Precipitation is a highly important and a key input for many hydrological and ecological models, including water resource management, recharge assessment, irrigation scheduling, vegetation, and crop production models. However, rainfall records are often incomplete due to the missing rainfall data in the measured period or insufficient stations in the study region. The spatial interpolation method is one of the most common technique, and it is frequently used to estimate values of meteorological parameters in locations where they are not measured or missing. The use of different interpolation schemes in the same catchment may cause significant differences and deviations from the actual spatial distribution of rainfall. It is needed to compare the performances of each interpolation method to get excellent interpolation technique. GIS is offering the vast rage range of statistical methods to interpolate precipitation based on data recorded at several irregularly spaced gauges. In this analysis, five methods were used to predict monthly precipitation, and each technique was compared.
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Precipitation is a highly important and a key input for many hydrological and ecological models, including water resource management, recharge assessment, irrigation scheduling, vegetation, and crop production models. However, rainfall records are often incomplete due to the missing rainfall data in the measured period or insufficient stations in the study region. The spatial interpolation method is one of the most common technique, and it is frequently used to estimate values of meteorological parameters in locations where they are not measured or missing. The use of different interpolation schemes in the same catchment may cause significant differences and deviations from the actual spatial distribution of rainfall. It is needed to compare the performances of each interpolation method to get excellent interpolation technique. GIS is offering the vast rage range of statistical methods to interpolate precipitation based on data recorded at several irregularly spaced gauges. In this analysis, five methods were used to predict monthly precipitation, and each technique was compared. 60 pp. Englisch. N° de réf. du vendeur 9786202069601
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Vendeur : Revaluation Books, Exeter, Royaume-Uni
Paperback. Etat : Brand New. 60 pages. 8.66x5.91x0.14 inches. In Stock. N° de réf. du vendeur zk6202069600
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Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Wijemannage Ajith L.K.Ajith L. K. Wijemannage, MSc in Meteorology in University of the Philippines, MSc in Geoinformatics in University of Colombo, Sri Lanka, Director, Department of Meteorology, Sri Lanka. Manjula Ranagalage, (BA, M. N° de réf. du vendeur 385924555
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Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Precipitation is a highly important and a key input for many hydrological and ecological models, including water resource management, recharge assessment, irrigation scheduling, vegetation, and crop production models. However, rainfall records are often incomplete due to the missing rainfall data in the measured period or insufficient stations in the study region. The spatial interpolation method is one of the most common technique, and it is frequently used to estimate values of meteorological parameters in locations where they are not measured or missing. The use of different interpolation schemes in the same catchment may cause significant differences and deviations from the actual spatial distribution of rainfall. It is needed to compare the performances of each interpolation method to get excellent interpolation technique. GIS is offering the vast rage range of statistical methods to interpolate precipitation based on data recorded at several irregularly spaced gauges. In this analysis, five methods were used to predict monthly precipitation, and each technique was compared.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 60 pp. Englisch. N° de réf. du vendeur 9786202069601
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Precipitation is a highly important and a key input for many hydrological and ecological models, including water resource management, recharge assessment, irrigation scheduling, vegetation, and crop production models. However, rainfall records are often incomplete due to the missing rainfall data in the measured period or insufficient stations in the study region. The spatial interpolation method is one of the most common technique, and it is frequently used to estimate values of meteorological parameters in locations where they are not measured or missing. The use of different interpolation schemes in the same catchment may cause significant differences and deviations from the actual spatial distribution of rainfall. It is needed to compare the performances of each interpolation method to get excellent interpolation technique. GIS is offering the vast rage range of statistical methods to interpolate precipitation based on data recorded at several irregularly spaced gauges. In this analysis, five methods were used to predict monthly precipitation, and each technique was compared. N° de réf. du vendeur 9786202069601
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Vendeur : preigu, Osnabrück, Allemagne
Taschenbuch. Etat : Neu. Mapping Precipitation in Sri Lanka | Analysis and Comparison of GIS Interpolation Techniques | Ajith L. K. Wijemannage (u. a.) | Taschenbuch | 60 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786202069601 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 113501166
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