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Enhancing data fusion, parallelisation for hydrological modelling and estimating sensitivity to spatialparameterization of SWAT to model nitrogen and phosphorus runoff at local and global scale

Total Cost €


EC-Contrib. €






 GLOMODAT project word cloud

Explore the words cloud of the GLOMODAT project. It provides you a very rough idea of what is the project "GLOMODAT" about.

precipitation    pollution    global    nodes    message    simulate    automate    landscape    put    paradigm    programmed    soil    compromised    runoff    spatial    model    spreading    computational    transport    mpi    diffuse    computers    sensitivity    local    performance    multiple    computation    specialised    interface    economy    pressure    tested    limited    nutrient    partitioning    ways    underlying    passing    data    flow    demands    understand    swat    mapreduce    estimate    population    loosely    limitation    either    land    becomes    datasets    world    countries    surpass    size    partition    effort    coupled    accessible    computing    computations    dem    calibration    entails    causing    too    parallelization    published    framework    input    variety    resolution    impacts    load    transparently    successfully    power    distributed    quality    clusters    balancing    limitations    tightly    automated    catchments    hpc    types    water    scales    tool    core   

Project "GLOMODAT" data sheet

The following table provides information about the project.


Organization address
address: ULIKOOLI 18
city: TARTU
postcode: 51005

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Estonia [EE]
 Total cost 148˙582 €
 EC max contribution 148˙582 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2017
 Funding Scheme MSCA-IF-EF-RI
 Starting year 2019
 Duration (year-month-day) from 2019-09-01   to  2021-08-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    TARTU ULIKOOL EE (TARTU) coordinator 148˙582.00


 Project objective

A growing economy and population in the world is causing landscape changes and an increasing pressure is put on water resources. Diffuse water pollution is considered to be one of the major problems for water quality in many countries. Modelling has been successfully used to simulate water quality in catchments to better understand the underlying landscape processes. The widely used Soil and Water Assessment Tool (SWAT) is a spatially distributed model that can be used to estimate flow and nutrient transport at a variety of scales.

In current published studies typically only one or two parameters of precipitation, DEM, land use or soil properties are used in. The proposed project aims to investigate how spatial resolution of core input datasets of all types (precipitation, DEM, land use and soil) impacts SWAT modelling results and estimate the nutrient runoff on a local and global scale.

Sensitivity analysis to all of precipitation, DEM, land use and soil will therefore be tested. The limitation to one or two parameters in current published studies is due to the computational demands. Due to the way the SWAT model is programmed using a tightly coupled Message Passing Interface (MPI) approaches the available computing power needs to accessible within specialised High Performance Computing (HPC) clusters of limited size. Thus, either scale or resolution is typically compromised.

As for higher resolution or global scale data the computational effort becomes too large for automated calibration, we aim to develop a novel method to automate data processing and balancing computational load transparently between many computers.

In order to surpass these limitations we test the MapReduce framework as a novel method for parallelization. This entails new ways of data management, model data partitioning and spreading the model partition computations transparently over multiple computing nodes fostering a loosely coupled distributed computation paradigm.


year authors and title journal last update
List of publications.
2019 Kmoch, Alexander
EstSoil-EH v1.0: An eco-hydrological modelling parameters dataset derived from the Soil Map of Estonia - Poster
published pages: , ISSN: , DOI: 10.5281/zenodo.3613441
X Mullapäev (World Soil Day) 2019 2020-03-05

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The information about "GLOMODAT" are provided by the European Opendata Portal: CORDIS opendata.

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