AI4WATER: A DIGITAL TWIN FOR IRRIGATED AGRICULTURE

被引：0

作者：

Camps, A. ^{[1
,2
,3
]}

Lopez-Martinez, C. ^{[1
,2
]}

Gonga, A. ^{[1
]}

Gracia, G. ^{[1
]}

Perez-Portero, A. ^{[1
]}

Alonso-Gonzalez, A. ^{[1
]}

Vallllosser, M. ^{[1
,2
]}

Park, H. ^{[1
,2
]}

Perez, V ^{[4
]}

Caselles, O. ^{[5
]}

Domenech, C. ^{[6
]}

Catala, P. ^{[6
]}

Ruiz-de-Azud, J. A. ^{[7
]}

Solsona, M. ^{[8
]}

机构：

[1] Univ Politecn Catalunya UPC, Dept Signal Theory & Commun, CommSensLab UPC, Barcelona 08034, Spain

[2] Inst Estudis Espacials Catalunya IEEC, Barcelona 08034, Spain

[3] UAE Univ CoE, Al Ain 15551, U Arab Emirates

[4] Univ Politecn Catalunya UPC, Barcelona East Sch Engn EEBE, Dept Strength Mat & Struct Engn GIES, Barcelona 08019, Spain

[5] Univ Politecn Catalunya UPC, Barcelona Sch Civil Engn, Dept Civil & Environm Engn GIES, Barcelona 08033, Spain

[6] Univ Politecn Catalunya UPC, Dept Mech Engn, CDEI DM, Barcelona 08028, Spain

[7] i2CAT Fdn, Space Commun Res Grp, Barcelona 08034, Spain

[8] Univ Politecn Catalunya UPC, Agrotech UPC, Castelldefels 08860, Spain

来源：

IGARSS 2024-2024 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, IGARSS 2024 | 2024年

关键词：

digital twin; water resources; soil moisture; irrigated agriculture; EO data; soil moisture probes;

D O I：

10.1109/IGARSS53475.2024.10641740

中图分类号：

P9 [自然地理学];

学科分类号：

0705 ; 070501 ;

摘要：

This study presents a Digital Twin (DT) that is being created to optimize the use of the available hydric resources, and mitigate the effects of the increasing water shortage in irrigated agriculture in fields in the Urgell channel region (Lleida). A DT is "a virtual representation of an object or system that spans its lifecycle, it is updated from real-time data, and uses simulation, machine learning and reasoning to help decision-making." It will model the water fluxes using the knowledge of the amounts of water taken in, used, and returned to the environment, and other parameters that impact the water budget, such as atmospheric variables (temperature, water vapor deficit, relative humidity, solar radiance.), surface soil moisture, and evapotranspiration maps, etc. Satellite Earth Observation (EO) data, collocated with in-situ data from a network of 20 soil moisture probes and 2 meteo stations will be used to train the DT. Additionally, a roverbased ground penetrating radar will be used for crosscalibration.

引用

页码：3545 / 3548

页数：4

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