Mapping Soil Organic Matter in Low-Relief Areas Based on Time Series Land Surface Diurnal Temperature Difference

2016 ◽  
pp. 47-62
Author(s):  
Ming-Song Zhao ◽  
Gan-Lin Zhang ◽  
Feng Liu ◽  
De-Cheng Li ◽  
Yu-Guo Zhao
Keyword(s):  
Time Series ◽  
Organic Matter ◽  
Soil Organic Matter ◽  
Temperature Difference ◽  
Land Surface ◽  
Diurnal Temperature

Mapping soil organic matter in low-relief areas based on land surface diurnal temperature difference and a vegetation index

2014 ◽  
Vol 39 ◽  
pp. 120-133 ◽  
Author(s):  
Ming-Song Zhao ◽  
David G. Rossiter ◽  
De-Cheng Li ◽  
Yu-Guo Zhao ◽  
Feng Liu ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Temperature Difference ◽  
Land Surface ◽  
Vegetation Index ◽  
Diurnal Temperature

scholarly journals Deriving pedotransfer functions for soil quartz fraction in southern France from reverse modeling

SOIL ◽  
2016 ◽  
Vol 2 (4) ◽  
pp. 615-629 ◽  
Author(s):  
Jean-Christophe Calvet ◽  
Noureddine Fritz ◽  
Christine Berne ◽  
Bruno Piguet ◽  
William Maurel ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Organic Matter ◽  
Soil Organic Matter ◽  
Land Surface ◽  
Geometric Mean ◽  
Sensible Heat Flux ◽  
Pedotransfer Functions ◽  
Quartz Content ◽  
Southern France ◽  
Weather Stations

Abstract. The quartz fraction in soils is a key parameter of soil thermal conductivity models. Because it is difficult to measure the quartz fraction in soils, this information is usually unavailable. This source of uncertainty impacts the simulation of sensible heat flux, evapotranspiration and land surface temperature in numerical simulations of the Earth system. Improving the estimation of soil quartz fraction is needed for practical applications in meteorology, hydrology and climate modeling. This paper investigates the use of long time series of routine ground observations made in weather stations to retrieve the soil quartz fraction. Profile soil temperature and water content were monitored at 21 weather stations in southern France. Soil thermal diffusivity was derived from the temperature profiles. Using observations of bulk density, soil texture, and fractions of gravel and soil organic matter, soil heat capacity and thermal conductivity were estimated. The quartz fraction was inversely estimated using an empirical geometric mean thermal conductivity model. Several pedotransfer functions for estimating quartz content from gravimetric or volumetric fractions of soil particles (e.g., sand) were analyzed. The soil volumetric fraction of quartz (fq) was systematically better correlated with soil characteristics than the gravimetric fraction of quartz. More than 60 % of the variance of fq could be explained using indicators based on the sand fraction. It was shown that soil organic matter and/or gravels may have a marked impact on thermal conductivity values depending on which predictor of fq is used. For the grassland soils examined in this study, the ratio of sand-to-soil organic matter fractions was the best predictor of fq, followed by the gravimetric fraction of sand. An error propagation analysis and a comparison with independent data from other tested models showed that the gravimetric fraction of sand is the best predictor of fq when a larger variety of soil types is considered.

Mapping Soil Texture of a Plain Area Using Fuzzy-c-Means Clustering Method Based on Land Surface Diurnal Temperature Difference

Pedosphere ◽  
2012 ◽  
Vol 22 (3) ◽  
pp. 394-403 ◽  
Author(s):  
De-Cai WANG ◽  
Gan-Lin ZHANG ◽  
Xian-Zhang PAN ◽  
Yu-Guo ZHAO ◽  
Ming-Song ZHAO ◽  
...  
Keyword(s):  
Temperature Difference ◽  
Soil Texture ◽  
Land Surface ◽  
Clustering Method ◽  
Diurnal Temperature ◽  
Fuzzy C Means ◽  
Plain Area ◽  
Fuzzy C Means Clustering

scholarly journals Warming and elevated CO2 promote incorporation of plant-derived lipids into soil organic matter in a spruce-dominated ombrotrophic bog

2021 ◽  
Author(s):  
Ofiti O.E. Nicholas ◽  
Zosso U. Cyrill ◽  
Solly F. Emily ◽  
Hanson J. Paul ◽  
Wiesenberg L.B. Guido ◽  
...  
Keyword(s):  
Fatty Acids ◽  
Organic Matter ◽  
Soil Organic Matter ◽  
Land Surface ◽  
Stable Carbon Isotopes ◽  
Specific Response ◽  
Microbial Decomposition ◽  
Short Period ◽  
Bulk Organic Matter ◽  
The Impact

<p>More than one third of global soil organic matter (SOM) is stored in peatlands, despite them occupying less than 3% of the land surface. Increasing global temperatures have the potential to stimulate the decomposition of carbon stored in peatlands, contributing to the release of disproportionate amounts of greenhouse gases to the atmosphere but increasing atmospheric CO<sub>2</sub> concentrations may stimulate photosynthesis and return C into ecosystems.  Key questions remain about the magnitude and rate of these interacting and opposite processes to environmental change drivers.</p><p>We assessed the impact of a 0–9°C temperature gradient of deep peat warming (4 years of warming; 0-200 cm depth) in ambient or elevated CO<sub>2</sub> (2 years of +500 ppm CO<sub>2</sub> addition) on the quantity and quality of SOM at the climate change manipulation experiment SPRUCE (Spruce and Peatland Responses Under Changing Environments) in Minnesota USA. We assessed how warming and elevated CO<sub>2</sub> affect the degradation of plant and microbial residues as well as the incorporation of these compounds into SOM. Specifically, we combined the analyses of free extractable <em>n</em>-alkanes and fatty acids together with measurements of compound-specific stable carbon isotopes (δ<sup>13</sup>C).</p><p>We observed a 6‰ offset in δ<sup>13</sup>C between bulk SOM and <em>n</em>-alkanes, which were uniformly depleted in δ<sup>13</sup>C when compared to bulk organic matter. Such an offset between SOM and <em>n</em>-alkanes is common due to biosynthetic isotope fractionation processes and confirms previous findings. After 4 years of deep peat warming, and 2 years of elevated CO<sub>2</sub> addition a strong depth-specific response became visible with changes in SOM quantity and quality. In the upper 0-30 cm depth, individual <em>n</em>-alkanes and fatty acid concentrations declined with increasing temperatures with warming treatments, but not below 50 cm depth. In turn, the δ<sup>13</sup>C values of bulk organic matter and of individual <em>n</em>-alkanes and fatty acids increased in the upper 0-30 cm with increasing temperatures, but not below 50 cm depth. Thus <em>n</em>-alkanes, which typically turnover slower than bulk SOM, underwent a rapid transformation after a relatively short period of simulated warming in the acrotelm. Our results suggest that warming accelerated microbial decomposition of plant-derived lipids, leaving behind more degraded organic matter. The non-uniform, and depth dependent warming response implies that warming will have cascading effects on SOM decomposition in the acrotelm in peatlands. It remains to be seen how fast the catotelm will respond to rising temperatures and atmospheric CO<sub>2</sub> concentrations.</p>

scholarly journals Spatial Estimation of Soil Organic Matter in Karst Peak-cluster Depression

2015 ◽  
Vol 9 (1) ◽  
pp. 1022-1027 ◽  
Author(s):  
Li Hui ◽  
Jiang Zhong-Cheng ◽  
Yang Qi-Yong ◽  
Yin Hui ◽  
Wang Yue
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Land Surface ◽  
Regression Kriging ◽  
Auxiliary Variables ◽  
Peak Cluster ◽  
Republic Of China ◽  
Spatial Estimation ◽  
Terrain Attributes ◽  
Karst Areas

In order to enhance the accuracy of spatial estimation of soil organic matter (SOM), spatial predictions of SOM in 0~20 cm depth were conducted in Guohua Ecological Experimental Area of Minister of Land and Resource of the People’s Republic of China. Analysis of multiple linear stepwise regressions showed that the two terrain attributes of relief degree of land surface (RS) and distance from ridge of mountains (DFR) entered into the regression equation. Therefore, RS and DFR were selected as auxiliary variables to predict SOM by MCOK and RK methods. The accuracy of spatial estimation of SOM was compared among methods of ordinary kriging (OK), multivariable cokriging (MCOK) and regression kriging (RK). Results showed that RK and MCOK methods with terrain attributes as auxiliary variables could enhance the accuracy of spatial estimation of SOM, and MCOK method could promote the accuracy notable by 31.33%. This study can provide a new idea and method for evaluation of soil quality in karst areas.

Soil organic matter dominates the magnitude of porosity and bulk density in temperate soils, with important implications for land surface models

2021 ◽  
Author(s):  
Amy Thomas ◽  
Fiona Seaton ◽  
Jack Cosby ◽  
Bridget Emmett ◽  
Sabine Reinsch ◽  
...  
Keyword(s):  
Climate Change ◽  
Organic Matter ◽  
Soil Organic Matter ◽  
Land Surface ◽  
Pedotransfer Functions ◽  
Soil Porosity ◽  
Land Surface Models ◽  
Surface Models ◽  
Global Land ◽  
Temperate Soils

<p>Soil porosity controls the flow of mass and energy through soil, and thus plays a fundamental role in regulating hydrological and biochemical cycling at the land surface. Global land surface and earth system models commonly derive porosity from soil texture using pedotransfer functions. This does not allow for response to change in environment or management, or potentially important climate feedbacks. Furthermore, the approach does not fully represent the baseline spatial variation in this important soil property. Here we show that porosity, and bulk density (BD), depend on SOM in temperate soils, using two comprehensive national data sets, covering the full range of soil organic matter (SOM) (n=1385 & n=2570). Our novel use of analytical models with machine learning (ML) algorithms opens up new physical insight into controls on porosity and BD, while generalized additive mixed models (GAMMs) provide further insights and opportunities for prediction. Our models allow us to consider influence of management on soil compaction and recent observations that soil porosity responds to climate change. The dependence of soil porosity on SOM, more so than texture, indicates the need for a paradigm shift in the conceptualization and modelling of these soil physical properties. Broad habitat was also an important control, and explained some of the variance in the relationship between SOM and porosity. This highlights that changes in soil porosity may occur due to land use or climate change, and will create feedbacks to hydrological and biogeochemical cycling which should be represented in Global land surface models. This will also be important for other pedotransfer functions, e.g. the use of BD to determine carbon stock from concentration.  In addition, we found opportunities for improved representation of the spatial pattern of porosity, even in the absence of measured data on SOM, based on climate and earth observation data.</p>

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