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A progressive simulation method to estimate the stocks of surface soil organic carbon and total nitrogen in an estuarine archipelago.

Authors :
Chi, Yuan
Liu, Dahai
Xie, Zuolun
Wang, Jing
Source :
CATENA. Feb2022:Part 2, Vol. 209, pN.PAG-N.PAG. 1p.
Publication Year :
2022

Abstract

[Display omitted] • A progressive simulation method was proposed to further improve the accuracy of estuarine DSM. • The method adequately utilized the close correlations among soil parameters in estuarine areas. • The progressive simulation increased accuracies for SOC and TN by 54.4% and 57.2%, respectively. • Island exploitations and reclamation activities determined the spatial pattern of SOC and TN stocks. • The method was proven to be applicable in estuarine DSM and showed potential for 3D and 4D mapping. Simulating the soil organic carbon (SOC) and total nitrogen (TN) stocks in estuarine areas is important for the development of digital soil mapping and the regional inventory of carbon and nitrogen, and simulation accuracy is the key issue. In this study, a progressive simulation method was proposed to further improve accuracy through the adequate utilization of the correlations among soil parameters and their relations with the comprehensive land surface factor system. Three soil parameters, namely, SOC, TN, and bulk density (BD), were simulated using the method for estimating SOC and TN stocks. The simulations were progressively conducted in three levels (Levels 1–3) by using partial least squares regression (PLSR) and cokriging. Each of the parameters was simulated separately in Level 1, one parameter was simulated based on each of the two other parameters in Level 2, and one parameter was simulated based on the two other parameters in Level 3. A typical estuarine archipelago in southern China was selected to demonstrate the performance of the method in surface soil (0–20 cm). Results showed the effectiveness of the progressive simulation in improving accuracy when the PLSR was used. The simulation results in Level 3 had the highest accuracy among the results in all levels, increasing the accuracies for SOC, TN, and BD by 54.35%, 57.24%, and 5.61%, respectively, compared with those in Level 1 and achieving high accuracies compared with those in similar studies. The SOC and TN stocks amounted to 270.66 and 26.96 Gg, respectively, and the mean values of SOC and TN densities were 2.65 and 0.26 kg/m2, respectively, which are lower than global values and those for China. The SOC and TN densities exhibited distinct spatial heterogeneities, which were fundamentally driven by different types of island exploitations and large-scale sea reclamation activities. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03418162
Volume :
209
Database :
Academic Search Index
Journal :
CATENA
Publication Type :
Academic Journal
Accession number :
153956042
Full Text :
https://doi.org/10.1016/j.catena.2021.105837