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.     

Impacts of annual precipitation extremes on soil and nutrient losses in vineyards of NE Spain

The objective of this research was to characterise annual precipitation extremes in a Mediterranean vineyard region. The number of exceptional events (P > 95th percentile) and annual extreme events (P > 99th percentile), as well as their strength, erosive character and return period were analysed for 2000–2004. The erosive character was evaluated according to the R‐factor (kinetic energy × maximum intensity in 30‐min periods). Soil and nutrient losses caused by these events were evaluated by combining field sampling and a hydrological model to estimate total runoff in a vineyard plot. The results show a clear increase in the number of very wet days and extreme events (P > 95th percentile), which represented up to 88% of annual rainfall. The severity of the extreme events (TS = precipitation event P > 99th percentile) reached values higher than 50 mm almost every year. These values were far exceeded in 2000, when one extraordinary event recorded 50% of the annual rainfall, with TS of 189 mm, about 80% of total rainfall being lost as runoff. Annual erosivity was driven not only by extreme events, but also by short events of less depth but high intensity. During some of the years analysed, rainfall erosivity was two or three times the average in the area. Most soil and nutrient losses occurred in a small number of events: one or two events every year were responsible for more than 75% of the annual soil and nutrient losses on average. Antecedent soil moisture conditions, runoff rates, and events with a return period higher than two years were responsible for the higher erosion rates. Apart from an exceptional event recorded in 2000, which produced more than 200 Mg ha^?1 soil losses, annual soil losses up to 25 Mg ha^?1 were recorded, which are much higher than the soil loss tolerance. Copyright © 2008 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.     

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.     

Exploring the effect of different time resolutions to calculate the rainfall erosivity factor R in Calabria,southern Italy

The rainfall erosivity factor R of the Universal Soil Loss Equation is a good indicator of the potential of a storm to erode soil, as it quantifies the raindrop impact effect on the soil based on storm intensity. The R‐factor is defined as the average annual value of rainfall erosion index, EI, calculated by cumulating the EI values obtained for individual storms for at least 22 years. By definition, calculation of EI is based on rainfall measurements at short time intervals over which the intensity is essentially constant, i.e. using so‐called breakpoint data. Because of the scarcity of breakpoint rainfall data, many authors have used different time resolutions (Δt = 5, 10, 15, 30, and 60 min) to deduce EI in different areas of the world. This procedure affects the real value of EI because it is strongly dependent on Δt. In this contribution, after a general overview of similar studies carried out in different countries, the relationship between EI and Δt is explored in Calabria, southern Italy. The use of 17 139 storm events collected from 65 rainfall stations allowed the calculation of EI for different time intervals ranging from 5 to 60 min. The overall results confirm that calculation of EI is dependent on time resolution and a conversion factor able to provide its value for the required Δt is necessary. Based on these results, a parametric equation that gives EI as a function of Δt is proposed, and a regional map of the scale parameter a that represents the conversion factor for converting fixed‐interval values of (EI₃₀)_Δt to values of (EI₃₀)₁₅ is provided in order to calculate R anywhere in the region using rainfall data of 60 min. Copyright © 2015 John Wiley & Sons, Ltd.     

The influence of leaf litter diversity and soil fauna on initial soil erosion in subtropical forests

Although the protective role of leaf litter cover against soil erosion is known for a long time, little research has been conducted on the processes involved. Moreover, the impact of soil meso‐ and macrofauna within the litter layer on erosion control is not clear. To investigate how leaf litter cover and diversity as well as meso‐ and macrofauna influence sediment discharge in subtropical forest ecosystems, a field experiment has been carried out in Southeast China. A full‐factorial random design with 96 micro‐scale runoff plots and 7 domestic leaf species was established and erosion was triggered by a rainfall simulator. Our results demonstrate that leaf litter cover protects soil from erosion (?82 % sediment discharge on leaf covered plots) by rainfall and this protection is removed as litter decomposes. The protective effect is influenced by the presence or absence of soil meso‐ and macrofauna. Fauna presence increases soil erosion rates significantly by 58 %, while leaf species diversity shows a non‐significant negative trend. We assume that the faunal effect arises from arthropods slackening and processing the soil surface as well as fragmenting and decomposing the protecting leaf litter covers. Even though the diversity level did not show a significant influence, single leaf species in monocultures show rather different impacts on sediment discharge and thus, erosion control. In our experiment, runoff plots with leaf litter from Machilus thunbergii showed the highest sediment discharge (68.0 g m^?2) whereas plots with Cyclobalanopsis glauca showed the smallest rates (7.9 g m^?2). Copyright © 2015 John Wiley & Sons, Ltd.     

Effects of rainfall and slope on runoff,soil erosion and rill development: an experimental study using two loess soils

Runoff generation and soil loss from slopes have been studied for decades, but the relationships among runoff, soil loss and rill development are still not well understood. In this paper, rainfall simulation experiments were conducted in two neighbouring plots (scale: 1 m by 5 m) with four varying slopes (17.6%, 26.8%, 36.4% and 46.6%) and two rainfall intensities (90 and 120 mm h^?1) using two loess soils. Data on rill development were extracted from the digital elevation models by means of photogrammetry. The effects of rainfall intensity and slope gradient on runoff, soil loss and rill development were different for the two soils. The runoff and soil loss from the Anthrosol surface were generally higher than those from the Calcaric Cambisol surface. Higher rainfall intensity produced less runoff and more sediment for almost each treatment. With increasing slope gradient, the values of cumulative runoff and soil loss peaked, except for the treatments with 90 mm h^?1 rainfall on the slopes with Anthrosol. With rainfall duration, runoff discharge decreased for Anthrosol and increased for Calcaric Cambisol for almost all the treatments. For both soils, sediment concentration was very high at the onset of rainfall and decreased quickly. Almost all the sediment concentrations increased on the 17.6% and 26.8% slopes and peaked on the 36.4% and 46.6% slopes. Sediment concentrations were higher on the Anthrosol slopes than on the Calcaric Cambisol slopes. At 90 mm h^?1 rainfall intensity, increasingly denser rills appeared on the Anthrosol slope as the slope gradient increased, while only steep slopes (36.4% and 46.6%) developed rills for the Calcaric Cambisol soil. The contributions of rill erosion ranged from 36% to 62% of the cumulative soil losses for Anthrosol, while the maximum contribution of rill erosion to the cumulative soil loss was only 37.9% for Calcaric Cambisol. Copyright © 2014 John Wiley & Sons, Ltd.     

Testing the Universal Soil Loss Equation‐MB equation in plots in Central and South Italy

Planning soil conservation strategies requires predictive techniques at event scale because a large percentage of soil loss over a long‐time period is due to relatively few large storms. Considering runoff is expected to improve soil loss predictions and allows relation of the process‐oriented approach with the empirical one, furthermore, the effects of detachment and transport on soil erosion processes can be distinguished by a runoff component. In this paper, the empirical model USLE‐MB (USLE‐M based), including a rainfall‐runoff erosivity factor in which the event rainfall erosivity index EI₃₀ of the Universal Soil Loss Equation (USLE) multiplies the runoff coefficient Q_R raised to an exponent b₁ > 1 is tested by the measurements carried out for the Masse (10 plots) and Sparacia (22 plots) experimental stations in Italy. For the Masse experimental station, an exponent b₁ > 1 was also estimated by tests carried out by a nozzle‐type rainfall simulator. For each experimental site in fallow conditions, the effect of the sample size of the plot soil loss measurements on the estimate of the b₁ coefficient was also studied by the extraction of a fixed number N of randomly obtained pairs of the normalized soil loss and runoff coefficient. The analysis showed that the variability of b₁ with N is low and that 350 pairs are sufficient to obtain a stable estimate of b₁. A total of 1,262 soil loss data were used to parameterize the model both locally and considering the two sites simultaneously. The b₁ exponent varied between the two sites (1.298–1.520), but using a common exponent (1.386) was possible. Using a common b₁ exponent for the two experimental areas increases the practical interest for the model and allows the estimation of a baseline component of the soil erodibility factor, which is representative of the at‐site soil intrinsic and quasi‐static properties. Development of a single USLE‐MB model appears possible, and sampling other sites is advisable to develop a single USLE‐MB model for general use.     

Influence of grass soil cover on water runoff and soil detachment under rainfall simulation in a sub‐humid South African degraded rangeland

In most regions of the world overgrazing plays a major role in land degradation and thus creates a major threat to natural ecosystems. Several feedbacks exist between overgrazing, vegetation, soil infiltration by water and soil erosion that need to be better understood. In this study of a sub‐humid overgrazed rangeland in South Africa, the main objective was to evaluate the impact of grass cover on soil infiltration by water and soil detachment. Artificial rains of 30 and 60 mm h^?1 were applied for 30 min on 1 m² micro‐plots showing similar sandy‐loam Acrisols with different proportions of soil surface coverage by grass (Class A: 75–100%; B: 75–50%; C: 50–25%; D: 25–5%; E: 5–0% with an outcropping A horizon; F: 0% with an outcropping B horizon) to evaluate pre‐runoff rainfall (Pr), steady state water infiltration (I), sediment concentration (SC) and soil losses (SL). Whatever the class of vegetal cover and the rainfall intensity, with the exception of two plots probably affected by biological activity, I decreased regularly to a steady rate <2 mm h^?1 after 15 min rain. There was no significant correlation between I and Pr with vegetal cover. The average SC computed from the two rains increased from 0·16 g L^?1 (class A) to 48·5 g L^?1 (class F) while SL was varied between 4 g m^?2 h^?1 for A and 1883 g m^?2 h^?1 for F. SL increased significantly with decreasing vegetal cover with an exponential increase while the removal of the A horizon increased SC and SL by a factor of 4. The results support the belief that soil vegetation cover and overgrazing plays a major role in soil infiltration by water but also suggest that the interrill erosion process is self‐increasing. Abandoned cultivated lands and animal preferred pathways are more vulnerable to erosive processes than simply overgrazed rangelands. Copyright © 2011 John Wiley & Sons, Ltd.     

Using beryllium‐7 to monitor the relative proportions of interrill and rill erosion from loessal soil slopes in a single rainfall event

Quantifying the relative proportions of soil losses due to interrill and rill erosion processes during erosion events is an important factor in predicting total soil losses and sediment transport and deposition. Beryllium‐7 (⁷Be) can provide a convenient way to trace sediment movement over short timescales providing information that can potentially be applied to longer‐term, larger‐scale erosion processes. We used simulated rainstorms to generate soil erosion from two experimental plots (5 m × 4 m; 25° slope) containing a bare, hand‐cultivated loessal soil, and measured ⁷Be activities to identify the erosion processes contributing to eroded material movement and/or deposition in a flat area at the foot of the slope. Based on the mass balance of ⁷Be detected in the eroded soil source and in the sediments, the proportions of material from interrill and rill erosion processes were estimated in the total soil losses, the deposited sediments in the flat area, and in the suspended sediments discharged from the plots. The proportion of interrill eroded material in the discharged sediment decreased over time as that of rill eroded material increased. The amount of deposited material was greatly affected by overland flow rates. The estimated amounts of rill eroded material calculated using ⁷Be activities were in good agreement with those based on physical measurements of total plot rill volumes. Although time lags of 45 and 11 minutes existed between detection of sediment being removed by rill erosion, based on ⁷Be activities, and observed rill initiation times, our results suggest that the use of ⁷Be tracer has the potential to accurately quantify the processes of erosion from bare, loessal cultivated slopes and of deposition in flatter, downslope areas that occur in single rainfall events. Such measurements could be applied to estimate longer‐term erosion occurring over larger areas possessing similar landforms. Copyright © 2010 John Wiley & Sons, Ltd.     

Characterization of rainfall generated by dripper‐type rainfall simulator using piezoelectric transducers and its impact on splash soil erosion

Rainfall erosivity represents the primary driver for particle detachment in splash soil erosion. Several raindrop erosivity indices have been developed in order to quantify the potential of rainfall to cause soil erosion. Different types of rainfall simulators have been used to relate rainfall characteristics to soil detachment. However, rainfall produced by different rainfall simulators has different characteristics, specifically different relationships between rainfall intensity and rainfall erosivity. For this reason, the effect of rainfall characteristics produced by a dripper‐type rainfall simulator on splash soil erosion (D_s) has been investigated. The simulated rainfall kinetic energy (KE) and drop size distribution (DSD) were measured using piezoelectric transducers, modified from the Vaisala RAINCAP^® rain sensor. The soil splash was evaluated under various simulated rainfall intensities ranging from 10 to 100 mm h^?1 using the splash‐cup method. The simulated rainfall intensity (I) and kinetic energy relationship (I–KE) was found to be different from natural rainfall. The simulated rainfall intensity and splash soil erosion relationship (I–D_s) also followed this same trend. The I–KE relationship was found to follow the natural rainfall trend until the rainfall intensity reached 30 mm h^?1 and above this limit the KE started to decrease. This emphasizes the importance of the I–KE relationship in determining the I‐D_s relationship, which can differ from one rainfall simulator to another. D_s was found to be highly correlated with KE (r = 0·85, P < 0·001), when data produced by the rainfall intensity ranged from 10 to 100 mm h^?1. However, when the threshold rainfall intensity (30 mm h^?1) was considered, the correlation coefficient further improved (r = 0·89, P = 0·001). Accordingly, to improve the soil splash estimation of simulated rainfall under various rainfall intensities the I–KE characterization relationship for rainfall simulators has to be taken into account. Copyright © 2010 John Wiley & Sons, Ltd.     

Estimation of soil losses within plots as affected by different agricultural land management

Abstract

Proper agricultural land management strategies improve soil structural properties, thereby reducing soil loss by water erosion. This study was conducted to estimate soil losses from plots of different agricultural land management using the Water Erosion Prediction Project (WEPP) (95.7) model. The study took place in a semiarid region in Kenya. The mean annual rainfall was 694 mm. The WEPP (95.7) model was initially used to estimate total sediment loading from the catchment into a reservoir. The estimate was about 2871 t corresponding to an average sedimentation rate of 1063 t km^?2 year^?1, which was about 76% of the measured total sediment inflow into the reservoir. Soil losses were estimated within 10 plots on the catchment of different sizes and slopes with the following treatments: conventional tillage (hand hoeing) with maize and soybean intercropping (HOCOBE); conservation tillage (disc plough) with maize and soybean intercropping (COBEAN); conservation tillage with only maize cultivation (CNTCORN); and conservation tillage with only soybean cultivation (CNTBEAN). The soil loss reduction of COBEAN, CNTCORN and CNTBEAN relative to HOCOBE ranged between 27–47%, 16–29% and 12–25%, respectively, depending on the size and slope of the plot. In general, conservation tillage reduced soil loss relative to conventional tillage. However, with conservation tillage, the single cropping system resulted in greater soil loss than the intercropping system. In the case of single cropping with conservation tillage, the soil loss reduction for maize ranged between 4 and 9%, relative to soybean. Overall, the study showed that there would be a significant reduction of soil losses from plots if conservation tillage with an intercropping system (maize and soybean) were to be adopted on agricultural lands in semiarid regions.     

Spatial distribution and temporal trends of rainfall and erosivity in the Eastern Africa region

Soil erosion by water is one of the main environmental concerns in the drought‐prone Eastern Africa region. Understanding factors such as rainfall and erosivity is therefore of utmost importance for soil erosion risk assessment and soil and water conservation planning. In this study, we evaluated the spatial distribution and temporal trends of rainfall and erosivity for the Eastern Africa region during the period 1981–2016. The precipitation concentration index, seasonality index, and modified Fournier index have been analysed using 5 × 5‐km resolution multisource rainfall product (Climate Hazards Group InfraRed Precipitation with Stations). The mean annual rainfall of the region was 810 mm ranging from less than 300 mm in the lowland areas to over 1,200 mm in the highlands being influenced by orography of the Eastern Africa region. The precipitation concentration index and seasonality index revealed a spatial pattern of rainfall seasonality dependent on latitude, with a more pronounced seasonality as we go far from the equator. The modified Fournier index showed high spatial variability with about 55% of the region subject to high to very high rainfall erosivity. The mean annual R‐factor in the study region was calculated at 3,246 ± 1,895 MJ mm ha^?1 h^?1 yr^?1, implying a potentially high water erosion risk in the region. Moreover, both increasing and decreasing trends of annual rainfall and erosivity were observed but spatial variability of these trends was high. This study offers useful information for better soil erosion prediction as well as can support policy development to achieve sustainable regional environmental planning and management of soil and water resources.     

Assessment of the impact of different vegetation patterns on soil erosion processes on semiarid loess slopes

Soil erosion hinders the recovery and development of ecosystems in semiarid regions. Rainstorms, coupled with the absence of vegetation and improper land management, are important causes of soil erosion in such areas. Greater effort should be made to quantify the initial erosion processes and try to find better solutions for soil and water conservation. In this research, 54 rainfall simulations were performed to assess the impacts of vegetation patterns on soil erosion in a semiarid area of the Loess Plateau, China. Three rainfall intensities (15 mm h^‐1, 30 mm h^‐1 and 60 mm h^‐1) and six vegetation patterns (arbors‐shrubs‐grass ‐A‐S‐G‐, arbors‐grass‐shrubs ‐A‐G‐S‐, shrubs‐arbors‐grass ‐S‐A‐G‐, shrubs‐grass‐arbors ‐S‐G‐A‐, grass‐shrubs‐arbors ‐G‐S‐A‐ and grass‐arbors‐shrubs ‐G‐A‐S‐) were examined at different slope positions (summits, backslopes and footslopes) in the plots (33.3%, 33.3%, 33.3%), respectively. Results showed that the response of soil erosion to rainfall intensity differed under different vegetation patterns. On average, increasing rainfall intensity by 2 to 4 times induced increases of 3.1 to 12.5 times in total runoff and 6.9 to 46.4 times in total sediment yield, respectively. Moreover, if total biomass was held constant across the slope, the patterns of A‐G‐S and A‐S‐G (planting arbor at the summit position) had the highest runoff (18.34 L m^‐2 h^‐1) and soil losses (197.98 g m^‐2 h^‐1), while S‐A‐G had the lowest runoff (5.51 L m^‐2 h^‐1) and soil loss (21.77 g m^‐2 h^‐1). As indicated by redundancy analysis (RDA) and Pearson correlation results, a greater volume of vegetation located on the back‐ and footslopes acted as effective buffers to prevent runoff generation and sediment yield. Our findings indicated that adjusting vegetation position along slopes can be a crucial tool to control water erosion and benefit ecosystem restoration on the Loess Plateau and other similar regions of the world. Copyright © 2018 John Wiley & Sons, Ltd.     

Modelling streamflow trends for a watershed with limited data: case of the Litani basin,Lebanon

Abstract

Streamflow variability in the Upper and Lower Litani basin, Lebanon was modelled as there is a lack of long-term measured runoff data. To simulate runoff and streamflow, daily rainfall was derived using a stochastic rainfall generation model and monthly rainfall data. Two distinct synthetic rainfall models were developed based on a two-part probabilistic distribution approach. The rainfall occurrence was described by a Markov chain process, while the rainfall distribution on wet days was represented by two different distributions (i.e. gamma and mixed exponential distributions). Both distributions yielded similar results. The rainfall data were then processed using water balance and routing models to generate daily and monthly streamflow. Compared with measured data, the model results were generally reasonable (mean errors ranging from 0.1 to 0.8?m³/s at select locations). Finally, the simulated monthly streamflow data were used to investigate discharge trends in the Litani basin during the 20th century using the Mann-Kendall and Sen slope nonparametric trend detection methods. A significant drying trend of the basin was detected, reaching a streamflow reduction of 0.8 and 0.7 m³/s per decade in January for the Upper and Lower basin, respectively.

Editor D. Koutsoyiannis; Associate editor Sheng Yue

Citation Ramadan, H.H., Beighley, R.E., and Ramamurthy, A.S., 2012. Modelling streamflow trends for a watershed with limited data: case of the Litani basin, Lebanon. Hydrological Sciences Journal, 57 (8), 1516–1529.     

A new procedure to estimate the RUSLE EI30 index, based on monthly rainfall data and applied to the Algarve region, Portugal

One of the best indicators of the potential erosion risks is the rainfall–runoff erosivity factor (R) of the revised universal soil loss equation (RUSLE). Frequently, however, there is not enough data available to compute the R value, and other parameters, such as the modified Fournier index (F_mod), are used instead. But RUSLE is less effective if only the alternative procedures exist. One of the major discrepancies between R and the alternative parameters is time resolution: individual storms are used to calculate R while monthly averages over the year are used to calculate F_mod.

In this study, a multiple linear regression (r²=0.89) involving monthly EI₃₀, monthly rainfall for days with ≥10.0 mm and monthly number of days with rainfall ≥10.0 mm, for the Algarve region, is presented. Twenty-seven years of monthly rainfall erosivity values were computed for the 32 standard daily-read raingauge stations of the Algarve region.     

Modelling soil erosion in tropical environments using remote sensing and geographical information systems

Abstract

Soil erosion probability maps were produced under various case scenarios by accounting for uncertainties in the data and in the decision rule, using the Universal Soil Loss Equation (USLE), remote sensing and geographical information systems (GIS). This objective was realized by applying the Bayesian Probability Theory within IDRISI, a raster based GIS. The outcomes were two continuous probability soil erosion maps ranging from zero to 1. Comparing these maps with an earlier study indicates that accounting for the uncertainties has, in general, decreased the probability of soil erosion. Based on average readings for specific sites on the maps, increases in erosion risk under the second case scenario have had the highest impact on the highlands that is in the central, eastern, and northern regions of Langkawi Island, Malaysia. Assuming a 10% risk, this impact has increased by 11.98, 11.83 and 5.741% for high, medium and low soil erosion risk areas on the island respectively.     

Impact of model simplifications on soil erosion predictions: application of the GLUE methodology to a distributed event‐based model at the hillslope scale

In this paper, we analyse how the performance and calibration of a distributed event‐based soil erosion model at the hillslope scale is affected by different simplifications on the parameterizations used to compute the production of suspended sediment by rainfall and runoff. Six modelling scenarios of different complexity are used to evaluate the temporal variability of the sedimentograph at the outlet of a 60 m long cultivated hillslope. The six scenarios are calibrated within the generalized likelihood uncertainty estimation framework in order to account for parameter uncertainty, and their performance is evaluated against experimental data registered during five storm events. The Nash–Sutcliffe efficiency, percent bias and coverage performance ratios show that the sedimentary response of the hillslope in terms of mass flux of eroded soil can be efficiently captured by a model structure including only two soil erodibility parameters, which control the rainfall and runoff production of suspended sediment. Increasing the number of parameters makes the calibration process more complex without increasing in a noticeable manner the predictive capability of the model. Copyright © 2015 John Wiley & Sons, Ltd.     

Modelling rainfall interception losses of three plantations in the Loess Plateau

The forest canopy affects the water entering the forest ecosystem by intercepting rainfall. This is especially pertinent in forests that depend on rainfall for their ecological water needs, quantifying and simulating interception losses provide critical insights into their ecological hydrological processes. In the semi-arid areas of the Loess Plateau, afforestation has become an effective ecological restoration measure. However, the rainfall interception process of these plantations is still unclear. To quantify and model the canopy interception of these plantations, we conducted a two-year rainfall redistribution measurement experiment in three typical plantations, including a deciduous broadleaf plantation (Robinia pseudoacacia) and two evergreen coniferous plantations (Platycladus orientalis and Pinus tabuliformis). Based on this, the revised Gash model was used to simulate their interception losses, and the model applicability across varying rainfall types was further compared and verified. The experiment clarified the rainfall redistribution in the three plantations, and the proportions of throughfall to gross rainfall in Robinia pseudoacacia, Platycladus orientalis, and Pinus tabuliformis were 84.8%, 70.4%, and 75.6%; corresponding, the stemflow proportions were 2.0%, 2.2%, and 1.8%; the interception losses were 13.2%, 27.4%, and 22.6%, respectively. The dominant rainfall pattern during the experiment was characterized by low-amounts, moderate-intensity, and short-duration, during which the highest interception proportions across the three plantations were observed. We used the Penman-Monteith equation and the regression method, respectively, to estimate the canopy average evaporation rate of the revised Gash model, finding that the latter provides a closer match to the measured cumulative interception (NSE >0.7). When simulating interception under the three rainfall patterns, the model with the regression method better simulated the cumulative interception and event-scale interception for Platycladus orientalis and Pinus tabuliformis plantations under the dominant rainfall pattern. The results contribute valuable information to assess the impact of forest rainfall interception on regional hydrologic processes.