scholarly journals Effect of soil moisture on spatial variation of soil heat capacity

2017 ◽  
Author(s):  
Huanzhuang Tao ◽  
Siwen Zheng ◽  
Ying Lin ◽  
Lei Gan ◽  
Yangjian Peng ◽  
...  
Keyword(s):  
Heat Capacity ◽  
Soil Moisture ◽  
Spatial Variation ◽  
Soil Heat Capacity

Net precipitation assessment in a grassland and soil moisture response at plot scale in a temperate climate

2021 ◽  
Author(s):  
Gökben Demir ◽  
Johanna Clara Metzger ◽  
Janett Filipzik ◽  
Christine Fischer ◽  
Beate Michalzik ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Spatial Variation ◽  
Canopy Structure ◽  
Sampling Period ◽  
Temperate Climate ◽  
Small Scale ◽  
Spatial Effects ◽  
Mixed Effect ◽  
Canopy Development ◽  
Canopy Effect

<div> <p>Evidence on spatial variation of net precipitation in grasslands is scarce. Challenges arise due to a small-scale canopy structure of grasslands.</p> <p>In this study, we designed and tested a new in-situ measurement device (interception grid) to assess net precipitation in grasslands. The collector allows the natural development of the canopy. We tested the device both in the lab for splash loss and in the field to test its capacity to assess net precipitation. In the field, we installed 25 collectors on a grassland within the Hainich Critical Zone Exploratory (Thuringia, Germany), 23 of which were paired with soil moisture sensors. We conducted weekly measurements gross and net precipitation (above and below the canopy), along with grass height in 2019 (March-August) and 2020 (January -February). We categorized the data into two groups (‘covered,’ ‘uncovered’), accounting for canopy development.</p> <p>In the lab, we found that the drop size strongly affects splash loss. Drops of ca. 2 mm, created more than 16% splash loss, decreasing to less than 3% for drops <1.5 mm. Drop sizes <1.75 mm during the sampling period (2019) suggest low to intermediate splash loss in the field, further decreased in the covered period as the canopy contact slows down the drops. Grid measurements corrected with estimated splash loss during the uncovered period agreed well with gross precipitation. Using linear mixed effect models, we found that wind speed and grass height significantly affected the grid measurements of covered periods. Therefore, grids were able to capture net precipitation variation due to grass development. These steps encouraged us to examine the canopy effect in the soil moisture response to rainfall.</p> <p>Soil moisture response over the entire period was not related to the spatial variation of net precipitation. However, for the drier period (June-August 2019), when the spatial variation in soil moisture is higher, and the overall response to rain events stronger, net precipitation slightly affected soil moisture response. LMEM analysis to estimate factors on soil moisture response showed that grass height, net precipitation are significant predictors. Yet, there is no remarkable difference between using net precipitation and gross precipitation as potential drivers for soil moisture response, indicating that the spatial effects are comparatively small. Overall, our findings suggest that the grids are cable to catch canopy effects on the precipitation, while the effect of wind on under-catch still needs to be investigated further.</p> </div>

scholarly journals Mapping the spatial variation of soil moisture at the large scale using GPR for pavement applications

2014 ◽  
Vol 13 (3) ◽  
pp. 269-278 ◽  
Author(s):  
Andrea Benedetto ◽  
Fabio Tosti ◽  
Bianca Ortuani ◽  
Mauro Giudici ◽  
Mauro Mele
Keyword(s):  
Soil Moisture ◽  
Spatial Variation ◽  
Large Scale

A review of factors affecting minimum temperature reached on clear, windless nights.

1991 ◽  
Vol 42 (1) ◽  
pp. 191 ◽  
Author(s):  
WK Gardner ◽  
GK McDonald ◽  
SE Ellis ◽  
M Platt ◽  
RG Flood
Keyword(s):  
Thermal Conductivity ◽  
Heat Capacity ◽  
Water Content ◽  
Temperature Profiles ◽  
Surface Emissivity ◽  
Factors Affecting ◽  
Surface Temperatures ◽  
Net Flux ◽  
Soil Heat Capacity ◽  
Initial Starting

A mathematical model of heat flux in which net flux was assumed to be proportional to the surface temperature was used to examine the effects of important environmental variables on minimum surface temperatures reached during cloudless nights. Variables considered were altitude, atmospheric water content, surface emissivity, soil heat capacity and conductivity, length of night, and initial starting temperature. Final temperatures reached were especially sensitive to changes in soil thermal conductivity and heat capacity. Both these parameters are affected by moisture content (particularly when low), making this the single most important factor affecting the severity of frost. Lower initial starting temperatures and longer nights increase the severity of frosting, as does any decrease in the depth of the atmosphere (as happens with changes in altitude) or reductions in the water content of the atmosphere. Emissivity of the radiating surface is relatively unimportant. Temperature profiles in the soil were similar, but extended to greater depths as heat capacitance declined, whereas lower thermal conductivity resulted in cooler surface temperatures while the decline in temperature did not extend as deep. The model was shown to be an improvement on one in which net flux was assumed to remain constant, and allows for a more instructive sensitivity analysis.

Spatial variation in soil physical properties and effects on soil NO3– production on forest hillslopes

2020 ◽  
Author(s):  
Tomoki Oda ◽  
Megumi Kuroiwa ◽  
Naoya Fujime ◽  
Kazuo Isobe ◽  
Naoya Masaoka ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Soil Moisture ◽  
Physical Properties ◽  
Spatial Variation ◽  
Volcanic Ash ◽  
Surface Soil ◽  
Soil Physical Properties ◽  
Slope Position ◽  
Surface Soil Moisture ◽  
Slope Bottom

<p>Ammonium (NH<sub>4</sub><sup>+</sup>) and nitrate (NO<sub>3</sub><sup>–</sup>) concentrations and production rates in forest soil vary by hillslope position due to variation in ammonia-oxidizing microorganism concentrations, soil chemistry, and surface soil moisture. These spatial distributions have a significant effect on nutrient cycles and streamwater chemistry. Soil moisture conditions significantly restrict microbial activity, influencing the spatial distribution of NO<sub>3</sub><sup>–</sup> concentrations on forest hillslopes. However, studies linking forest hydrological processes to nitrogen cycling are limited. Therefore, we investigated the determinants of spatial variation in soil moisture and evaluated the effects of soil moisture fluctuations on spatial variation in NO<sub>3</sub><sup>–</sup> concentration and production rate.</p><p>The study sites were the Fukuroyamasawa Experimental Watershed (FEW) and Oyasan Experimental Watershed (OEW) in Japan. The two have similar topographies, climates, and tree species. In each watershed, a 100 m transect was set up from the ridge to the base of the slope, and soil moisture sensors were installed at soil depths of 10 cm and 30 cm at both the top and bottom of the slope. We collected surface soil samples at a depth of 10 cm at the top, middle, and bottom of the slopes using 100 cm<sup>3</sup> cores, and measured soil physical properties, particle size distribution, volcanic ash content, chemical properties (pH, NO<sub>3</sub><sup>–</sup>, NH<sub>4</sub><sup>+</sup>, nitrification rate, and mineralization rate), and microbial content (archaeal content). Spatial and temporal changes in soil moisture on the hillslope were calculated using HYDRUS-2D to examine contributing factors of soil moisture.</p><p>At FEW, high NO<sub>3</sub><sup>–</sup> concentrations and nitrification rates were observed only at the slope bottom and middle, and no NO<sub>3</sub><sup>–</sup> concentrations were detected at up slope. By contrast, at OEW, high NO<sub>3</sub><sup>–</sup> concentrations and nitrification rates were observed at all points. NH<sub>4</sub><sup>+</sup> concentrations were similar at all points in both watersheds. At FEW, 10 cm surface soil moisture fluctuated within 25–40% at the slope top but was within 40–50% at the slope bottom. At OEW, surface soil moisture was 30–40% at both the slope top and bottom, with no significant differences according to slope position. It was confirmed that soil moisture was significantly involved in NO<sub>3</sub><sup>– </sup>concentration and nitrification rates. Model simulations showed that the difference in soil moisture fluctuations between FEW and OEW was mainly explained by the spatial variation in soil physical properties. In particular, volcanic ash influenced soil moisture along the entire slope at OEW, resulting in high water retention, but only influenced soil moisture at the slope bottom at FEW. These findings indicate that spatial variability in soil physical properties has a significant effect on soil moisture fluctuation and leads to a spatial distribution of NO<sub>3</sub><sup>–</sup> production.</p>

Temporal and spatial variation in how vegetation alters the soil moisture response to climate manipulation

2011 ◽  
Vol 351 (1-2) ◽  
pp. 249-261 ◽  
Author(s):  
Pierre Liancourt ◽  
Anarmaa Sharkhuu ◽  
Lkhagva Ariuntsetseg ◽  
Bazartseren Boldgiv ◽  
Brent R. Helliker ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Spatial Variation ◽  
Temporal And Spatial Variation ◽  
Temporal And Spatial ◽  
Climate Manipulation
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