Effects of Climatic and Soil Data on Soil Drought Monitoring Based on Different Modelling Schemes

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00020699%3A_____%2F21%3AN0000030" target="_blank" >RIV/00020699:_____/21:N0000030 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/86652079:_____/21:00544203 RIV/62156489:43210/21:43920094 RIV/00216224:14310/21:00121945

Výsledek na webu

<a href="https://www.mdpi.com/2073-4433/12/7/913/htm" target="_blank" >https://www.mdpi.com/2073-4433/12/7/913/htm</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/atmos12070913" target="_blank" >10.3390/atmos12070913</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Effects of Climatic and Soil Data on Soil Drought Monitoring Based on Different Modelling Schemes

Popis výsledku v původním jazyce

Satisfactory requirements for the spatial resolution of climate and the influences of soil data in defining the starting points, endings, and the intensities of droughts have become matters of discussion in recent years. The overall inclusiveness of the modelling tools applied is also frequently discussed. In this light, five model setups (MSs) of the daily SoilClim water balance model were developed and tested for the Czech Republic (CR) in the 1961–2020 period. These included two versions of the SoilClim model, two sets of soil data, and two sets of climatic data at different spatial resolutions. MS1–MS4 were based on local, spatially-interpolated data from meteorological stations (500 × 500 m resolution), while MS5 was developed for global drought monitoring, based on the coarser ERA5-Land reanalysis (0.1◦ × 0.1◦). During the 1961–2020 period, all the MSs indicated strong, statistically significant increases in the occurrence of 10th-percentile soil drought in the April–June season; however, trends remained largely non-significant for the remainder of the year. Variations among MS1–MS4 demonstrate that the range of soil property input data affects results to a lesser extent than different modelling schemes. The major simplification of the model grid in MS5 still led to an acceptable conformity of results, while the non-conformities disclosed may be explained by differences between meteorological inputs. Comparison with the Palmer Drought Severity Index (PDSI) confirmed that the SoilClim model depicts the variability of soil drought occurrence in greater detail, while PDSI tends to highlight the most severe events. The discussion arising out of the study centers around model uncertainties and the expression of soil drought episodes in different MSs.

Název v anglickém jazyce

Effects of Climatic and Soil Data on Soil Drought Monitoring Based on Different Modelling Schemes

Popis výsledku anglicky

Satisfactory requirements for the spatial resolution of climate and the influences of soil data in defining the starting points, endings, and the intensities of droughts have become matters of discussion in recent years. The overall inclusiveness of the modelling tools applied is also frequently discussed. In this light, five model setups (MSs) of the daily SoilClim water balance model were developed and tested for the Czech Republic (CR) in the 1961–2020 period. These included two versions of the SoilClim model, two sets of soil data, and two sets of climatic data at different spatial resolutions. MS1–MS4 were based on local, spatially-interpolated data from meteorological stations (500 × 500 m resolution), while MS5 was developed for global drought monitoring, based on the coarser ERA5-Land reanalysis (0.1◦ × 0.1◦). During the 1961–2020 period, all the MSs indicated strong, statistically significant increases in the occurrence of 10th-percentile soil drought in the April–June season; however, trends remained largely non-significant for the remainder of the year. Variations among MS1–MS4 demonstrate that the range of soil property input data affects results to a lesser extent than different modelling schemes. The major simplification of the model grid in MS5 still led to an acceptable conformity of results, while the non-conformities disclosed may be explained by differences between meteorological inputs. Comparison with the Palmer Drought Severity Index (PDSI) confirmed that the SoilClim model depicts the variability of soil drought occurrence in greater detail, while PDSI tends to highlight the most severe events. The discussion arising out of the study centers around model uncertainties and the expression of soil drought episodes in different MSs.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10510 - Climatic research

Projekt

<a href="/cs/project/EF16_019%2F0000797" target="_blank" >EF16_019/0000797: SustES - Adaptační strategie pro udržitelnost ekosystémových služeb a potravinové bezpečnosti v nepříznivých přírodních podmínkách</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název periodika

Atmosphere

ISSN

2073-4433

e-ISSN

2073-4433

Svazek periodika

12

Číslo periodika v rámci svazku

7

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

20

Strana od-do

1-20

Kód UT WoS článku

000675957200001

EID výsledku v databázi Scopus

2-s2.0-85111149152