COMPARISON OF MEASURED SOIL 137-CESIUM LOSSES AND EROSION RATES

1987 ◽  
Vol 67 (1) ◽  
pp. 199-203 ◽  
Author(s):  
R. G. KACHANOSKI
Keyword(s):  
Atmospheric Deposition ◽  
Soil Loss ◽  
Accurate Method ◽  
Soil Samples ◽  
Deposition Rates ◽  
Southern Ontario ◽  
Erosion Rates ◽  
Soil Losses ◽  
Runoff Plots

Atmospheric deposition rates of 90Sr and analysis of soil samples from non-eroded sites indicated base levels of total soil 137Cs were approximately 2700 Bq m−2 in southern Ontario in 1985. Measured 137Cs losses (1965–1976) from long-term runoff plots were significantly correlated to measured soil losses during the same period. Monitoring temporal changes in soil 137Cs should be an accurate method of estimating soil loss in southern Ontario. Key words: Soil loss, 137Cs, Ontario, runoff plots

COMPARISON OF PREDICTED AND MEASURED SHEET AND RILL EROSION LOSSES IN SOUTHERN ONTARIO

1979 ◽  
Vol 59 (2) ◽  
pp. 211-213 ◽  
Author(s):  
L. J. P. VAN VLIET ◽  
G. J. WALL
Keyword(s):  
Soil Loss ◽  
Universal Soil Loss Equation ◽  
Rill Erosion ◽  
Southern Ontario ◽  
Loss Data ◽  
Soil Losses ◽  
Runoff Plots ◽  
Soil Loss Equation

Sheet and rill erosion losses evaluated by the universal soil loss equation were compared with 4–6 yr of measured soil loss data from runoff-plots at two locations in southern Ontario. Results indicated no significant differences (P = 0.10) between predicted and measured soil losses.

scholarly journals Soil erosion by snow gliding – a first quantification attempt in a subalpine area in Switzerland

2014 ◽  
Vol 18 (9) ◽  
pp. 3763-3775 ◽  
Author(s):  
K. Meusburger ◽  
G. Leitinger ◽  
L. Mabit ◽  
M. H. Mueller ◽  
A. Walter ◽  
...  
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Land Cover ◽  
Sediment Yield ◽  
Soil Loss ◽  
Water Erosion ◽  
Erosion Rates ◽  
The Difference ◽  
Snow Gliding

Abstract. Snow processes might be one important driver of soil erosion in Alpine grasslands and thus the unknown variable when erosion modelling is attempted. The aim of this study is to assess the importance of snow gliding as a soil erosion agent for four different land use/land cover types in a subalpine area in Switzerland. We used three different approaches to estimate soil erosion rates: sediment yield measurements in snow glide depositions, the fallout radionuclide 137Cs and modelling with the Revised Universal Soil Loss Equation (RUSLE). RUSLE permits the evaluation of soil loss by water erosion, the 137Cs method integrates soil loss due to all erosion agents involved, and the measurement of snow glide deposition sediment yield can be directly related to snow-glide-induced erosion. Further, cumulative snow glide distance was measured for the sites in the winter of 2009/2010 and modelled for the surrounding area and long-term average winter precipitation (1959–2010) with the spatial snow glide model (SSGM). Measured snow glide distance confirmed the presence of snow gliding and ranged from 2 to 189 cm, with lower values on the north-facing slopes. We observed a reduction of snow glide distance with increasing surface roughness of the vegetation, which is an important information with respect to conservation planning and expected and ongoing land use changes in the Alps. Snow glide erosion estimated from the snow glide depositions was highly variable with values ranging from 0.03 to 22.9 t ha−1 yr−1 in the winter of 2012/2013. For sites affected by snow glide deposition, a mean erosion rate of 8.4 t ha−1 yr−1 was found. The difference in long-term erosion rates determined with RUSLE and 137Cs confirms the constant influence of snow-glide-induced erosion, since a large difference (lower proportion of water erosion compared to total net erosion) was observed for sites with high snow glide rates and vice versa. Moreover, the difference between RUSLE and 137Cs erosion rates was related to the measured snow glide distance (R2 = 0.64; p < 0.005) and to the snow deposition sediment yields (R2 = 0.39; p = 0.13). The SSGM reproduced the relative difference of the measured snow glide values under different land uses and land cover types. The resulting map highlighted the relevance of snow gliding for large parts of the investigated area. Based on these results, we conclude that snow gliding appears to be a crucial and non-negligible process impacting soil erosion patterns and magnitude in subalpine areas with similar topographic and climatic conditions.

scholarly journals Uso de Técnicas de Geoprocessamento para Estudo da Erosão Hídrica Laminar em Bacia Hidrográfica do Sudoeste do Paraná.

2020 ◽  
Vol 13 (3) ◽  
pp. 1117
Author(s):  
Julio Caetano Tomazoni ◽  
Ana Paula Vansan
Keyword(s):  
Soil Erosion ◽  
Soil Conservation ◽  
Soil Loss ◽  
Satellite Images ◽  
Water Erosion ◽  
Soil Samples ◽  
Universal Equation ◽  
Erosion Rates ◽  
Loss Estimate

Este trabalho tem como objetivo avaliar a erosão hídrica laminar do solo, por meio da Equação Universal de Perdas de Solos Revisada (RUSLE) na bacia hidrográfica do rio São José, localizada no município de Francisco Beltrão (PR).  A perda de solo média anual (A) foi determinada através da RUSLE para os anos 2000, 2005, 2009, 2015 e 2017 utilizando-se técnicas de geoprocessamento com o auxílio do software ArcGis 10.0. O fator erosividade da chuva (R) foi determinado utilizando-se dados pluviométricos correspondentes ao período de 1974 a 2016. O fator erodibilidade do solo (K) foi obtido através da análise de amostras de solo coletadas in loco. O fator topográfico (LS) foi estimado por meio dos dados altimétricos e hidrográficos da bacia. Os fatores de uso e manejo do solo (C) e de práticas conservacionistas do solo (P) foram determinados por meio da caracterização multitemporal do uso e ocupação do solo, através de imagens de satélite. O potencial natural de erosão (PNE) foi determinado pela multiplicação dos fatores R, K e LS.A estimativa de perda de solo (A) foi determinada pela multiplicação do PNE pelos fatores C e P.  Use of Geoprocessing Techniques to Study Laminar Water Erosion in Watershed of Southwest Paraná A B S T R A C TThe objective of this work is evaluate the soil erosion by the Universal Equation of Soil Losses Revised (RUSLE) in the São José river basin, located in the municipality of Francisco Beltrão (PR). The average annual soil loss (A) was determined through RUSLE for the years 2000, 2005, 2009, 2015 and 2017 using geoprocessing techniques with ArcGis 10.0 software. Rainfallerosivity (R) was determined using rainfall data from 1974 to 2016, being determined at 11521.26 11521,26 MJ.mm.ha-1.h-1.year-1. The soil erodibility factor (K) was obtained through the analysis of soil samples collected on the spot (0,03018 t.ha.h/ha.MJ.mm, 0,02771 t.ha.h/ha.MJ.mm e 0,02342 t.ha.h/ha.MJ.mm). The topographic factor (LS) was estimated by the altimetric and hydrographic data of the basin. Soil use and management (C) and soil conservation (P) were determined through multitemporal characterization of land use and occupation, using satellite images. The natural erosion potential (NEP) was determined by multiplying the R, K and LS factors, with more than half of the total area of the watershed with very strong PNE. The soil loss estimate (A) was determined by multiplying the NEP by factors C and P with predominance of the class called low (0 to 10 t/ha/year) denoting the reduction of erosion rates through factors C and P, helping to protect the soil from the erosion process.Key words: Soil Erosion; Watershed, Revised Universal Soil Loss Equation, Geoprocessing, Software.

Using 137Cs to investigate net soil erosion at two soil benchmark sites in Quebec

1993 ◽  
Vol 73 (4) ◽  
pp. 515-526 ◽  
Author(s):  
Y. Z. Cao ◽  
D. R. Coote ◽  
C. Wang ◽  
M. C. Nolin
Keyword(s):  
Soil Erosion ◽  
Key Words ◽  
Soil Conservation ◽  
Soil Loss ◽  
Soil Samples ◽  
Grid Pattern ◽  
Erosion Rates ◽  
The Past ◽  
Soil Erosion Rates ◽  
Small Grains

137Cs in the soil was used to estimate soil erosion at two National Soil Conservation Program benchmark sites in the province of Quebec (sites 15-QU and 16-QU). The 137Cs baseline in an uneroded forest area was approximately 3100 Bq m−2. The 137Cs content at site 15-QU ranged from 1072 Bq m−2 to 6389 Bq m−2, while at site 16-QU it ranged from 663 Bq m−2 to 5444 Bq m−2. Computed net erosion over the past 30 yr at site 15-QU varied from a loss of 9.65 kg m−2 yr−1 to a gain of 10.88 kg m−2 yr−1 and at site 16-QU from a loss of 6.38 kg m−2 yr−1 to a gain of 1.73 kg m−2 yr−1. The average net erosion rates were 2.43 kg m−2 yr−1 at site 15-QU and 1.29 kg m−2 yr−1 at site 16-QU. Soil samples collected on a grid pattern indicated that 90% and 83% of the area at sites 15-QU and 16-QU, respectively, was subjected to net soil loss. A comparison of total 137Cs movement from eroded areas to depositional areas showed that 24.2% of 137Cs was lost from site 15-QU, while about 17.6% of 137Cs was lost from site 16-QU. Mapping of 137Cs content and calculated soil loss and deposition showed that soil erosion was closely related to topography.Under similar slope conditions, the soil erosion rates were 27–68% higher at site 15-QU than at site 16-QU. Higher tillage frequency and use of silage corn were the suggested reasons for the higher soil erosion rates at site 15-QU compared with site 16-QU, which had been used for hay and small grains. Key words: 137Cs, erosion, deposition, soil conservation

Erosion rates evaluated by the 137Cs technique and direct measurements on long-term runoff plots under tropical conditions

2006 ◽  
Vol 86 (2) ◽  
pp. 199-208 ◽  
Author(s):  
V. Correchel ◽  
O.O.S. Bacchi ◽  
I.C. De Maria ◽  
S.C.F. Dechen ◽  
K. Reichardt
Keyword(s):  
Erosion Rates ◽  
Direct Measurements ◽  
Tropical Conditions ◽  
137Cs Technique ◽  
Runoff Plots

scholarly journals High natural erosion rates are the backdrop for present-day soil erosion in the agricultural Middle Hills of Nepal

2015 ◽  
Vol 3 (3) ◽  
pp. 363-387 ◽  
Author(s):  
A. J. West ◽  
M. Arnold ◽  
G. AumaÎtre ◽  
D. L. Bourlès ◽  
K. Keddadouche ◽  
...  
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Soil Loss ◽  
Mass Wasting ◽  
Catchment Scale ◽  
Erosion Rates ◽  
Denudation Rates ◽  
Soil Production ◽  
The Himalaya

Abstract. Although agriculturally accelerated soil erosion is implicated in the unsustainable environmental degradation of mountain environments, such as in the Himalaya, the effects of land use can be challenging to quantify in many mountain settings because of the high and variable natural background rates of erosion. In this study, we present new long-term denudation rates, derived from cosmogenic 10Be analysis of quartz in river sediment from the Likhu Khola, a small agricultural river basin in the Middle Hills of central Nepal. Calculated long-term denudation rates, which reflect background natural erosion processes over 1000+ years prior to agricultural intensification, are similar to present-day sediment yields and to soil loss rates from terraces that are well maintained. Similarity in short- and long-term catchment-wide erosion rates for the Likhu is consistent with data from elsewhere in the Nepal Middle Hills but contrasts with the very large increases in short-term erosion rates seen in agricultural catchments in other steep mountain settings. Our results suggest that the large sediment fluxes exported from the Likhu and other Middle Hills rivers in the Himalaya are derived in large part from natural processes, rather than from soil erosion as a result of agricultural activity. Catchment-scale erosional fluxes may be similar over short and long timescales if both are dominated by mass wasting sources such as gullies, landslides, and debris flows (e.g., as is evident in the landslide-dominated Khudi Khola of the Nepal High Himalaya, based on compiled data). As a consequence, simple comparison of catchment-scale fluxes will not necessarily pinpoint land use effects on soils where these are only a small part of the total erosion budget, unless rates of mass wasting are also considered. Estimates of the mass wasting contribution to erosion in the Likhu imply catchment-averaged soil production rates on the order of ~ 0.25–0.35 mm yr−1, though rates of mass wasting are poorly constrained. The deficit between our best estimates for soil production rates and measurements of soil loss rates supports conclusions from previous studies that terraced agriculture in the Likhu may not be associated with a large systematic soil deficit, at least when terraces are well maintained, but that poorly managed terraces, forest, and scrubland may lead to rapid depletion of soil resources.

scholarly journals A systematic assessment of uncertainties in large scale soil loss estimation from different representations of USLE input factors – A case study for Kenya and Uganda

2019 ◽  
Author(s):  
Christoph Schürz ◽  
Bano Mehdi ◽  
Jens Kiesel ◽  
Karsten Schulz ◽  
Mathew Herrnegger
Keyword(s):  
Sensitivity Analysis ◽  
Spatial Patterns ◽  
Soil Loss ◽  
Field Data ◽  
Large Scale ◽  
Small Scale ◽  
Model Input ◽  
Study Results ◽  
Soil Losses

Abstract. The Universal Soil Loss Equation (USLE) is the most commonly used model to assess soil erosion by water. The model equation quantifies long-term average annual soil loss as a product of the rainfall erosivity R, soil erodibility K, slope length and steepness LS, soil cover C and support measures P. A large variety of methods exist to derive these model inputs from readily available data. However, the estimated values of a respective model input can strongly differ when employing different methods and can eventually introduce large uncertainties in the estimated soil loss. The potential to evaluate soil loss estimates at a large scale are very limited, due to scarce in-field observations and their comparability to long-term soil estimates. In this work we addressed (i) the uncertainties in the soil loss estimates that can potentially be introduced by different representations of the USLE input factors and (ii) challanges that can arise in the evaluation of uncertain soil loss estimates with observed data. In a systematic analysis we developed different representations of USLE inputs for the study domain of Kenya and Uganda. All combinations of the generated USLE inputs resulted in 756 USLE model setups. We assessed the resulting distributions in soil loss, both spatially distributed and on district level for Kenya and Uganda. In a sensitivity analysis we analyzed the contributions of the USLE model inputs to the ranges in soil loss and analyzed their spatial patterns. We compared the calculated USLE ensemble soil estimates to available in-field data and other study results and addressed possibilities and limitations of the USLE model evaluation. The USLE model ensemble resulted in wide ranges of estimated soil loss, exceeding the mean soil loss by over an order of magnitude particularly in hilly topographies. The study implies that a soil loss assessment with the USLE is highly uncertain and strongly depends on the realizations of the model input factors. The employed sensitivity analysis enabled us to identify spatial patterns in the importance of the USLE input factors. The C and K factors showed large scale patterns of importance in the densely vegetated part of Uganda and the dry north of Kenya, respectively, while LS was relevant in small scale heterogeneous patterns. Major challenges for the evaluation of the estimated soil losses with in-field data were due to spatial and temporal limitations of the observation data, but also due to measured soil losses describing processes that are different to the ones that are represented by the USLE.

scholarly journals Long-term forecast of changes in soil erosion losses during spring snowmelt caused by climate within the plain part of Ukraine

2020 ◽  
Vol 29 (3) ◽  
pp. 591-605
Author(s):  
Oleksandr A. Svetlitchnyi
Keyword(s):  
Soil Erosion ◽  
Snow Cover ◽  
21St Century ◽  
Soil Loss ◽  
Baseline Period ◽  
Average Value ◽  
Relative Change ◽  
Spring Snowmelt ◽  
Soil Losses

The paper deals with the forecast of changes in erosion soil losses during the spring snowmelt due to climate change in the regions of Ukraine in the middle of the 21st century (during 2031–2050) and at its end (during 2081–2100) compared with the values of the baseline period (1961–1990). The forecast is based on the use of the so-called “hydrometeorological factor of spring soil loss”. This factor is a part of the physical-statistical mathematical model of soil erosion lossduring spring snowmelt, developed at the Department of Physical Geography of Odesa I. I. Mechnikov State (since 2000 — National) University during the 1980s – 1990s. The long-term average value of the hydrometeorological factor is linearly related to the long-term average value of spring erosion soil loss. Therefore, the relative change in the hydrometeorological factor corresponds to the relative change in soil erosion losses. The developed methodology for assessing climate-induced changes in soil erosion losses in five regions of Ukraine (North, West, Center, East and South) takes into account the change in water equivalent of snow cover at the beginning of snow melting, the change in surface runoff and its turbidity, and changes in soil erodibility. The forecast of changes in erosion soil loss was carried out using projections of annual and monthly average air temperatures and precipitation for 2031–2050 and 2081–2100 in accordance with scenario A1B from AR4 of the IPCC. As a result of the research, it was found that both in the middle and at the end of the 21st century a decrease in the rate of soil erosion during the period of spring snowmelt is expected. During 2031–2050, the expected soil losses will be less than corresponding baseline period values within the West region by 79%, within the North and East regions by 81%, and within the Center region by 85%. In the South region, the spring soil losses will be zero due to the lack of snow cover. During 2081–2100 snow cover will be absent not only in the South region, but also in the Center and East regions. In the regions North and West snow cover will remain, but the spring soil erosion losses will decrease by dozens of times and will be so small that they can also be ignored.

scholarly journals A Review of the Science and Logic Associated with Approach Used in the Universal Soil Loss Equation Family of Models

Soil Systems ◽  
2019 ◽  
Vol 3 (4) ◽  
pp. 62 ◽  
Author(s):  
Kinnell
Keyword(s):  
Soil Loss ◽  
Agricultural Land ◽  
Universal Soil Loss Equation ◽  
Physical Situation ◽  
Rill Erosion ◽  
The Impact ◽  
Soil Losses ◽  
Soil Loss Equation ◽  
Rainfall Erosion

Soil erosion caused by rain is a major factor in degrading agricultural land, and agricultural practices that conserve soil should be used to maintain the long-term sustainability of agricultural land. The Universal Soil Loss Equation (USLE) was developed in the 1960s and 1970s to predict the long-term average annual soil loss from sheet and rill erosion on field-sized areas as an aid to making management decisions to conserve soil. The USLE uses six factors to take account of the effects of climate, soil, topography, crops, and crop management, and specific actions designed to conserve soil. Although initially developed as an empirical model based on data from more than 10,000 plot years of data collected in plot experiments in the USA, the selection of the independent factors used in the model was made taking account of scientific understanding of the drivers involved in rainfall erosion. In addition, assumptions and approximations were needed to make an operational model that met the needs of the decision makers at that time. Those needs have changed over time, leading to the development of the Revised USLE (RUSLE) and a second version of that, the Revised USLE, Version 2 (RUSLE2). While the original USLE model was not designed to predict short-term variations in erosion well, these developments have involved more use of conceptualization in order to deal with the time-variant impacts of the drivers involved in rainfall erosion. The USLE family of models is based on the concept that the “unit” plot, a bare fallow area 22.1 m long on a 9% slope gradient with cultivation up and down the slope, provides a physical situation where the effect of climate and soil on rainfall erosion can be determined without the need to consider the impact of the four other factors. The science and logic associated with this approach is reviewed. The manner by which the soil erodibility factor is determined from plot data ensures that the long-term average annual soil loss for the unit plot is predicted well, even when the assumption that event soil loss is directly related to the product of event rainfall energy, and the maximum 30-min intensity is not wholly appropriate. RUSLE2 has a capacity to use CLIGEN, the weather generator used in WEPP, and so can predict soil losses based on individual storms in a similar way to WEPP. Including a direct consideration of runoff in determining event erosivity enhances the ability to predict event soil losses when runoff is known or predicted well, but similar to more process-based models, this ability is offset by the difficulty in predicting runoff well.

scholarly journals Spatiotemporal Changes in Atmospheric Deposition Rates Across The Czech Republic Estimated in The Selected Biomonitoring Campaigns. Examples of Results Available For Landscape Ecology and Land Use Planning

2015 ◽  
Vol 8 (2) ◽  
pp. 10-28 ◽  
Author(s):  
Ivan Suchara ◽  
Julie Sucharová ◽  
Marie Holá
Keyword(s):  
Atmospheric Deposition ◽  
Hot Spots ◽  
Forest Floor ◽  
Isotopic Ratios ◽  
Emission Sources ◽  
Deposition Rates ◽  
The Czech Republic ◽  
Spruce Bark ◽  
Moss Monitoring

AbstractSeveral large-scale and fine-scale biomonitoring surveys were carried out in the Czech Republic to estimate current and long-term accumulated atmospheric deposition rates using moss, spruce bark and forest floor humus as bioindicators since the end of 1980s. The results of the bioindicator analyses significantly correlated with available figures of deposition rates detected at the EMEP or Czech national measurement stations.The moss monitoring programmes revealed position of about 7 hot spots of high deposition loads of about 35-40 elements and indicated spatiotemporal decrease in the element deposition rates caused by restructuralization of industry, desulphurization of coal power plants and ceased distribution of leaded petrol. The deposition loads of toxic and risk elements have significantly decreased since the end of 1980s; however, increasing atmospheric deposition rates of reactive nitrogen has been bioindicated recently. The fine-scale moss monitoring campaigns, for example, delimited deposition zones around selected emission sources, revealed changes in deposition rates after introducing new technologies or delimited contaminated area in the surroundings of a chlor-alkali plant after a catastrophic flood episode. Deposition ranges of main pollution sources were mapped depicting the aerial distribution of stable lead isotopic ratios in moss, because the isotopic ratios are highly specific for each pollution source.Monitoring the spruce bark parameters enabled to recognise the distribution of acid rain, dust and sulphate deposition rates and their spatiotemporal changes across the country between 1987 and 2010. The bark investigations along altitudinal profiles showed diminishing effect of air pollution on spruce bark parameters with increasing elevation. This phenomenon can be explained by a decreasing capacity of reduced tree crowns to trap air pollutants in the mountain environment.The mapping of element content in forest floor humus revealed position of long-term spots of high accumulation of industrial pollutants and Chernobyl-derived137Cs in forests. Knowledge of these hot spots is important for health and environmental protection mainly in the areas where most of the former emission sources were cancelled and the current low atmospheric deposition rates may make a false impression of the clean landscape.The data of the Czech national moss biomonitoring surveys were accepted and stored in the database of UN ECE ICP-Vegetation for checking of air pollution and its possible effects on vegetation in Europe.

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