首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献,搜索用时 31 毫秒
1.
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   

2.
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   

3.
4.
Several rainfall measurement techniques are available for hydrological applications, each with its own spatial and temporal resolution and errors. When using these rainfall datasets as input for hydrological models, their errors and uncertainties propagate through the hydrological system. The aim of this study is to investigate the effect of differences between rainfall measurement techniques on groundwater and discharge simulations in a lowland catchment, the 6.5‐km2 Hupsel Brook experimental catchment. We used five distinct rainfall data sources: two automatic raingauges (one in the catchment and another one 30 km away), operational (real‐time and unadjusted) and gauge‐adjusted ground‐based C‐band weather radar datasets and finally a novel source of rainfall information for hydrological purposes, namely, microwave link data from a cellular telecommunication network. We used these data as input for the, a recently developed rainfall‐runoff model for lowland catchments, and intercompared the five simulated discharges time series and groundwater time series for a heavy rainfall event and a full year. Three types of rainfall errors were found to play an important role in the hydrological simulations, namely: (1) Biases, found in the unadjusted radar dataset, are amplified when propagated through the hydrological system; (2) Timing errors, found in the nearest automatic raingauge outside the catchment, are attenuated when propagated through the hydrological system; (3) Seasonally varying errors, found in the microwave link data, affect the dynamics of the simulated catchment water balance. We conclude that the hydrological potential of novel rainfall observation techniques should be assessed over a long period, preferably a full year or longer, rather than on an event basis, as is often done. Copyright © 2016 The Authors. Hydrological Processes. Published by John Wiley & Sons Ltd.  相似文献   

5.
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   

6.
The emergence of regional and global satellite‐based rainfall products with high spatial and temporal resolution has opened up new large‐scale hydrological applications in data‐sparse or ungauged catchments. Particularly, distributed hydrological models can benefit from the good spatial coverage and distributed nature of satellite‐based rainfall estimates (SRFE). In this study, five SRFEs with temporal resolution of 24 h and spatial resolution between 8 and 27 km have been evaluated through their predictive capability in a distributed hydrological model of the Senegal River basin in West Africa. The main advantage of this evaluation methodology is the integration of the rainfall model input in time and space when evaluated at the sub‐catchment scale. An initial data analysis revealed significant biases in the SRFE products and large variations in rainfall amounts between SRFEs, although the spatial patterns were similar. The results showed that the Climate Prediction Center/Famine Early Warning System (CPC‐FEWS) and cold cloud duration (CCD) products, which are partly based on rain gauge data and produced specifically for the African continent, performed better in the modelling context than the global SRFEs, Climate Prediction Center MORPHing technique (CMORPH), Tropical Rainfall Measuring Mission (TRMM) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN). The best performing SRFE, CPC‐FEWS, produced good results with values of R2NS between 0·84 and 0·87 after bias correction and model recalibration. This was comparable to model simulations based on traditional rain gauge data. The study highlights the need for input specific calibration of hydrological models, since major differences were observed in model performances even when all SRFEs were scaled to the same mean rainfall amounts. This is mainly attributed to differences in temporal dynamics between products. Copyright © 2009 John Wiley & Sons, Ltd.  相似文献   

7.
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   

8.
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   

9.
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   

10.
In this paper the temporal behaviour of soil moisture is modelled and statistically characterized by use of the zero‐dimensional model for soil moisture dynamics and the rectangular pulses Poisson process model for rainfall forcing. The mean, covariance and spectral density function of soil moisture (both instantaneous and locally averaged cases) are analytically derived to evaluate its sensitivity to the model parameters. Finally, the probability density function of soil moisture is derived to evaluate the effect of rainfall forcing. All the model parameters used have been tuned to the Monsoon '90 data. Results can be summarized as follows. (1) Only the soil moisture model parameters (η and nZr) are found to affect the autocorrelation function in a distinguishable manner. On the other hand, both the rainfall model parameter (θ) and the effective soil depth (nZr) are found to be of impact to the soil moisture spectrum. However, as the smoothing (or damping) effect of soil is so dominant, about ±20% variation of one parameter seems not to affect significantly the second‐order statistics of soil moisture. (2) More difference can be found by applying a longer averaging time, which is found to obviously decrease the variance but increase the correlation even though no overlapping between neighbouring soil moisture data was allowed. (3) Among rainfall model parameters, the arrival rate (λ) was found to be most important for the soil moisture evolution. When increasing the arrival rate of rainfall, the histogram of soil moisture shifts its peak to a certain value as well as becomes more concentrated around the peak. However, by decreasing the arrival rate of rainfall, a much smaller (almost to zero) mean value of soil moisture was estimated, even though the total volume of rainfall remained constant. This indicates that desertification may take place without decreasing the total volume of rainfall. Copyright © 2005 John Wiley & Sons, Ltd.  相似文献   

11.
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   

12.
Hydrological processes of lowland watersheds of the southern USA are not well understood compared to a hilly landscape due to their unique topography, soil compositions, and climate. This study describes the seasonal relationships between rainfall patterns and runoff (sum of storm flow and base flow) using 13 years (1964–1976) of rainfall and stream flow data for a low‐gradient, third‐order forested watershed. It was hypothesized that runoff–rainfall ratios (R/P) are smaller during the dry periods (summer and fall) and greater during the wet periods (winter and spring). We found a large seasonal variability in event R/P potentially due to differences in forest evapotranspiration that affected seasonal soil moisture conditions. Linear regression analysis results revealed a significant relationship between rainfall and runoff for wet (r2 = 0·68; p < 0·01) and dry (r2 = 0·19; p = 0·02) periods. Rainfall‐runoff relationships based on a 5‐day antecedent precipitation index (API) showed significant (r2 = 0·39; p < 0·01) correspondence for wet but not (r2 = 0·02; p = 0·56) for dry conditions. The same was true for rainfall‐runoff relationships based on 30‐day API (r2 = 0·39; p < 0·01 for wet and r2 = 0·00; p = 0·79 for dry). Stepwise regression analyses suggested that runoff was controlled mainly by rainfall amount and initial soil moisture conditions as represented by the initial flow rate of a storm event. Mean event R/P were higher for the wet period (R/P = 0·33), and the wet antecedent soil moisture condition based on 5‐day (R/P = 0·25) and 30‐day (R/P = 0·26) prior API than those for the dry period conditions. This study suggests that soil water status, i.e. antecedent soil moisture and groundwater table level, is important besides the rainfall to seasonal runoff generation in the coastal plain region with shallow soil argillic horizons. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

13.
The incidence of large rain events in Mediterranean ecosystems vary among years. Summer aridity is interpreted as a resetting event, eliminating previous soil‐moisture dynamics. The dynamics of soil moisture and retention are critical to tree survival, particularly in dry regions. This study examines the long‐term soil water content (θV) dynamics in two distinct locations within the forest, under the canopy and forest clearing, within two diverse oak forests: subhumid mixed oak forests (MG) and semiarid monospecific oak woodlands (YE). Plots were established at small‐scale catchments and soil water contents were measured during 2010–2013, at three depths in the two different locations. Cumulative rainfall was used as an independent proxy for θV analysis. A novel bell‐bilogistic mathematical model of wetting, saturation, and drying arms was developed. We aimed to study the θV distribution differences between soil profiles giving the large climatic gradient between the two forested sub basins, the differences in vegetation traits along with soil attributes. We further aimed at determining the role of an individual tree in regulating soil‐moisture dynamics. We hypothesized the occurrence of distinct responses between sites in all soil‐moisture indices with higher θV at the wetter site. We tested the hypothesis that seasonal cumulative rainfall dictates the variations in soil‐moisture regimes throughout contiguous years. Annual rainfall was higher than long‐term average throughout the study. Soil profiles under the canopies at both sites were consistently wetter. Infiltration and depletion constants were higher at MG whereas maximum soil moisture was higher at YE. Homogenous recharge patterns were seen at MG although YE evinced more variation. Oaks had no effect on recharge at MG compared with the forest clearing. Soil properties primarily affected the wetting arm whereas vegetation composition regulated the drying arm. Mixed‐stands characterized by ever‐green and deciduous species may maintain favourable soil‐moisture conditions, in comparison with other mixed stand morphologies. The increasing role of slacking forces in infiltration process may alter the interaction between trees and herbaceous vegetation.  相似文献   

14.
Upland agricultural land management activities such as grazing, vegetation burning, and bare ground restoration impact hydrological elements of headwater catchments, many of which may be important for downstream flood peaks (e.g., overland flow and soil water storage). However, there is poor understanding of how these management practices affect river flow peaks during high magnitude rainfall events. Using the distributed TOPMODEL, spatial configurations of land management were modelled to predict flood response in an upland catchment, which contains different regions operating subsidized agricultural stewardship schemes. Heavy grazing leading to soil compaction and loss of vegetation cover in stewardship regions covering 79.8% of the catchment gave a 42‐min earlier flow peak, which was 82.2% higher (under a 1‐hr 15‐mm storm) than the current simulated hydrograph. Light grazing over the same regions of the catchment had much less influence on river flow peaks (18 min earlier and 32.9% increase). Rotational burning (covering 8.8% of the catchment), most of which is located in the headwater areas, increased the peak by 3.2% in the same rainfall event. Vegetation restoration with either Eriophorum or Sphagnum (higher density) in bare areas (5.8%) of the catchment provided a reduction of flood peak (3.9% and 5.2% in the 15‐mm storm event), whereas the same total area revegetated with Sphagnum in riparian regions delivered a much larger decrease (15.0%) in river flow peaks. We show that changes of vegetation cover in highly sensitive areas (e.g., near‐stream zones) generate large impacts on flood peaks. Thus, it is possible to design spatially distributed management systems for upland catchments, which reduce flood peaks while at the same time ensuring economic viability for upland farmers.  相似文献   

15.
The aim of this study was to investigate rainfall–groundwater dynamics over space and annual time scales in a hard‐rock aquifer system of India by employing time series, geographic information system and geostatistical modelling techniques. Trends in 43‐year (1965–2007) annual rainfall time series of ten rainfall stations and 16‐year (1991–2006) pre‐monsoon and post‐monsoon groundwater levels of 140 sites were identified by using Mann–Kendall, Spearman rank order correlation and Kendall rank correlation tests. Trends were quantified by Kendall slope method. Furthermore, the study involves novelty of examining homogeneity of pre‐monsoon and post‐monsoon groundwater levels, for the first time, by applying seven tests. Regression analysis between rainfall and post‐monsoon groundwater levels was performed. The pre‐monsoon and post‐monsoon groundwater levels for four periods – 1991–1994, 1995–1998, 1999–2002 and 2003–2006 – were subjected to geographic information system‐based geostatistical modelling. The rainfall showed considerable spatiotemporal variations, with a declining trend at the Mavli rainfall station (p‐value < 0.05). The Levene's tests revealed spatial homogeneity of rainfall at α = 0.05. Regression analyses indicated significant relationships (r2 > 0.5) between groundwater level and rainfall for eight rainfall stations. Non‐homogeneity and declining trends in the groundwater level, attributed to anthropogenic and hydrologic factors, were found at 5–61 more sites in pre‐monsoon compared with post‐monsoon season. The groundwater declining rates in phyllite–schist, gneiss, schist and granite formations were found to be 0.18, 0.26, 0.21 and 0.14 m year?1 and 0.13, 0.19, 0.16 and 0.02 m year?1 during the pre‐monsoon and post‐monsoon seasons, respectively. The geostatistical analyses for four time periods revealed linkages between the rainfall and groundwater levels. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

16.
Water driven soil erosion is a major cause of land degradation worldwide. Ephemeral gullies (EGs) are considered key contributors to agricultural catchment soil loss. Despite their importance, the parameters and drivers controlling EG dynamics have not been adequately quantified. Here we investigate the effects of rainfall characteristics on EGs, using the physically based landform evolution model (LEM) CAESAR‐Lisflood. An initial goal of this study was to test the feasibility of using a LEM to estimate EG dynamics based on an easily obtainable and moderate spatial resolution (2 × 2 m) Digital Elevation Model (DEM). EG evolution was simulated for two rainfall seasons in a 0.37 km2 agricultural plot situated in a semiarid catchment in central Israel. The 2014 rainfall season was used to calibrate the model and the 2015 season was used for validation. The model overall well predicted the EG network structure and average depth but tended to underestimate the EG length. The effects of rainfall characteristics on EG dynamics were investigated by comparing simulations employing seven rainfall scenarios. Four of these scenarios differ in their overall rainfall volume relative to observed precipitation (+20%, +10%, ?10%, ?20%). The remaining three scenarios vary in the temporal distribution of rainfall during each storm, allowing us to isolate the effect of rainfall intensity on EG evolution. The results show that: (1) EG dynamics strongly correlated with changes in rainfall volume; (2) small‐scale morphological behavior varies between rainfall scenarios, resulting in different meandering and connectivity variability; (3) EG evolution is divided into two main stages, an initial rapid development occurring after the first two weeks of the rainy season, followed by a stable development period; (4) a 12 mm h?1 intensity threshold was observed to initiate and, later, modify EGs; and (5) inner storm rainfall variability can have a considerable effect on EG evolution. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   

17.
The Chinese Loess Plateau (CLP) is a unique Critical Zone with deep loess deposits, where soil moisture is primarily replenished by seasonal monsoon rainfall. However, the role of vegetation, coupled with complex topography, on rainwater infiltration on the CLP, especially after long‐term revegetation for controlling erosion, is inadequately quantified. Over the growing season of 2016, we monitored soil moisture at the 30‐min interval at 5 depths (10, 20, 40, 60, and 100 cm) in an afforested catchment and a nearby catchment with natural regrowth of grasses. Two monitoring sites were established in each catchment, one in the downhill gully and the other in the uphill slope. We found that vegetation, topography, and rainfall attributes together determined rainwater infiltration and soil moisture replenishment. An accumulated rainfall amount of 9 mm was required to trigger soil moisture response at 10‐cm depth at the 2 grassland sites and the forestland uphill‐slope site whereas 14 mm of rainfall was required for the forestland gully site covered by dense undergrowth and trees. Rainfall events with larger sums and higher peak intensities permitted rainwater infiltration to deeper soil depths. However, no rain recharged soil moisture to 100‐cm depth during the monitoring period. The forestland uphill‐slope site showed the deepest wetting depth (up to 60‐cm depth), fastest wetting‐front velocity (up to 4 cm/hr below 10‐cm depth), and the most significant soil moisture increase (up to 15% cm 3 cm?3 increase at 10‐cm depth) after rainfall in the growing season. The grassland gully site had the highest soil water storage, whereas soil moisture was depleted the most at the forestland gully site. Findings of this study reveal the transient dynamics of soil moisture after rainfall on the CLP, which signifies the role of revegetation on rainwater infiltration in the loess Critical Zone.  相似文献   

18.
Post‐wildfire runoff and erosion are major concerns in fire‐prone landscapes around the world, but these hydro‐geomorphic responses have been found to be highly variable and difficult to predict. Some variations have been observed to be associated with landscape aridity, which in turn can influence soil hydraulic properties. However, to date there has been no attempt to systematically evaluate the apparent relations between aridity and post‐wildfire runoff. In this study, five sites in a wildfire burnt area were instrumented with rainfall‐runoff plots across an aridity index (AI) gradient. Surface runoff and effective rainfall were measured over 10 months to allow investigation of short‐ (peak runoff) and longer‐term (runoff ratio) runoff characteristics over the recovery period. The results show a systematic and strong relation between aridity and post‐wildfire runoff. The average runoff ratio at the driest AI site (33.6%) was two orders of magnitude higher than at the wettest AI site (0.3%). Peak runoff also increased with AI, with up to a thousand‐fold difference observed during one event between the driest and wettest sites. The relation between AI, peak 15‐min runoff (Q15) and peak 15‐min rainfall intensity (I15) (both in mm h‐1) could be quantified by the equation: Q15 = 0.1086I15 × AI 2.691 (0.65<AI<1.80, 0<I15<45) (adjusted r2 = 0.84). The runoff ratios remained higher at drier AI sites (AI 1.24 and 1.80) throughout the monitoring period, suggesting higher AI also lengthens the window of disturbance after wildfire. The strong quantifiable link which this study has determined between AI and post‐wildfire surface runoff could greatly improve our capacity to predict the magnitude and location of hydro‐geomorphic processes such as flash floods and debris flows following wildfire, and may help explain aridity‐related patterns of soil properties in complex upland landscapes. Copyright © 2018 John Wiley & Sons, Ltd.  相似文献   

19.
The factors influencing soil erosion may vary with scale. It remains unclear whether the spatial variation in soil erosion resistance is controlled by regional variables (e.g. precipitation, temperature, and vegetation zone) or by local specific variables (e.g. soil properties, root traits, land use, and farming operations) when the study area enlarges from a hillslope or catchment to the regional scale. This study was performed to quantify the spatial variations in soil erosion resistance to flowing water under three typical land uses along a regional transect on the Loess Plateau and to identify whether regional or local specific variables are responsible for these changes. The results indicated that the measured soil detachment capacities (Dc) of cropland exhibited an irregular trend along the regional transect. The Dc of grassland increased with mean annual precipitation, except for two sites (Yijun and Erdos). The measured Dc of woodland displayed an inverted ‘U’ shape. The changes in rill erodibility (Kr) of three land uses were similar to Dc, whereas no distinguishable trend was found for critical shear stress (τc). No significant correlation was detected between Dc, Kr and τc, and the regional variables. The spatial variation in soil erosion resistance could be explained reasonably by changes in soil properties, root traits, land use, and farming operations, rather than regional variables. The adjustment coefficient of Kr for grassland and woodland could be well simulated by soil cohesion and root mass density (R2 = 0.70, P < 0.01), and the adjustment coefficient of critical shear stress could be estimated with aggregate stability (R2 = 0.57, P < 0.01). The results are helpful for quantifying the spatial variation in soil detachment processes by overland flow and to develop process‐based erosion model at a regional scale. Copyright © 2015 John Wiley & Sons, Ltd.  相似文献   

20.
In this paper, the controls of different indicators on the statistical moments (i.e. mean annual flood (MAF), coefficient of variation (CV) and skewness (CS)) of the maximum annual flood records of 459 Austrian catchments are analysed. The process controls are analysed in terms of the correlation of the flood moments within five hydrologically homogeneous regions to two different types of indicators. Indicators of the first type are static catchment attributes, which are associated with long‐term observations such as mean annual precipitation, the base flow index, and the percentage of catchment area covered by a geological unit or soil type. Indicators of the second type are dynamic catchment attributes that are associated with the event scale. Indicators of this type used in the study are event runoff coefficients and antecedent rainfall. The results indicate that MAF and CV are strongly correlated with indicators characterising the hydro‐climatic conditions of the catchments, such as mean annual precipitation, long‐term evaporation and the base flow index. For the catchments analysed, the flood moments are not significantly correlated with static catchment attributes representing runoff generation, such as geology, soil types, land use and the SCS curve number. Indicators of runoff generation that do have significant predictive power for flood moments are dynamic catchment attributes such as the mean event runoff coefficients and mean antecedent rainfall. The correlation analysis indicates that flood runoff is, on average, more strongly controlled by the catchment moisture state than by event rainfall. Copyright © 2008 John Wiley & Sons, Ltd.  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号