Vertical changes in the flux of atmospheric nitrate from a forest canopy to the surface soil based on Δ 17 O values

Abstract. Interception is the storage and subsequent evaporation of rainfall by above-ground structures, including canopy and groundcover vegetation and surface litter. Accurately quantifying interception is critical for understanding how ecosystems partition incoming precipitation, but it is difficult and costly to measure, leading most studies to rely on modeled interception estimates. Moreover, forest interception estimates typically focus only on canopy storage, despite the potential for substantial interception by groundcover vegetation and surface litter. In this study, we developed an approach to quantify “total” interception (i.e., including forest canopy, understory, and surface litter layers) using measurements of shallow soil moisture dynamics during rainfall events. Across 34 pine and mixed forest stands in Florida (USA), we used soil moisture and precipitation (P) data to estimate interception storage capacity (βs), a parameter required to estimate total annual interception (Ia) relative to P. Estimated values for βs(mean βs=0.30 cm; 0.01≤βs≤0.62 cm) and Ia∕P (mean Ia/P=0.14; 0.06≤Ia/P≤0.21) were broadly consistent with reported literature values for these ecosystems and were significantly predicted by forest structural attributes (leaf area index and percent ground cover) as well as other site variables (e.g., water table depth). The best-fit model was dominated by LAI and explained nearly 80 % of observed βs variation. These results suggest that whole-forest interception can be estimated using near-surface soil moisture time series, though additional direct comparisons would further support this assertion. Additionally, variability in interception across a single forest type underscores the need for expanded empirical measurement. Potential cost savings and logistical advantages of this proposed method relative to conventional, labor-intensive interception measurements may improve empirical estimation of this critical water budget element.

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Estimating Interception from Near-Surface Soil Moisture Response

10.5194/hess-2019-157 ◽

2019 ◽

Author(s):

Subodh Acharya ◽

Daniel McLaughlin ◽

David Kaplan ◽

Matthew J. Cohen

Keyword(s):

Soil Moisture ◽

Forest Canopy ◽

Surface Soil ◽

Forest Type ◽

Mixed Forest ◽

Surface Soil Moisture ◽

Empirical Estimation ◽

Potential Cost ◽

Area Index ◽

Near Surface

Abstract. Interception is the storage and subsequent evaporation of rainfall by above-ground structures, including canopy and groundcover vegetation and surface litter. Accurately quantifying interception is critical for understanding how ecosystems partition incoming precipitation, but it is difficult and costly to measure, leading most studies to rely on modeled interception estimates. Moreover, forest interception estimates typically focus only on canopy storage, despite the potential for substantial interception by groundcover vegetation and surface litter. In this study, we developed an approach to quantify total interception losses (i.e., including forest canopy, understory, and surface litter layers) using measurements of shallow soil moisture dynamics during rainfall events. Across 36 pine and mixed forest stands in Florida (USA), we used soil moisture and rainfall data to estimate the interception storage capacity (βs), a parameter required to estimate total annual interception losses (Ia) relative to rainfall (R). Estimated values for βs (mean βs = 0.30 cm; 0.01 ≤ βs ≤ 0.62 cm) and Ia/R (mean Ia/R = 0.14; 0.06 ≤ Ia/R ≤ 0.21) were consistent with reported literature values for these ecosystems and were significantly predicted by forest structural attributes (leaf area index and percent groundcover), as well as other site variables (e.g., water table depth). The best-fit model was dominated by LAI and explained nearly 80 % of observed βs variation. These results suggest that whole-forest interception can be measured using a single near-surface soil moisture time series and highlight the variability in interception losses across a single forest type, underscoring the need for expanded empirical measurement. Potential cost savings and logistical advantages of this method relative to conventional, labor-intensive interception measurements may improve empirical estimation of this critical water budget element.

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Forest Canopy Density and ASTER DEM based Study for Dense Forest Investigation using Remote Sensing and GIS Techniques around East Singhbhum in Jharkhand, India

International Journal of Advanced Remote Sensing and GIS ◽

10.23953/cloud.ijarsg.96 ◽

2015 ◽

Vol 4 (1) ◽

pp. 1026-1032 ◽

Cited By ~ 6

Author(s):

Jai Kumar ◽

◽

Paras Talwar ◽

Krishna A.P. ◽

◽

...

Keyword(s):

Remote Sensing ◽

Forest Canopy ◽

Remote Sensing And Gis ◽

Canopy Density ◽

Gis Techniques ◽

Dense Forest ◽

Forest Canopy Density

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Relation between soil temperature and biophysical parameters in Indian mustard seeds

International Agrophysics ◽

10.2478/intag-2013-0005 ◽

2013 ◽

Vol 27 (4) ◽

pp. 359-367 ◽

Cited By ~ 1

Author(s):

T. Adak ◽

N.V.K. Chakravarty

Keyword(s):

Regression Analysis ◽

Linear Regression ◽

Soil Temperature ◽

Surface Soil ◽

Linear Regression Analysis ◽

Indian Mustard ◽

Biophysical Parameters ◽

Oil Accumulation ◽

Area Index ◽

Surface Soil Temperature

Abstract Temporal changes in surface soil temperature were studied in winter crop. Significant changes in bare and cropped soil temperature were revealed. Air temperature showed a statistically positive and strong relationship (R2 = 0.79** to 0.92**) with the soil temperature both at morning and afternoon hours. Linear regression analysis indicated that each unit increase in ambient temperature would lead to increase in minimum and maximum soil temperatures by 1.04 and 1.02 degree, respectively. Statistically positive correlation was revealed among biophysical variables with the cumulative surface soil temperature. Linear and non-linear regression analysis indicated 62-69, 72-86 and 72-80% variation in Leaf area index, dry matter production and heat use efficiency in Indian mustard crop as a function of soil degree days. Below 60% variation in yield in Indian mustard was revealed as a function of soil temperature. In contrast, non-significant relationship between oil content and soil temperature was found, which suggests that oil accumulation in oilseed crops was not affected significantly by the soil temperature as an independent variable.

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