Dynamics of spatial and temporal outflow from a soil column influenced by earthworm activity

2021 ◽  
Author(s):  
sidra bibi ◽  
Keyword(s):  
Spatial Variability ◽  
Soil Aggregates ◽  
Soil Column ◽  
Lumbricus Terrestris ◽  
Spatial And Temporal Variability ◽  
Deep Soil ◽  
Soil Irrigation ◽  
The One ◽  
Water Outflow ◽  
Earthworm Activity

<p>Earthworms are known as ecosystem engineers, which influence the chemical and physical properties in their own environment and thereby strongly modify soil processes. Soil structure (soil aggregates and macropores) formed by earthworms during burrowing activity may influence the soil moisture retention and water flow, enhancing infiltration into deep soil layers.</p><p>We studied the influence of anecic earthworms (<em>Lumbricus terrestris</em> fed on poplar leaves) on the spatial and temporal variability in water outflow and storage through a soil column. Therefore, we established a cylinder (30cm diameter, 50cm high) with silty loamy soil. At the bottom boundary, 15 fiberglass wicks drain the water from the soil column. With these wicks the water outflow is measured with a spatial and temporal resolution.  After an initial wetting of the soil, irrigation of the soil cylinder was done twice per week with a full cone nozzle, with an intensity of 36 mm/h and a duration of 20 minutes After 17 weeks 10 adult earthworms were added to the column. The research design consists of three phases (i) soil-filled column ( 14  weeks, with a gap of 4 weeks in the middle due to the corona lockdown) (ii) transition phase: initial earthworm activity (3 days) (iii) soil column with earthworm created structure (7 weeks).</p><p>After the experiment, the column was excavated carefully by layers of 4cm at a time. All of the earthworms were found back alive in the column. There was evidence of earthworm burrows down to 26 cm depth in the soil column, earthworm created aggregates were seen only in the top few centimeters.</p><p>We expected the outflow of water from the soil column to change due to the earthworm activity: on the one hand, the creation of macroaggregates was expected to increase the water retention in the soil, and on the other hand, the macropores were expected to create a stronger spatial variability in outflow and a more rapid reaction of outflow to the irrigation events. </p><p>We observed mainly an earlier and slightly higher peak in the total outflow of the column coinciding with an earlier and higher peak in the spatial variability in the outflow of the wicks.</p>

Dynamics of spatial and temporal outflow from a soil column influenced by earthworm activity

2020 ◽  
Author(s):  
Sidra Bibi ◽  
Loes Van Schaik
Keyword(s):  
Soil Aggregates ◽  
Soil Column ◽  
Lumbricus Terrestris ◽  
Spatial And Temporal Variability ◽  
Deep Soil ◽  
Burrowing Activity ◽  
The One ◽  
Water Outflow ◽  
Soil Moisture Retention ◽  
Earthworm Activity

<p>Earthworms are known as ecosystem engineers, which influence the chemical and physical properties in their own environment and thereby strongly modify soil processes. Soil structure (soil aggregates and macropores) formed by earthworms during burrowing activity may influence the soil moisture retention and water flow, enhancing infiltration into deep soil layers.</p><p>We will study the influence of anecic earthworms (<em>Lumbricus terrestris</em> fed on poplar leaves) on the spatial and temporal variability in water outflow and storage through a soil column. Therefore, we established a cylinder (30cm diameter, 50cm high) with silty loamy soil. At the bottom boundary, 15 fiberglass wicks drain the water from the soil column. With these wicks, the water outflow is measured with a spatial and temporal resolution.  After an initial wetting of the soil (), [LvS1] irrigation of the soil cylinder takes place twice per week with a full cone nozzle, with an intensity of 40 mm/h and a duration of 10 minutes. The research design consists of three phases (i) soil-filled column (4 weeks) (ii) transition phase: initial earthworm activity (4 weeks) (iii) soil column with earthworm created structure (4 weeks).</p><p>We expect the outflow of water from the soil column to change due to the earthworm activity: on the one hand, the creation of macroaggregates is expected to increase the water retention in the soil and on the other hand, the macropores are expected to create a spatial variability in outflow and a more rapid reaction of outflow to the irrigation events. </p>

scholarly journals Sources of black carbon aerosols in South Asia and surrounding regions during the Integrated Campaign for Aerosols, Gases and Radiation Budget (ICARB)

2015 ◽  
Vol 15 (10) ◽  
pp. 5415-5428 ◽  
Author(s):  
R. Kumar ◽  
M. C. Barth ◽  
V. S. Nair ◽  
G. G. Pfister ◽  
S. Suresh Babu ◽  
...  
Keyword(s):  
Spatial Variability ◽  
South Asia ◽  
Black Carbon ◽  
Biomass Burning ◽  
Regional Scale ◽  
Anthropogenic Sources ◽  
Radiation Budget ◽  
Anthropogenic Emissions ◽  
Spatial And Temporal Variability ◽  
Mass Concentrations

Abstract. This study examines differences in the surface black carbon (BC) aerosol loading between the Bay of Bengal (BoB) and the Arabian Sea (AS) and identifies dominant sources of BC in South Asia and surrounding regions during March–May 2006 (Integrated Campaign for Aerosols, Gases and Radiation Budget, ICARB) period. A total of 13 BC tracers are introduced in the Weather Research and Forecasting Model coupled with Chemistry to address these objectives. The model reproduced the temporal and spatial variability of BC distribution observed over the AS and the BoB during the ICARB ship cruise and captured spatial variability at the inland sites. In general, the model underestimates the observed BC mass concentrations. However, the model–observation discrepancy in this study is smaller compared to previous studies. Model results show that ICARB measurements were fairly well representative of the AS and the BoB during the pre-monsoon season. Elevated BC mass concentrations in the BoB are due to 5 times stronger influence of anthropogenic emissions on the BoB compared to the AS. Biomass burning in Burma also affects the BoB much more strongly than the AS. Results show that anthropogenic and biomass burning emissions, respectively, accounted for 60 and 37% of the average ± standard deviation (representing spatial and temporal variability) BC mass concentration (1341 ± 2353 ng m−3) in South Asia. BC emissions from residential (61%) and industrial (23%) sectors are the major anthropogenic sources, except in the Himalayas where vehicular emissions dominate. We find that regional-scale transport of anthropogenic emissions contributes up to 25% of BC mass concentrations in western and eastern India, suggesting that surface BC mass concentrations cannot be linked directly to the local emissions in different regions of South Asia.

Spatial and Temporal Variability of Surface Snowfall and Snowpack Chemistry in Central Ontario

1985 ◽  
Vol 7 ◽  
pp. 185-190 ◽  
Author(s):  
R.S. Schemenauer ◽  
P.W. Summers ◽  
H.A. Wiebe ◽  
K.G. Anlauf
Keyword(s):  
Chemical Composition ◽  
Chemical Structure ◽  
Precipitation Chemistry ◽  
Spatial And Temporal Variability ◽  
Vertical Variation ◽  
Ph Values ◽  
Pollutant Concentrations ◽  
The One ◽  
Physical And Chemical ◽  
Annual Deposition

The physical and chemical structure of the snowpack near North Bay, Ontario was examined during the winter of 1984. precipitation chemistry measurements were also made. A marked areal uniformity was noted in the layered structure of the snowpack and in the vertical variation of the chemical composition. In late January, pH values of the snowpack varied from ∼4.1 at the surface to ∼4.8 near the ground. After rain and a major thaw in February the pH was near 4.8 throughout. Nitrate concentrations exceeded those of sulfate in the snowpack. The molar concentration ratio of / was typically 0.5. Samples of precipitation from six sites had pH values ranging from 3.4 to 5.2. to equivalent ratios were <1 in snow and near 1 or >1 in rain. The chemical composition of the precipitation was closely related to the airmass trajectory. Southerly trajectories yielded the lowest pH values and highest pollutant concentrations. The one-month period from 20 January to 21 February had a deposition of 0.2 g m−2 and a deposition of 0.35 g m−2. For , this deposition would be about one-twelfth the expected annual deposition and for about one-fifth.

scholarly journals A hydrochemical modelling framework for combined assessment of spatial and temporal variability in stream chemistry: application to Plynlimon, Wales

2001 ◽  
Vol 5 (1) ◽  
pp. 49-58 ◽  
Author(s):  
H.J. Foster ◽  
M.J. Lees ◽  
H.S. Wheater ◽  
C. Neal ◽  
B. Reynolds
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Spatial Variability ◽  
Temporal Variability ◽  
Biological Diversity ◽  
Spatial And Temporal Variability ◽  
Stream Chemistry ◽  
Two Component ◽  
End Members

Abstract. Recent concern about the risk to biota from acidification in upland areas, due to air pollution and land-use change (such as the planting of coniferous forests), has generated a need to model catchment hydro-chemistry to assess environmental risk and define protection strategies. Previous approaches have tended to concentrate on quantifying either spatial variability at a regional scale or temporal variability at a given location. However, to protect biota from ‘acid episodes’, an assessment of both temporal and spatial variability of stream chemistry is required at a catchment scale. In addition, quantification of temporal variability needs to represent both episodic event response and long term variability caused by deposition and/or land-use change. Both spatial and temporal variability in streamwater chemistry are considered in a new modelling methodology based on application to the Plynlimon catchments, central Wales. A two-component End-Member Mixing Analysis (EMMA) is used whereby low and high flow chemistry are taken to represent ‘groundwater’ and ‘soil water’ end-members. The conventional EMMA method is extended to incorporate spatial variability in the two end-members across the catchments by quantifying the Acid Neutralisation Capacity (ANC) of each in terms of a statistical distribution. These are then input as stochastic variables to a two-component mixing model, thereby accounting for variability of ANC both spatially and temporally. The model is coupled to a long-term acidification model (MAGIC) to predict the evolution of the end members and, hence, the response to future scenarios. The results can be plotted as a function of time and space, which enables better assessment of the likely effects of pollution deposition or land-use changes in the future on the stream chemistry than current methods which use catchment average values. The model is also a useful basis for further research into linkage between hydrochemistry and intra-catchment biological diversity. Keywords: hydrochemistry, End-Member Mixing Analysis (EMMA), uplands, acidification

Microplastics and earthworms in soils: A case study on translocation, toxicity and fate

2020 ◽  
Author(s):  
Nils Dietrich ◽  
Daniel Wilkinson ◽  
Florian Hirsch ◽  
Magdalena Sut-Lohmann ◽  
Antonia Geschke ◽  
...  
Keyword(s):  
Organic Waste ◽  
Soil Column ◽  
Column Experiment ◽  
Lumbricus Terrestris ◽  
Natural Soil ◽  
Arable Soils ◽  
Different Types ◽  
Soil Column Experiment ◽  
Illegal Waste

<p>Microplastics are not only found in marine and lacustrine environments but also in soils. Microplastics enter natural soil environments from legal or illegal waste deposition. In arable soils, microplastics often stem from the decomposition of plastic sheeting. The accumulation of (micro-)plastic from garbage bags in which biological waste is often disposed, is also a significant problem for the recycling and composting of organic waste. Commercially available compostable bags are advertised as degradable. Thus, these compostable bags ought to accumulate less in soils than non-compostable bags. We present a pilot study to determine the preference of earthworms (Lumbricus terrestris and Eisenia hortensis) for taking up and translocating different types of microplastic in soils. Our initial findings from the soil column experiment suggest that the earthworms show a strong tendency for the uptake of microplastic.  We also observed direct and indirect transport of microplastic by earthworms from the surface to deeper parts of the soil columns.</p>

Evaluating an interpolation approach for modelling spatial variability in pest development

2002 ◽  
Vol 92 (3) ◽  
pp. 219-231 ◽  
Author(s):  
C.H. Jarvis ◽  
R.H. Collier
Keyword(s):  
Spatial Variability ◽  
Input Data ◽  
Spline Interpolation ◽  
Local Variation ◽  
Estimation Methods ◽  
Horticultural Crops ◽  
Air Temperatures ◽  
Using Data ◽  
The One ◽  
The Uk

AbstractAir temperatures estimated by partial thin plate spline interpolation, or from the ‘nearest station’ (Voronoi polygon method), were used to model the phenology of three pests of horticultural crops throughout England and Wales. Temperatures for a particularly hot (1976) and a particularly cold (1986) year were interpolated to a grid resolution of 1 km. Estimates were made of the timing of spring emergence (Cecidophyopsis ribis (Westwood)), the maximum number of generations completed during the summer (Plutella xylostella (Linnaeus)) and the numbers of days when mating was possible (Merodon equestris (Fabricius)). The relative accuracy of the two temperature estimation methods was compared using jack-knife cross-validation. For C. ribis and P. xylostella, modelling with interpolated temperature input data was more accurate than using data from the ‘nearest station’. Of the three phenology models used, the one that relied on an activity threshold (M. equestris) was the most sensitive to both types of input data. Spatial variability in the activity of M. equestris adults was investigated in the two main areas (south-west peninsula and Lincolnshire) where its host crop (Narcissus) is grown. Modelling at cruder scales (up to 25*25 km) masked local variation, but the degree to which this was important varied from region to region and over time, as did the geography of the variability itself. The results indicate that interpolated data, computed to a resolution of 1 km using the UK synoptic network, have the potential for wider use within agricultural decision support systems for horticultural crops.

scholarly journals Notes on the Marine Oligochæta of Plymouth

1889 ◽  
Vol 1 (1) ◽  
pp. 69-71 ◽  
Author(s):  
Frank E. Beddard
Keyword(s):  
Fresh Water ◽  
Lumbricus Terrestris ◽  
The Other ◽  
Red River ◽  
Other Hand ◽  
The Common ◽  
Marine Oligochaeta ◽  
The One

The Oligochæta form a division of the Annelida, of which the most familiar type is the common earthworm (Lumbricus terrestris); the group comprises also a great number of smaller worms, which are for the most part inhabitants of ponds and streams, such as the red River worm (Tubifex rivulorum). The Oligochæta were at one time believed to be entirely terrestrial or inhabitants of fresh water, and to be distinguished thus from the Polychæta, which were supposed to be exclusively marine in their habitat. Although the progress of research has not broken down the structural distinctions between these two divisions of the Annelida chætopoda, it has been provedthat no absolute line of demarcation can be drawn between the Oligochæta and the Polychæta as regards their habitat; on the one hand Polychæta have been found in fresh water, and, on the other hand, certain species of Oligochæta are now known to inhabit the mud and gravel of the seashore.

scholarly journals Analysis of Long-Term Solar Resource Variability Using NSRDB Version 3

2021 ◽  
Author(s):  
Manajit Sengupta ◽  
Aron Habte
Keyword(s):  
Solar Radiation ◽  
Spatial Variability ◽  
Temporal Variability ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Spatial And Temporal Variability ◽  
Cloud Optical Depth ◽  
Resource Variability ◽  
Solar Resource

<p>Understanding long-term solar resource variability is essential for planning and deployment of solar energy systems. These variabilities occur due to deterministic effects such as sun cycle and nondeterministic such as complex weather patterns. The NREL’s National Solar Radiation Database (NSRDB) provides long term solar resource data covering 1998- 2019 containing more than 2 million pixels over the Americas and gets updated on an annual basis. This dataset is satellite-based and uses a two-step physical model for it’s development. In the first step we retrieve cloud properties such as cloud mask, cloud type, cloud optical depth and effective radius. The second step uses a fast radiative transfer model to compute solar radiation.  This dataset is ideal for studying solar resource variability. For this study, NSRDB version 3 which contains data from 1998-2017 on a half hourly and 4x4 km temporal and spatial resolution was used. The study analyzed the spatial and temporal trend of solar resource of global horizontal irradiance (GHI) and direct normal irradiance (DNI) using long-term 20-years NSRDB data. The coefficient of variation (COV) was used to analyze the spatio-temporal interannual and seasonal variabilities. The spatial variability was analyzed by comparing the center pixel to neighboring pixels. The spatial variability result showed higher COV as the number of neighboring pixels increased. Similarly, the temporal variability for the NSRDB domain ranges on average from ±10% for GHI and ±20% for DNI. Furthermore, the long-term variabilities were also analyzed using the Köppen-Geiger climate classification. This assisted in the interpretation of the result by reducing the originally large number of pixels into a smaller number of groups. This presentation will provided a unique look at long-term spatial and temporal variability of solar radiation using high-resolution satellite-based datasets.</p>

scholarly journals Intra-urban spatial variability of surface ozone and carbon dioxide in Riverside, CA: viability and validation of low-cost sensors

2017 ◽  
Author(s):  
Kira Sadighi ◽  
Evan Coffey ◽  
Andrea Polidori ◽  
Brandon Feenstra ◽  
Qin Lv ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Los Angeles ◽  
Spatial Variability ◽  
Low Cost ◽  
Surface Ozone ◽  
Calibration Method ◽  
Measurement Tool ◽  
Spatial And Temporal Variability ◽  
Air Quality Monitoring Stations ◽  
Binned Data

Abstract. Abstract. Sensor networks are being more widely used to characterize and understand compounds in the atmosphere such as ozone and carbon dioxide. This study employs a measurement tool, called the U-Pod, constructed at the University of Colorado Boulder, to investigate spatial and temporal variability of O3 and CO2 in a 314 km2 area of Riverside County near Los Angeles, California. This tool provides low-cost sensors to collect ambient data at non-permanent locations. The U-Pods were calibrated using a pre-deployment field calibration technique; all the U-Pods were collocated with regulatory monitors. After collocation, the U-Pods were deployed in the area mentioned. A subset of pods was deployed at two local regulatory air quality monitoring stations providing validation for the collocation calibration method. Field validation of sensor O3 and CO2 measurements to minute resolution reference observations resulted in R-squared and root mean squared errors (RMSE) of 0.95–0.97 and 4.4–7.2 ppbv for O3 and 0.79 and 15 ppmv CO2, respectively. Using the deployment data, ozone and carbon dioxide concentrations were observed to vary on this small spatial scale. In the analysis based on hourly binned data, the median R-squared values between all possible U-Pod pairs varied from 0.52 to 0.86 for ozone during the deployment. The medians of absolute differences were calculated between all possible pod pairs, 21 pairs total. The median values of those median absolute differences for each hour of the day varied between 2.2 and 9.3 ppb for the ozone deployment. For carbon dioxide, distributions of all measurements vary from 413–425 ppm during the calibration (collocation) and 406–472 during the deployment. Since median differences between U-Pod concentrations during deployment are larger than the respective root mean square error values for ozone and carbon dioxide, we can conclude that there is spatial variability in these pollutants across the study area. This is important because it means that citizens may be exposed to more ozone than they would assume based on current regulatory monitoring.

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