FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3146023712> ?p ?o ?g. }

• W3146023712 abstract "Abstract Soil moisture prediction is of great importance in crop yield forecasting and drought monitoring. In this study, the multi‐layer root zone soil moisture (0‐5, 0‐10, 10‐40 and 40‐100 cm) prediction is conducted over an agriculture dominant basin, namely the Xiang River Basin, in southern China. The support vector machines (SVM) coupled with dual ensemble Kalman filter (EnKF) technique (SVM‐EnKF) is compared with SVM for its potential capability to improve the efficiency of soil moisture prediction. Three remote sensing soil moisture products, namely SMAP, ASCAT and AMSR2, are evaluated for their performance in multi‐layer soil moisture prediction with SVM and SVM‐EnKF, respectively. Multiple cases are designed to investigate the performance of SVM, the effectiveness of coupling dual EnKF technique and the applicability of the remote sensing products in soil moisture prediction. The main results are as follows: (a) The efficiency of soil moisture prediction with SVM using meteorological variables as inputs is satisfactory for the surface layers (0‐5 and 0‐10 cm), while poor for the root zone layers (10‐40 and 40‐100 cm). Adding SMAP as input to SVM can improve its performance in soil moisture prediction, with more than 47% increase in the R ‐value and at least 11% reduction in RMSE for all layers. However, adding ASCAT or AMSR2 has no improvement for its performance. (b) Coupling dual EnKF can significantly improve the performance of SVM in the soil moisture prediction of both surface and the root zone layers. The increase in R ‐value is above 80%, while the reduction in BIAS and RMSE is respectively more than 90% and 63%. However, adding remote sensing soil moisture products as inputs can no further improve the performance of SVM‐EnKF. (c) The SVM‐EnKF can eliminate the influence of remote sensing soil moisture extreme values in soil moisture prediction, therefore, improve its accuracy." @default.
• W3146023712 created "2021-04-13" @default.
• W3146023712 creator A5022391069 @default.
• W3146023712 creator A5052796762 @default.
• W3146023712 creator A5086452619 @default.
• W3146023712 date "2021-04-01" @default.
• W3146023712 modified "2023-10-18" @default.
• W3146023712 title "Improvement of multi‐layer soil moisture prediction using support vector machines and ensemble Kalman filter coupled with remote sensing soil moisture datasets over an agriculture dominant basin in China" @default.
• W3146023712 cites W1972046686 @default.
• W3146023712 cites W1974445113 @default.
• W3146023712 cites W1976534896 @default.
• W3146023712 cites W1994086902 @default.
• W3146023712 cites W2006947831 @default.
• W3146023712 cites W2013829694 @default.
• W3146023712 cites W2039348932 @default.
• W3146023712 cites W2039580128 @default.
• W3146023712 cites W2051692999 @default.
• W3146023712 cites W2063422594 @default.
• W3146023712 cites W2075581597 @default.
• W3146023712 cites W2076196252 @default.
• W3146023712 cites W2084580541 @default.
• W3146023712 cites W2092532914 @default.
• W3146023712 cites W2100401723 @default.
• W3146023712 cites W2111072639 @default.
• W3146023712 cites W2128216612 @default.
• W3146023712 cites W2148615700 @default.
• W3146023712 cites W2167962096 @default.
• W3146023712 cites W2168622160 @default.
• W3146023712 cites W2172996688 @default.
• W3146023712 cites W2175379292 @default.
• W3146023712 cites W2185905748 @default.
• W3146023712 cites W2188200382 @default.
• W3146023712 cites W2192767806 @default.
• W3146023712 cites W2338345836 @default.
• W3146023712 cites W2521425865 @default.
• W3146023712 cites W2551535721 @default.
• W3146023712 cites W2593356872 @default.
• W3146023712 cites W2616928132 @default.
• W3146023712 cites W2732645921 @default.
• W3146023712 cites W2734508657 @default.
• W3146023712 cites W2741401957 @default.
• W3146023712 cites W2772008925 @default.
• W3146023712 cites W2774547596 @default.
• W3146023712 cites W2796168650 @default.
• W3146023712 cites W2803497162 @default.
• W3146023712 cites W2883126732 @default.
• W3146023712 cites W2891043313 @default.
• W3146023712 cites W2899505594 @default.
• W3146023712 cites W2901420999 @default.
• W3146023712 cites W2909049492 @default.
• W3146023712 cites W2913300173 @default.
• W3146023712 cites W2917728215 @default.
• W3146023712 cites W2971534406 @default.
• W3146023712 cites W2998199582 @default.
• W3146023712 cites W3081016949 @default.
• W3146023712 cites W3097726034 @default.
• W3146023712 cites W4239510810 @default.
• W3146023712 cites W848621242 @default.
• W3146023712 doi "https://doi.org/10.1002/hyp.14154" @default.
• W3146023712 hasPublicationYear "2021" @default.
• W3146023712 type Work @default.
• W3146023712 sameAs 3146023712 @default.
• W3146023712 citedByCount "12" @default.
• W3146023712 countsByYear W31460237122022 @default.
• W3146023712 countsByYear W31460237122023 @default.
• W3146023712 crossrefType "journal-article" @default.
• W3146023712 hasAuthorship W3146023712A5022391069 @default.
• W3146023712 hasAuthorship W3146023712A5052796762 @default.
• W3146023712 hasAuthorship W3146023712A5086452619 @default.
• W3146023712 hasConcept C119857082 @default.
• W3146023712 hasConcept C12267149 @default.
• W3146023712 hasConcept C127313418 @default.
• W3146023712 hasConcept C153294291 @default.
• W3146023712 hasConcept C154945302 @default.
• W3146023712 hasConcept C157286648 @default.
• W3146023712 hasConcept C159390177 @default.
• W3146023712 hasConcept C176864760 @default.
• W3146023712 hasConcept C187320778 @default.
• W3146023712 hasConcept C205649164 @default.
• W3146023712 hasConcept C206833254 @default.
• W3146023712 hasConcept C24939127 @default.
• W3146023712 hasConcept C39432304 @default.
• W3146023712 hasConcept C41008148 @default.
• W3146023712 hasConcept C62649853 @default.
• W3146023712 hasConcept C79334102 @default.
• W3146023712 hasConceptScore W3146023712C119857082 @default.
• W3146023712 hasConceptScore W3146023712C12267149 @default.
• W3146023712 hasConceptScore W3146023712C127313418 @default.
• W3146023712 hasConceptScore W3146023712C153294291 @default.
• W3146023712 hasConceptScore W3146023712C154945302 @default.
• W3146023712 hasConceptScore W3146023712C157286648 @default.
• W3146023712 hasConceptScore W3146023712C159390177 @default.
• W3146023712 hasConceptScore W3146023712C176864760 @default.
• W3146023712 hasConceptScore W3146023712C187320778 @default.
• W3146023712 hasConceptScore W3146023712C205649164 @default.
• W3146023712 hasConceptScore W3146023712C206833254 @default.
• W3146023712 hasConceptScore W3146023712C24939127 @default.
• W3146023712 hasConceptScore W3146023712C39432304 @default.
• W3146023712 hasConceptScore W3146023712C41008148 @default.
• W3146023712 hasConceptScore W3146023712C62649853 @default.

• next