20.500.12556/RUL-163186 Spatial statistics analysis of precipitation in the Urmia Lake Basin Prostorska statistična analiza padavin v porečju jezera Urmia Most of the world's population lives in areas facing a severe water crisis. Climatology researchers need precipitation information, pattern analysis, modeling of spatial relationships, and more to cope with these conditions. Therefore, in this paper, a comprehensive approach is developed for describing geographic phenomenon using various geostatistical techniques. Two main methods of interpolation (Inverse Distance Weighting and Kriging) are used and their results are compared. The Urmia Lake Basin in Iran was selected as a case-study area that has faced critical conditions in recent years. Precipitation was initially modeled using both conventional, non-statistical approaches and advanced geo-statistical methods. The result of the comparison shows that ordinary Kriging is the best interpolation method for precipitation, with an RMS of 4.15, and Local Polynomial Interpolation with the exponential kernel function is the worst method, with an RMS of 5.02. Finally, a general regression analysis was conducted on precipitation data to examine its relationship with other variables. The results show that the latitude variable was identified as the dependent variable with the most influence on precipitation, with an impact factor of 81%, and that the slope has the lowest impact on precipitation, at nearly zero percent. The influence of latitude on precipitation appears to be localized, suggesting that it may not be a significant variable for predicting global environmental threats. Večina svetovnega prebivalstva živi na območjih, ki se soočajo s hudo krizo zaradi pomanjkanja vode. Klimatologi za spopadanje s temi izzivi potrebujejo informacije o padavinah, analize prostorskih vzorcev in modele prostorskih odnosov. V prispevku opisujemo celoviti pristop k opisovanju geografskega pojava z uporabo različnih geostatističnih tehnik. Uporabljeni sta dve glavni metodi interpolacije (metoda inverzne utežene razdalje in Kriging) ter primerjani njuni rezultati. Kot območje študije primera je bilo izbrano porečje jezera Urmia, ki se je v zadnjih letih soočalo s kritičnimi razmerami. Padavine smo najprej modelirali s klasičnimi in geostatističnimi metodami. Rezultati kažejo, da je navadni Kriging najboljša interpolacijska metoda za padavine – z vrednostjo RMS 4,15, metoda z eksponentno jedrno funkcijo pa je najslabša – z vrednostjo RMS 5,02. Na koncu je bila izvedena splošna regresijska analiza padavin. Rezultati kažejo, da je bila spremenljivka širine najvplivnejša odvisna spremenljivka s faktorjem vpliva 81 %, naklon pa ima najmanjši vpliv na padavine s skoraj nič odstotki. Zdi se, da je vpliv zemljepisne širine lokalne narave in morda ne predstavlja pomembne globalne okoljske grožnje. precipitation estimation geostatistics spatial relationship modeling hydrology kriging interpolation ocena padavin geostatistika modeliranje prostorskih odnosov hidrologija krigiranje true false true Angleški jezik Slovenski jezik Članek v reviji 2024-10-03 14:09:28 2024-10-03 14:09:35 2024-10-22 09:53:30 0000-00-00 00:00:00 2023 0 0 Str. 139-154 no. 65 Vol. 36 Dec. 2023 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 502/504:551.577.5(55)(078.7) 0352-3551 10.15292/acta.hydro.2023.09 210122499 Aghamohammadi,_Behzadi,_Moshtaghinejad-Spatial_statistics_analysis_of_precipitation_....pdf Aghamohammadi,_Behzadi,_Moshtaghinejad-Spatial_statistics_analysis_of_precipitation_....pdf 1 9D1EFA88FB0E3E048E51E0E5153671B8 832e82f25db86bd389ef3cb1de8344047e53f663e7217cce65fa0081ad72448b 4a1488b8-8180-11ef-b232-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=192720 https://actahydrotechnica.fgg.uni-lj.si/si/paper/a36ha 1 32348fb3-8180-11ef-b232-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=192718 Fakulteta za gradbeništvo in geodezijo Acta hydrotechnica 0 0 0