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Simultaneous soil moisture and properties estimation for a drip irrigated field by assimilating cosmic-ray neutron intensity

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Simultaneous soil moisture and properties estimation for a drip irrigated field by assimilating cosmic-ray neutron intensity

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dc.contributor.author Han, Xujun es_ES
dc.contributor.author Hendricks Franssen, Harrie-Jan es_ES
dc.contributor.author Jiménez Bello, Miguel Ángel es_ES
dc.contributor.author Rosolem, R. es_ES
dc.contributor.author Bogena, Heye es_ES
dc.contributor.author Martínez Alzamora, Fernando es_ES
dc.contributor.author Chanzy, André es_ES
dc.contributor.author Vereecken, Harry es_ES
dc.date.accessioned 2017-05-26T10:20:18Z
dc.date.available 2017-05-26T10:20:18Z
dc.date.issued 2016-08
dc.identifier.issn 0022-1694
dc.identifier.uri http://hdl.handle.net/10251/81817
dc.description.abstract Neutron intensity measured by the aboveground cosmic-ray neutron intensity probe (CRP) allows estimating soil moisture content at the field scale. In this work, synthetic neutron intensities were used to remove the bias of simulated soil moisture content or update soil hydraulic properties (together with soil moisture) in the Community Land Model (CLM) using the Local Ensemble Transform Kalman Filter. The cosmic-ray forward model COSMIC was used as the non-linear measurement operator which maps between neutron intensity and soil moisture. The novel aspect of this work is that synthetically measured neutron intensity was used for real time updating of soil states and soil properties (or soil moisture bias) and posterior use for the real time scheduling of irrigation (data assimilation based real-time control approach). Uncertainty of model forcing and soil properties (sand fraction, clay fraction and organic matter density) were considered in the ensemble predictions of the soil moisture profiles. Horizontal and vertical weighting of soil moisture was introduced in the data assimilation in order to handle the scale mismatch between the cosmic-ray footprint and the CLM grid cell. The approach was illustrated in a synthetic study with the real-time irrigation scheduling of fields of citrus trees. After adjusting soil moisture content by assimilating neutron intensity, the irrigation requirements were calculated based on the water deficit method. Model bias was introduced by using coarser soil texture in the data assimilation experiments than in reality. A series of experiments was done with different combinations of state, parameter and bias estimation in combination with irrigation scheduling. Assimilation of CRP neutron intensity improved soil moisture characterization. Irrigation requirement was overestimated if biased soil properties were used. The soil moisture bias was reduced by 35% after data assimilation. The scenario of joint state-parameter estimation resulted in the best soil moisture characterization (50% decrease in root mean square error compared to open loop simulations), and the best estimate of needed irrigation amount (86% decrease in Hausdorff distance compared to open loop). The coarse scale synthetic CRP observation was proven to be useful for the fine scale soil moisture and soil properties estimation for the objective of irrigation scheduling es_ES
dc.description.sponsorship This work was supported by AGADAPT (adapting water use by the agriculture sector) financed by Climate Knowledge and Innovation Community (Climate-KIC) of the European Union. AGADAPT focuses on the development and deployment of novel methods to reduce and optimize the water usage of rain-fed and irrigated agriculture by combining knowledge-based innovative technologies, modelling and transfer of technologies and innovative practices. The work was also supported by Transregional Collaborative Research Centre 32, and the NSFC project (grant number: 41271357, 91125001). The support of the supercomputing facilities of Forschungszentrum Julich (JUROPA) is gratefully acknowledged. en_EN
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation AGADAPT (adapting water use by the agriculture sector) - Climate Knowledge and Innovation Community (Climate-KIC) of the European Union es_ES
dc.relation Transregional Collaborative Research Centre 32 es_ES
dc.relation NSFC 41271357 91125001 es_ES
dc.relation.ispartof Journal of Hydrology es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Data assimilation es_ES
dc.subject Cosmic ray es_ES
dc.subject Soil moisture es_ES
dc.subject Parameter estimation es_ES
dc.subject Bias estimation es_ES
dc.subject Irrigation scheduling es_ES
dc.subject.classification INGENIERIA HIDRAULICA es_ES
dc.title Simultaneous soil moisture and properties estimation for a drip irrigated field by assimilating cosmic-ray neutron intensity es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.jhydrol.2016.05.050
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Universitario de Ingeniería del Agua y del Medio Ambiente - Institut Universitari d'Enginyeria de l'Aigua i Medi Ambient es_ES
dc.description.bibliographicCitation Han, X.; Hendricks Franssen, H.; Jiménez Bello, MA.; Rosolem, R.; Bogena, H.; Martínez Alzamora, F.; Chanzy, A.... (2016). Simultaneous soil moisture and properties estimation for a drip irrigated field by assimilating cosmic-ray neutron intensity. Journal of Hydrology. 539:611-624. doi:10.1016/j.jhydrol.2016.05.050 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://doi.org/10.1016/j.jhydrol.2016.05.050 es_ES
dc.description.upvformatpinicio 611 es_ES
dc.description.upvformatpfin 624 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 539 es_ES
dc.relation.senia 323810 es_ES
dc.identifier.eissn 1879-2707


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