Regional scale spatial and temporal variability of soil moisture in a prairie region

2016 ◽  
Vol 30 (20) ◽  
pp. 3639-3649 ◽  
Author(s):  
Travis T. Burns ◽  
Aaron A. Berg ◽  
Jaclyn Cockburn ◽  
Erica Tetlock
Keyword(s):  
Soil Moisture ◽  
Temporal Variability ◽  
Regional Scale ◽  
Spatial And Temporal Variability

scholarly journals Multiscale observations of NH<sub>3</sub> around Toronto, Canada

2021 ◽  
Vol 14 (2) ◽  
pp. 905-921
Author(s):  
Shoma Yamanouchi ◽  
Camille Viatte ◽  
Kimberly Strong ◽  
Erik Lutsch ◽  
Dylan B. A. Jones ◽  
...  
Keyword(s):  
Temporal Variability ◽  
Grid Point ◽  
Regional Scale ◽  
Model Performance ◽  
In Situ Measurements ◽  
Coefficient Of Determination ◽  
Spatial And Temporal Variability ◽  
Predictive Capacity ◽  
Total Column

Abstract. Ammonia (NH3) is a major source of nitrates in the atmosphere and a major source of fine particulate matter. As such, there have been increasing efforts to measure the atmospheric abundance of NH3 and its spatial and temporal variability. In this study, long-term measurements of NH3 derived from multiscale datasets are examined. These NH3 datasets include 16 years of total column measurements using Fourier transform infrared (FTIR) spectroscopy, 3 years of surface in situ measurements, and 10 years of total column measurements from the Infrared Atmospheric Sounding Interferometer (IASI). The datasets were used to quantify NH3 temporal variability over Toronto, Canada. The multiscale datasets were also compared to assess the representativeness of the FTIR measurements. All three time series showed positive trends in NH3 over Toronto: 3.34 ± 0.89 %/yr from 2002 to 2018 in the FTIR columns, 8.88 ± 5.08 %/yr from 2013 to 2017 in the surface in situ data, and 8.38 ± 1.54 %/yr from 2008 to 2018 in the IASI columns. To assess the representative scale of the FTIR NH3 columns, correlations between the datasets were examined. The best correlation between FTIR and IASI was obtained with coincidence criteria of ≤25 km and ≤20 min, with r=0.73 and a slope of 1.14 ± 0.06. Additionally, FTIR column and in situ measurements were standardized and correlated. Comparison of 24 d averages and monthly averages resulted in correlation coefficients of r=0.72 and r=0.75, respectively, although correlation without averaging to reduce high-frequency variability led to a poorer correlation, with r=0.39. The GEOS-Chem model, run at 2∘ × 2.5∘ resolution, was compared to FTIR and IASI to assess model performance and investigate the correlation of observational data and model output, both with local column measurements (FTIR) and measurements on a regional scale (IASI). Comparisons on a regional scale (a domain spanning 35 to 53∘ N and 93.75 to 63.75∘ W) resulted in r=0.57 and thus a coefficient of determination, which is indicative of the predictive capacity of the model, of r2=0.33, but comparing a single model grid point against the FTIR resulted in a poorer correlation, with r2=0.13, indicating that a finer spatial resolution is needed for modeling NH3.

Spatial and temporal variability of soil moisture over India using IRS P4 MSMR data

2005 ◽  
Vol 26 (10) ◽  
pp. 2241-2247 ◽  
Author(s):  
R. P. Singh ◽  
D. R. Mishra ◽  
A. K. Sahoo † ◽  
S. Dey
Keyword(s):  
Soil Moisture ◽  
Temporal Variability ◽  
Spatial And Temporal Variability

scholarly journals Controls and characteristics of variability in soil moisture and groundwater in a headwater catchment

2014 ◽  
Vol 11 (8) ◽  
pp. 9475-9517
Author(s):  
H. K. McMillan ◽  
M. S. Srinivasan
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Water Table ◽  
Temporal Variability ◽  
Extreme Values ◽  
Stream Water ◽  
Spatial And Temporal Variability ◽  
Multiple Time ◽  
Strong Impact ◽  
Strong Control

Abstract. This paper presents experimental results from a new headwater research catchment in New Zealand. We made distributed measurements of streamflow, soil moisture and groundwater levels, sampling across a range of aspects, hillslope positions, distances from stream and depths. Our aim was to assess the controls, types and implications of spatial and temporal variability in surface and groundwaters. We found that temporal variability is strongly controlled by the seasonal cycle, for both soil moisture and water table, and for both the mean and extremes of the distributions. The standard deviation of both soil moisture and groundwater values calculated per timestep is larger in winter than in summer, and standard deviations typically peak during rainfall events due to partial saturation of the catchment. Controls on the spatial variability differed between the water stores. Aspect had a strong control on groundwater but not on soil moisture, distance from stream controlled both soil moisture and groundwater. The depth of the soil moisture sensor had little impact in terms of mean water content, but a strong impact on the extreme values, i.e. saturation. Co-measurement of soil moisture and water table level variability allowed us to identify variability components that differed between these water stores e.g. patterns of strong response in soil water content were not the same for groundwater level, and those that were consistent e.g. vertical infiltration of summer rainfall through upper and lower soil depths, or rising near-stream water tables through shallow wells to lower soil depths. Signatures of variability were observed in the streamflow series, showing that understanding variability is important for hydrological prediction. Total catchment variability is composed of multiple variability sources. The dominant variability type changes with catchment wetness conditions according to which water stores are active, and in particular those which are close to a threshold such as field capacity or saturation. Our results suggest that the integrative processes that create emergent catchment behaviour should be understood as the sum of these multiple, time varying components.

scholarly journals Response of water vapour D-excess to land-atmosphere interactions in a semi-arid environment

2016 ◽  
Author(s):  
Stephen D. Parkes ◽  
Matthew F. McCabe ◽  
Alan D. Griffiths ◽  
Lixin Wang ◽  
Scott Chambers ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Relative Humidity ◽  
Water Vapour ◽  
Regional Scale ◽  
Measurement Techniques ◽  
Spatial And Temporal Variability ◽  
Moisture Source ◽  
Moisture Recycling ◽  
Nocturnal Inversion ◽  
Semi Arid

Abstract. The stable isotopic composition of water vapour provides information about moisture sources and processes that is difficult to obtain with traditional measurement techniques. Recently, it has been proposed that the D-excess (dv = δ2H − 8 × δ18O) of water vapour can provide a diagnostic tracer of continental moisture recycling. However, D-excess exhibits a diurnal cycle that has been observed across a variety of ecosystems and may be influenced by a range of processes beyond regional scale moisture recycling, including local evaporation (ET) fluxes. There is a lack of measurements of D-excess in evaporation (ET) fluxes, which has made it difficult to assess how ET fluxes modify the D-excess in water vapour (dv). With this in mind, we employed a chamber based approach to directly measure D-excess in ET (dET) fluxes. We show that ET fluxes imposed a negative forcing on the ambient vapour and could not explain the higher daytime dv values. The low dET observed here was sourced from a soil water pool that had undergone an extended drying period, leading to low D-excess of the soil moisture. A strong correlation between daytime dv and locally measured relative humidity was consistent with an oceanic moisture source, suggesting that remote hydrological processes were the major contributor to daytime dv variability. During the early evening, ET fluxes into a shallow nocturnal inversion layer caused a lowering of the dv values near the surface. In addition, transient mixing of vapour with a higher D-excess from above the nocturnal inversion modified these values, causing large within night variability. These results indicate dET can generally be expected to show large spatial and temporal variability and to depend on the soil moisture state. For long periods between rain events, common in semi-arid environments, ET would be expected to impose negative forcing on the surface dv. The variability of D-excess in ET fluxes therefore needs to be considered when using dv to study moisture recycling and during extended dry periods may act as a tracer of the relative humidity of the oceanic moisture source.

scholarly journals The Impact of Land–Atmosphere Interactions on the Temporal Variability of Soil Moisture at the Regional Scale

2005 ◽  
Vol 6 (1) ◽  
pp. 53-67 ◽  
Author(s):  
John P. Kochendorfer ◽  
Jorge A. Ramírez
Keyword(s):  
Differential Equation ◽  
Soil Moisture ◽  
Probability Density Function ◽  
Probability Density ◽  
Density Function ◽  
Temporal Variability ◽  
Regional Scale ◽  
Precipitation Efficiency ◽  
Precipitation Recycling ◽  
The Impact

Abstract This study examines the impact of the nonlinear dynamics of soil-moisture feedbacks to precipitation on the temporal variability of soil moisture at the regional scale. It is a modeling study in which the large-scale soil-water balance is first formulated as an ordinary differential equation and then recast as a stochastic differential equation by incorporating colored noise representing the high-frequency temporal variability and correlation of precipitation. The underlying model couples the atmospheric and surface-water balances and accounts for both precipitation recycling and precipitation-efficiency feedbacks, which arise from the surface energy balance. Based on the governing Fokker–Planck equation, three different analytical solutions (corresponding to differing forms and combinations of feedbacks) are derived for the steady-state probability density function of soil moisture. Using NCEP–NCAR reanalysis data, estimates of potential evapotranspiration, and long-term observations of precipitation, streamflow, and soil moisture, the model is parameterized for a 5° × 5° region encompassing the state of Illinois. It is shown that precipitation-efficiency feedbacks can be significant contributors to the variability of soil moisture at the regional scale. Precipitation recycling, on the other hand, increases the variability by a negligible amount. For all feedback cases, the probability density function is unimodal and nearly symmetric. The analysis concludes with an examination of the dependence of the shape of the probability density functions on spatial scale. It is shown that the associated increases in either the correlation time scale or the variance of the noise will produce a bimodal distribution when precipitation-efficiency feedbacks are included. However, the magnitudes of the necessary increases are of an unrealistic magnitude.

Spatial and temporal variability of benzo[a]pyrene over Poland based on modelling and observations

2020 ◽  
Author(s):  
Jacek W. Kaminski ◽  
Joanna Struzewska ◽  
Pawel Durka ◽  
Grzegorz Jeleniewicz ◽  
Marcin Kawka
Keyword(s):  
Temporal Variability ◽  
Emission Inventory ◽  
Regional Scale ◽  
Meteorological Conditions ◽  
Spatial And Temporal Variability ◽  
Entire Area ◽  
P Concentration ◽  
The World ◽  
National Measurement ◽  
Waste Burning

&lt;p&gt;Benzo[a]pyrene is relatively stable in the atmosphere and can be transported on a regional scale. Benzo[a]pyrene concentrations exceed standard limits in many regions of the world. It is proved that this compound is harmful to the environment and human health.&lt;/p&gt;&lt;p&gt;According to the CAF&amp;#201; Directive (2008/50/EC), the objective is to achieve a concentration of B[a]P below 1ng/m3 in PM10 aerosol. Observed B[a]P concentration in Poland is among the highest in Europe. These exceedances are attributed to the emission from individual heating, where many old installations are still in operation. Major B[a]P emissions are due to low-quality fuels and non-reported municipal waste burning.&lt;/p&gt;&lt;p&gt;To support the Chief Inspectorate of Environmental Protection in the frame of the annual assessment for 2018 and five-year assessment for the period 2014-2018, the spatial distribution of B[a]P was calculated using the GEM-AQ model (Kaminski et al. 2008). A new national high-resolution bottom-up emission inventory was used for the entire area of Poland. The results at the resolution of 2.5 km were compared with observations from over 100 stations from the National Measurement Network. We will discuss the spatial and seasonal variability od B[a]P concentrations as well as year-to-year changes related to meteorological conditions.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

scholarly journals Spatial and Temporal Variability of Root-Zone Soil Moisture Acquired From Hydrologic Modeling and AirMOSS P-Band Radar

2018 ◽  
Vol 11 (12) ◽  
pp. 4578-4590 ◽  
Author(s):  
Wade T. Crow ◽  
Sushil Milak ◽  
Mahta Moghaddam ◽  
Alireza Tabatabaeenejad ◽  
Sermsak Jaruwatanadilok ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Temporal Variability ◽  
Hydrologic Modeling ◽  
Root Zone ◽  
Spatial And Temporal Variability
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