Comparative Analysis of Different Interpolation Methods in Modeling Spatial Distribution of Monthly Precipitation

For many water resources planning and management studies such as water budget and hydrological modeling, it is very important to estimate areal precipitation from point observation stations. There are many deterministic and geostatistical methods for determining the spatial distribution of precipita...

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Main Authors: Yılmaz İçağa, Emin Taş
Format: Article
Language:English
Published: Artvin Coruh University 2018-05-01
Series:Doğal Afetler ve Çevre Dergisi
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Online Access:http://dacd.artvin.edu.tr/tr/download/article-file/469243
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author Yılmaz İçağa
Emin Taş
author_facet Yılmaz İçağa
Emin Taş
author_sort Yılmaz İçağa
collection DOAJ
description For many water resources planning and management studies such as water budget and hydrological modeling, it is very important to estimate areal precipitation from point observation stations. There are many deterministic and geostatistical methods for determining the spatial distribution of precipitation. In this study, the most widely used methods, inverse distance weighting (IDW), Simple Kriging (SK) and Co-Kriging (CK) are applied. It is the main objective of the study that Geographic Information Systems (GIS) techniques are used to compare widely preferred interpolation methods and to model the spatial distribution of monthly precipitation values for prediction in ungauged areas in Akarcay Sinanpasa and Suhut sub-basins, Turkey. At the same time, the effects of number of stations, basin area, characteristics and secondary data usage such as elevation on model performance are investigated. The IDW, a deterministic method and the SK-CK, geostatistical methods are compared with each other by cross validation technique and the applicability of the interpolation techniques for the study areas is analyzed. According to the cross validation test results of IDW, SK and CK methods, the mean RMSE (root mean square error) values of Sinanpasa sub-basin are respectively 13,76 mm, 9,32 mm and 8,72 mm while these values are 9,43 mm, 7,82 mm and 7,90 mm for Suhut sub-basin. Then, uncertainty analysis by means of PSE (prediction standard error) is applied to SK-CK methods with clear advantages over the IDW method and with the close RMSE values. In consideration of the results of the uncertainty analysis, the SK method with the mean PSE values 10,30 mm and 8,54 mm has a little superiority to the CK method whose average PSE values are 11,03 mm and 9,02 mm for both Sinanpasa and Suhut sub-basins, respectively. When the findings are evaluated, it can be seen that all three methods can be used for the study areas. The determination of the spatial distribution of precipitation in this way is considered to be beneficial for many water resources engineering studies in areas of ungauged/sparsely gauged.
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series Doğal Afetler ve Çevre Dergisi
spelling doaj-art-9899f618abef495eaeb93cc6acc375e22025-02-02T16:27:18ZengArtvin Coruh UniversityDoğal Afetler ve Çevre Dergisi2528-96402528-96402018-05-01428910410.21324/dacd.387061Comparative Analysis of Different Interpolation Methods in Modeling Spatial Distribution of Monthly PrecipitationYılmaz İçağa0Emin Taş1Afyon Kocatepe University, Faculty of Engineering, Department of Civil Engineering, 03200, Afyonkarahisar.Afyon Kocatepe University, Faculty of Engineering, Department of Civil Engineering, 03200, Afyonkarahisar.For many water resources planning and management studies such as water budget and hydrological modeling, it is very important to estimate areal precipitation from point observation stations. There are many deterministic and geostatistical methods for determining the spatial distribution of precipitation. In this study, the most widely used methods, inverse distance weighting (IDW), Simple Kriging (SK) and Co-Kriging (CK) are applied. It is the main objective of the study that Geographic Information Systems (GIS) techniques are used to compare widely preferred interpolation methods and to model the spatial distribution of monthly precipitation values for prediction in ungauged areas in Akarcay Sinanpasa and Suhut sub-basins, Turkey. At the same time, the effects of number of stations, basin area, characteristics and secondary data usage such as elevation on model performance are investigated. The IDW, a deterministic method and the SK-CK, geostatistical methods are compared with each other by cross validation technique and the applicability of the interpolation techniques for the study areas is analyzed. According to the cross validation test results of IDW, SK and CK methods, the mean RMSE (root mean square error) values of Sinanpasa sub-basin are respectively 13,76 mm, 9,32 mm and 8,72 mm while these values are 9,43 mm, 7,82 mm and 7,90 mm for Suhut sub-basin. Then, uncertainty analysis by means of PSE (prediction standard error) is applied to SK-CK methods with clear advantages over the IDW method and with the close RMSE values. In consideration of the results of the uncertainty analysis, the SK method with the mean PSE values 10,30 mm and 8,54 mm has a little superiority to the CK method whose average PSE values are 11,03 mm and 9,02 mm for both Sinanpasa and Suhut sub-basins, respectively. When the findings are evaluated, it can be seen that all three methods can be used for the study areas. The determination of the spatial distribution of precipitation in this way is considered to be beneficial for many water resources engineering studies in areas of ungauged/sparsely gauged.http://dacd.artvin.edu.tr/tr/download/article-file/469243areal precipitationspatial interpolationgisidwkriging
spellingShingle Yılmaz İçağa
Emin Taş
Comparative Analysis of Different Interpolation Methods in Modeling Spatial Distribution of Monthly Precipitation
Doğal Afetler ve Çevre Dergisi
areal precipitation
spatial interpolation
gis
idw
kriging
title Comparative Analysis of Different Interpolation Methods in Modeling Spatial Distribution of Monthly Precipitation
title_full Comparative Analysis of Different Interpolation Methods in Modeling Spatial Distribution of Monthly Precipitation
title_fullStr Comparative Analysis of Different Interpolation Methods in Modeling Spatial Distribution of Monthly Precipitation
title_full_unstemmed Comparative Analysis of Different Interpolation Methods in Modeling Spatial Distribution of Monthly Precipitation
title_short Comparative Analysis of Different Interpolation Methods in Modeling Spatial Distribution of Monthly Precipitation
title_sort comparative analysis of different interpolation methods in modeling spatial distribution of monthly precipitation
topic areal precipitation
spatial interpolation
gis
idw
kriging
url http://dacd.artvin.edu.tr/tr/download/article-file/469243
work_keys_str_mv AT yılmazicaga comparativeanalysisofdifferentinterpolationmethodsinmodelingspatialdistributionofmonthlyprecipitation
AT emintas comparativeanalysisofdifferentinterpolationmethodsinmodelingspatialdistributionofmonthlyprecipitation