Modelling soil losses from the ardeche rangelands

Soil erosion remains one of the principal environmental problems in arid regions. This study aims to assess and quantify the variability of soil erosion in the Koutine catchment using the RUSLE (Revised Universal Soil Loss Equation) model. The Koutine catchment is located in an arid area in southeastern Tunisia and is characterized by an annual mean precipitation of less than 200 mm. The model was used to examine the influence of topography, extreme rainstorm intensity and soil texture on soil loss. The data used for model validation were obtained from field measurements by monitoring deposited sediment in settlement basins of 25 cisterns (a traditional water harvesting and storage technique) over 4 years, from 2015 to 2018. Results showed that slope is the most controlling factor of soil loss. The average annual soil loss in monitoring sites varies between 0.01 and 12.5 t/ha/y. The storm events inducing the largest soil losses occurred in the upstream part of the Koutine catchment with a maximum value of 7.3 t/ha per event. Soil erosion is highly affected by initial and preceding soil conditions. The RUSLE model reasonably reproduced (R2 = 0.81) the spatiotemporal variability of measured soil losses in the study catchment during the observation period. This study revealed the importance of using the cisterns in the data-scarce dry areas as a substitute for the classic soil erosion monitoring fields. Besides, combining modeling of outputs and field measurements could improve our physical understanding of soil erosion processes and their controlling factors in an arid catchment. The study results are beneficial for decision-makers to evaluate the existing soil conservation and water management plans, which can be further adjusted using appropriate soil erosion mitigation options based on scientific evidence.

Download Full-text

Soil losses and runoff variabilities in varieties of surface coverages

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/686/1/012022 ◽

2021 ◽

Vol 686 (1) ◽

pp. 012022

Author(s):

R Tirtalistyani ◽

Ngadisih ◽

R Irhamnia ◽

E W Alfiani

Keyword(s):

Soil Losses

Download Full-text

Use of satellite and modeled soil moisture data for predicting event soil loss at plot scale

Hydrology and Earth System Sciences ◽

10.5194/hess-19-3845-2015 ◽

2015 ◽

Vol 19 (9) ◽

pp. 3845-3856 ◽

Cited By ~ 9

Author(s):

F. Todisco ◽

L. Brocca ◽

L. F. Termite ◽

W. Wagner

Keyword(s):

Soil Moisture ◽

Soil Loss ◽

Large Scale ◽

Central Italy ◽

Remote Sensing Data ◽

Loss Estimation ◽

Balance Model ◽

Estimation Accuracy ◽

Soil Losses

Abstract. The potential of coupling soil moisture and a Universal Soil Loss Equation-based (USLE-based) model for event soil loss estimation at plot scale is carefully investigated at the Masse area, in central Italy. The derived model, named Soil Moisture for Erosion (SM4E), is applied by considering the unavailability of in situ soil moisture measurements, by using the data predicted by a soil water balance model (SWBM) and derived from satellite sensors, i.e., the Advanced SCATterometer (ASCAT). The soil loss estimation accuracy is validated using in situ measurements in which event observations at plot scale are available for the period 2008–2013. The results showed that including soil moisture observations in the event rainfall–runoff erosivity factor of the USLE enhances the capability of the model to account for variations in event soil losses, the soil moisture being an effective alternative to the estimated runoff, in the prediction of the event soil loss at Masse. The agreement between observed and estimated soil losses (through SM4E) is fairly satisfactory with a determination coefficient (log-scale) equal to ~ 0.35 and a root mean square error (RMSE) of ~ 2.8 Mg ha−1. These results are particularly significant for the operational estimation of soil losses. Indeed, currently, soil moisture is a relatively simple measurement at the field scale and remote sensing data are also widely available on a global scale. Through satellite data, there is the potential of applying the SM4E model for large-scale monitoring and quantification of the soil erosion process.

Download Full-text

Biopolymer additives to reduce erosion-induced soil losses during irrigation

Industrial Crops and Products ◽

10.1016/s0926-6690(99)00030-8 ◽

2000 ◽

Vol 11 (1) ◽

pp. 19-29 ◽

Cited By ~ 70

Author(s):

William J. Orts ◽

Robert E. Sojka ◽

Gregory M. Glenn

Keyword(s):

Soil Losses

Download Full-text

Identifying erosive periods by using RUSLE factors in mountain fields of the Central Spanish Pyrenees

Hydrology and Earth System Sciences ◽

10.5194/hess-12-523-2008 ◽

2008 ◽

Vol 12 (2) ◽

pp. 523-535 ◽

Cited By ~ 53

Author(s):

M. López-Vicente ◽

A. Navas ◽

J. Machín

Keyword(s):

Soil Moisture ◽

Moisture Content ◽

Soil Loss ◽

Rainfall Intensity ◽

Soil Moisture Content ◽

Rainfall Erosivity ◽

Soil Erodibility ◽

Maximum Rainfall ◽

Freeze Thaw ◽

Soil Losses

Abstract. The Mediterranean environment is characterized by strong temporal variations in rainfall volume and intensity, soil moisture and vegetation cover along the year. These factors play a key role on soil erosion. The aim of this work is to identify different erosive periods in function of the temporal changes in rainfall and runoff characteristics (erosivity, maximum intensity and number of erosive events), soil properties (soil erodibility in relation to freeze-thaw processes and soil moisture content) and current tillage practices in a set of agricultural fields in a mountainous area of the Central Pyrenees in NE Spain. To this purpose the rainfall and runoff erosivity (R), the soil erodibility (K) and the cover-management (C) factors of the empirical RUSLE soil loss model were used. The R, K and C factors were calculated at monthly scale. The first erosive period extends from July to October and presents the highest values of erosivity (87.8 MJ mm ha−1 h−1), maximum rainfall intensity (22.3 mm h−1) and monthly soil erosion (0.25 Mg ha−1 month−1) with the minimum values of duration of erosive storms, freeze-thaw cycles, soil moisture content and soil erodibility (0.007 Mg h MJ−1 mm−1). This period includes the harvesting and the plowing tillage practices. The second erosive period has a duration of two months, from May to June, and presents the lowest total and monthly soil losses (0.10 Mg ha−1 month−1) that correspond to the maximum protection of the soil by the crop-cover ($C$ factor = 0.05) due to the maximum stage of the growing season and intermediate values of rainfall and runoff erosivity, maximum rainfall intensity and soil erodibility. The third erosive period extends from November to April and has the minimum values of rainfall erosivity (17.5 MJ mm ha−1 h−1) and maximum rainfall intensity (6.0 mm h−1) with the highest number of freeze-thaw cycles, soil moisture content and soil erodibility (0.021 Mg h MJ−1 mm−1) that explain the high value of monthly soil loss (0.24 Mg ha−1 month−1). The interactions between the rainfall erosivity, soil erodibility, and cover-management factors explain the similar predicted soil losses for the first and the third erosive periods in spite of the strong temporal differences in the values of the three RUSLE factors. The estimated value of annual soil loss with the RUSLE model (3.34 Mg ha−1 yr−1) was lower than the measured value with 137Cs (5.38 Mg ha−1 yr−1) due to the low values of precipitation recorded during the studied period. To optimize agricultural practices and to promote sustainable strategies for the preservation of fragile Mediterranean agrosystems it is necessary to delay plowing till October, especially in dryland agriculture regions. Thus, the protective role of the crop residues will extend until September when the greatest rainfall occurs together with the highest runoff erosivity and soil losses.

Download Full-text

Soil and Water Loss Rates in Oxisols Under No-tillage System in Western Paraná, Brazil

Journal of Agricultural Science ◽

10.5539/jas.v10n10p132 ◽

2018 ◽

Vol 10 (10) ◽

pp. 132

Author(s):

Luana Salete Celante ◽

Deonir Secco ◽

Aracéli Ciotti de Marins ◽

Daniela Trentin Nava ◽

Flávio Gurgacz ◽

...

Keyword(s):

Water Loss ◽

Soil Loss ◽

No Tillage ◽

Linear Regression Models ◽

Water Losses ◽

Soil And Water Loss ◽

Tillage System ◽

Soil Losses ◽

Soil And Water ◽

Loss Rates

The objective of work was to quantify soil and water loss rates as a function of slope variation, correlating these rates with soybean yield. In addition to developing multiple linear regression models that associate water and soil loss rates in function of their physical attributes. The experiment was conducted in an Oxisols under a no-tillage system. The experiment was carried out in Cascavel, PR, Brazil. Four slopes (3.5%; 8.2%; 11.4% and 13.5%) were considered as treatments. The water and soil loss rates were monitored in the rainfall occurring during the crop development cycle. The water drained in each plot was collected in gutters made of polyvinyl chloride and stored in containers for the quantification of soil and water losses. The stepwise backward method was used to identify the variables that had a significant influence on water and soil losses. The unevenness of the terrain did not influence the soil and water loss rates. The maximum soil and water losses during the soybean cycle were, respectively, 0.01962 Mg ha-1 and 4.07 m3 ha-1. The maximum soil and water losses occurred when the precipitation volume was up to 82 mm. Soil and water losses showed a higher correlation with macroporosity and bulk density. Soybean grain yield showed a higher linear correlation with water, and soil loss and was higher at the slopes of 8.2% and 13.4%. The low water and soil losses demonstrate the soil capacity, managed under a no-tillage system, to minimize environmental impacts.

Download Full-text

MAGNITUDE OF SOIL LOSSES THROUGHOUT THE CARIBBEAN

The Journal of Agriculture of the University of Puerto Rico ◽

10.46429/jaupr.v79i1-2.4302 ◽

1969 ◽

Vol 79 (1-2) ◽

pp. 89-90

Author(s):

Miguel A. Lugo-López ◽

F. Abruña

Keyword(s):

The Caribbean ◽

Soil Losses

MAGNITUDE OF SOIL LOSSES THROUGHOUT THE CARIBBEAN

Download Full-text

Soil losses under simulated rainfall in semi-arid shrublands of the Ebro Valley, Spain

Soil Use and Management ◽

10.1111/j.1475-2743.1993.tb00946.x ◽

1993 ◽

Vol 9 (4) ◽

pp. 152-157 ◽

Cited By ~ 11

Author(s):

A. Navas

Keyword(s):

Simulated Rainfall ◽

Ebro Valley ◽

Arid Shrublands ◽

Semi Arid ◽

Soil Losses

Download Full-text

Long-term evaluation of cover crops on soil and runoff losses under trafficked conditions in olive orchards

10.5194/egusphere-egu21-606 ◽

2021 ◽

Author(s):

Jose Alfonso Gomez ◽

Gema Guzman

Keyword(s):

Cover Crops ◽

Cover Crop ◽

Soil Management ◽

Ground Vegetation ◽

Small Scale ◽

Erosion Processes ◽

Runoff Losses ◽

Hillslope Scale ◽

Soil Losses ◽

Runoff Plots

Maintenance of ground cover vegetation in olive orchards has been shown to reduce soil and runoff losses as compared to bare soil. However, extrapolation of its impact at hillslope scale under different conditions still challenging for several reasons. One is the limited duration of available experiments, usually shorter than 3 years, which can&#180;t capture the annual variability in precipitation typical of Mediterranean type of climate. A second reason is the small scale in which many experiments are carried out, which do not capture all the relevant erosion processes at hillslope scale. A third reason, hardly discussed, is the use of the runoff plots that limits traffic resulting in conditions that might not be fully representative of actual orchards.&#160;For evaluating the effect of temporary cover crops on water erosion processes in olives at hillslope scale, runoff and soil losses have been monitored from 2008 to 2019 in La Conchuela. This is an olive farm located in Southern Spain, where average annual precipitation is 655 mm, on Typic Haploxerert (clay content > 50%). Six runoff plots (14x24 m) delimited by steel beams on concrete foundation were established in a 13.4 % slope, containing 3 rows of 4 trees. This allows normal farm operations. Since 2008-2009, two soil management systems, conventional tillage (CT) and temporary cover crops (CC), were tested. In the two CT plots ground vegetation was controlled by 2-3chisel ploughing passes during the year. CC in the other four plots consisted of sowing manually in mid Fall a grass or a mix with grasses every 1 to 3 years without disturbing the soil surface, been mowed in early Spring. The aim of this cover crop was to be grown up spontaneously from seed produced the previous year. Weeds along the tree rows are controlled by herbicides in both cases.No significant differences were detected (p < 0.05) for the whole period, although CC showed lower runoff and soil losses values. Runoff data ranged from 157.7 &#177; 61.2 to 144.5 &#177; 46.4 mm, and soil losses varied from 24.3 &#177; 9.1 to 16.4 &#177; 7.0 t&#183;ha-1 at the CT and CC treatments respectively. The lack of statistical differences can be explained by the large variability recorded in the measurements at the six plots, especially at the CC due to the specific weather and traffic conditions. Our experiment shows how in a crop, olives, subject to intense traffic during the harvesting season (happening in late fall or early winter, rainy season) and in an orchard on heavy soils, maintenance of a good cover crop is challenging in many years. Our results call for caution when extrapolating the benefits of cover crops in olives from the experimental plots to real world conditions. It also highlights the need for improved soil management under these conditions (e.g. controlled traffic, combination with inert mulch, &#8230;) to improve soil and water conservation in intensively cultivated olive orchards in heavy soils.&#160;

Download Full-text