Benchmarking of topsoil moisture estimation methods based on a field study

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F86652079%3A_____%2F25%3A00641480" target="_blank" >RIV/86652079:_____/25:00641480 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/62156489:43210/25:43926597

Výsledek na webu

<a href="https://www.cambridge.org/core/journals/journal-of-agricultural-science/article/abs/benchmarking-of-topsoil-moisture-estimation-methods-based-on-a-field-study/2CB245646B8586D906809598E154F565#article" target="_blank" >https://www.cambridge.org/core/journals/journal-of-agricultural-science/article/abs/benchmarking-of-topsoil-moisture-estimation-methods-based-on-a-field-study/2CB245646B8586D906809598E154F565#article</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1017/S0021859625000036" target="_blank" >10.1017/S0021859625000036</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Benchmarking of topsoil moisture estimation methods based on a field study

Popis výsledku v původním jazyce

Extreme weather events caused by climate change, such as drought and heavy rainfall, will further increase in Central Europe in the near future. Resilient crop production requires in-depth knowledge of soil moisture (SM), its spatial and temporal variability and the dynamics of agriculturally used land. In the current study, different SM estimation methods, including measurement and simulation-based methods, were evaluated over a 17-ha experimental arable crop field with respect to their abilities to capture the spatial and temporal SM dynamics of within-field areas and their related uncertainty and spatial representativeness. The high-spatial resolution in-situ topsoil moisture measurements (50 m grid) were compared with the estimated SM from satellite-based remote sensing (S1ASCAT) and the simulated SM from three different crop water balance models (Agricultural Risk Information System [ARIS], AquaCrop and DSSAT). The evaluation revealed that the spatial variability in the experimental field obtained from the reference could not be captured by the alternative methods investigated because of the limitations of the grid size-related soil map information. Nevertheless, the analysis revealed a very good temporal correlation of SM dynamics with the field area average across all approaches, with AquaCrop and ARIS at a soil depth of 0-10 cm and S1ASCAT soil-water index 05 achieving a R2 and a Kling-Gupta efficiency >0.80. These results indicate the added value of complementary methods for estimating SM to reduce spatial and temporal uncertainties in the estimated topsoil water content.

Název v anglickém jazyce

Benchmarking of topsoil moisture estimation methods based on a field study

Popis výsledku anglicky

Extreme weather events caused by climate change, such as drought and heavy rainfall, will further increase in Central Europe in the near future. Resilient crop production requires in-depth knowledge of soil moisture (SM), its spatial and temporal variability and the dynamics of agriculturally used land. In the current study, different SM estimation methods, including measurement and simulation-based methods, were evaluated over a 17-ha experimental arable crop field with respect to their abilities to capture the spatial and temporal SM dynamics of within-field areas and their related uncertainty and spatial representativeness. The high-spatial resolution in-situ topsoil moisture measurements (50 m grid) were compared with the estimated SM from satellite-based remote sensing (S1ASCAT) and the simulated SM from three different crop water balance models (Agricultural Risk Information System [ARIS], AquaCrop and DSSAT). The evaluation revealed that the spatial variability in the experimental field obtained from the reference could not be captured by the alternative methods investigated because of the limitations of the grid size-related soil map information. Nevertheless, the analysis revealed a very good temporal correlation of SM dynamics with the field area average across all approaches, with AquaCrop and ARIS at a soil depth of 0-10 cm and S1ASCAT soil-water index 05 achieving a R2 and a Kling-Gupta efficiency >0.80. These results indicate the added value of complementary methods for estimating SM to reduce spatial and temporal uncertainties in the estimated topsoil water content.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10509 - Meteorology and atmospheric sciences

Projekt

<a href="/cs/project/EH22_008%2F0004635" target="_blank" >EH22_008/0004635: AdAgriF - Pokročilé metody redukce emisí a sekvestrace skleníkových plynů v zemědělské a lesní krajině pro mitigaci změny klimatu</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

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

Název periodika

Journal of Agricultural Science

ISSN

0021-8596

e-ISSN

1469-5146

Svazek periodika

163

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

17

Strana od-do

71-87

Kód UT WoS článku

001420483100001

EID výsledku v databázi Scopus

2-s2.0-105002269837