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1.
A statistically based runoff‐yield model is proposed in this paper. The model considers spatial heterogeneities of rainfall, soil infiltration capacity and soil water storage capacity that are main factors controlling runoff‐yield process. It assumes that the spatial variation of rainfall intensity at each time step can be characterized by a probability density function, which is estimated by matching the hyetograph through goodness‐of‐fit measure, whereas the spatial heterogeneities of soil infiltration capacity and soil water storage capacity are described by parabola‐type functions. Surface runoff is calculated according to infiltration excess mechanism; the statistical distribution of surface runoff rate can be deduced with the joint distribution of rainfall intensity and soil infiltration rate, thus obtaining a quasi‐analytical solution for surface runoff. Based on saturation excess mechanism, the groundwater flow (flows below the ground are collectively referred to as groundwater flow) is calculated by infiltration and the probability distribution of soil water storage capacity. Consequently, the total runoff is composed of infiltration excess and saturation excess runoff components. As an example, this model is applied to flood event simulation in Dongwan catchment, a semi‐humid region and a tributary of Yellow River in China. It indicates that the proposed runoff‐yield model could achieve acceptable accuracy. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

2.
A 40 m × 20 m mowed, grass hillslope adjacent to a headwater stream within a 26‐ha watershed in east‐central Pennsylvania, USA, was instrumented to identify and map the extent and dynamics of surface saturation (areas with the water table at the surface) and surface runoff source areas. Rainfall, stream flow and surface runoff from the hillslope were recorded at 5‐min intervals from 11 August to 22 November 1998, and 13 April to 12 November 1999. The dynamics of the water table (0 to 45 cm depth from the soil surface) and the occurrence of surface runoff source areas across the hillslope were recorded using specially designed subsurface saturation and surface runoff sensors, respectively. Detailed data analyses for two rainfall events that occurred in August (57·7 mm in 150 min) and September (83·6 mm in 1265 min) 1999, illustrated the spatial and temporal dynamics of surface saturation and surface runoff source areas. Temporal data analyses showed the necessity to measure the hillslope dynamics at time intervals comparable to that of rainfall measurements. Both infiltration excess surface runoff (runoff caused when rainfall intensity exceeds soil infiltration capacity) and saturation excess surface runoff (runoff caused when soil moisture storage capacity is exceeded) source areas were recorded during these rainfall events. The August rainfall event was primarily an infiltration excess surface runoff event, whereas the September rainfall event produced both infiltration excess and saturation excess surface runoff. Occurrence and disappearance of infiltration excess surface runoff source areas during the rainfall events appeared scattered across the hillslope. Analysis of surface saturation and surface runoff data showed that not all surface saturation areas produced surface runoff that reached the stream. Emergence of subsurface flow to the surface during the post‐rainfall periods appeared to be a major flow process dominating the hillslope after the August rainfall event. Copyright © 2002 John Wiley & Sons, Ltd.  相似文献   

3.
This study first explores the role of spatial heterogeneity, in both the saturated hydraulic conductivity Ks and rainfall intensity r, on the integrated hydrological response of a natural slope. On this basis, a mathematical model for estimating the expected areal‐average infiltration is then formulated. Both Ks and r are considered as random variables with assessed probability density functions. The model relies upon a semi‐analytical component, which describes the directly infiltrated rainfall, and an empirical component, which accounts further for the infiltration of surface water running downslope into pervious soils (the run‐on effect). Monte Carlo simulations over a clay loam soil and a sandy loam soil were performed for constructing the ensemble averages of field‐scale infiltration used for model validation. The model produced very accurate estimates of the expected field‐scale infiltration rate, as well as of the outflow generated by significant rainfall events. Furthermore, the two model components were found to interact appropriately for different weights of the two infiltration mechanisms involved. Copyright © 2005 John Wiley & Sons, Ltd.  相似文献   

4.
Soil surface crusts are widely reported to favour Hortonian runoff, but are not explicitly represented in most rainfall‐runoff models. The aim of this paper is to assess the impact of soil surface crusts on infiltration and runoff modelling at two spatial scales, i.e. the local scale and the plot scale. At the local scale, two separate single ring infiltration experiments are undertaken. The first is performed on the undisturbed soil, whereas the second is done after removal of the soil surface crust. The HYDRUS 2D two‐dimensional vertical infiltration model is then used in an inverse modelling approach, first to estimate the soil hydraulic properties of the crust and the subsoil, and then the effective hydraulic properties of the soil represented as a single uniform layer. The results show that the crust hydraulic conductivity is 10 times lower than that of the subsoil, thus illustrating the limiting role the crust has on infiltration. Moving up to the plot scale, a rainfall‐runoff model coupling the Richards equation to a transfer function is used to simulate Hortonian overland flow hydrographs. The previously calculated hydraulic properties are used, and a comparison is undertaken between a single‐layer and a double‐layer representation of the crusted soil. The results of the rainfall‐runoff model show that the soil hydraulic properties calculated at the local scale give acceptable results when used to model runoff at the plot scale directly, without any numerical calibration. Also, at the plot scale, no clear improvement of the results can be seen when using a double‐layer representation of the soil in comparison with a single homogeneous layer. This is due to the hydrological characteristics of Hortonian runoff, which is triggered by a rainfall intensity exceeding the saturated hydraulic conductivity of the soil surface. Consequently, the rainfall‐runoff model is more sensitive to rainfall than to the subsoil's hydrodynamic properties. Therefore, the use of a double‐layer soil model to represent runoff on a crusted soil does not seem necessary, as the increase of precision in the soil discretization is not justified by a better performance of the model. Copyright © 2005 John Wiley & Sons, Ltd.  相似文献   

5.
This paper investigates the effect of introducing spatially varying rainfall fields to a hydrological model simulating runoff and erosion. Pairs of model simulations were run using either spatially uniform (i.e. spatially averaged) or spatially varying rainfall fields on a 500‐m grid. The hydrological model used was a simplified version of Thales which enabled runoff generation processes to be isolated from hillslope averaging processes. Both saturation excess and infiltration excess generation mechanisms were considered, as simplifications of actual hillslope processes. A 5‐year average recurrence interval synthetic rainfall event typical of temperate climates (Melbourne, Australia) was used. The erosion model was based on the WEPP interrill equation, modified to allow nonlinear terms relating the erosion rate to rainfall or runoff‐squared. The model results were extracted at different scales to investigate whether the effects of spatially varying rainfall were scale dependent. A series of statistical metrics were developed to assess the variability due to introducing the spatially varying rainfall field. At the catchment (approximately 150 km2) scale, it was found that particularly for saturation excess runoff, model predictions of runoff were insensitive to the spatial resolution of the rainfall data. Generally, erosion processes at smaller sub‐catchment scales, particularly when the sediment generation equation had non linearity, were more sensitive to spatial rainfall variability. Introducing runon infiltration reduced the total runoff and sediment yield at all scales, and this process was also most sensitive to the rainfall resolution. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

6.
Excessive application of poultry litter to pastures in the Sand Mountain region of north Alabama has resulted in phosphorus (P) contamination of surface water bodies and buildup of P in soils of this region. Since surface runoff is recognized as the primary mechanism of P transport, understanding surface runoff generation mechanisms are crucial for alleviating water quality problems in this region. Identification of surface runoff generation mechanisms is also important for delineation of hydrologically active areas (HAAs). Therefore, the specific objective of this study was to identify surface runoff generation mechanisms (infiltration excess versus saturation excess) using distributed surface and subsurface sensors and rain gauge. Results from three rainfall events (2·13–3·43 cm) of differing characteristics, and sensor data at four locations with differing soil hydraulic properties along the hillslope showed that the main surface runoff generation mechanism in this region is infiltration excess. Because of this, rainfall intensity and soil hydraulic conductivity were found to play dominant roles in surface runoff generation in this region. Further, only short periods of a few rainfall events during which the rainfall intensity is high produce surface runoff. This study indicates that perhaps subsurface flows and transport of P in subsurface flows need to be quantified to reduce P contamination of surface water bodies in this region. Current studies at this location are identifying spatial and temporal distribution of HAAs, quantifying rainfall characteristics that generate runoff, and estimating runoff volume that results from connected HAAs. Copyright © 2008 John Wiley & Sons, Ltd.  相似文献   

7.
The paper focusses on connectivity in the context of infiltration‐excess overland flow and its integrated response as slope‐base overland flow hydrographs. Overland flow is simulated on a sloping surface with some minor topographic expression and spatially differing infiltration rates. In each cell of a 128 × 128 grid, water from upslope is combined with incident rainfall to generate local overland flow, which is stochastically routed downslope, partitioning the flow between downslope neighbours. Simulations show the evolution of connectivity during simple storms. As a first approximation, total storm runoff is similar everywhere, discharge increasing proportionally with drainage area. Moderate differences in plan topography appear to have only a second‐order impact on hydrograph form and runoff amount. Total storm response is expressed as total runoff, runoff coefficient or total volume infiltrated; each plotted against total storm rainfall, and allowing variations in average gradient, overland flow roughness, infiltration rate and storm duration. A one‐parameter algebraic expression is proposed that fits simulation results for total runoff, has appropriate asymptotic behaviour and responds rationally to the variables tested. Slope length is seen to influence connectivity, expressed as a scale distance that increases with storm magnitude and can be explicitly incorporated into the expression to indicate runoff response to simple events as a function of storm size, storm duration, slope length and gradient. The model has also been applied to a 10‐year rainfall record, using both hourly and daily time steps, and the implications explored for coarser scale models. Initial trails incorporating erosion continuously update topography and suggest that successive storms produce an initial increase in erosion as rilling develops, while runoff totals are only slightly modified. Other factors not yet considered include the dynamics of soil crusting and vegetation growth. Copyright © 2014 John Wiley & Sons, Ltd.  相似文献   

8.
The Soil Conservation Service Curve Number (SCS‐CN) method is a popular rainfall–runoff model that is widely used to estimate direct runoff from small and ungauged basins. The SCS‐CN is a simple and valuable approach to quantify the total streamflow volume generated by storm rainfall, but its use is not appropriate for estimating the sub‐daily incremental rainfall excess. To overcome this drawback, we propose to include the Green‐Ampt (GA) infiltration model into a mixed procedure, which is referred to as Curve Number for Green‐Ampt (CN4GA), aiming to distribute in time the information provided by the SCS‐CN method. For a given storm, the computed SCS‐CN total net rainfall amount is employed to calibrate the soil hydraulic conductivity parameter of the GA model. The proposed procedure is evaluated by analysing 100 rainfall–runoff events that were observed in four small catchments of varying size. CN4GA appears to provide encouraging results for predicting the net rainfall peak and duration values and has shown, at least for the test cases considered in this study, better agreement with the observed hydrographs than the classic SCS‐CN method. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

9.
In semi‐arid areas, high‐intensity rainfall events are often held responsible for the main part of soil erosion. Long‐term landscape evolution models usually use average annual rainfall as input, making the evaluation of single events impossible. Event‐based soil erosion models are better suited for this purpose but cannot be used to simulate longer timescales and are usually applied to plots or small catchments. In this study, the openLISEM event‐based erosion model was applied to the medium‐sized (～50 km2) Prado catchment in SE Spain. Our aim was to (i) test the model's performance for medium‐sized catchments, (ii) test the ability to simulate four selected typical Mediterranean rainfall events of different magnitude and (iii) explore the relative contribution of these different storms to soil erosion using scenarios of future climate variability. Results show that because of large differences in the hydrologic response between storms of different magnitudes, each event needed to be calibrated separately. The relation between rainfall event characteristics and the calibration factors might help in determining optimal calibration values if event characteristics are known. Calibration of the model features some drawbacks for large catchments due to spatial variability in Ksat values. Scenario calculations show that although ～50% of soil erosion occurs as a result of high frequency, low‐intensity rainfall events, large‐magnitude, low‐frequency events potentially contribute significantly to total soil erosion. The results illustrate the need to incorporate temporal variability in rainfall magnitude–frequency distributions in landscape evolution models. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

10.
This paper focuses on the problem of quantifying real world catchment response using a distributed model and discusses the ability of the model to capture that response. The rainfall–runoff responses of seven small agricultural catchments in the eastern wheatbelt region of south-western Australia are examined. The variability in runoff generation and the factors that contribute to that variability (i.e. rainfall intensity, soil properties and topography) are investigated to determine if their influence can be captured in a mathematical model. The spatially distributed rainfall–runoff model used in this study is based on the TOPMODEL concepts of Beven and Kirkby (1979), and simulates runoff generation by both the infiltration excess and saturation excess mechanisms. Simulations with the model revealed the highly complex nature of catchment response to rainfall events. Runoff generation was highly heterogeneous in both space and time, with the runoff response being governed by the spatial variability of soil properties and topography, and by the temporal variation in rainfall intensity. Although the model proved capable of simulating catchment response for many events, the investigation has demonstrated that not all aspects of the variability associated with agricultural catchments (particularly the effects of land management) can be captured using this relatively simple model. © 1997 by John Wiley & Sons, Ltd  相似文献   

11.
Abstract

A relatively simple process-oriented, physically-based distributed (PBD) hydrological model, the distributed runoff and erosion assessment model (DREAM), is described, and a validation study conducted in the semi-forested watershed of Pathri Rao, in the Garhwal Himalayas, India, is reported. DREAM takes account of watershed heterogeneity as reflected by land use, soil type, topography and rainfall, measured in the field or estimated through remote sensing, and generates estimates of runoff and sediment yield in spatial and temporal domains. The model is based on simultaneous solution of flow dynamics, based on kinematic wave theory, followed by solution of soil erosion dynamics. As the storm rainfall proceeds, the process of overland flow generation is dependent on the interception storage and infiltration rates. The components of the soil erosion model have been modified to provide better prediction of sediment flow rates and sediment yields. The validation study conducted to test the performance of the model in simulating soil erosion and sediment yield during different storm events monitored in the study watershed showed that the model outputs are satisfactory. Details of a sensitivity analysis, model calibration and the statistical evaluation of the results obtained are also presented and discussed. It is noteworthy that the distributed nature of the model combined with the use of geographical information system (GIS) techniques permits the computation and representation of the spatial distribution of sediment yield for simulated storm events, and a map of the spatial distribution of sediment yield for a simulated storm event is presented to highlight this capability.

Citation Ramsankaran, R., Kothyari, U.C., Ghosh, S.K., Malcherek, A., and Murugesan, K., 2013. Physically-based distributed soil erosion and sediment yield model (DREAM) for simulating individual storm events. Hydrological Sciences Journal, 58 (4), 872–891.  相似文献   

12.
Uncontrolled overland flow drives flooding, erosion, and contaminant transport, with the severity of these outcomes often amplified in urban areas. In pervious media such as urban soils, overland flow is initiated via either infiltration‐excess (where precipitation rate exceeds infiltration capacity) or saturation‐excess (when precipitation volume exceeds soil profile storage) mechanisms. These processes call for different management strategies, making it important for municipalities to discern between them. In this study, we derived a generalized one‐dimensional model that distinguishes between infiltration‐excess overland flow (IEOF) and saturation‐excess overland flow (SEOF) using Green–Ampt infiltration concepts. Next, we applied this model to estimate overland flow generation from pervious areas in 11 U.S. cities. We used rainfall forcing that represented low‐ and high‐intensity events and compared responses among measured urban versus predevelopment reference soil hydraulic properties. The derivation showed that the propensity for IEOF versus SEOF is related to the equivalence between two nondimensional ratios: (a) precipitation rate to depth‐weighted hydraulic conductivity and (b) depth of soil profile restrictive layer to soil capillary potential. Across all cities, reference soil profiles were associated with greater IEOF for the high‐intensity set of storms, and urbanized soil profiles tended towards production of SEOF during the lower intensity set of storms. Urban soils produced more cumulative overland flow as a fraction of cumulative precipitation than did reference soils, particularly under conditions associated with SEOF. These results will assist cities in identifying the type and extent of interventions needed to manage storm water produced from pervious areas.  相似文献   

13.
A procedure combining the Soil Conservation Service‐Curve Number (SCS‐CN) method and the Green–Ampt (GA) infiltration equation was recently developed to overcome some of the drawbacks of the classic SCS‐CN approach when estimating the volume of surface runoff at a sub‐daily time resolution. The rationale of this mixed procedure, named Curve Number for Green–Ampt (CN4GA), is to use the GA infiltration model to distribute the total volume of the net hyetograph (rainfall excess) provided by the SCS‐CN method over time. The initial abstraction and the total volume of rainfall given by the SCS‐CN method are used to identify the ponding time and to quantify the hydraulic conductivity parameter of the GA equation. In this paper, a sensitivity analysis of the mixed CN4GA parameters is presented with the aim to identify conditions where the mixed procedure can be effectively used within the Prediction in Ungauged Basin perspective. The effects exerted by changes in selected input parameters on the outputs are evaluated using rectangular and triangular synthetic hyetographs as well as 100 maximum annual storms selected from synthetic rainfall time series. When applied to extreme precipitation events, which are characterized by predominant peaks of rainfall, the CN4GA appears to be rather insensitive to the input hydraulic parameters of the soil, which is an interesting feature of the CN4GA approach and makes it an ideal candidate for the rainfall excess estimation at sub‐daily temporal resolution at ungauged sites. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

14.
Concerns for microbial safety of surface water facilitate development of predictive models that estimate concentrations and total numbers of pathogen and indicator organisms leaving manure‐fertilized fields in overland flow during runoff events. Spatial variability of bacterial concentrations in applied manure introduces high uncertainty in the model predictions. The objective of this work was to evaluate the uncertainty in model predictions of the manure‐borne bacteria overland transport caused by limited information on the spatial distribution of bacteria in surface‐applied manure. Experiments were carried out at the ARS Beltsville experimental watershed site (OPE3) in Maryland. Dairy bovine manure was applied at a 59·3 t/ha rate on the 3·55 hectare experimental field. Faecal coliform (FC) concentrations in manure measured in 2004, 2005, 2007, and 2009 varied by 4 orders of magnitude each year. Both runoff volume and FC concentrations in runoff water were monitored using a runoff flume equipped with a refrigerated pump sampler. Two runoff events occurred before the manure was incorporated into the soil. A bacteria transport add‐on module simulator of transport with infiltration and runoff (STWIR) was linked with the event‐based kinematic runoff and erosion model (KINEROS2) to simulate convective‐dispersive overland transport, bacteria release from manure, reversible attachment–detachment to soil, and surface straining of infiltrating bacteria. The model was successfully calibrated with the field experiment data. Monte Carlo simulations were carried out to account for the spatial variation in FC in applied manure and uncertainty in the FC distribution in manure caused by the small number of samples. A tenfold and twofold variation in FC concentrations in the runoff were obtained within the 90% probability interval when initial FC spatial distributions in the manure were represented by 5 and 29 samples, respectively. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

15.
The Tabernas desert, an extensive badlands area in Almeria province (south‐east Spain), is characterized by a high variability in soil surface cover and soil properties along with important topographical contrasts giving rise to a wide range of hydrological behaviour. A double approach through field monitoring and modelling has been used to ascertain the influence of soil‐surface variability on the overall hydrological response. Small plots were monitored for 3 years to assess runoff from the different surface types. Data provided by the long‐term monitoring of three small catchments formed by different soil surfaces were used to find out the specific contribution of each soil surface to the catchment runoff. A simple spatially distributed model was built to predict runoff generation based on the infiltration rate of each soil‐surface type (defined as terrain units with the same cover, the same soil type and on the same landform). Plot results prove that the soil surface units within the study area behave differently in terms of hydrological response to natural rainfall. These responses are explained by the types of cover, topographical characteristics and soil properties. When runoff events are simple (with one or two runoff peaks), the modelled hydrographs reproduce the hydrographs observed reasonably well, but in complex events (with several runoff peaks) the adjustment is not as good. The model also shows the influence of the spatial distribution of soil surfaces on the overall runoff, aiding exploration of the spatial hydrological relationships among different landscape units. Copyright © 2002 John Wiley & Sons, Ltd.  相似文献   

16.
Infiltration into frozen soil is a key hydrological process in cold regions. Although the mechanisms behind point‐scale infiltration into frozen soil are relatively well understood, questions remain about upscaling point‐scale results to estimate hillslope‐scale run‐off generation. Here, we tackle this question by combining laboratory, field, and modelling experiments. Six large (0.30‐m diameter by 0.35‐m deep) soil cores were extracted from an experimental hillslope on the Canadian Prairies. In the laboratory, we measured run‐off and infiltration rates of the cores for two antecedent moisture conditions under snowmelt rates and diurnal freeze–thaw conditions observed on the same hillslope. We combined the infiltration data with spatially variable data from the hillslope, to parameterise a surface run‐off redistribution model. We used the model to determine how spatial patterns of soil water content, snowpack water equivalent (SWE), and snowmelt rates affect the spatial variability of infiltration and hydrological connectivity over frozen soil. Our experiments showed that antecedent moisture conditions of the frozen soil affected infiltration rates by limiting the initial soil storage capacity and infiltration front penetration depth. However, shallow depths of infiltration and refreezing created saturated conditions at the surface for dry and wet antecedent conditions, resulting in similar final infiltration rates (0.3 mm hr?1). On the hillslope‐scale, the spatial variability of snowmelt rates controlled the development of hydrological connectivity during the 2014 spring melt, whereas SWE and antecedent soil moisture were unimportant. Geostatistical analysis showed that this was because SWE variability and antecedent moisture variability occurred at distances shorter than that of topographic variability, whereas melt variability occurred at distances longer than that of topographic variability. The importance of spatial controls will shift for differing locations and winter conditions. Overall, our results suggest that run‐off connectivity is determined by (a) a pre‐fill phase, during which a thin surface soil layer wets up, refreezes, and saturates, before infiltration excess run‐off is generated and (b) a subsequent fill‐and‐spill phase on the surface that drives hillslope‐scale run‐off.  相似文献   

17.
The surface susceptibility to erosion (erodibility) is an important component of soil erosion models. Many studies of wind erosion have shown that even relatively small changes in surface conditions can have a considerable effect on the temporal and spatial variability of dust emissions. One of the main difficulties in measuring erodibility is that it is controlled by a number of highly variable soil factors. Collection of these data is often limited in scale because in situ measurements are labour‐intensive and very time‐consuming. To improve wind erosion model predictions over several spatial and temporal scales simultaneously, there is a requirement for a non‐invasive approach that can be used to rapidly assess changes in the compositional and structural nature of a soil surface in time and space. Spectral reflectance of the soil surface appears to meet these desirable requirements and it is controlled by properties that affect the soil erodibility. Three soil surfaces were modified using rainfall simulation and wind tunnel abrasion experiments. Observations of those changes were made and recorded using digital images and on‐nadir spectral reflectance. The results showed clear evidence of the information content in the spectral domain that was otherwise difficult to interpret given the complicated interrelationships between soil composition and structure. Changes detected at the soil surface included the presence of a crust produced by rainsplash, the production of loose erodible material covering a rain crust and the selective erosion of the soil surface. The effect of rainsplash and aeolian abrasion was different for each soil tested and crust abrasion was shown to decrease as rainfall intensity increased. The relative contributions of the eroded material from each soil surface to trapped mixtures of material assisted the erodibility assessment. Ordination analyses within each of two important soil types explained significant amounts of the variation in the reflectance of all wavebands by treatments of the soil and hence changes in the soil surface. The results show that soil surface conditions within a soil type are an underestimated source of variation in the characterization of soil surface erodibility and in the remote sensing of soil. Copyright © 2005 John Wiley & Sons, Ltd.  相似文献   

18.
In order to harvest runoff to palliate water disaster as well as effectively manage irrigation and fertilizer application in the studied region, it is necessary to better understand the runoff processes. A newly designed runoff collection system for a plot scale was used to partition runoff under contrasting rainfall events into surface flow and subsurface flow to obtain characteristics of surface runoff and throughflow in a purple soil (Regosols in FAO taxonomy, Entisol in USDA taxonomy) of Sichuan, China. Under small rainfall (shower and drizzle), only surface runoff was observed. It is noted that, under shower, particularly with antecedent dry soil conditions, the highest peak surface runoff significantly lagged behind that of rainfall, because air‐locked soil pores of the top layer appeared temporally. Under rainstorm and downpour, surface runoff and throughflow both commenced and showed hysteresis. The hydrograph of surface runoff better resembled that of rainfall than throughflow did. The durations of throughflow discharge of post‐rainfall‐end were near the same (within 24 h) under various rainfalls and rather dependent upon the soil properties than the rainfall characteristics. Throughflow is about 60–90% of total runoff, and especially significant in a ploughed layer under downpour. The chloride concentration of throughflow was over twice that of surface runoff and rainfall, implying that throughflow contains more nutrients than surface runoff. Presumably, surface runoff was primarily governed by an infiltration‐excess or saturated excess‐infiltration mechanism under unsaturated or saturated soil conditions. Therefore, the management of water and fertilizer, and the harvesting of water flow in the ploughed soil layer, should be emphasized in this region. Copyright © 2005 John Wiley & Sons, Ltd.  相似文献   

19.
Understanding the dynamics of spatial and temporal variability of soil moisture at the regional scale and daily interval, respectively, has important implications for remote sensing calibration and validation missions as well as environmental modelling applications. The spatial and temporal variability of soil moisture was investigated in an agriculturally dominated region using an in‐situ soil moisture network located in central Saskatchewan, Canada. The study site evaluated three depths (5, 20, 50 cm) through 139 days producing a high spatial and temporal resolution data set, which were analysed using statistical and geostatistical means. Processes affecting standard deviation at the 5‐cm depth were different from the 20‐cm and 50‐cm depths. Deeper soil measurements were well correlated through the field season. Further analysis demonstrated that lag time to maximum correlation between soil depths increased through the field season. Temporal autocorrelation was approximately twice as long at depth compared to surface soil moisture as measured by the e‐folding frequency. Spatial correlation was highest under wet conditions caused by uniform rainfall events with low coefficient of variation. Overall soil moisture spatial and temporal variability was explained well by rainfall events and antecedent soil moisture conditions throughout the Kenaston soil moisture network. It is expected that the results of this study will support future remote sensing calibration and validation missions, data assimilation, as well as hydrologic model parameterization for use in agricultural regions. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   

20.
Soil moisture is a key process in the hydrological cycle. During ecological restoration of the Loess Plateau, soil moisture status has undergone important changes, and infiltration of soil moisture during precipitation events is a key link affecting water distribution. Our study aims to quantify the effects of vegetation cover, rainfall intensity and slope length on total infiltration and the spatial variation of water flow. Infiltration data from the upper, middle and lower slopes of a bare slope, a natural grassland and an artificial shrub grassland were obtained using a simulated rainfall experiment. The angle of the study slope was 15° and rainfall intensity was set at 60, 90, 120, 150, and 180 mm/hr. The effect these factors have on soil moisture infiltration was quantified using main effect analysis. Our results indicate that the average infiltration depth (ID) of a bare slope, a grassland slope and an artificial shrub grassland slope was 46.7–73.3, 60–80, and 60–93.3 cm, respectively, and average soil moisture storage increment was 3.5–5.7, 5.0–9.4, and 5.7–10.2 mm under different rainfall intensities, respectively. Heavy rainfall intensity and vegetation cover reduced the difference of soil infiltration in the 0–40 cm soil layer, and rainfall intensity increased surface infiltration differences on the bare slope, the grassland slope and the artificial shrub grassland slope. Infiltration was dominated by rainfall intensity, accounting for 63.03–88.92%. As rainfall continued, the contribution of rainfall intensity to infiltration gradually decreased, and the contribution of vegetation cover and slope length to infiltration increased. The interactive contribution was: rainfall intensity * vegetation cover > vegetation cover * slope length > rainfall * slope length. In the grass and shrub grass slopes, lateral flow was found at a depth of 23–37 cm when the slope length was 5–10 m, this being related to the difference in soil infiltration capacity between different soil layers formed by the spatial cross-connection of roots.  相似文献   

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