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GLOMODAT SIGNED

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 €

0

EC-Contrib. €

0

Partnership

0

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 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.

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

Project "GLOMODAT" data sheet

The following table provides information about the project.

Coordinator
TARTU ULIKOOL 

Organization address
address: ULIKOOLI 18
city: TARTU
postcode: 51005
website: www.ut.ee

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

 Partnership

Take a look of project's partnership.

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

Map

 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.

 Publications

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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