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1.
Soil moisture influences many hydrologic applications including agriculture, land management and flood prediction. Most remote‐sensing methods that estimate soil moisture produce coarse resolution patterns, so methods are required to downscale such patterns to the resolutions required by these applications (e.g. 10‐ to 30‐m grid cells). At such resolutions, topography is known to affect soil moisture patterns. Although methods have been proposed to downscale soil moisture based on topography, they usually require the availability of past high‐resolution soil moisture patterns from the application region. The objective of this article is to determine whether a single topographic‐based downscaling method can be used at multiple locations without relying on detailed local observations. The evaluated downscaling method is developed on the basis of empirical orthogonal function (EOF) analysis of space–time soil moisture data at a reference catchment. The most important EOFs are then estimated from topographic attributes, and the associated expansion coefficients are estimated on the basis of the spatial‐average soil moisture. To test the portability of this EOF‐based method, it is developed separately using four data sets (Tarrawarra, Tarrawarra 2, Cache la Poudre and Satellite Station), and the relationships that are derived from these data sets to estimate the EOFs and expansion coefficients are compared. In addition, each of these downscaling methods is applied not only for the catchment where it was developed but also to the other three catchments. The results suggest that the EOF downscaling method performs well for the location where it is developed, but its performance degrades when applied to other catchments. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

2.
Characterizing the spatial dynamics of soil moisture fields is a key issue in hydrology, offering an avenue to improve our understanding of complex land surface–atmosphere interactions. In this paper, the statistical structure of soil moisture patterns is examined using modelled soil moisture obtained from the North American Land Data Assimilation System (NLDAS) at 0.125° resolution. The study focuses on the vertically averaged soil moisture in the top 10 cm and 100 cm layers. The two variables display a weak dependence for lower values of surface soil moisture, with the strength of the relationship increasing with the water content of the top layer. In both cases, the variance of the soil moisture follows a power law decay as a function of the averaging area. The superficial layer shows a lower degree of spatial organization and higher temporal variability, which is reflected in rapid changes in time of the slope of the scaling functions of the soil moisture variance. Conversely, the soil moisture in the top 100 cm has lower variability in time and larger spatial correlation. The scaling of these patterns was found to be controlled by the changes in the soil water content. Results have implications for the downscaling of soil moisture to prevent model bias.  相似文献   

3.
In situ soil moisture data from the Bibeschbach experimental catchment in Luxembourg are used to evaluate relative surface soil moisture observed with the MetOp‐A Advanced Scatterometer (ASCAT). Filtered and bias‐corrected surface soil wetness indices (SWIs) derived from coarse‐resolution (25 km) C‐band scatterometer observations are shown to be highly correlated (r = 0.86) with catchment‐averaged soil moisture measured in the field. The combination of ASCAT and ENVISAT Advanced Synthetic Aperture Radar (ASAR) data sets yields high‐resolution (1 km) relative surface soil moisture that is equally well correlated with in situ measurements. It is concluded that for soil moisture monitoring applications at a catchment scale, the two soil moisture products are equivalent. The best correlation between the SWI derived from ASCAT and ASCAT‐ASAR with in situ soil moisture observations at ca. 5 cm depth is obtained with a characteristic time length parameter T equal to 288 h. These results suggest that satellite‐derived surface soil wetness may serve as proxy for soil storage that enables the monitoring of abrupt switches in river system dynamics to appear when an effective field capacity is exceeded and rapid subsurface stormflow is initiated. In catchments where soil moisture is the main controlling factor of rapid subsurface flow, MetOp ASCAT–derived SWI has the potential to monitor how a river system approaches a critical threshold. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

4.
The coarse resolution soil moisture (SM) data from NASA SMAP mission have been steadily produced with the expected performance since April 2015. These coarse resolution observations could be downscaled to fine resolution using fine scale observations of SM sensitive quantities from existing satellite sensors. For operational users who need near-real-time (NRT) high resolution SM data, the downscaling approach should be feasible for operational implementation, requiring limited ancillary information and primarily depending on readily available satellite observations. Based on these principles, nine potential candidate downscaling schemes were selected for developing an optimal downscaling strategy. Using remotely sensed land surface temperature (LST) and enhanced vegetation index (EVI) observations, the optimal downscaling approach was tested for operational producing a NRT 1 km SM data product from SMAP. Comprehensive assessments on the 1 km SM product were conducted based on agreement statistics with in-situ SM measurements. Statistical results show that the accuracy of the original coarse spatial resolution SMAP SM product can be significantly improved by 8% by the downscaled 1 km SM. With respect to the in-situ measurements, the 1 km SM mapping capability developed here presents a clear advantage over the SMAP/Sentinel SM data product; and it also provides better data availability for users. This study suggests that a NRT 1 km SMAP SM data product could be routinely generated from SMAP at the centre for Satellite Applications and Research of NOAA NESDIS for operational users.  相似文献   

5.
The spatial distribution of forests, meadows, arable land, water bodies and settlements in a catchment influences the spatial and temporal dynamics of evapotranspiration, surface runoff, soil moisture and ground water recharge. Four digital data sets from different sources were available for land cover distribution to be applied in a regional case study in the Ucker catchment with an area of about 2415 km2. The first data set was obtained from the German digital topographic data set “Atkis” and the second one from the federal German biotope mapping procedure “Biotoptypenkartierung”. In addition, Corine land cover data and a land cover obtained from a supervised, multitemporal classification of three Landsat-TM5-scenes from the year 2000 were used in our study. These data sets differ in spatial resolution and in information content and this leads to different areal proportions of the main land cover classes forests, meadows, arable land, water bodies and settlements. This has to be considered as an uncertainty in the land cover data. In our case study, we analyzed how and to which extent this uncertainty influences the outputs of a hydrological catchment model such as evapotranspiration and discharge. For the time period 1996-2001, meteorological time series were obtained from four meteorological stations and five additional precipitation stations. Measured daily discharge rates were available from two gauges located in the catchment. In the different land cover data sets, the proportions of arable land ranged from 52.7% to 61.7% of the catchment area and for forests from 19.5% to 24.6%. These different proportions showed only minor impacts with small differences below ±10 mm y−1 on the simulated annual rates of evapotranspiration and ground water recharge. In contrast, the simulated surface runoff rates showed a strong correlation to the amount of the settlement areas in the catchment. The highest proportion of settlements with 4.9% of the catchment area in comparison to the lowest proportion of 2.9% leads to an increase in the simulated surface runoff of 70%.  相似文献   

6.
Soil moisture is highly variable both spatially and temporally. It is widely recognized that improving the knowledge and understanding of soil moisture and the processes underpinning its spatial and temporal distribution is critical. This paper addresses the relationship between near‐surface and root zone soil moisture, the way in which they vary spatially and temporally, and the effect of sampling design for determining catchment scale soil moisture dynamics. In this study, catchment scale near‐surface (0–50 mm) and root zone (0–300 mm) soil moisture were monitored over a four‐week period. Measurements of near‐surface soil moisture were recorded at various resolutions, and near‐surface and root zone soil moisture data were also monitored continuously within a network of recording sensors. Catchment average near‐surface soil moisture derived from detailed spatial measurements and continuous observations at fixed points were found to be significantly correlated (r2 = 0·96; P = 0·0063; n = 4). Root zone soil moisture was also found to be highly correlated with catchment average near‐surface, continuously monitored (r2 = 0·81; P < 0·0001; n = 26) and with detailed spatial measurements of near‐surface soil moisture (r2 = 0·84). The weaker relationship observed between near‐surface and root zone soil moisture is considered to be caused by the different responses to rainfall and the different factors controlling soil moisture for the soil depths of 0–50 mm and 0–300 mm. Aspect is considered to be the main factor influencing the spatial and temporal distribution of near‐surface soil moisture, while topography and soil type are considered important for root zone soil moisture. The ability of a limited number of monitoring stations to provide accurate estimates of catchment scale average soil moisture for both near‐surface and root zone is thus demonstrated, as opposed to high resolution spatial measurements. Similarly, the use of near‐surface soil moisture measurements to obtain a reliable estimate of deeper soil moisture levels at the small catchment scale was demonstrated. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

7.
In order to evaluate the relationship between the apparent complexity of hillslope soil moisture and the emergent patterns of catchment hydrological behaviour and water quality, we need fine‐resolution catchment‐wide data on soil moisture characteristics. This study proposes a methodology whereby vegetation patterns obtained from high‐resolution orthorectified aerial photographs are used as an indicator of soil moisture characteristics. This enables us to examine a set of hypotheses regarding what drives the spatial patterns of soil moisture at the catchment scale (material properties or topography). We find that the pattern of Juncus effusus vegetation is controlled largely by topography and mediated by the catchment's material properties. Characterizing topography using the topographic index adds value to the soil moisture predictions relative to slope or upslope contributing area (UCA). However, these predictions depart from the observed soil moisture patterns at very steep slopes or low UCAs. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

8.
This research develops a one-parameter model of saturated source area dynamics and the spatial distribution of soil moisture. The single required parameter is the maximum soil moisture deficit within the catchment. The concept behind the development of the model comes from the fact that the complexity of topographically-driven runoff generation can be reduced through the use of geomorphological scaling relations. The scaling formulation allows the prediction of the dynamics of saturated source areas as a function of basin-wide soil moisture state. This model offers a number of potential advantages. Firstly, the model parameter is independent of topographic index distribution and its associated scale effects. Secondly, it may be possible to measure this single parameter using field measurements or perhaps remote sensing, which gives the model significant potential for application in ungauged basins. Finally, the fact that this parameter is a physical characteristic of the basin, estimation of this parameter avoids regionalization and parameter transferability problems. The model is tested using rainfall–runoff data from the 10.4 ha experimental catchment known as Tarrawara in Australia, the 37 km2 Town Creek catchment in U.S.A., and the 620 km2 Balaphi and the 850 km2 Likhu sub-catchments of the Koshi river in Nepal. In sub-catchments of Koshi river, the simulation results compare favorably against the calibrated TOPMODEL both in terms of direct runoff and the spatial distribution of soil moisture state. In the Tarrawara and Town Brook catchments, simulation results compare favorably against observed storm runoff using all observed data, without calibration.  相似文献   

9.
This paper analyses the effect of spatial resolution and distribution of model input data on the results of regional-scale land use scenarios using three different hydrological catchment models. A 25 m resolution data set of a mesoscale catchment and three land use scenarios are used. Data are systematically aggregated to resolutions up to 2 km. Land use scenarios are spatially redistributed, both randomly and topography based. Using these data, water fluxes are calculated on a daily time step for a 16 year time period without further calibration. Simulation results are used to identify grid size, distribution and model dependent scenario effects. In the case of data aggregation, all applied models react sensitively to grid size. WASIM and TOPLATS simulate constant water balances for grid sizes from 50 m to 300–500 m, SWAT is more sensitive to input data aggregation, simulating constant water balances between 50 m and 200 m grid size. The calculation of scenario effects is less robust to data aggregation. The maximum acceptable grid size reduces to 200–300 m for TOPLATS and WASIM. In case of spatial distribution, SWAT and TOPLATS are slightly sensitive to a redistribution of land use (below 1.5% for water balance terms), whereas WASIM shows almost no reaction. Because the aggregation effects were stronger than the redistribution effects, it is concluded that spatial discretisation is more important than spatial distribution. As the aggregation effect was mainly associated with a change in land use fraction, it is concluded that accuracy of data sets is much more important than a high spatial resolution.  相似文献   

10.
This article investigates the soil moisture dynamics within two catchments (Stanley and Krui) in the Goulburn River in NSW during a 3‐year period (2005–2007) using the HYDRUS‐1D soil water model. Sensitivity analyses indicated that soil type, and leaf area index were the key parameters affecting model performance. The model was satisfactorily calibrated on the Stanley microcatchment sites with a single point rainfall record from this microcatchment for both surface 30 cm and full‐profile soil moisture measurements. Good correlations were obtained between observed and simulated soil water storage when calibrations for one site were applied to the other sites. We extended the predictions of soil moisture to a larger spatial scale using the calibrated soil and vegetation parameters to the sites in the Krui catchment where soil moisture measurement sites were up to 30 km distant from Stanley. Similarly good results show that it is possible to use a calibrated soil moisture model with measurements at a single site to extrapolate the soil moisture to other sites for a catchment with an area of up to 1000 km2 given similar soils and vegetation and local rainfall data. Site predictions were effectively improved by our simple data assimilation method using only a few sample data collected from the site. This article demonstrates the potential usefulness of continuous time, point‐scale soil moisture data (typical of that measured by permanently installed TDR probes) and simulations for predicting the soil wetness status over a catchment of significant size (up to 1000 km2). Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

11.
High resolution radar rainfall fields and a distributed hydrologic model are used to evaluate the sensitivity of flood and flash flood simulations to spatial aggregation of rainfall and soil properties at catchment scales ranging from 75 to 983 km2. Hydrologic modeling is based on a Hortonian infiltration model and a network-based representation of hillslope and channel flow. The investigation focuses on three extreme flood and flash flood events occurred on the Sesia river basin, North Western Italy, which are analysed by using four aggregation lengths ranging from 1 to 16 km. The influence of rainfall spatial aggregation is examined by using the flow distance as a spatial coordinate, hence emphasising the role of river network in the averaging of space–time rainfall. The effects of reduced and distorted rainfall spatial variability on peak discharge have been found particularly severe for the flash flood events, with peak errors up to 35% for rainfall aggregation of 16 km and at 983 km2 catchment size. Effects are particularly remarkable when significant structured rainfall variability combines with relatively important infiltration volumes due to dry initial conditions, as this emphasises the non-linear character of the rainfall–runoff relationship. In general, these results confirm that the correct estimate of rainfall volume is not enough for the accurate reproduction of flash flood events characterised by large and structured rainfall spatial variability, even at catchment scales around 250 km2. However, accurate rainfall volume estimation may suffice for less spatially variable flood events. Increasing the soil properties aggregation length exerts similar effects on peak discharge errors as increasing the rainfall aggregation length, for the cases considered here and after rescaling to preserve the rainfall volume. Moreover, peak discharge errors are roughly proportional to runoff volume errors, which indicates that the shape of the flood wave is influenced in a limited way by modifying the detail of the soil property spatial representation. Conversely, rainfall aggregation may exert a pronounced influence on the discharge peak by reshaping the spatial organisation of the runoff volumes and without a comparable impact on the runoff volumes.  相似文献   

12.
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13.
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14.
The upcoming deployment of satellite-based microwave sensors designed specifically to retrieve surface soil moisture represents an important milestone in efforts to develop hydrologic applications for remote sensing observations. However, typical measurement depths of microwave-based soil moisture retrievals are generally considered too shallow (top 2–5 cm of the soil column) for many important water cycle and agricultural applications. Recent work has demonstrated that thermal remote sensing estimates of surface radiometric temperature provide a complementary source of land surface information that can be used to define a robust proxy for root-zone (top 1 m of the soil column) soil moisture availability. In this analysis, we examine the potential benefits of simultaneously assimilating both microwave-based surface soil moisture retrievals and thermal infrared-based root-zone soil moisture estimates into a soil water balance model using a series of synthetic twin data assimilation experiments conducted at the USDA Optimizing Production Inputs for Economic and Environmental Enhancements (OPE3) site. Results from these experiments illustrate that, relative to a baseline case of assimilating only surface soil moisture retrievals, the assimilation of both root- and surface-zone soil moisture estimates reduces the root-mean-square difference between estimated and true root-zone soil moisture by 50% to 35% (assuming instantaneous root-zone soil moisture retrievals are obtained at an accuracy of between 0.020 and 0.030 m3 m−3). Most significantly, improvements in root-zone soil moisture accuracy are seen even for cases in which root-zone soil moisture retrievals are assumed to be relatively inaccurate (i.e. retrievals errors of up to 0.070 m3 m−3) or limited to only very sparse sampling (i.e. one instantaneous measurement every eight days). Preliminary real data results demonstrate a clear increase in the R2 correlation coefficient with ground-based root-zone observations (from 0.51 to 0.73) upon assimilation of actual surface soil moisture and tower-based thermal infrared temperature observations made at the OPE3 study site.  相似文献   

15.
Upgrading agriculture in semi-arid areas and ensuring its sustainability require an optimal management of rainfall partition between blue and green waters in the farmed water harvesting catchment. The main objective of this study is to analyze the influence of heterogeneous land use on the spatial and temporal variation of rainfall partitioning and blue water production within a typical farmed catchment located in north-eastern Tunisia. The catchment has an area of 2.6 km2 and comprises at its outlet a dam, which retains the runoff water in a reservoir. Overland flow and soil water balance components were monitored during two cropping seasons (2000/2001 and 2001/2002) on a network of eleven plots of 2 m2 each with different land use and soil characteristics. The hydrological balances of both the catchment and reservoir have been monitored since 1994.Observed data showed a very large temporal and spatial variability of overland flow within the catchment reflecting the great importance of total rainfall as well as land use. During the 2001/2002 season the results showed a large variation of the number of observed runoff events, from 27 to 39, and of the annual overland flow depths, from 8 mm (under vineyard on calcaric cambisols) up to 43 mm (under shrubs-pasture on haplic regosols), between the plots. The annual runoff amounts were moderate; they always corresponded to less than 15% of the annual rainfall amount whatever the observation scale. It was also observed that changes in land use in years with similar rainfall could lead to significant differences in blue water flow. An attempt for predicting the overland flow by the general linear regression approach showed an r2 of 31%, the predictors used are the class of soil infiltration capacity, the initial moisture saturation ratio of the soil surface layer and the total rainfall amounts.These experimental results indicate that the variation in land use in a semi-arid catchment is a main factor of variation in soil surface conditions and explain the major role played by the former on hydrological behavior of the upstream area and on rainfall partition between overland flow and infiltration. Therefore, to predict the water harvesting capacities in terms of blue water production of a farmed catchment in semi-arid areas it seems essential to consider precisely its land use and its temporal evolution related to management practices.  相似文献   

16.
ABSTRACT

This work aimed to evaluate the capability of modelled vs in situ soil moisture observations in the northwest of Spain for a period of four years (2010–2013) in order to validate the SMOS L2 product. Comparisons were performed for a set of representative stations of the Soil Moisture Measurement Stations network of the University of Salamanca (REMEDHUS) at both point and area scales. The SMOS series showed good correlation with the modelled series, better than that obtained with the in situ observations (0.77 vs 0.68 average correlation coefficients). However, some underestimation or overestimation of the SMOS series, related to the soil characteristics, was observed with respect to both the in situ and the modelled series. The SMOS data normalization produced a notable improvement in the results, highlighting the capability of the modelled data to validate the SMOS soil moisture series. This research provides a solid foundation for the future validation of SMOS at large scales, overcoming the spatial representativeness issues arising from the use of in situ point measurements.
Editor M.C. Acreman; Associate editor N. Verhoest  相似文献   

17.
Soil moisture data, obtained from four AmeriFlux sites in the US, were examined using an ecohydrological framework. Sites were selected for the analysis to provide a range of plant functional type, climate, soil particle size distribution, and time series of data spanning a minimum of two growing seasons. Soil moisture trends revealed the importance of measuring water content at several depths throughout the rooting zone; soil moisture at the surface (0–10 cm) was approximately 20–30% less than that at 50–60 cm. A modified soil moisture dynamics model was used to generate soil moisture probability density functions at each site. Model calibration results demonstrated that the commonly used soil matric potential values for finding the vegetation stress point and field content may not be appropriate, particularly for vegetation adapted to a water-controlled environment. Projections of future soil moisture patterns suggest that two of the four sites will become severely stressed by climate change induced alterations to the precipitation regime.  相似文献   

18.
Soil moisture has been widely recognized as a key variable in hydro-meteorological processes and plays an important role in hydrological modelling. Remote sensing techniques have improved the availability of soil moisture data, however, most previous studies have only focused on the evaluation of retrieved data against point-based observations using only one overpass (i.e., the ascending orbit). Recently, the global Level-3 soil moisture dataset generated from Soil Moisture and Ocean Salinity (SMOS) observations was released by the Barcelona Expert Center. To address the aforementioned issues, this study is particularly focused on a basin scale evaluation in which the soil moisture deficit is derived from a three-layer Xinanjiang model used as a hydrological benchmark for all comparisons. In addition, both ascending and descending overpasses were analyzed for a more comprehensive comparison. It was interesting to find that the SMOS soil moisture accuracy did not improve with time as we would have expected. Furthermore, none of the overpasses provided reliable soil moisture estimates during the frozen season, especially for the ascending orbit. When frozen periods were removed, both overpasses showed significant improvements (i.e., the correlations increased from r = −0.53 to r = −0.65 and from r = −0.62 to r = −0.70 for the ascending and descending overpasses, respectively). In addition, it was noted that the SMOS retrievals from the descending overpass consistently were approximately 11.7% wetter than the ascending retrievals by volume. The overall assessment demonstrated that the descending orbit outperformed the ascending orbit, which was unexpected and enriched our knowledge in this area. Finally, the potential reasons were discussed.  相似文献   

19.
Lu Zhuo  Dawei Han 《水文研究》2016,30(10):1637-1648
Soil moisture is a significant state variable in flood forecasting. Nowadays more and more satellite soil moisture products are available, yet their usage in the operational hydrology is still limited. This is because the soil moisture state variables in most operational hydrological models (mostly conceptual models) are over‐simplified—resulting in poor compatibility with the satellite soil moisture observations. A case study is provided to discuss this in more detail, with the adoption of the XAJ model and the Soil Moisture and Ocean Salinity (SMOS) level‐3 soil moisture observation to illustrate the relevant issues. It is found that there are three distinct deficiencies existed in the XAJ model that could cause the mismatch issues with the SMOS soil moisture observation: (i) it is based on runoff generation via the field capacity excess mechanism (interestingly, such a runoff mechanism is called the saturation excess in XAJ while in fact it is clearly a misnomer); (ii) evaporation occurs at the potential rate in its upper soil layer until the water storage in the upper layer is exhausted, and then the evapotranspiration process from the lower layers will commence – leading to an abrupt soil water depletion in the upper soil layer; (iii) it uses the multi‐bucket concept at each soil layer – hence the model has varied soil layers. Therefore, it is a huge challenge to make an operational hydrological model compatible with the satellite soil moisture data. The paper argues that this is possible and some new ideas have been explored and discussed. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   

20.
Within the scope of the upcoming launch of a new water related satellite mission (SMOS) a global evaluation study was performed on two available global soil moisture products. ERS scatterometer surface wetness data was compared to AMSR-E soil moisture data. This study pointed out a strong similarity between both products in sparse to moderate vegetated regions with an average correlation coefficient of 0.83. Low correlations were found in densely vegetated areas and deserts. The low values in the vegetated regions can be explained by the limited soil moisture retrieval capabilities over dense vegetation covers. Soil emission is attenuated by the canopy and tends to saturate the microwave signal with increasing vegetation density, resulting in a decreased sensor sensitivity to soil moisture variations. It is expected that the new low frequency satellite mission (SMOS) will obtain soil moisture products with a higher quality in these regions. The low correlations in the desert regions are likely due to volume scattering or to the dielectric dynamics within the soil. The volume scattering in dry soils causes a higher backscatter under very dry conditions than under conditions when the sub-surface soil layers are somewhat wet. In addition, at low moisture levels the dielectric constant has a reduced sensitivity in response to changes in the soil moisture content. At a global scale the spatial correspondence of both products is high and both products clearly distinguish similar regions with high seasonal and inter annual variations. Based on the global analyses we concluded that the quality of both products was comparable and in the sparse to moderate vegetated regions both products may be beneficial for large scale validation of SMOS soil moisture. Some limitations of the studied products are different, pointing to significant potential for combining both products into one superior soil moisture data set.  相似文献   

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