Assessing the impact of soil erosion on plant vigor (NDVI) and the spatial patterns of soil-bound Cu, Zn and B micro- and N, P macronutrients in a sloping vineyard (Tokaj, Hungary)

2021 ◽  
Author(s):  
Izabella Babcsányi ◽  
Ferenc Kovács ◽  
Szabolcs Juhász ◽  
Péter Balling ◽  
Nhung Pham Thi Ha ◽  
...  
Keyword(s):  
Organic Matter ◽  
Spatial Distribution ◽  
Soil Erosion ◽  
Soil Loss ◽  
Vegetation Indices ◽  
Moderate Degree ◽  
Nutrient Contents ◽  
Plant Vigor ◽  
Nitrate N ◽  
Nitrite Nitrate

<p>Soil erosion in sloping vineyards greatly influence the spatial distribution of soil nutrient contents and can affect plant nutrition and vigor. The study aimed to evaluate possible links between the grapevine (Vitis Vinifera) vigor and the erosion-impacted macro- and micronutrient contents in the topsoil. Our study combined field observations, laboratory measurements and remote sensing data.</p><p>The field experiment was performed in a 1.8 ha vineyard plot in Tokaj (NE Hungary) with a mean slope of 8° and a slope length of 270 m. The main soil type in the vineyard is Regosol developed on loess. The stock unearthing method was applied for estimating soil loss/sedimentation in the vineyard. The study plot is separated by pathways perpendicular to the south-facing main slope into four equal areas with decreasing slope steepness. A total of 42 soil samples (0-10 cm) were collected (10-12 in each area) to measure organic matter content, plant-available nitrite+nitrate-N, P<sub>2</sub>O<sub>5</sub>-P, and total contents of Cu, Zn and B micronutrients. Additionally, five subsoil samples were taken at 2 m depth for determining micronutrient accumulation in the topsoil due to vine treatments. The spatial variability of topsoil nutrient contents was assessed by interpolating the measured parameters using the inverse distance weighting method. The effects of soil erosion and spatial distribution of the nutrient contents on plant vigor were analyzed using the Normalized Difference Vegetation Index (NDVI). Sentinel-2 images with 10 m resolution were acquired on three dates in June and July 2020. In the study area, a median Cu enrichment factor (EF=topsoil/subsoil) of 2.7 can be attributed to a prevailing anthropogenic origin of the topsoil-bound Cu content. The vineyard is an organic farm, therefore Cu use (in a dose of 4 kg/ha/year) is an obvious way to protect grapevines against fungal infections. We also observed a moderate degree of Zn and B enrichment in the topsoil (EF<sub>Zn</sub>: 1.2, EF<sub>B</sub>: 1.4) due to vine treatments with foliar fertilizers. The element distribution maps show a fairly similar spatial pattern of Cu, available P<sub>2</sub>O<sub>5</sub>-P, and organic matter contents. Their accumulation in the footslope area with the lowest steepness can be seen. Compared with the soil loss/sedimentation map based on stock unearthing data, the Cu, P<sub>2</sub>O<sub>5</sub>-P and organic matter contents of the topsoil are lower in areas subject to more intense erosion, which may even affect the development of vines. The latter is to be examined in the light of vegetation indices (NDVI). Changes in vegetation indices along the main slope can be observed with clearly increasing NDVI values in the footslope area. Spatial changes in B, Zn and nitrite-nitrate-N contents do not show a clear relationship with the topographic patterns of the area and the resulting soil erosion losses. Besides the nutrient contents, the presumably higher soil moisture content in the footslope area may also explain the higher NDVI values.</p><p><sub>I. B. is grateful for the support of the Premium Postdoctoral Research Program of the Hungarian Academy of Sciences. The research received funds from the OTKA 1K 116981.</sub></p>

scholarly journals Sediment Yield and Soil Loss Estimation Using GIS Based Soil Erosion Model: A Case Study in the MAN Catchment, Madhya Pradesh, India

2021 ◽  
Vol 8 (1) ◽  
pp. 26
Author(s):  
Manti Patil ◽  
Radheshyam Patel ◽  
Arnab Saha
Keyword(s):  
Spatial Distribution ◽  
Soil Erosion ◽  
Soil Loss ◽  
Crop Production ◽  
Erosion Rate ◽  
Agricultural Land ◽  
Reservoir Sedimentation ◽  
Reservoir Water ◽  
Slope Length ◽  
Soil Erosion Rate

Soil erosion is one of the most critical environmental hazards of recent times. It broadly affects to agricultural land and reservoir sedimentation and its consequences are very harmful. In agricultural land, soil erosion affects the fertility of soil and its composition, crop production, soil quality and land quality, yield and crop quality, infiltration rate and water holding capacity, organic matter and plant nutrient and groundwater regimes. In reservoir sedimentation process the consequences of soil erosion process are reduction of the reservoir capacity, life of reservoir, water supply, power generation etc. Based on these two aspects, an attempt has been made to the present study utilizing Revised Universal Soil Loss Equation (RUSLE) has been used in integration with remote sensing and GIS techniques to assess the spatial pattern of annual rate of soil erosion, average annual soil erosion rate and erosion prone areas in the MAN catchment. The RUSLE considers several factors such as rainfall, soil erodibility, slope length and steepness, land use and land cover and erosion control practice for soil erosion prediction. In the present study, it is found that average annual soil erosion rate for the MAN catchment is 13.01-tons/ha/year, which is higher than that of adopted and recommended values for the project. It has been found that 53% area of the MAN catchment has negligible soil erosion rate (less than 2-tons/ha/year). Its spatial distribution found on flat land of upper MAN catchment. It has been detected that 26% area of MAN catchment has moderate to extremely severe soil erosion rate (greater than 10-tons/ha/year). Its spatial distribution has been found on undulated topography of the middle MAN catchment. It is proposed to treat this area by catchment area treatment activity.

Soil Sediment Loading and Related Environmental Impacts from Farms

2017 ◽  
Author(s):  
Vito Ferro
Keyword(s):  
Organic Matter ◽  
Spatial Distribution ◽  
Soil Erosion ◽  
Sediment Yield ◽  
Water Storage ◽  
Sediment Deposition ◽  
Delivery Ratio ◽  
Sediment Delivery Ratio ◽  
Sediment Delivery ◽  
Soil Particles

Beyond damage to rainfed agricultural and forestry ecosystems, soil erosion due to water affects surrounding environments. Large amounts of eroded soil are deposited in streams, lakes, and other ecosystems. The most costly off-site damages occur when eroded particles, transported along the hillslopes of a basin, arrive at the river network or are deposited in lakes. The negative effects of soil erosion include water pollution and siltation, organic matter loss, nutrient loss, and reduction in water storage capacity. Sediment deposition raises the bottom of waterways, making them more prone to overflowing and flooding. Sediments contaminate water ecosystems with soil particles and the fertilizer and pesticide chemicals they contain. Siltation of reservoirs and dams reduces water storage, increases the maintenance cost of dams, and shortens the lifetime of reservoirs. Sediment yield is the quantity of transported sediments, in a given time interval, from eroding sources through the hillslopes and river network to a basin outlet. Chemicals can also be transported together with the eroded sediments. Sediment deposition inside a reservoir reduces the water storage of a dam. The prediction of sediment yield can be carried out by coupling an erosion model with a mathematical operator which expresses the sediment transport efficiency of the hillslopes and the channel network. The sediment lag between sediment yield and erosion can be simply represented by the sediment delivery ratio, which can be calculated at the outlet of the considered basin, or by using a distributed approach. The former procedure couples the evaluation of basin soil loss with an estimate of the sediment delivery ratio SDRW for the whole watershed. The latter procedure requires that the watershed be discretized into morphological units, areas having a constant steepness and a clearly defined length, for which the corresponding sediment delivery ratio is calculated. When rainfall reaches the surface horizon of the soil, some pollutants are desorbed and go into solution while others remain adsorbed and move with soil particles. The spatial distribution of the loading of nitrogen, phosphorous, and total organic carbon can be deduced using the spatial distribution of sediment yield and the pollutant content measured on soil samples. The enrichment concept is applied to clay, organic matter, and all pollutants adsorbed by soil particles, such as nitrogen and phosphorous. Knowledge of both the rate and pattern of sediment deposition in a reservoir is required to establish the remedial strategies which may be practicable. Repeated reservoir capacity surveys are used to determine the total volume occupied by sediment, the sedimentation pattern, and the shift in the stage-area and stage-storage curves. By converting the sedimentation volume to sediment mass, on the basis of estimated or measured bulk density, and correcting for trap efficiency, the sediment yield from the basin can be computed.

scholarly journals Modelling soil erosion at European scale: towards harmonization and reproducibility

2014 ◽  
Vol 2 (4) ◽  
pp. 2639-2680 ◽  
Author(s):  
C. Bosco ◽  
D. de Rigo ◽  
O. Dewitte ◽  
J. Poesen ◽  
P. Panagos
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Computational Modelling ◽  
Mitigation Strategies ◽  
Rainfall Erosivity ◽  
Large Spatial Scale ◽  
Nutrient Contents ◽  
Continental Scale ◽  
Country Level ◽  
Soil Erosion By Water

Abstract. Soil erosion by water is one of the most widespread forms of soil degradation. The loss of soil as a result of erosion can lead to decline in organic matter and nutrient contents, breakdown of soil structure and reduction of the water holding capacity. Measuring soil loss across the whole landscape is impractical and thus research is needed to improve methods of estimating soil erosion with computational modelling, upon which integrated assessment and mitigation strategies may be based. Despite the efforts, the prediction value of existing models is still limited, especially at regional and continental scale. A new approach for modelling soil erosion at large spatial scale is here proposed. It is based on the joint use of low data demanding models and innovative techniques for better estimating model inputs. The proposed modelling architecture has at its basis the semantic array programming paradigm and a strong effort towards computational reproducibility. An extended version of the Revised Universal Soil Loss Equation (RUSLE) has been implemented merging different empirical rainfall-erosivity equations within a climatic ensemble model and adding a new factor for a better consideration of soil stoniness within the model. Pan-European soil erosion rates by water have been estimated through the use of publicly available datasets and locally reliable empirical relationships. The accuracy of the results is corroborated by a visual plausibility check (63% of a random sample of grid cells are accurate, 83% at least moderately accurate, bootstrap p ≤ 0.05). A comparison with country level statistics of pre-existing European maps of soil erosion by water is also provided.

scholarly journals MODELO MATEMÁTICO DEL ECOSISTEMA DE LA CIÉNAGA GRANDE DE SANTA MARTA

2016 ◽  
Vol 32 ◽  
Author(s):  
Yuri S. Tuchkovenko ◽  
Luis Alfredo Calero
Keyword(s):  
Mathematical Model ◽  
Organic Matter ◽  
Spatial Distribution ◽  
Dissolved Oxygen ◽  
Coastal Lagoon ◽  
Two Dimensional ◽  
Balance Equations ◽  
Dead Organic Matter ◽  
Shallow Reservoir ◽  
Nitrite Nitrate

The structure of the chemical – biological block of two-dimensional mathematical model of ecosystem and shallow reservoir and his methods of calibration is described in detail. The model includes the balance equations for the following components of ecosystem: phytoplankton, bacteria, zooplankton, dead (organic) matter, phosphate, ammonium, nitrite, nitrate and dissolved oxygen. Results of calculations of spatial distribution of several components of the ecosystem for the Ciénaga Grande de Santa Marta coastal lagoon (Colombia) in various seasons of year are given.

scholarly journals SPATIAL DISTRIBUTION OF SOIL LOSS IN UPPER DIDESSA WATERSHED, ETHIOPIA

2019 ◽  
Vol 4 (4) ◽  
pp. 434-443 ◽  
Author(s):  
Fayera Gudu Tufa ◽  
Tolera Abdissa Feyissa
Keyword(s):  
Spatial Distribution ◽  
Soil Erosion ◽  
Soil Loss ◽  
Loss Rate ◽  
Agricultural Land ◽  
Nutrient Loss ◽  
Geographical Information ◽  
Water Supply Systems ◽  
Factor C ◽  
Soil Loss Rate

Soil erosion is dramatically increasing and accelerating in developing countries like Ethiopia. It has worrisome economic and environmental impacts and causes nutrient loss on agricultural land, sedimentation in rivers and reservoirs, clogged canals and other water supply systems. Determination of spatial distribution of soil loss rate in upper Didessa watershed is an important priority for prioritizing the area for watershed management practices in order to reduce soil erosion. The Revised Universal Soil Loss Equation (RUSLE) framed with geographical information system and remote sensing technique was used to estimate the mean annual soil loss in Upper Didessa Watershed, Ethiopia. Digital elevation model (DEM) with 30mx30m resolution was collected from Ministry of Water, Irrigation and Energy and used to delineate the watershed. Soil loss factors of the watershed like length and slope factor (LS), soil erodibility factor (K), cover management factor (C), support practicing factor (P) and rain fall erosivity factor (R) were evaluated and integrated in GIS to compute the annual soil loss rate of the watershed. The results of this work reveal that the annual rate of soil loss in the watershed is 5.23 t / ha / year. They also show that the central part of the watershed is an area prone to soil erosion. DISTRIBUIÇÃO ESPACIAL DA PERDA DO SOLO NA BACIA HIDROGRÁFICA SUPERIOR DIDESSA, ETIÓPIA ResumoA erosão do solo está aumentando e acelerando dramaticamente em países em desenvolvimento como a Etiópia. Tem impactos econômicos e ambientais preocupantes e causa perda de nutrientes em terras agrícolas, sedimentação em rios e reservatórios, entupimento de canais e outros sistemas de fornecimento de água. A determinação da distribuição espacial da taxa de perda de solo na bacia hidrográfica superior do Rio Didessa é uma prioridade importante para priorizar a área para práticas de manejo de bacias hidrográficas a fim de reduzir a erosão do solo. A Equação Universal de Perda de Solo Revisada (RUSLE), enquadrada com sistema de informação geográfica e técnica de sensoriamento remoto, foi usada para estimar a perda média anual de solo na Bacia do Alto Didessa, na Etiópia. O modelo digital de elevação (DEM) com resolução de 30mx30m foi coletado no Ministério da Água, Irrigação e Energia e utilizado para delinear a bacia hidrográfica. Os fatores de perda de solo da bacia hidrográfica, como comprimento e fator de inclinação (LS), fator de erodibilidade do solo (K), fator de manejo da cobertura (C), fator de prática de apoio (P) e fator de erosividade da chuva (R) foram avaliados e integrados no SIG para calcular a taxa anual de perda de solo da bacia hidrográfica. Os resultados deste trabalho revelam que taxa anual de perda de solo da bacia hidrográfica é de 5,23 t / ha / ano. Mostram ainda que a parte central da bacia hidrográfica é uma área propensa à erosão do solo. Palavras-chave: SIG. Perda de solo. RUSLE. Didessa superior da bacia hidrográfica.

scholarly journals Soil erodibility indices under different land uses in Ri-Bhoi district of Meghalaya (India)

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Manish Olaniya ◽  
Pradip Kumar Bora ◽  
Susanta Das ◽  
Pukhrambam Helena Chanu
Keyword(s):  
Land Use ◽  
Organic Matter ◽  
Soil Erosion ◽  
Soil Loss ◽  
Universal Soil Loss Equation ◽  
Soil Erodibility ◽  
Land Uses ◽  
Modified Clay ◽  
K Index ◽  
Soil Loss Equation

Abstract In absence of soil erosion plots for determination of erodibility index (K) for erosion models like Universal Soil Loss Equation (USLE) or Revised Universal Soil Loss Equation (RUSLE) to estimate soil erosion, empirical relations are used. In the present study, soil erodibility index was determined for entire Ri-bhoi district of Meghalaya based on soil physical and chemical properties through empirical relationship and presented in a map form. Dominant land uses of the district were identified through geo-spatial tools which were viz. agriculture, forest, jhum land and wasteland. Soil samples from surface depth (01–15 cm) were collected from areas of different dominant land uses. Twenty five sampling points were selected under each land use type and geo-coded them on the base map of Ri-bhoi district. Apart from K-index, Clay Ratio, Modified Clay Ratio and Critical Soil Organic Matter were also determined for understanding the effect of primary soil particles on erodibility. In agriculture land use system K-index values were found in the range of 0.08–0.41 with an average of 0.25 ± 0.02. In case of jhum, forest and wasteland these were in the range of 0.08–0.42 with an average of 0.20 ± 0.01; 0.09–0.40 with an average of 0.22 ± 0.02, and 0.10–0.34 with an average value of 0.23 ± 0.02, respectively. Clay ratio (2.74) and Modified clay ratio (2.41) were observed to be higher in forest LUS, lower clay ratio (1.97) and modified clay ratio (1.81) were found in the wasteland indicating erosion susceptibility in forested area. The values of Critical Level of Organic Matter (CLOM) for the district ranged from 4.72 to 16.56. Out of 100 samples, only one sample had CLOM value less than 5 and rest 99 samples had values more than 5 indicating that the soils of the district had moderate to stable soil structure and offer resistance to erosion. All the indices values of geo-coded points were then interpolated in the Arc-GIS environment to produce land use based maps for Ri-bhoi district of Meghalaya. As K-index is a quantitative parameter which is used in models, the index can be then interpolated for estimation of soil erosion through USLE or RUSLE for any given situation.

scholarly journals Soil Erosion Prediction Using Morgan-Morgan-Finney Model in a GIS Environment in Northern Ethiopia Catchment

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Gebreyesus Brhane Tesfahunegn ◽  
Lulseged Tamene ◽  
Paul L. G. Vlek
Keyword(s):  
Spatial Distribution ◽  
Soil Erosion ◽  
Soil Loss ◽  
Overland Flow ◽  
Scientific Information ◽  
Geographical Information ◽  
Northern Ethiopia ◽  
Soil Transport ◽  
Erosion Processes ◽  
Erosion Prediction

Even though scientific information on spatial distribution of hydrophysical parameters is critical for understanding erosion processes and designing suitable technologies, little is known in Geographical Information System (GIS) application in developing spatial hydrophysical data inputs and their application in Morgan-Morgan-Finney (MMF) erosion model. This study was aimed to derive spatial distribution of hydrophysical parameters and apply them in the Morgan-Morgan-Finney (MMF) model for estimating soil erosion in the Mai-Negus catchment, northern Ethiopia. Major data input for the model include climate, topography, land use, and soil data. This study demonstrated using MMF model that the rate of soil detachment varied from <20 t ha−1y−1to >170 t ha−1y−1, whereas the soil transport capacity of overland flow (TC) ranged from 5 t ha−1y−1to >42 t ha−1y−1. The average soil loss estimated by TC using MMF model at catchment level was 26 t ha−1y−1. In most parts of the catchment (>80%), the model predicted soil loss rates higher than the maximum tolerable rate (18 t ha−1y−1) estimated for Ethiopia. Hence, introducing appropriate interventions based on the erosion severity predicted by MMF model in the catchment is crucial for sustainable natural resources management.

scholarly journals Integrated Use of Satellite Remote Sensing, Artificial Neural Networks, Field Spectroscopy, and GIS in Estimating Crucial Soil Parameters in Terms of Soil Erosion

2019 ◽  
Vol 11 (9) ◽  
pp. 1106 ◽  
Author(s):  
Dimitrios D. Alexakis ◽  
Evdokia Tapoglou ◽  
Anthi-Eirini K. Vozinaki ◽  
Ioannis K. Tsanis
Keyword(s):  
Remote Sensing ◽  
Organic Matter ◽  
Soil Erosion ◽  
Soil Properties ◽  
Satellite Remote Sensing ◽  
Soil Loss ◽  
Assessment Model ◽  
Landsat 8 ◽  
Field Spectroscopy ◽  
K Factor

Soil erosion is one of the main causes of soil degradation among others (salinization, compaction, reduction of organic matter, and non-point source pollution) and is a serious threat in the Mediterranean region. A number of soil properties, such as soil organic matter (SOM), soil structure, particle size, permeability, and Calcium Carbonate equivalent (CaCO3), can be the key properties for the evaluation of soil erosion. In this work, several innovative methods (satellite remote sensing, field spectroscopy, soil chemical analysis, and GIS) were investigated for their potential in monitoring SOM, CaCO3, and soil erodibility (K-factor) of the Akrotiri cape in Crete, Greece. Laboratory analysis and soil spectral reflectance in the VIS-NIR (using either Landsat 8, Sentinel-2, or field spectroscopy data) range combined with machine learning and geostatistics permitted the spatial mapping of SOM, CaCO3, and K-factor. Synergistic use of geospatial modeling based on the aforementioned soil properties and the Revised Universal Soil Loss Equation (RUSLE) erosion assessment model enabled the estimation of soil loss risk. Finally, ordinary least square regression (OLSR) and geographical weighted regression (GWR) methodologies were employed in order to assess the potential contribution of different approaches in estimating soil erosion rates. The derived maps captured successfully the SOM, the CaCO3, and the K-factor spatial distribution in the GIS environment. The results may contribute to the design of erosion best management measures and wise land use planning in the study region.

scholarly journals Modelling of Soil Erosion and Accumulation in an Agricultural Landscape—A Comparison of Selected Approaches Applied at the Small Stream Basin Level in the Czech Republic

Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 404 ◽  
Author(s):  
Jiří Jakubínský ◽  
Vilém Pechanec ◽  
Jan Procházka ◽  
Pavel Cudlín
Keyword(s):  
Spatial Distribution ◽  
Czech Republic ◽  
Soil Erosion ◽  
Soil Loss ◽  
Agricultural Landscape ◽  
Sediment Accumulation ◽  
Calculation Algorithm ◽  
Specific Calculation ◽  
Small Stream ◽  
Area Of Interest

This article deals with the modelling of erosion and accumulation processes in the contemporary cultural landscape of Central Europe. The area of interest is the headwater part of the small stream catchment—the Kopaninský Stream in central Czech Republic. It is an agricultural and forest–agricultural landscape with a relatively rugged topography and riverbed slope, which makes the terrain very vulnerable to water erosion. The main aim of this article is to compare the results of four selected soil erosion and sediment delivery models, which are currently widely used to quantitate the soil erosion and sediment accumulation rates, respectively. The models WaTEM/SEDEM, USPED, InVEST and TerrSet work on several different algorithms. The model outputs are compared in terms of the total volume of eroded and accumulated sediment within the catchment per time unit, and further according to the spatial distribution of sites susceptible to soil loss or sediment accumulation. Although each model is based partly on a specific calculation algorithm and has different data pre-processing requirements, we have achieved relatively comparable results in calculating the average annual soil loss and accumulation. However, each model is distinct in identifying the spatial distribution of specific locations prone to soil loss or accumulation processes.

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