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Opendata, web and dolomites

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 €

EC-Contrib. €

Partnership

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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.

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

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 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.	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

List of publications.
year	authors and title	journal	last update
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 MullapÃ¤ev (World Soil Day) 2019	2020-03-05

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