All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

Optimization of soil hydraulic parameters within a constrained sampling space

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11310%2F25%3A10500344" target="_blank" >RIV/00216208:11310/25:10500344 - isvavai.cz</a>

  • Result on the web

    <a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=Sg.KDaM9aj" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=Sg.KDaM9aj</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.geoderma.2025.117210" target="_blank" >10.1016/j.geoderma.2025.117210</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Optimization of soil hydraulic parameters within a constrained sampling space

  • Original language description

    The direct optimization of soil hydraulic parameters (SHP) in unconstrained parameter space introduces significant uncertainties in ecohydrological modeling, particularly when addressing the complex model structure of Richards&apos; equation combined with Penman-Monteith equation. Pedotransfer functions (e.g., the latest version of Rosetta 3), which have been extensively trained using abundant soil hydraulic data, could potentially provide a physical constraint for sampling SHP. This study integrates optimization algorithms (Particle Swarm Optimization, PSO; Markov Chain Monte Carlo, MCMC; Sequential Monte Carlo, SMC; Generalized Likelihood Uncertainty Estimation, GLUE) with two sampling strategies- direct optimization of SHP and indirect optimization of SHP derived from soil particle composition (SPC) using Rosetta 3- to evaluate their performance in ecohydrological modeling under predefined soil conditions. The results demonstrated that indirect optimization of SHP significantly enhances the accuracy in recovering predefined true parameters and states, and reduces the uncertainty of ecohydrological modeling compared to direct optimization of SHP. Specifically, the mean quartile deviation of biases in soil water content and evaporation were reduced from 0.0347 m3/m3 and 0.0027 m/h to 0.0061 m3/m3 and 0.0010 m/h, respectively. Furthermore, integration of the Rosetta 3 diminished the dimensionality of inverse modeling, thereby significantly enhancing algorithm convergence speed and precision. It is recommended to integrate Rosetta 3 with various optimization algorithms to enhance the accuracy of ecohydrological modeling.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10508 - Physical geography

Result continuities

  • Project

    <a href="/en/project/GN22-20422O" target="_blank" >GN22-20422O: Insect induced tree mortality under climate change – Impacts on hydrology and geochemistry across scales</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2025

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Geoderma

  • ISSN

    0016-7061

  • e-ISSN

    1872-6259

  • Volume of the periodical

    455

  • Issue of the periodical within the volume

    February

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    17

  • Pages from-to

    117210

  • UT code for WoS article

    001440056500001

  • EID of the result in the Scopus database

    2-s2.0-85217959854