Identifying individual rain events from pluviograph records: a review with analysis of data from an Australian dryland site

Rainfall is routinely reported as falling in ‘events’ or ‘storms’ whose beginning and end are defined by rainless intervals of a nominated duration (minimum inter‐event time, MIT). Rain events commonly exhibit fluctuations in rain rate as well as periods when rain ceases altogether. Event characteristics such as depth, mean rain rate, and the surface runoff volume generated, are defined in relation to the length of the rain event. These derived properties are dependent upon the value of MIT adopted to define the event, and the literature reveals a wide range of MIT criteria. Surprisingly little attention has been paid to this dependency, which limits the inter‐comparison of results in published work. The diversity in criteria also diminishes the usefulness of historical data on event durations, rain rates, etc., in attempts to document changes in the rainfall climate. This paper reviews the range of approaches used in the recognition of rain events, and a 5 year pluviograph record from an arid location is analysed. Changing MIT from 15 min to 24 h (lying within the range of published criteria) alters the number of rain events from 550 to 118. The mean rain rate declines from 2·04 mm h^?1 to 0·94 mm h^?1, and the geometric mean event duration rises from 0·66 h to 3·98 h. This wide variation in the properties of rain events indicates that more attention needs to be paid to the selection and reporting of event criteria in studies that adopt event‐based data analysis. The selection of a MIT criterion is shown to involve a compromise between the independence of widely‐spaced events and their increasingly variable intra‐event characteristics. Copyright © 2008 John Wiley & Sons, Ltd.     

Spatial variability and interdependence of rain event characteristics in the Czech Republic

Rain event characteristics are assessed in a 10‐year (1991–2000) record for 122 stations in the Czech Republic. Individual rain events are identified using the minimum interevent time (mit) concept. For each station, the optimal mit value is estimated by examining the distribution of interevent times. In addition, various mit values are considered to account for the effect of mit on rain event characteristics and their interrelationships. The interdependence between rain event characteristics and altitude, average rainfall depth, and geographic location are explored using simple linear models. Most rain event characteristics can be to some extent explained by average total rainfall or altitude, although models including the former significantly outperformed models using the latter. Significant correlation was found among several pairs of monthly mean characteristics often including event rain rate (with event duration, depth, maximum intensity, and fraction of intraevent rainless periods). Moreover, strong correlation was revealed between number of events, interevent time, event depth, and duration. In general, correlation decreases in absolute value with mit. Strong spatial correlation was found for the mean monthly interevent time and number of events. Spatial correlation was considerably smaller for other characteristics. In general, spatial dependence was smaller for larger mit values. Copyright © 2013 John Wiley & Sons, Ltd.     

The identification of an appropriate Minimum Inter‐event Time (MIT) based on multifractal characterization of rainfall data series

Different hydrological models of sediment entrainment, infiltration, overland flow production, soil loss, landslide occurrence, among others, need rainfall events data. The Minimum Inter‐event Time (MIT) used to separate rainfall events affects their properties. Therefore, it is highly important their correct definition. Various event definitions are commonly used in hydrology, and a high variety of MIT is applied. In this work, an easy method is proposed for deciding the proper MIT in a certain place when dealing with hourly rainfall data series. This new methodology is based on the scale invariance properties of rainfall, analysed with both multifractal and Self‐Organized Criticality theories. The similarity between some parameters from both analyses allows picking out the more appropriate MIT for the hourly rainfall data sets analysed, in Malaga (Southern Spain) and Bullileo (Central Chile). The method can be applied for different rainfall time resolutions according to the purpose of the model that needs the rain event information. Copyright © 2016 John Wiley & Sons, Ltd.     

Rain event properties in nature and in rainfall simulation experiments: a comparative review with recommendations for increasingly systematic study and reporting

In hydrology and geomorphology, less attention has been paid to rain event properties such as duration, mean and peak rain rate than to rain properties such as drop size or kinetic energy. A literature review shows a lack of correspondence between natural and simulated rain events. For example, 26 studies that report event statistics from substantial records of natural rain reveal a mean rain rate of just 3·47 mm h^?1 (s.d. 2·38 mm h^?1). In 17 comparable studies dealing with extreme rain rates including events in cyclonic, tropical convective, and typhoon conditions, a mean maximum rain rate (either hourly or mean event rain rate) of 86·3 mm h^?1 (s.d. 57·7 mm h^?1) is demonstrated. However, 49 studies using rainfall simulation involve a mean maximum rain rate of 103·1 mm h^?1 (s.d. 81·3 mm h^?1), often sustained for > 1 h, exceeding even than of extreme rain events, and nearly 30 times the mean rain rate in ordinary, non‐exceptional, rain events. Thus rainfall simulation is often biased toward high rain rates, and many of the rates employed (in several instances exceeding 150 mm h^?1) appear to have limited relevance to ordinary field conditions. Generally, simulations should resemble natural rain events in each study region. Attention is also drawn to the raindrop arrival rate at the surface. In natural rain, this is known to vary from < 100 m^?2 s^?1 to > 5000 m^?2 s^?1. Arrival rate may need to be added to the list of parameters that must be reproduced realistically in rainfall simulation studies. Copyright © 2008 John Wiley & Sons, Ltd.     

Characteristics of rain events at an inland locality in northeastern Borneo,Malaysia

Understanding the intensity and duration of tropical rain events is critical to modelling the rate and timing of wet‐canopy evaporation, the suppression of transpiration, the generation of infiltration‐excess overland flow and hence to erosion, and to river responsiveness. Despite this central role, few studies have addressed the characteristics of equatorial rainstorms. This study analyses rainfall data for a 5 km² region largely comprising of the 4 km² Sapat Kalisun Experimental Catchment in the interior of northeastern Borneo at sampling frequencies from 1 min^?1 to 1 day^?1. The work clearly shows that most rainfall within this inland, forested area is received during regular short‐duration events (<15 min) that have a relatively low intensity (i.e. less than two 0·2 mm rain‐gauge tips in almost all 5 min periods). The rainfall appears localized, with significant losses in intergauge correlations being observable in minutes in the case of the typical mid‐afternoon, convective events. This suggests that a dense rain‐gauge network, sampled at a high temporal frequency, is required for accurate distributed rainfall‐runoff modelling of such small catchments. Observed rain‐event intensity is much less than the measured infiltration capacities, and thus supports the tenet of the dominance of quick subsurface responses in controlling river behaviour in this small equatorial catchment. Copyright © 2006 John Wiley & Sons, Ltd.     

Effects of rainfall intensity fluctuations on infiltration and runoff: rainfall simulation on dryland soils,Fowlers Gap,Australia

Small plots and a dripper rainfall simulator were used to explore the significance of the intensity fluctuations (‘event profile’) within simulated rainfall events on infiltration and runoff from bare, crusted dryland soils. Rainfall was applied at mean rain rates of 10 mm/h. Fourteen simulated rainfall events each involved more than 5000 changes of intensity and included multipeak events with a 25‐mm/h peak of intensity early in the event or late in the event and an event that included a temporary cessation of rain. These are all event profiles commonly seen in natural rain but rarely addressed in rainfall simulation. A rectangular event profile of constant intensity, as commonly used in rainfall simulation experiments, was also adopted for comparative purposes. Results demonstrate that event profile exerts an important effect on infiltration and runoff for these soils and rainfall event profiles. ‘Uniform’ events of unvarying intensity yielded the lowest total runoff, the lowest peak runoff rate and the lowest runoff ratio (0.13). These parameters increased for ‘early peak’ profiles (runoff ratio 0.24) and reached maxima for ‘late peak’ profiles (runoff ratio 0.50). Differences in runoff ratio and peak runoff rate between the ‘uniform’ event profile and those of varying intensity were all statistically significant at p ≤ 0.01. Compared with ‘uniform’ runs, the varying intensity runs yielded larger runoff ratios and peak runoff rates, exceeding those of the ‘uniform’ events by 85%–570%. These results suggest that for small‐plot studies of infiltration and erosion, the continued use of constant rainfall intensity simulations may be sacrificing important information and misrepresenting the mechanisms involved in runoff generation. The implications of these findings for the ecohydrology of the research site, an area of contour‐aligned banded vegetation in which runoff and runon are of critical importance, are highlighted. Copyright © 2011 John Wiley & Sons, Ltd.     

Stemflow production and intrastorm rainfall intensity variation: an experimental analysis using laboratory rainfall simulation

Laboratory rainfall simulation experiments using a small artificial olive tree are used to show that the fraction of rain falling at a constant intensity that becomes stemflow rises from 9% at 2.5 mm/h to 36.1% at 35 mm/h. Natural rainfall events commonly exhibit wide fluctuations of intensity. Simulated rainfall events each having a mean intensity of 10 mm/h, but containing short intensity peaks of 20 to 100 mm/h at varying intra‐event positions, were used to explore the effect of varying intensity profiles. Results demonstrate that changes in rainfall event profile are associated with wide variation in stemflow flux, stemflow volume and stemflow fraction. When applied to an initially dry plant, rainfall events with a late intensity peak yielded an average peak stemflow flux up to 188% larger than events of contrasting profile, such as early peak events. The increase was smaller, up to 141%, when rain was applied to plants that were already partially wet, but was again found in events with a late intensity peak. Moreover, such events yielded a peak stemflow flux up to approximately seven times larger than comparable events of uniform intensity. Likewise, changing event profile with no change in rainfall depth was associated with a maximum stemflow fraction that was 31% larger than theminimum stemflow fraction, and a maximum stemflow volume that was nearly 37% larger than the minimum stemflow volume. These results suggest that rainfall event profile exerts a significant effect on all of the studied stemflow parameters. It is hypothesized that this is a consequence of the way in which intensity profile affects the rate of wetting‐up of trickle pathways on the plant, and variation in the time taken for these pathways to become fully connected. Event profile must therefore be considered along with plant architecture in seeking to understand stemflow. Copyright © 2014 John Wiley & Sons, Ltd.     

Spatial variability of rainfall on a sub‐kilometre scale

The variability of rainfall in space and time is an essential driver of many processes in nature but little is known about its extent on the sub‐kilometre scale, despite many agricultural and environmental experiments on this scale. A network of 13 tipping‐bucket rain gauges was operated on a 1·4 km² test site in southern Germany for four years to quantify spatial trends in rainfall depth, intensity, erosivity, and predicted runoff. The random measuring error ranged from 10% to 0·1% in case of 1 mm and 100 mm rainfall, respectively. The wind effects could be well described by the mean slope of the horizon at the stations. Except for one station, which was excluded from further analysis, the relative differences due to wind were in maximum ±5%. Gradients in rainfall depth representing the 1‐km² scale derived by linear regressions were much larger and ranged from 1·0 to 15·7 mm km^?1 with a mean of 4·2 mm km^?1 (median 3·3 mm km^?1). They mainly developed during short bursts of rain and thus gradients were even larger for rain intensities and caused a variation in rain erosivity of up to 255% for an individual event. The trends did not have a single primary direction and thus level out on the long term, but for short‐time periods or for single events the assumption of spatially uniform rainfall is invalid on the sub‐kilometre scale. The strength of the spatial trend increased with rain intensity. This has important implications for any hydrological or geomorphologic process sensitive to maximum rain intensities, especially when focusing on large, rare events. These sub‐kilometre scale differences are hence highly relevant for environmental processes acting on short‐time scales like flooding or erosion. They should be considered during establishing, validating and application of any event‐based runoff or erosion model. Copyright © 2009 John Wiley & Sons, Ltd.     

Quantifying the role of the snowpack in generating water available for run‐off during rain‐on‐snow events from snow pillow records

Rain‐on‐snow events have generated major floods around the world, particularly in coastal, mountainous regions. Most previous studies focused on a limited number of major rain‐on‐snow events or were based primarily on model results, largely due to a lack of long‐term records from lysimeters or other instrumentation for quantifying event water balances. In this analysis, we used records from five automated snow pillow sites in south coastal British Columbia, Canada, to reconstruct event water balances for 286 rain‐on‐snow events over a 10‐year period. For large rain‐on‐snow events (event rainfall >40 mm), snowmelt enhanced the production of water available for run‐off (WAR) by approximately 25% over rainfall alone. For smaller events, a range of antecedent and meteorological factors influenced WAR generation, particularly the antecedent liquid water content of the snowpack. Most large events were associated with atmospheric rivers. Rainfall dominated WAR generation during autumn and winter events, whereas snowmelt dominated during spring and summer events. In the majority of events, the sensible heat of rain contributed less than 10% of the total energy consumed by snowmelt. This analysis illustrated the importance of understanding the amount of rainfall occurring at high elevations during rain‐on‐snow events in mountainous regions.     

The relationship between rainfall inputs and flood generation in south–east Spain

Rainfall and flood data are relatively sparse in semi‐arid areas; hence there have been relatively few investigations into the relationships between rainfall inputs and flood generation in these environments. Previous work has shown that flood properties are influenced by a combination of precipitation characteristics including amount, intensity, duration and spatial distribution. Therefore floods may be produced by high intensity, short duration storms, or longer duration, low intensity rainfall. Most of this research has been undertaken in small catchments in either hyper‐arid or relatively high rainfall Mediterranean climates. This paper presents results from a 6 year data record in south‐east Spain from research conducted in two basins, the Rambla Nogalte (171 km²) and the Rambla de Torrealvilla (200 km²). Data cover an area of approximately 500 km² and an annual average rainfall of 300 mm. At coarse temporal resolutions gauges spread over large areas record similar patterns of rainfall, although spells of rain show much more complexity; pulses of rain within storms can vary considerably in total rainfall, intensity and duration over the same area. The analysis for south‐east Spain shows that most storms occur over a period of less than 24 h, but that the number of rainfall events declines as the duration exceeds 8 h. This is at odds with data on floods for the study area suggesting that they are produced by storms lasting longer than 18 h. However, one flood event was produced by a very short (15 min) storm with high intensity rainfall. Most floods tended to occur in May/June or September, which coincides with wetter months of the year (September, October, December and May). Floods are also more highly related to the total rainfall occurring in a spell of rain, than to intensity. The complexity of storm rainfall increases with the storm total, which makes it difficult to generalize on the importance of rainfall intensity for flood generation. Copyright © 2007 John Wiley & Sons, Ltd.     

Evaluation of remote‐sensing‐based rainfall products through predictive capability in hydrological runoff modelling

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 R²_NS 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.     

Estimation of rainfall from infrared‐microwave satellite data for basin‐scale hydrologic modelling

The infrared‐microwave rainfall algorithm (IMRA) was developed for retrieving spatial rainfall from infrared (IR) brightness temperatures (TBs) of satellite sensors to provide supplementary information to the rainfall field, and to decrease the traditional dependency on limited rain gauge data that are point measurements. In IMRA, a SLOPE technique (ST) was developed for discriminating rain/no‐rain pixels through IR image cloud‐top temperature gradient, and 243K as the IR threshold temperature for minimum detectable rainfall rate. IMRA also allows for the adjustment of rainfall derived from IR‐TB using microwave (MW) TBs. In this study, IMRA rainfall estimates were assessed on hourly and daily basis for different spatial scales (4, 12, 20, and 100 km) using NCEP stage IV gauge‐adjusted radar rainfall data, and daily rain gauge data. IMRA was assessed in terms of the accuracy of the rainfall estimates and the basin streamflow simulated by the hydrologic model, Sacramento soil moisture accounting (SAC‐SMA), driven by the rainfall data. The results show that the ST option of IMRA gave accurate satellite rainfall estimates for both light and heavy rainfall systems while the Hessian technique only gave accurate estimates for the convective systems. At daily time step, there was no improvement in IR‐satellite rainfall estimates adjusted with MW TBs. The basin‐scale streamflow simulated by SAC‐SMA driven by satellite rainfall data was marginally better than when SAC‐SMA was driven by rain gauge data, and was similar to the case using radar data, reflecting the potential applications of satellite rainfall in basin‐scale hydrologic modelling. Copyright © 2010 John Wiley & Sons, Ltd.     

Calibration of an oscillating nozzle‐type rainfall simulator

Nozzle‐type rainfall simulators are commonly used in hydrologic and soil erosion research. Simulated rainfall intensity, originating from the nozzle, increases as the distance between the point of measurement and the source is decreased. Hence, rainfall measured using rain gauges would systematically overestimate the rainfall received at the ground level. A simple model was developed to adjust rainfall measured anywhere under the simulator to plot‐wide average rainfall at the ground level. Nozzle height, plot width, gauge diameter and height, and gauge location are required to compute this adjustment factor. Results from 15 runs at different rain intensities and durations, and with different rain gauge layouts, showed that a simple average of measured rain would overestimate the plot‐wide rain by about 20 per cent. Using the adjustment factor to convert measured rainfall for individual gauges before averaging improved the estimate of plot‐wide rainfall considerably. For the 15 runs considered, overall discrepancy between actual and measured rain is reduced to less than 1 per cent with a standard error of 0·97 mm. This model can be easily tested in the ?eld by comparing rainfall depths of different sized gauges. With the adjustment factor they should all give very similar values. Copyright © 2003 John Wiley & Sons, Ltd.     

Rainfall partitioning into throughfall,stemflow, and interception within a single beech (Fagus sylvatica L.) canopy: influence of foliation,rain event characteristics,and meteorology

While the hydrological balance of forest ecosystems has often been studied at the annual level, quantitative studies on the factors determining rainfall partitioning of individual rain events are less frequently reported. Therefore, the effect of the seasonal variation in canopy cover on rainfall partitioning was studied for a mature deciduous beech (Fagus sylvatica L.) tree over a 2‐year period. At the annual level, throughfall amounted to 71% of precipitation, stemflow 8%, and interception 21%. Rainfall partitioning at the event level depended strongly on the amount of rainfall and differed significantly (p < 0·001) between the leafed and the leafless period of the year. Therefore, water fluxes of individual events were described using a multiple regression analysis (r_a² > 0·85, n = 205) with foliation, rainfall characteristics and meteorological variables as predictor variables. For a given amount of rainfall, foliation significantly increased interception and decreased throughfall and stemflow amounts. In addition, rainfall duration, maximum rainfall rate, vapour pressure deficit, and wind speed significantly affected rainfall partitioning at the event level. Increasing maximum hourly rainfall rate increased throughfall and decreased stemflow generation, while higher hourly vapour pressure deficit decreased event throughfall and stemflow amounts. Wind speed decreased throughfall in the growing period only. Since foliation and the event rainfall amount largely determined interception loss, the observed net water input under the deciduous canopy was sensitive to the temporal distribution of rainfall. Copyright © 2007 John Wiley & Sons, Ltd.     

Modelling event soil losses using the QREI30 index within RUSLE2

Recently, a USDA Curve Number‐based method for obtaining estimates of event runoff has been developed for use in enhancing the capacity of Revised Universal Soil Loss Equation (RUSLE2) to deal with runoff‐driven phenomena. However, RUSLE2 still uses the EI₃₀ index as the basis for determining the erosivity of the rainfall for sets of runoff producing storms at a location even though the product of the runoff ratio (Q_R) and EI₃₀ index is better at prediction event erosion when runoff is known or predicted well. This paper reports the results of applying the Q_REI₃₀ index using data available from tables within RUSLE2 to predict storm event soil losses from bare fallow areas and areas with continuous corn at Holly Springs, MS, and Morris, MN. In RUSLE2, all rainfall during a calendar year is considered to detach soil material that is flushed from the area if and when runoff occurs. However, the Q_REI₃₀ index is calculated using the EI₃₀ value for the amount of rain in the storm that produces runoff. Consequently, changes were made to the timing of events during the calendar year in order to meet the criteria for using the Q_REI₃₀ index. As a general rule, the peak event soil loss produced using the Q_REI₃₀ index were higher than produced by RUSLE2, and the peak event soil loss for the bare fallow occurred later than for the continuous corn. The results of the work reported here show that the Q_REI₃₀ index may be used to model event erosion produced by a set of storms within RUSLE2 provided that the appropriate mathematical rules upon which the USLE was developed are adhered to. Copyright © 2013 John Wiley & Sons, Ltd.     

Interpretation of mean‐field bias correction of radar rain rate using the concept of linear regression

In this study, the correction problem of mean‐field bias of radar rain rate was investigated using the concept of linear regression. Three different relationships were reviewed for their slopes to be used as the bias correction factor: Relationship 1 (R1) is based on the conventional linear regression, relationship 2 (R2) is forced to pass the origin and relationship 3 (R3) is the line whose slope is the G/R ratio. In other words, R1 is the regression line connecting the intercept and the mass centre of measurement pairs, R2 is the regression line forced to pass the origin, and R3 is the line connecting the origin and the mass centre. The slopes of all three relationships were reviewed analytically to compare them, and thereby, the effect of zero measurements could be evaluated. Additionally, the effect of using switched independent and dependent variables on the derived slopes was also evaluated. The theoretically derived results were then verified by analysing the rainfall event on 10–11 August 2010 in Korea. Finally, the difference between the bias‐corrected radar rain rate and the rain gauge rain rate was quantified by root mean square error and mean error so that it could be used as a measure for the evaluation of bias correction factors. In conclusion, the slope of R2 was found to be the best for the bias correction factor. However, when deciding the slope of this R2, the radar rain rate should be used as the independent variable in the low rain rate region, and the rain gauge rain rate in the high rain rate region above a certain threshold. Copyright © 2013 John Wiley & Sons, Ltd.     

First‐year post‐fire erosion rates in Bitterroot National Forest,Montana

Accelerated runoff and erosion commonly occur following forest fires due to combustion of protective forest floor material, which results in bare soil being exposed to overland flow and raindrop impact, as well as water repellent soil conditions. After the 2000 Valley Complex Fires in the Bitterroot National Forest of west‐central Montana, four sets of six hillslope plots were established to measure first‐year post‐wildfire erosion rates on steep slopes (greater than 50%) that had burned with high severity. Silt fences were installed at the base of each plot to trap eroded sediment from a contributing area of 100 m². Rain gauges were installed to correlate rain event characteristics to the event sediment yield. After each sediment‐producing rain event, the collected sediment was removed from the silt fence and weighed on site, and a sub‐sample taken to determine dry weight, particle size distribution, organic matter content, and nutrient content of the eroded material. Rainfall intensity was the only significant factor in determining post‐fire erosion rates from individual storm events. Short duration, high intensity thunderstorms with a maximum 10‐min rainfall intensity of 75 mm h^?1 caused the highest erosion rates (greater than 20 t ha^?1). Long duration, low intensity rains produced little erosion (less than 0·01 t ha^?1). Total C and N in the collected sediment varied directly with the organic matter; because the collected sediment was mostly mineral soil, the C and N content was small. Minimal amounts of Mg, Ca, and K were detected in the eroded sediments. The mean annual erosion rate predicted by Disturbed WEPP (Water Erosion Prediction Project) was 15% less than the mean annual erosion rate measured, which is within the accuracy range of the model. Published in 2007 by John Wiley & Sons, Ltd.     

The impact of slope length on the discharge of sediment by rain impact induced saltation and suspension

Simulations using a mechanistic model of raindrop driven erosion in rain‐impacted flow were performed with particles travelling by suspension, raindrop induced saltation and flow driven saltation. Results generated by both a high intensity storm, and a less intense one, indicate that, because of the effect of flow depth on the delivery of raindrop energy to the bed, there is a decline in sediment concentration, and hence soil loss per unit area, with slope length when particles are transported by raindrop induced saltation. However, that decline is reversed when the critical velocities that lead to flow driven saltation are episodically exceeded during an event. The simulations were performed on smooth surfaces and a single drop size but the general relationships are likely to apply for rain made up of a wide range of drop size. Although runoff is not always produced uniformly, as a general rule, flow velocities increase with slope length so that, typically, the distance particles travel before being discharged during an event increase with slope length. The effect of slope length on soil loss per unit area is often considered to vary with slope length to a power greater than zero and less that 1·0. The simulations show that effect of slope length on sediment discharge is highly dependent on the variations in runoff response resulting from variations in rainfall duration‐intensity‐infiltration conditions rather than plot length per se. Consequently, predicting soil loss per unit area using slope length with positive powers close to zero when sheet erosion occurs may not be as effective as commonly expected. Erosion by rain‐impacted flow is a complex process and that complexity needs to be considered when analysing the results of experiments associated with rain‐impacted flow under both natural and artificial conditions. Copyright © 2009 John Wiley & Sons, Ltd.     

Spatial–temporal variability and hydrologic connectivity of runoff generation areas in a North Alabama pasture—implications for phosphorus transport

This study delineated spatially and temporally variable runoff generation areas in the Sand Mountain region pasture of North Alabama under natural rainfall conditions, and demonstrated that hydrologic connectivity is important for generating hillslope response when infiltration‐excess (IE) runoff mechanism dominates. Data from six rainfall events (13·7–32·3 mm) on an intensively instrumented pasture hillslope (0·12 ha) were analysed. Analysis of data from surface runoff sensors, tipping bucket rain gauge and HS‐flume demonstrated spatial and temporal variability in runoff generation areas. Results showed that the maximum runoff generation area, which contributed to runoff at the outlet of the hillslope, varied between 67 and 100%. Furthermore, because IE was the main runoff generation mechanism on the hillslope, the data showed that as the rainfall intensity changed during a rainfall event, the runoff generation areas expanded or contracted. During rainfall events with high‐intensity short‐ to medium‐duration, 4–8% of total rainfall was converted to runoff at the outlet. Rainfall events with medium‐ to low‐intensity, medium‐duration were found less likely to generate runoff at the outlet. In situ soil hydraulic conductivity (k) was measured across the hillslope, which confirmed its effect on hydrologic connectivity of runoff generation areas. Combined surface runoff sensor and k‐interpolated data clearly showed that during a rainfall event, lower k areas generate runoff first, and then, depending on rainfall intensity, runoff at the outlet is generated by hydrologically connected areas. It was concluded that in IE‐runoff‐dominated areas, rainfall intensity and k can explain hydrologic response. The study demonstrated that only connected areas of low k values generate surface runoff during high‐intensity rainfall events. Identification of these areas would serve as an important foundation for controlling nonpoint source pollutant transport, especially phosphorus. The best management practices can be developed and implemented to reduce transport of phosphorus from these hydrologically connected areas. Copyright © 2009 John Wiley & Sons, Ltd.