean–SD relationships, and (3) use these generalised mean–SD relationships to quantify their impacts on catchment scale nitrification and denitrification potential. Our study found that 98% of all measurements formed a generalised mean–SD relationship like those observed at hillslope and catchment spatial scales. The remaining 2% of data comprised a mean–SD relationship with greater spatial variation that originated from two riparian plots reported in a previous study. Incorporating the generalised mean–SD relationship into estimates of nitrification and denitrification potential revealed strong bias that was even greater when incorporating mean–SD observations from the two riparian plots with significantly greater spatial variation.  相似文献   

5.
Soil moisture state and variability control many hydrological and ecological processes as well as exchanges of energy and water between the land surface and the atmosphere. However, its state and variability are poorly understood at spatial scales larger than the fields (i.e. 1 km2) as well as the ability to extrapolate field scale to larger spatial scales. This study investigates soil moisture profiles, their spatial organization, and physical drivers of variability within the Walnut Creek watershed, Iowa, during Soil Moisture Experiment 2005 and relates the watershed scale findings to previous field‐scale results. For all depths, the watershed soil moisture variability was negatively correlated with the watershed mean soil moisture and followed an exponential relationship that was nearly identical to that for field scales. This relationship differed during drying and wetting. While the overall time stability characteristics were improved with observation depth, the relatively wet and dry locations were consistent for all depths. The most time stable locations, capturing the mean soil moisture of the watershed within ± 0·9% volumetric soil moisture, were typically found on hill slopes regardless of vegetation type. These mild slope locations consistently preserve the time stability patterns from field to watershed scales. Soil properties also appear to impact stability but the findings are sensitive to local variations that may not be well defined by existing soil maps. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

6.
The interaction between the land surface and the atmosphere is a crucial driver of atmospheric processes. Soil moisture and precipitation are key components in this feedback. Both variables are intertwined in a cycle, that is, the soil moisture – precipitation feedback for which involved processes and interactions are still discussed. In this study the soil moisture – precipitation feedback is compared for the sempiternal humid Ammer catchment in Southern Germany and for the semiarid to subhumid Sissili catchment in West Africa during the warm season, using precipitation datasets from the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), from the German Weather Service (REGNIE) and simulation datasets from the Weather Research and Forecasting (WRF) model and the hydrologically enhanced WRF-Hydro model. WRF and WRF-Hydro differ by their representation of terrestrial water flow. With this setup we want to investigate the strength, sign and variables involved in the soil moisture – precipitation feedback for these two regions. The normalized model spread between the two simulation results shows linkages between precipitation variability and diagnostic variables surface fluxes, moisture flux convergence above the surface and convective available potential energy in both study regions. The soil moisture – precipitation feedback is evaluated with a classification of soil moisture spatial heterogeneity based on the strength of the soil moisture gradients. This allows us to assess the impact of soil moisture anomalies on surface fluxes, moisture flux convergence, convective available potential energy and precipitation. In both regions the amount of precipitation generally increases with soil moisture spatial heterogeneity. For the Ammer region the soil moisture – precipitation feedback has a weak negative sign with more rain near drier patches while it has a positive signal for the Sissili region with more rain over wetter patches. At least for the observed moderate soil moisture values and the spatial scale of the Ammer region, the spatial variability of soil moisture is more important for surface-atmosphere interactions than the actual soil moisture content. Overall, we found that soil moisture heterogeneity can greatly affect the soil moisture – precipitation feedback.  相似文献   

7.
Spatial variation of soil moisture after snow thawing in South Gurbantunggut was quantitatively studied using ANOVA and geostatistics at various scales. The results show that the soil moisture heterogeneity varies along with spatial scales. At the shrub individual scale, there is a gradient in soil moisture from shrub-canopied area to canopy margin and to the interspaces between shrubs. At the community scale, soil moisture is highly autocorrelated and the semivariogram is fitted as spherical model, with an 89.6% structural variance and a range of 4.02 m. In addition, Kringing map indicates that the soil moisture distribution pattern after snow thawing is highly consistent with the shrub patch pattern. At the typical inter-dune transect scale, soil moisture presents a pattern of high value at inter-dune depression and low value at dune, and this variation is fitted as Gaussian model with a structural variance of 95.8% and a range of 66.16 m. The range is comparable with the scale of topography zoning, suggesting that the topography pattern controls the pattern of snowmelt at this scale. The evidence indicates that the heterogeneity of soil moisture at various scales is controlled by various land surface processes after snow thawing. For Gurbantunggut Desert, the spatial heterogeneity of snowmelt at various scales is ecologically valuable, because it promotes the utilization efficiency of the snowmelt for the desert vegetation.  相似文献   

8.
As an alternative to geostatistical modeling, we characterized the hydrology of a semi-arid landscape in southeastern Washington state, USA, by coupling spatial patterns identified in the distributions of relative relief and vegetation with the influence each has on soil moisture storage and evapotranspiration at the appropriate scale. Gauging precipitation, soil moisture, and evapotranspiration over a two-year period while concurrently mapping relative relief and vegetation distributions at three scales ranging from centimeters to 90 m, we determined that soil moisture and soil moisture storage are significantly greater in topographic concavities than in convexities at the microrelief (20–50 cm) scale but are not significantly different in relief features at larger scales. A generalized microrelief surface produced using a two-dimensional Fourier transformation provided a good representation of the distribution of soil moisture within microrelief when scaled to soil moisture values. Applying a spatial point process analysis we determined that big sage are randomly distributed across the landscape at all scales, suggesting that lysimeter-derived sage evapotranspiration rates also be distributed randomly across the landscape. Where sage were not present, we applied an autoregressive moving-average model conditioned on grass lysimeter measurements to derive evapotranspiration rates. Combining these hydrologic spatial patterns derived from distributions in relief and vegetation with measured precipitation inputs and evapotranspiration outputs, we created a spatially distributed model of soil moisture which we tested against measured values over an eight-week period. The model provides accurate characterization of soil moisture, allows estimates of soil moisture between measurement points, permits extrapolation of soil moisture distributions outside the gauged area, and maintains small-scale variability when aggregating soil moisture to successively larger scales.  相似文献   

9.
Spatial variation of soil moisture after snow thawing in South Gurbantunggut was quantitatively studied using ANOVA and geostatistics at various scales. The results show that the soil moisture heterogeneity varies along with spatial scales. At the shrub individual scale, there is a gradient in soil moisture from shrub-canopied area to canopy margin and to the interspaces between shrubs. At the community scale, soil moisture is highly autocorrelated and the semivariogram is fitted as spherical model, with an 89.6% structural variance and a range of 4.02 m. In addition, Kringing map indicates that the soil moisture distribution pattern after snow thawing is highly consistent with the shrub patch pattern. At the typical inter-dune transect scale, soil moisture presents a pattern of high value at inter-dune depression and low value at dune, and this variation is fitted as Gaussian model with a structural variance of 95.8% and a range of 66.16 m. The range is comparable with the scale of topography zoning, suggesting that the topography pattern controls the pattern of snowmelt at this scale. The evidence indicates that the heterogeneity of soil moisture at various scales is controlled by various land surface processes after snow thawing. For Gurbantunggut Desert, the spatial heterogeneity of snowmelt at various scales is ecologically valuable, because it promotes the utilization efficiency of the snowmelt for the desert vegetation.  相似文献   

10.
Li  Jun  Zhao  ChenYi  Zhu  Hong  Wang  Feng  Wang  LiJuan  Kou  SiYong 《中国科学:地球科学(英文版)》2007,50(1):49-55

Spatial variation of soil moisture after snow thawing in South Gurbantunggut was quantitatively studied using ANOVA and geostatistics at various scales. The results show that the soil moisture heterogeneity varies along with spatial scales. At the shrub individual scale, there is a gradient in soil moisture from shrub-canopied area to canopy margin and to the interspaces between shrubs. At the community scale, soil moisture is highly autocorrelated and the semivariogram is fitted as spherical model, with an 89.6% structural variance and a range of 4.02 m. In addition, Kringing map indicates that the soil moisture distribution pattern after snow thawing is highly consistent with the shrub patch pattern. At the typical inter-dune transect scale, soil moisture presents a pattern of high value at inter-dune depression and low value at dune, and this variation is fitted as Gaussian model with a structural variance of 95.8% and a range of 66.16 m. The range is comparable with the scale of topography zoning, suggesting that the topography pattern controls the pattern of snowmelt at this scale. The evidence indicates that the heterogeneity of soil moisture at various scales is controlled by various land surface processes after snow thawing. For Gurbantunggut Desert, the spatial heterogeneity of snowmelt at various scales is ecologically valuable, because it promotes the utilization efficiency of the snowmelt for the desert vegetation.

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11.
Using a coupled large‐eddy simulation–land surface model framework, the impact of two‐dimensional soil moisture heterogeneity on the cloudy boundary layer under varied free‐atmosphere stabilities is investigated. Specifically, the impacts of soil moisture heterogeneity length scale and heterogeneity in terms of soil moisture gradients on micrometeorological states, surface fluxes, boundary layer characteristics, and cloud development are examined. The results show that mesoscale circulations due to surface heterogeneity in soil moisture play an important role in transferring water vapour within the boundary layer and in regulating cloud distribution at the entrainment zone, which, in turn, provides feedbacks on boundary layer/surface energy budgets. The initial domain‐averaged soil moisture is identical for all homogenous and heterogeneous cases; however, the soil moisture heterogeneity in gradient and length scale between dry and wet regions has a significant impact on the estimates of near‐surface micrometeorological properties and surface fluxes, which further affect the boundary layer states and characteristics. Both liquid water potential temperature and liquid water mixing ratio increase with an increasing soil moisture gradient, whereas the amount of specific humidity decreases. Heterogeneity length scale and free atmosphere stability also amplify these impacts on the boundary layer structure and cloud formation. In a low atmospheric stability condition that potentially allows for a deeper boundary layer and a higher entrainment rate, cloud base height and cloud thickness significantly increase as the soil moisture gradient and length scale increase. Analysis to differentiate the influences of surface heterogeneity type (i.e. length scale vs gradient) shows that in general soil moisture gradient provides a larger impact than heterogeneity length scale, although the heterogeneity length scale is large enough to initiate circulation features responsible for differences in the coupled system between homogeneous and heterogeneous soil moisture cases. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

12.
The main thrust of the HAPEX-MOBILHY experiment was towards investigating techniques involved in integrating the turbulent surface fluxes measured at local sites to a larger scale approaching that used in general circulation models.Some aspects of the field data collected at various times and spatial scales are presented. Annual cycle of the soil moisture at many sites is discussed in relation with outputs of a large scale hydrological model. At shorter time scales, the spatial variability of surface energy partition is examined with regard to spatial contrasts in albedo, surface roughness and plant properties related to the two main vegetation classes found in the HAPEX square: A pine forest and the nearby agricultural area.Finally, examples of daily spatial integration with an atmospheric mesoscale model including a comprehensive treatment of land surface processes are presented.  相似文献   

13.
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14.
Soil moisture is essential for plant growth and terrestrial ecosystems, especially in arid and semi‐arid regions. This study aims to quantify the variation of soil moisture content and its spatial pattern as well as the influencing factors. The experiment is conducted in a small catchment named Yangjuangou in the loess hilly region of China. Soil moisture to a depth of 1 m has been obtained by in situ sampling at 149 sites with different vegetation types before and after the rainy season. Elevation, slope position, slope aspect, slope gradient and vegetation properties are investigated synchronously. With the rainy season coming, soil moisture content increases and then reaches the highest value after the rainy season. Fluctuation range and standard deviation of soil moisture decrease after a 4‐month rainy season. Standard deviation of soil moisture increases with depth before the rainy season; after the rainy season, it decreases within the 0‐ to 40‐cm soil depth but then increases with depths below 40 cm. The stability of the soil moisture pattern at the small catchment scale increases with depth. The geographical position determines the framework of soil moisture pattern. Soil moisture content with different land‐use types is significantly increased after the rainy season, but the variances of land‐use types are significantly different. Landform and land‐use types can explain most of the soil moisture spatial variations. Soil moisture at all sample sites increases after the rainy season, but the spatial patterns of soil moisture are not significantly changed and display temporal stability despite the influence of the rainy season. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

15.
Soil moisture distribution shows highly variation both spatially and temporally. This study assesses the spatial heterogeneity of soil moisture on a hill-slope scale in the Loess Plateau in West China by using a geostatistical approach. Soil moisture was measured by time-domain reflectometry （TDR） in 313 samples. Two kinds of sampling scales were used （2 × 2 m and 20 ×20 m） at two soil layers （0-30 cm and 30-60 cm）. The general characteristics of soil moisture were analyzed by a classical statistics method, and the spatial heterogeneity of soil moisture was analyzed using a geostatistical approach. The results showed that the spherical model is the best-fit model to simulate soil moisture on the experimental hill-slope. The parameters of this model indicated that the spatial dependence of soil moisture in the selected hill-slope was moderate. Even the 2 × 2 m sampling scale was too coarse to show the detailed spatial variances of soil moisture in this area. The dependent distance increased from 27.4 m to 494.16 m as the sampling scale became coarse （from 2× 2 m to 20 ×20 m）. A map of soil moisture was generated by using original soil moisture data and interpolated values determined by the Kriging method. The average soil moisture （area weighted） in the different layers of soil was calculated on the basis of this map （10.94% for the 0-30 cm soil layer, 11.88% for the 30-60 cm soil layer）. This average soil moisture is lower than the corresponding average effective soil moisture, which suggests that the soil moisture is not sufficient to support vegetation in this area.  相似文献   

16.
The crucial role of root-zone soil moisture is widely recognized in land–atmosphere interaction, with direct practical use in hydrology, agriculture and meteorology. But it is difficult to estimate the root-zone soil moisture accurately because of its space-time variability and its nonlinear relationship with surface soil moisture. Typically, direct satellite observations at the surface are extended to estimate the root-zone soil moisture through data assimilation. But the results suffer from low spatial resolution of the satellite observation. While advances have been made recently to downscale the satellite soil moisture from Soil Moisture and Ocean Salinity (SMOS) mission using methods such as the Disaggregation based on Physical And Theoretical scale Change (DisPATCh), the assimilation of such data into high spatial resolution land surface models has not been examined to estimate the root-zone soil moisture. Consequently, this study assimilates the 1-km DisPATCh surface soil moisture into the Joint UK Land Environment Simulator (JULES) to better estimate the root-zone soil moisture. The assimilation is demonstrated using the advanced Evolutionary Data Assimilation (EDA) procedure for the Yanco area in south eastern Australia. When evaluated using in-situ OzNet soil moisture, the open loop was found to be 95% as accurate as the updated output, with the updated estimate improving the DisPATCh data by 14%, all based on the root mean square error (RMSE). Evaluation of the root-zone soil moisture with in-situ OzNet data found the updated output to improve the open loop estimate by 34% for the 0–30 cm soil depth, 59% for the 30–60 cm soil depth, and 63% for the 60–90 cm soil depth, based on RMSE. The increased performance of the updated output over the open loop estimate is associated with (i) consistent estimation accuracy across the three soil depths for the updated output, and (ii) the deterioration of the open loop output for deeper soil depths. Thus, the findings point to a combined positive impact from the DisPATCh data and the EDA procedure, which together provide an improved soil moisture with consistent accuracy both at the surface and at the root-zone.  相似文献   

17.
Organized convection in the tropics occurs across a range of spatial and temporal scales and strongly influences cloud cover and humidity. One mode of organization found is “self-aggregation,” in which moist convection spontaneously organizes into one or several isolated clusters despite spatially homogeneous boundary conditions and forcing. Self-aggregation is driven by interactions between clouds, moisture, radiation, surface fluxes, and circulation, and occurs in a wide variety of idealized simulations of radiative–convective equilibrium. Here we provide a review of convective self-aggregation in numerical simulations, including its character, causes, and effects. We describe the evolution of self-aggregation including its time and length scales and the physical mechanisms leading to its triggering and maintenance, and we also discuss possible links to climate and climate change.  相似文献   

18.
A soil–vegetation–atmosphere transfer model (SVAT), interactions between the soil–biosphere–atmosphere (ISBA) of Météo France, is modified and applied to the Athabasca River Basin (ARB) to model its water and energy fluxes. Two meteorological datasets are used: the archived forecasts from the Meteorological Survey of Canada’s Global Environmental Multiscale Model (GEM) and the European Centre for Mid-range Weather Forecasts global re-analysis (ERA-40), representing spatial scales typical of a weather forecasting model and a global circulation model (GCM), respectively. The original treatment of soil moisture and rainfall in ISBA (OISBA) is modified to statistically account for sub-grid heterogeneity of soil moisture and rainfall to produce new, highly non-linear formulations for surface and sub-surface runoff (MISBA). These new formulations can be readily applied to most existing SVATs. Stand alone mode simulations using the GEM data demonstrate that MISBA significantly improves streamflow predictions despite requiring two fewer parameters than OISBA. Simulations using the ERA-40 data show that it is possible to reproduce the annual variation in monthly, mean annual, and annual minimum flows at GCM scales without using downscaling techniques. Finally, simulations using a simple downscaling scheme show that the better performance of higher resolution datasets can be primarily attributed to improved representation of local variation of land cover, topography, and climate.  相似文献   

19.
The seasonally‐dry climate of Northern California imposes significant water stress on ecosystems and water resources during the dry summer months. Frequently during summer, the only water inputs occur as non‐rainfall water, in the form of fog and dew. However, due to spatially heterogeneous fog interaction within a watershed, estimating fog water fluxes to understand watershed‐scale hydrologic effects remains challenging. In this study, we characterized the role of coastal fog, a dominant feature of Northern Californian coastal ecosystems, in a San Francisco Peninsula watershed. To monitor fog occurrence, intensity, and spatial extent, we focused on the mechanisms through which fog can affect the water balance: throughfall following canopy interception of fog, soil moisture, streamflow, and meteorological variables. A stratified sampling design was used to capture the watershed's spatial heterogeneities in relation to fog events. We developed a novel spatial averaging scheme to upscale local observations of throughfall inputs and evapotranspiration suppression and make watershed‐scale estimates of fog water fluxes. Inputs from fog water throughfall (10–30 mm/year) and fog suppression of evapotranspiration (125 mm/year) reduced dry‐season water deficits by 25% at watershed scales. Evapotranspiration suppression was much more important for this reduction in water deficit than were direct inputs of fog water. The new upscaling scheme was analyzed to explore the sensitivity of its results to the methodology (data type and interpolation method) employed. This evaluation suggests that our combination of sensors and remote sensing allows an improved incorporation of spatially‐averaged fog fluxes into the water balance than traditional interpolation approaches.  相似文献   

20.
Ephemeral aeolian sand strips are commonplace on beaches. Their formation during high energy sand transport events often precedes the development of protodunes and their dynamics present interesting feedback mechanisms with surface moisture patterns. However, due to their temporary nature, little is known of their formation, mobility or the specifics of their interaction with beach surface characteristics. Similarly surface moisture has an important influence on sediment availability and transport in aeolian beach systems, yet it is difficult to quantify accurately due to its inherent variability over both short spatial and temporal scales. Whilst soil moisture probes and remote sensing imagery techniques can quantify large changes well, their resolution over mainly dry sand, close to the aeolian transport threshold is not ideal, particularly where moisture gradients close to the surface are large. In this study we employed a terrestrial laser scanner to monitor beach surface moisture variability during a three and a half hour period after a rain event and investigated relationships between bedform development, surface roughness and surface moisture. Our results demonstrate that as the beach surface dries, sand transport increases, with sediment erosion occurring at the wet/dry surface boundary, and deposition further downwind. This dynamic structure, dependent upon changing surface moisture characteristics, results in the formation of a rippled sand strip and ultimately a protodune. Our findings highlight dynamic mobility relationships and confirm the need to consider transient bedforms and surface moisture across a variety of scales when measuring aeolian transport in beach settings. The terrestrial laser scanner provides a suitable apparatus with which to accomplish this. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

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