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.     

Assessing changes in rainfall erosivity in Sicily during the twentieth century

Changes in rainfall erosivity are an expected consequence of climate change. Long‐term series of the single storm erosion index, EI, may be analysed to detect trends in rainfall erosivity. An indirect approach has to be applied for estimating EI, given that long series of rainfall intensities are seldom available. In this paper, a method for estimating EI from the corresponding rainfall amount, h_e, was developed for Sicily. This method was then applied at 17 Sicilian locations, representative of different climatic zones of the region, to generate a long series (i.e. from 1916 to 1999 in most cases) of EI values. Linear and step (step located at 1970) trends in annual and seasonal erosivity were detected by both classical approaches (Mann–Kendall test, Wilcoxon‐Mann‐Whitney rank‐sum test) and a new empirical approach (quantile approach, QA), based on the determination of the erosivity values corresponding to selected probability levels. A power relationship between EI and h_e with a space‐ and time‐variable scale factor and a time‐variable process parameter yielded the most accurate predictions of EI. However, a simpler model, using a time‐variable scale factor and a constant process parameter, yielded reasonably accurate EI estimates. Annual erosivity did not increase in Sicily during the twentieth century. At the most, it decreased at a few locations (three of the 17 considered locations). Significant trends were observed more frequently for winter erosivity (six locations) than for summer erosivity (two locations), suggesting that the erosive storms of winter determined the occasional occurrence of a negative trend in annual erosivity. In general, the QA compared reasonably well with more classical approaches. The QA appears promising since step trends for different return periods may be detected but efforts are needed to statistically formalize the proposed approach. Copyright © 2007 John Wiley & Sons, Ltd.     

Applying the QREI30 index within the USLE modelling environment

The USLE/RUSLE model was designed to predict long‐term (~20 years) average annual soil loss by accounting for the effects of climate, soil, topography and crops. The USLE/RUSLE model operates mathematically in two steps. The first step involves the prediction of soil loss from the ‘unit’ plot, a bare fallow area 22.1 m long on a 9% slope gradient with cultivation up and down the slope. Appropriate values of the factors accounting for slope length, gradient, crops and crop management and soil conservation practice are then used to adjust that soil loss to predict soil loss from areas that have conditions that are different from the unit plot. Replacing EI₃₀, the USLE/RUSLE event erosivity index, by the product of the runoff ratio (Q_R) and EI₃₀, can enhance the capacity of the model to predict short‐term soil loss from the unit plot if appropriate data on runoff is available. Replacing the EI₃₀ index by another index has consequences on other factors in the model. The USLE/RUSLE soil erodibility factor cannot be used when the erosivity factor is based on Q_REI₃₀. Also, the USLE/RUSLE factors for slope length, slope gradient crops and crop management, and soil conservation practice cannot be used when runoff from other than the unit plot is used to calculate Q_R. Here, equations are provided to convert the USLE/RUSLE factors to values suitable for use when the erosivity factor is based on the Q_REI₃₀ index under these circumstances. At some geographic locations, non linear relationships exist between soil loss from bare fallow areas and the Q_REI₃₀ index. The effect of this on the slope length factor associated with the Q_REI₃₀ index is demonstrated using data from runoff and soil loss plots located at the Sparacia site, Sicily. Copyright © 2012 John Wiley & Sons, Ltd.     

Testing alternative erosivity indices to predict event soil loss from bare plots in Southern Italy

Methods for predicting unit plot soil loss for the ‘Sparacia’ Sicilian (Southern Italy) site were developed using 316 simultaneous measurements of runoff and soil loss from individual bare plots varying in length from 11 to 44 m. The event unit plot soil loss was directly proportional to an erosivity index equal to (Q_REI₃₀)^1·47, being Q_REI₃₀ the runoff ratio (Q_R) times the single storm erosion index (EI₃₀). The developed relationship represents a modified version of the USLE‐M, and therefore it was named USLE‐MM. By the USLE‐MM, a constant erodibility coefficient was deduced for plots of different lengths, suggesting that in this case the calculated erodibility factor is representative of an intrinsic soil property. Testing the USLE‐M and USLE‐MM schemes for other soils and developing simple procedures for estimating the plot runoff ratio has practical importance to develop a simple method to predict soil loss from bare plots at the erosive event temporal scale. Copyright © 2009 John Wiley & Sons, Ltd.     

Runoff dependent erosivity and slope length factors suitable for modelling annual erosion using the Universal Soil Loss Equation

Despite revisions and refinements, the Revised Universal Soil Loss Equation (RUSLE), which is the revised version of the Universal Soil Loss Equation (USLE), over predicts small annual soil losses and under predicts large annual soil losses. To some large extent, this results from the equation over estimating small event soil losses and under estimating large event soil losses. Replacing the USLE/RUSLE event erosivity index (EI₃₀) by the product of EI₃₀ and the runoff ratio (Q_R) significantly reduces the errors in estimating event erosion when runoff is measured, but the USLE‐M, the USLE variant that uses the Q_REI₃₀ index, requires crop and support practice factors that differ from those used in the RUSLE. The theory which enables the Q_REI₃₀ index to be used in association with the RUSLE crop and support practice factors is presented. In addition, the USLE/RUSLE approach was developed for conditions where runoff is produced uniformly over a hill slope. A runoff dependent slope length factor that takes account of runoff variations over a hill slope is presented and demonstrated for the situation where runoff from a low runoff producing area passes onto an area where runoff is produced more readily. Copyright © 2007 John Wiley & Sons, Ltd.     

Real-time prediction of the peak suspended sediment concentration and sediment yield of the Lao-Nung River during storms

Based on rainfall erosion of soil and suspended sediment transport in storm events, a method is proposed to predict peak suspended sediment concentration and suspended sediment yield in watersheds based on rainfall characteristics prior to peak rainfall intensity. The rainfall characteristics factors that dominate peak suspended sediment concentration C_p are rainfall erosion factor R_ef, first peak rainfall intensity of area-average rainfall i_p1 and antecedent precipitation index I_ap; the rainfall characteristics factors that dominate suspended sediment yield Y_ss in storm events are total rainfall P, suspended sediment yield factor R_sf and antecedent precipitation index I_ap. This research focuses on watersheds in Liau-Kwei observation station along Lao-Nung River in southern Taiwan as the research object, and adopts the PSED-model to simulate the discharge hydrograph, suspended sediment concentration hydrograph and suspended sediment yield in 11 storm events for analysis. The analytical results show that there is a good correlation between the above-mentioned rainfall characteristics factors and C_p as well as Y_ss, thus enabling C_p and Y_ss to be predicted by using Expressions (13) and (14). These two expressions are utilized to predict C_p and Y_ss of Typhoon Morakot in 2009, and the results are compared with those from simulation by using the PSED-model. The result of comparison shows there is a good capability in predicting. For the watersheds where it is necessary to predict C_p and Y_ss of a storm event for the benefit of effective operation of water resource facilities, the aforesaid rainfall characteristics factors can be utilized to establish applicable models for prediction.     

A shot noise model for the generation of soil moisture data

An attempt is made to estimate the expected contribution of rainfall to soil moisture during the irrigation season. Effective rainfall and evapotranspiration are the parameters considered in the water balance carried out in the root zone. Rainfall occurrence is simulated by a Poisson process whereas evapotranspiration is described by a simple deterministic function of potential evapotranspiration and soil moisture in the root zone. Using the theory of shot noise models a closed form solution is derived from the expected soil moisture in the root zone at the end of the time interval (0,t]. For illustration purposes the proposed model is applied to a series of data from Mikra meteorological station in Greece.List of symbols x change in water storage in the root zone during the time interval t - X infiltrated rainfall of thei th storm event - ET actual evapotranspiration during thej th day - Poisson rate - number of storm events in (0,t] - t _r duration of rainfall - t _b interarrival time - h _i rainfall depth of thei th storm event - i _m mean rainfall intensity - i(t) instantaneous rainfall intensity - x(0),x(t) available soil moisture in the root zone at time 0 andt, respectively - PET potential evapotranspiration rate - x _F available soil moisture in the root zone at field capacity - soil moisture depletion rate (=PET/x _F ) - w impulse shape of filtered Poisson processes - E[·] mean value - S _i time of thei th rainfall event - N(t) time of storm events in (0,t] - estimated standard deviation The following symbols were used in this paper     

Effect of auroral electrojets and solar wind parameters on variations in the intensity of low-latitude geomagnetic disturbances and Dst during the extremely large magnetic storm of November 20–21, 2003

The effect of auroral electrojets on the variations in the low-latitude geomagnetic disturbances and Dst during a strong magnetic storm of November 20–21, 2003, with Dst ≈ ?472 nT has been studied based on the global magnetic observations. It has been indicated that the magnetospheric storm expansive phase with Δt ≈ 1–2 h results in positive low-latitude disturbances (ΔH) of the same duration and with an amplitude of ～ 1–2 h results in positive low-latitude disturbances (ΔH) of the same duration and with an amplitude of ～ 30–100 nT in the premidnight-dawn sector. A growth of negative low-latitude ΔH values and Dst is mainly caused by regular convection electrojets with Δt ≥ 10 h, the centers of which shift to latitudes of ～ 50°–55° during the storm development. It has been established that the maximal low-latitude values of the field ΔH component at 1800–2400 MLT are observed when the auroral luminosity equatorward boundary shifts maximally southward during an increase in the negative values of the IMF B _z component. It has been assumed that, during this storm, a magnetic field depression at low latitudes was mainly caused by an enhancement of the partially-ring current which closes through field-aligned currents into the ionosphere at the equatorward boundary of the auroral luminosity zone.     

Comparing theoretically supported rainfall‐runoff erosivity factors at the Sparacia (South Italy) experimental site

Interpreting rainfall‐runoff erosivity by a process‐oriented scheme allows to conjugate the physical approach to soil loss estimate with the empirical one. Including the effect of runoff in the model permits to distinguish between detachment and transport in the soil erosion process. In this paper, at first, a general definition of the rainfall‐runoff erosivity factor REF_e including the power of both event runoff coefficient Q_R and event rainfall erosivity index EI₃₀ of the Universal Soil Loss Equation (USLE) is proposed. The REF_e factor is applicable to all USLE‐based models (USLE, Modified USLE [USLE‐M] and Modified USLE‐M [USLE‐MM]) and it allows to distinguish between purely empirical models (e.g., Modified USLE‐M [USLE‐MM]) and those supported by applying theoretical dimensional analysis and self‐similarity to Wischmeier and Smith scheme. This last model category includes USLE, USLE‐M, and a new model, named USLE‐M based (USLE‐MB), that uses a rainfall‐runoff erosivity factor in which a power of runoff coefficient multiplies EI₃₀. Using the database of Sparacia experimental site, the USLE‐MB is parameterized and a comparison with soil loss data is carried out. The developed analysis shows that USLE‐MB (characterized by a Nash–Sutcliffe Efficiency Index NSEI equal to 0.73 and a root mean square error RMSE = 11.7 Mg ha^?1) has very similar soil loss estimate performances as compared with the USLE‐M (NSEI = 0.72 and RMSE = 12.0 Mg ha^?1). However, the USLE‐MB yields a maximum discrepancy factor between predicted and measured soil loss values (176) that is much lower than that of USLE‐M (291). In conclusion, the USLE‐MB should be preferred in the context of theoretically supported USLE type models.     

Infiltration and runoff generation processes in fire‐affected soils

Post‐wildfire runoff was investigated by combining field measurements and modelling of infiltration into fire‐affected soils to predict time‐to‐start of runoff and peak runoff rate at the plot scale (1 m²). Time series of soil‐water content, rainfall and runoff were measured on a hillslope burned by the 2010 Fourmile Canyon Fire west of Boulder, Colorado during cyclonic and convective rainstorms in the spring and summer of 2011. Some of the field measurements and measured soil physical properties were used to calibrate a one‐dimensional post‐wildfire numerical model, which was then used as a ‘virtual instrument’ to provide estimates of the saturated hydraulic conductivity and high‐resolution (1 mm) estimates of the soil‐water profile and water fluxes within the unsaturated zone. Field and model estimates of the wetting‐front depth indicated that post‐wildfire infiltration was on average confined to shallow depths less than 30 mm. Model estimates of the effective saturated hydraulic conductivity, K_s, near the soil surface ranged from 0.1 to 5.2 mm h^?1. Because of the relatively small values of K_s, the time‐to‐start of runoff (measured from the start of rainfall), t_p, was found to depend only on the initial soil‐water saturation deficit (predicted by the model) and a measured characteristic of the rainfall profile (referred to as the average rainfall acceleration, equal to the initial rate of change in rainfall intensity). An analytical model was developed from the combined results and explained 92–97% of the variance of t_p, and the numerical infiltration model explained 74–91% of the variance of the peak runoff rates. These results are from one burned site, but they strongly suggest that t_p in fire‐affected soils (which often have low values of K_s) is probably controlled more by the storm profile and the initial soil‐water saturation deficit than by soil hydraulic properties. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.     

Spatially distributed long‐term hydrologic simulation using a continuous SCS CN method‐based hybrid hydrologic model

A continuous Soil Conservation Service (SCS) curve number (CN) method that considers time‐varied SCS CN values was developed based on the original SCS CN method with a revised soil moisture accounting approach to estimate run‐off depth for long‐term discontinuous storm events. The method was applied to spatially distributed long‐term hydrologic simulation of rainfall‐run‐off flow with an underlying assumption for its spatial variability using a geographic information systems‐based spatially distributed Clark's unit hydrograph method (Distributed‐Clark; hybrid hydrologic model), which is a simple few parameter run‐off routing method for input of spatiotemporally varied run‐off depth, incorporating conditional unit hydrograph adoption for different run‐off precipitation depth‐based direct run‐off flow convolution. Case studies of spatially distributed long‐term (total of 6 years) hydrologic simulation for four river basins using daily NEXRAD quantitative precipitation estimations demonstrate overall performances of Nash–Sutcliffe efficiency (E_NS) 0.62, coefficient of determination (R²) 0.64, and percent bias 0.33% in direct run‐off and E_NS 0.71, R² 0.72, and percent bias 0.15% in total streamflow for model result comparison against observed streamflow. These results show better fit (improvement in E_NS of 42.0% and R² of 33.3% for total streamflow) than the same model using spatially averaged gauged rainfall. Incorporation of logic for conditional initial abstraction in a continuous SCS CN method, which can accommodate initial run‐off loss amounts based on previous rainfall, slightly enhances model simulation performance; both E_NS and R² increased by 1.4% for total streamflow in a 4‐year calibration period. A continuous SCS CN method‐based hybrid hydrologic model presented in this study is, therefore, potentially significant to improved implementation of long‐term hydrologic applications for spatially distributed rainfall‐run‐off generation and routing, as a relatively simple hydrologic modelling approach for the use of more reliable gridded types of quantitative precipitation estimations.     

Interrill erosion on cultivated Greek soils: modelling sediment delivery

For interrill erosion, raindrop‐induced detachment and transport of sediment by rainfall‐disturbed sheet flow are the predominant processes, while detachment by sheet flow and transport by raindrop impact are negligible. In general, interrill subprocesses are inter‐actively affected by rainfall, soil and surface properties. The objective of this work was to study the relationships among interrill runoff and sediment loss and some selected para‐meters, for cultivated soils in central Greece, and also the development of a formula for predicting single storm sediment delivery. Runoff and soil loss measurement field experiments have been conducted for a 3·5‐year period, under natural storms. The soils studied were developed on Tertiary calcareous materials and Quaternary alluvial deposits and were textured from sandy loam to clay. The second group of soils showed greater susceptibility to sealing and erosion than the first group. Single storm sediment loss was mainly affected by rain and runoff erosivity, being significantly correlated with rain kinetic energy (r = 0·64***), its maximum 30‐minute intensity (r = 0·64***) and runoff amount (r = 0·56***). Runoff had the greatest correlation with rain kinetic energy (r = 0·64***). A complementary effect on soil loss was detected between rain kinetic energy and its maximum 30‐minute intensity. The same was true for rain kinetic energy and topsoil aggregate instability, on surface seal formation and thus on infiltration characteristics and overland flow rate. Empirical analysis showed that the following formula can be used for the successful prediction of sediment delivery (D_i): D_i = 0·638βEI₃₀tan(θ) (R² = 0·893***), where β is a topsoil aggregate instability index, E the rain kinetic energy, I₃₀ the maximum 30‐minute rain intensity and θ the slope angle. It describes soil erodibility using a topsoil aggregate instability index, which can be determined easily by a simple laboratory technique, and runoff through the product of this index and rain kinetic energy. Copyright © 2006 John Wiley & Sons, Ltd.     

Accounting for the influence of runoff on event soil erodibilities associated with the EI30 index in RUSLE2

Soil erodibilities (K) associated with the EI₃₀ index vary not only with soil properties but also with soil moisture as it varies in time and space. In Revised Universal Soil Loss Equation Version 2 (RUSLE2), temporal variations in soil erodibility in the USA are calculated using monthly precipitation and temperature as independent variables. K_UM, the soil erodibility factor associated with the Q_REI₃₀ index, varies independently of runoff and the product of K_UM and the runoff ratio for the unit plot (Q_R1) provides an alternative to the temporally varying Ks currently used in predicting storm soil loss in RUSLE2. Comparisons were made between the product of Q_R1 and K_UM and RUSLE2 Ks for representative storms at four locations representing the north to south variation in climate in the USA. Peak erosion associated with the current approach used in RUSLE2 was slightly higher at two locations and slightly lower at the other two locations. One other location, Morris, MN, provided an exception with the peak loss predicted by using the product of Q_R1 and K_UM being 1.7 times that obtained using RUSLE2 Ks. In theory, average annual K_UM values should be better related to soil properties than the average annual values of K frequently used when the average annual values of EI₃₀ are used to predict soil loss. However, work has yet to be performed to determine how K_UM varies directly with soil properties and in space and time. Copyright © 2014 John Wiley & Sons, Ltd.     

Book Review

Abstract

The instantaneous unit hydrograph (IUH) of a watershed is the result of one instantaneous unit of rainfall excess distributed uniformly over the watershed. Although the geomorphological characteristics of the basin remain relatively constant, the variable characteristics of storms cause variations in the shape of the resulting hydrographs. It is, therefore, inadequate to use one typical IUH to represent the hydrological response generated from any specific storm. In this study, a variable IUH was derived that directly reflects the time-varying rainfall intensity during storms. The rainfall intensity used to generate the variable IUH at time t is the mean rainfall intensity occurring from the time t—T _c to t in which T _c is the watershed time of concentration. Hydrological records from three watersheds in Taiwan were used to demonstrate the applicability of the proposed model. The results show that better simulations can be obtained by using the proposed model than by using the conventional unit hydrograph method, especially for concentrated rainstorm cases.     

A coupled model for simulating surface water and groundwater interactions in coastal wetlands

Coastal wetlands are characterized by strong, dynamic interactions between surface water and groundwater. This paper presents a coupled model that simulates interacting surface water and groundwater flow and solute transport processes in these wetlands. The coupled model is based on two existing (sub) models for surface water and groundwater, respectively: ELCIRC (a three‐dimensional (3‐D) finite‐volume/finite‐difference model for simulating shallow water flow and solute transport in rivers, estuaries and coastal seas) and SUTRA (a 3‐D finite‐element/finite‐difference model for simulating variably saturated, variable‐density fluid flow and solute transport in porous media). Both submodels, using compatible unstructured meshes, are coupled spatially at the common interface between the surface water and groundwater bodies. The surface water level and solute concentrations computed by the ELCIRC model are used to determine the boundary conditions of the SUTRA‐based groundwater model at the interface. In turn, the groundwater model provides water and solute fluxes as inputs for the continuity equations of surface water flow and solute transport to account for the mass exchange across the interface. Additionally, flux from the seepage face was routed instantaneously to the nearest surface water cell according to the local sediment surface slope. With an external coupling approach, these two submodels run in parallel using time steps of different sizes. The time step (Δt_g) for the groundwater model is set to be larger than that (Δt_s) used by the surface water model for computational efficiency: Δt_g = M × Δt_s where M is an integer greater than 1. Data exchange takes place between the two submodels through a common database at synchronized times (e.g. end of each Δt_g). The coupled model was validated against two previously reported experiments on surface water and groundwater interactions in coastal lagoons. The results suggest that the model represents well the interacting surface water and groundwater flow and solute transport processes in the lagoons. Copyright © 2011 John Wiley & Sons, Ltd.     

A note on spectral evaluation at the Nyquist frequency

The determination of the spectral component of a signal corresponding to the Nyquist frequencyf _N is not reliable. A rule is proposed to determine the highest reliable frequencyf _R for a given sampling rate Δt and time windowN Δt (whereN is the total number of samples) asf _R=f _N(1?1/2N).     

A new version of the USLE‐MM for predicting bare plot soil loss at the Sparacia (South Italy) experimental site

Improving empirical prediction of plot soil erosion at the event temporal scale has both scientific and practical importance. In this investigation, 492 runoff and soil loss data from plots of different lengths, λ (11 ≤ λ ≤ 44 m), and steepness, s (14.9 ≤ s ≤ 26.0%), established at the Sparacia experimental station, in Sicily, South Italy, were used to derive a new version of Universal Soil Loss Equation (USLE)‐MM model, by only assuming a value of one for the topographic length, L, and steepness, S, factors for λ = 22 m and s = 9%, respectively. An erosivity index equal to (Q_REI₃₀)^b1, Q_R and EI₃₀ being the runoff coefficient and the event rainfall erosivity index, respectively, with b₁ > 1 was found to be an appropriate choice for the Sparacia area. The specifically developed functions for L and S did not differ appreciably from other, more widely accepted relationships (maximum differences by a factor of 1.22 for L and 1.09 for S). The new version of the USLE‐MM performed particularly well for highly erosive events, because predicted soil loss differed by not more than a factor of 1.19 from the measured soil loss for measured values of more than 100 Mg ha^?1. The choice of the relationships to predict topographic effects on plot soil loss should not represent a point of particular concern in the application of the USLE‐MM in other environments. However, tests of the empirical approach should be carried out in other experimental areas in an attempt to develop analytical tools, usable at the event temporal scale, reasonably simple and of wide validity. Copyright © 2015 John Wiley & Sons, Ltd.     

Formulae for errors for initial displacement and velocity problems using the Newmark method

A standard test of the Newmark method in structural dynamics is its application to the determination of the response of a damped or undamped single-degree-of-freedom system to a prescribed initial displacement or velocity. In this paper formulae for the error, Δ_j, in the response, after applying the Newmark method for j time-steps each of duration Δt, are proposed and their acceptable accuracy is demonstrated.     

Application of connectivity theory to model the impact of terrace failure on runoff in semi‐arid catchments

Terraces are a common feature of Mediterranean landscapes. In many places they are no longer maintained so that the number of intact terraces is in prolonged decline. The aim of this paper is to examine the effect of terrace removal and failure on hydrological connectivity and peak discharge in an agricultural catchment (475 ha) in south‐east Spain. The situation of 2006 is compared to that in 1956 and to a scenario without terraces (S2). The spatial distribution of concentrated flow was mapped after four storms in 2006. The degree of connectivity was quantified by means of connectivity functions and related to storm characteristics, land use and topography. For 1956, 2006 and scenario S2, connectivity functions and peak discharge to the river were determined for a storm with a return period of 8·2 years. The results show that the decrease in intact terraces has led to a strong increase in connectivity and discharge. The contributing area to the river system has increased by a factor 3·2 between 1956 and 2006. If all terraces were to be removed (scenario S2), the contributing area may further increase by a factor 6·0 compared to 2006. The spatial extent of concentrated flow and the degree of connectivity are related to storm magnitude as expressed by the erosivity index (EI₃₀). Although a large part of the concentrated flow (25–50%) occurs on dirt roads, it appears that croplands become a major source of runoff with increasing rainfall. The results suggest that connectivity theory can be used to improve rainfall–runoff models in semi‐arid areas. Copyright © 2009 John Wiley & Sons, Ltd.     

Streamflow and suspended sediment yield following the 2000 Bobcat fire,Colorado

Postfire runoff and erosion are a concern, and more data are needed on the effects of wildfire at the watershed‐scale, especially in the Colorado Front Range. The goal of this study was to characterize and compare the streamflow and suspended sediment yield response of two watersheds (Bobcat Gulch and Jug Gulch) after the 2000 Bobcat fire. Bobcat Gulch had several erosion control treatments applied after the fire, including aerial seeding, contour log felling, mulching, and straw wattles. Jug Gulch was partially seeded. Study objectives were to: (1) measure precipitation, streamflow, and sediment yields; (2) assess the effect of rainfall intensity on peak discharges, storm runoff, and sediment yields; (3) evaluate short‐term hydrologic recovery. Two months after the fire, a storm with a maximum 30 min rainfall intensity I₃₀ of 42 mm h^?1 generated a peak discharge of 3900 l s^?1 km^?2 in Bobcat Gulch. The same storm produced less than 5 l s^?1 km^?2 in Jug Gulch, due to less rainfall and the low watershed response. In the second summer, storms with, I₃₀ of 23 mm h^?1 and 32 mm h^?1 generated peak discharges of 1100 l s^?1 km^?2 and 1700 l s^?1 km^?2 in the treated and untreated watersheds respectively. Maximum water yield efficiencies were 10% and 17% respectively, but 18 of the 23 storms returned ≤2% of the rainfall as runoff, effectively obscuring interpretation of the erosion control treatments. I₃₀ explained 86% of the variability in peak discharges, 74% of the variability in storm runoff, and >80% of the variability in sediment yields. Maximum single‐storm sediment yields in the second summer were 370 kg ha^?1 in the treated watershed and 950 kg ha^?1 in the untreated watershed. Copyright © 2005 John Wiley & Sons, Ltd.