Soil organic carbon prediction with terrain derivatives using geostatistics and sequential Gaussian simulation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41210%2F21%3A89188" target="_blank" >RIV/60460709:41210/21:89188 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S1658077X21000485" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1658077X21000485</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.jssas.2021.04.005" target="_blank" >10.1016/j.jssas.2021.04.005</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Soil organic carbon prediction with terrain derivatives using geostatistics and sequential Gaussian simulation

Popis výsledku v původním jazyce

This current study investigated the relationship between soil organic carbon SOC and terrain derivatives on soil developed on dissimilar lithology while comparing the best modelling approach. Sixty bulk soil samples were taken from the depth of 0 to 30 cm according to five identified basement complex materials and analyzed for SOC. The models considered are ordinary kriging OK, principal components kriging (PCA-OK) and regression kriging (RK). For the predictions accuracy, 2 fold, and leave one out cross validation was carried out. The study indicated SOC in soil developed on granite gneiss and biotite hornblende gneiss to be significantly higher than those on other lithology materials. RK improved the map structure with terrain derivatives, but the area was generally low in SOC. Model limitations showed that OK requires larger samples to improve the quality of prediction. Also, RK significant dissatisfaction is that the regression model parameters and covariance function parameters need to be estima

Název v anglickém jazyce

Soil organic carbon prediction with terrain derivatives using geostatistics and sequential Gaussian simulation

Popis výsledku anglicky

This current study investigated the relationship between soil organic carbon SOC and terrain derivatives on soil developed on dissimilar lithology while comparing the best modelling approach. Sixty bulk soil samples were taken from the depth of 0 to 30 cm according to five identified basement complex materials and analyzed for SOC. The models considered are ordinary kriging OK, principal components kriging (PCA-OK) and regression kriging (RK). For the predictions accuracy, 2 fold, and leave one out cross validation was carried out. The study indicated SOC in soil developed on granite gneiss and biotite hornblende gneiss to be significantly higher than those on other lithology materials. RK improved the map structure with terrain derivatives, but the area was generally low in SOC. Model limitations showed that OK requires larger samples to improve the quality of prediction. Also, RK significant dissatisfaction is that the regression model parameters and covariance function parameters need to be estima

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

40104 - Soil science

Projekt

<a href="/cs/project/EF16_019%2F0000845" target="_blank" >EF16_019/0000845: Centrum pro studium vzniku a transformací nutričně významných látek v potravním řetězci v interakci s potenciálně rizikovými látkami antropogenního původu: komplexní posouzení rizika kontaminace půdy pro kvalitu zemědělské produkce</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of the Saudi Society of Agricultural Sciences

ISSN

1658-077X

e-ISSN

—

Svazek periodika

20

Číslo periodika v rámci svazku

sep

Stát vydavatele periodika

SA - Království Saúdská Arábie

Počet stran výsledku

11

Strana od-do

379-389

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85106303642