Uncertainty in Determination of Meteorological Drought Zones Based on Standardized Precipitation Index in the Territory of Poland
The primary aim of this work is to assess the accuracy of the methods for spatial interpolation applied for the reconstruction of the spatial distribution of the Standardized Precipitation Index (SPI). The one-month version called SPI-1 is chosen for this purpose due to the known greatest variabilit...
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| Vydáno v: | International journal of environmental research and public health Ročník 19; číslo 23; s. 15797 |
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| Jazyk: | angličtina |
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27.11.2022
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| ISSN: | 1660-4601, 1661-7827, 1660-4601 |
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| Abstract | The primary aim of this work is to assess the accuracy of the methods for spatial interpolation applied for the reconstruction of the spatial distribution of the Standardized Precipitation Index (SPI). The one-month version called SPI-1 is chosen for this purpose due to the known greatest variability of this index in comparison with its other versions. The analysis has been made for the territory of the entire country of Poland. At the same time the uncertainty related to the application of such computational procedures is determined based on qualitative and quantitative measures. The public data of two kinds are applied: (1) measurements of precipitation and (2) the locations of the meteorological stations in Poland. The analysis has been made for the period 1990–2020. However, all available observations since 1950 have been implemented. The number of available meteorological stations has decreased over the analyzed period. In January 1990 there were over one thousand stations making observations. In the end of the period of the study, the number of stations was below six hundred. Obviously, the temporal scarcity of data had an impact on the obtained results. The main tools applied were ArcGIS supported with Python scripting, including generally used modules and procedures dedicated to geoprocessing. Such an approach appeared crucial for the effective processing of the large number of data available. It also guaranteed the accuracy of the produced results and brought about drought maps based on SPI-1. The methods tested included: Inverse Distance Weighted, Natural Neighbor, Linear, Kriging, and Spline. The presented results prove that all the procedures are inaccurate and uncertain, but some of them provide satisfactory results. The worst method seems to be the interpolation based on Spline functions. The practical aspects related to the implementation of the methods led to removal of the Linear and Kriging interpolations from further use. Hence, Inverse Distance Weighted, as well as Natural Neighbor, seem to be well suited for this problem. |
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| AbstractList | The primary aim of this work is to assess the accuracy of the methods for spatial interpolation applied for the reconstruction of the spatial distribution of the Standardized Precipitation Index (SPI). The one-month version called SPI-1 is chosen for this purpose due to the known greatest variability of this index in comparison with its other versions. The analysis has been made for the territory of the entire country of Poland. At the same time the uncertainty related to the application of such computational procedures is determined based on qualitative and quantitative measures. The public data of two kinds are applied: (1) measurements of precipitation and (2) the locations of the meteorological stations in Poland. The analysis has been made for the period 1990–2020. However, all available observations since 1950 have been implemented. The number of available meteorological stations has decreased over the analyzed period. In January 1990 there were over one thousand stations making observations. In the end of the period of the study, the number of stations was below six hundred. Obviously, the temporal scarcity of data had an impact on the obtained results. The main tools applied were ArcGIS supported with Python scripting, including generally used modules and procedures dedicated to geoprocessing. Such an approach appeared crucial for the effective processing of the large number of data available. It also guaranteed the accuracy of the produced results and brought about drought maps based on SPI-1. The methods tested included: Inverse Distance Weighted, Natural Neighbor, Linear, Kriging, and Spline. The presented results prove that all the procedures are inaccurate and uncertain, but some of them provide satisfactory results. The worst method seems to be the interpolation based on Spline functions. The practical aspects related to the implementation of the methods led to removal of the Linear and Kriging interpolations from further use. Hence, Inverse Distance Weighted, as well as Natural Neighbor, seem to be well suited for this problem. The primary aim of this work is to assess the accuracy of the methods for spatial interpolation applied for the reconstruction of the spatial distribution of the Standardized Precipitation Index (SPI). The one-month version called SPI-1 is chosen for this purpose due to the known greatest variability of this index in comparison with its other versions. The analysis has been made for the territory of the entire country of Poland. At the same time the uncertainty related to the application of such computational procedures is determined based on qualitative and quantitative measures. The public data of two kinds are applied: (1) measurements of precipitation and (2) the locations of the meteorological stations in Poland. The analysis has been made for the period 1990-2020. However, all available observations since 1950 have been implemented. The number of available meteorological stations has decreased over the analyzed period. In January 1990 there were over one thousand stations making observations. In the end of the period of the study, the number of stations was below six hundred. Obviously, the temporal scarcity of data had an impact on the obtained results. The main tools applied were ArcGIS supported with Python scripting, including generally used modules and procedures dedicated to geoprocessing. Such an approach appeared crucial for the effective processing of the large number of data available. It also guaranteed the accuracy of the produced results and brought about drought maps based on SPI-1. The methods tested included: Inverse Distance Weighted, Natural Neighbor, Linear, Kriging, and Spline. The presented results prove that all the procedures are inaccurate and uncertain, but some of them provide satisfactory results. The worst method seems to be the interpolation based on Spline functions. The practical aspects related to the implementation of the methods led to removal of the Linear and Kriging interpolations from further use. Hence, Inverse Distance Weighted, as well as Natural Neighbor, seem to be well suited for this problem.The primary aim of this work is to assess the accuracy of the methods for spatial interpolation applied for the reconstruction of the spatial distribution of the Standardized Precipitation Index (SPI). The one-month version called SPI-1 is chosen for this purpose due to the known greatest variability of this index in comparison with its other versions. The analysis has been made for the territory of the entire country of Poland. At the same time the uncertainty related to the application of such computational procedures is determined based on qualitative and quantitative measures. The public data of two kinds are applied: (1) measurements of precipitation and (2) the locations of the meteorological stations in Poland. The analysis has been made for the period 1990-2020. However, all available observations since 1950 have been implemented. The number of available meteorological stations has decreased over the analyzed period. In January 1990 there were over one thousand stations making observations. In the end of the period of the study, the number of stations was below six hundred. Obviously, the temporal scarcity of data had an impact on the obtained results. The main tools applied were ArcGIS supported with Python scripting, including generally used modules and procedures dedicated to geoprocessing. Such an approach appeared crucial for the effective processing of the large number of data available. It also guaranteed the accuracy of the produced results and brought about drought maps based on SPI-1. The methods tested included: Inverse Distance Weighted, Natural Neighbor, Linear, Kriging, and Spline. The presented results prove that all the procedures are inaccurate and uncertain, but some of them provide satisfactory results. The worst method seems to be the interpolation based on Spline functions. The practical aspects related to the implementation of the methods led to removal of the Linear and Kriging interpolations from further use. Hence, Inverse Distance Weighted, as well as Natural Neighbor, seem to be well suited for this problem. |
| Author | Wicher-Dysarz, Joanna Dysarz, Tomasz Jaskuła, Joanna |
| AuthorAffiliation | 1 Department of Hydraulic and Sanitary Engineering, Faculty of Environmental Engineering and Mechanical Engineering, Poznan’ University of Life Sciences, Piątkowska St. 94A, 60-649 Poznan, Poland 2 Department of Land Improvement, Environmental Development and Spatial Management, Faculty of Environmental Engineering and Mechanical Engineering, Poznan’ University of Life Sciences, Piątkowska St. 94E, 60-649 Poznan, Poland |
| AuthorAffiliation_xml | – name: 1 Department of Hydraulic and Sanitary Engineering, Faculty of Environmental Engineering and Mechanical Engineering, Poznan’ University of Life Sciences, Piątkowska St. 94A, 60-649 Poznan, Poland – name: 2 Department of Land Improvement, Environmental Development and Spatial Management, Faculty of Environmental Engineering and Mechanical Engineering, Poznan’ University of Life Sciences, Piątkowska St. 94E, 60-649 Poznan, Poland |
| Author_xml | – sequence: 1 givenname: Joanna orcidid: 0000-0003-0926-5462 surname: Wicher-Dysarz fullname: Wicher-Dysarz, Joanna – sequence: 2 givenname: Tomasz orcidid: 0000-0002-7035-9874 surname: Dysarz fullname: Dysarz, Tomasz – sequence: 3 givenname: Joanna orcidid: 0000-0002-0768-499X surname: Jaskuła fullname: Jaskuła, Joanna |
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| Cites_doi | 10.1016/j.agrformet.2019.107707 10.1016/j.agwat.2022.107849 10.3390/rs11050485 10.1016/j.jhydrol.2022.127941 10.1007/s10584-021-03131-y 10.1016/0898-1221(88)90255-6 10.1080/19475705.2018.1564706 10.1007/s41324-018-0216-9 10.1002/ird.285 10.3390/w13060807 10.1016/S0003-2670(00)82860-3 10.1007/s12517-020-5059-8 10.1007/s00024-021-02704-3 10.1016/j.heliyon.2021.e08660 10.1175/2008JHM983.1 10.1080/02626667.2013.862335 10.1016/j.atmosres.2021.105687 10.1175/BAMS-D-20-0087.1 10.1016/j.pce.2018.07.001 10.1016/j.jenvman.2022.115494 10.1002/joc.7424 10.1016/j.wace.2022.100505 10.3390/atmos13020292 10.1007/s11269-020-02683-5 10.1016/0898-1221(82)90009-8 10.1007/s12594-022-2073-3 10.1016/j.ijdrr.2022.102936 10.1111/j.1365-2389.1986.tb00392.x 10.1029/2018JD029145 10.3390/ijerph18094449 10.1016/j.advwatres.2013.03.009 10.1007/s10661-018-7058-8 10.1016/j.envint.2019.104951 10.1007/s11269-021-02891-7 10.1080/01431161.2020.1851799 10.3390/atmos12091098 10.1016/j.ecolind.2021.108460 10.1080/02693799008941549 10.1080/10106048609354060 10.3390/cli7060082 10.1016/B978-0-12-811689-0.00004-5 10.1007/s12517-021-07670-7 10.1016/j.ejrh.2015.01.001 10.1016/j.jclepro.2022.131248 10.1038/s41598-020-80527-3 |
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| Keywords | standardized precipitation index (SPI) meteorological drought analysis Python scripting spatial interpolation |
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| References | Ellahi (ref_64) 2021; 73 ref_14 Shen (ref_65) 2019; 79 ref_54 ref_53 Tirivarombo (ref_10) 2018; 106 Liu (ref_24) 2021; 11 ref_59 Ali (ref_67) 2011; 15 Wu (ref_58) 2018; 123 Zhao (ref_9) 2019; 10 Zhang (ref_57) 2021; 166 ref_61 Kumar (ref_68) 2022; 98 Yang (ref_13) 2022; 272 Spinoni (ref_2) 2015; 3 ref_23 Yu (ref_12) 2019; 130 ref_63 Um (ref_16) 2022; 317 Hu (ref_18) 2019; 279 ref_29 ref_28 (ref_33) 2007; 56 Hao (ref_15) 2013; 57 ref_27 Watson (ref_42) 1985; 2 Mahmoudi (ref_22) 2021; 35 Philip (ref_41) 1982; 22 (ref_37) 2018; 190 Cammalleri (ref_20) 2022; 42 Oliver (ref_48) 1990; 4 Jahangir (ref_19) 2020; 13 (ref_34) 2011; 11 ref_36 ref_32 ref_31 ref_30 Marumbwa (ref_55) 2021; 42 Lee (ref_8) 2022; 74 Franke (ref_51) 1982; 8 Kuriqi (ref_4) 2021; 133 ref_39 ref_38 Wang (ref_11) 2022; 610 Elouissi (ref_21) 2021; 14 Rhee (ref_56) 2008; 9 Karatayev (ref_1) 2022; 8 Subedi (ref_66) 2019; 27 Mocko (ref_6) 2021; 102 Wang (ref_17) 2022; 347 McBratney (ref_47) 1986; 37 Azimi (ref_62) 2020; 34 Zarei (ref_26) 2021; 178 ref_45 ref_44 ref_43 ref_40 Zhang (ref_7) 2022; 38 ref_3 Sojka (ref_60) 2018; 20 Tokarczyk (ref_35) 2014; 59 ref_49 Yerdelen (ref_25) 2021; 260 ref_5 Heine (ref_46) 1986; 2 Royle (ref_50) 1981; 1 Mitas (ref_52) 1988; 16 |
| References_xml | – volume: 279 start-page: 107707 year: 2019 ident: ref_18 article-title: Agricultural drought monitoring using European Space Agency Sentinel 3A land surface temperature and normalized difference vegetation index imageries publication-title: Agric. For. Meteorol. doi: 10.1016/j.agrformet.2019.107707 – volume: 272 start-page: 107849 year: 2022 ident: ref_13 article-title: Spatial-temporal distribution characteristics and hazard assessment of millet drought disaster in Northern China under climate change publication-title: Agric. Water Manag. doi: 10.1016/j.agwat.2022.107849 – ident: ref_59 doi: 10.3390/rs11050485 – volume: 610 start-page: 127941 year: 2022 ident: ref_11 article-title: Historical and future Palmer Drought Severity Index with improved hydrological modeling publication-title: J. Hydrol. doi: 10.1016/j.jhydrol.2022.127941 – ident: ref_32 – volume: 166 start-page: 41 year: 2021 ident: ref_57 article-title: Meteorological drought and its large-scale climate patterns in each season in Central Asia from 1901 to 2015 publication-title: Clim. Change doi: 10.1007/s10584-021-03131-y – volume: 16 start-page: 983 year: 1988 ident: ref_52 article-title: General Variational Approach to the Interpolation Problem publication-title: Comput. Math. Appl. doi: 10.1016/0898-1221(88)90255-6 – volume: 15 start-page: 474 year: 2011 ident: ref_67 article-title: Assessment of geostatistical methods for spatial analysis of SPI and EDI drought indices publication-title: World Appl. Sci. J. – volume: 10 start-page: 1084 year: 2019 ident: ref_9 article-title: Assessing socio-economic drought evolution characteristics and their possible meteorological driving force publication-title: Geomat. Nat. Hazards Risk doi: 10.1080/19475705.2018.1564706 – volume: 1 start-page: 377 year: 1981 ident: ref_50 article-title: Practical Universal Kriging and Automatic Contouring publication-title: Geoprocessing – volume: 27 start-page: 11 year: 2019 ident: ref_66 article-title: Assessment of geostatistical methods for spatiotemporal analysis of drought patterns in East Texas, USA publication-title: Spat. Inf. Res. doi: 10.1007/s41324-018-0216-9 – ident: ref_39 – volume: 56 start-page: 67 year: 2007 ident: ref_33 article-title: Estimation of local drought frequency in central Poland using the standardized precipitation index SPI publication-title: Irrig. Drain. doi: 10.1002/ird.285 – ident: ref_5 doi: 10.3390/w13060807 – ident: ref_49 doi: 10.1016/S0003-2670(00)82860-3 – volume: 13 start-page: 110 year: 2020 ident: ref_19 article-title: Hydrological drought analyzing and monitoring by using Streamflow Drought Index (SDI) (case study: Lorestan, Iran) publication-title: Arab. J. Geosci. doi: 10.1007/s12517-020-5059-8 – volume: 178 start-page: 1387 year: 2021 ident: ref_26 article-title: Accuracy assessment of the SPEI, RDI and SPI drought indices in regions of Iran with different climate conditions publication-title: Pure Appl. Geophys. doi: 10.1007/s00024-021-02704-3 – volume: 8 start-page: e08660 year: 2022 ident: ref_1 article-title: Monitoring climate change, drought conditions and wheat production in Eurasia: The case study of Kazakhstan publication-title: Heliyon doi: 10.1016/j.heliyon.2021.e08660 – volume: 9 start-page: 1523 year: 2008 ident: ref_56 article-title: Drought index mapping at different spatial units publication-title: J. Hydrometeorol. doi: 10.1175/2008JHM983.1 – volume: 73 start-page: 1 year: 2021 ident: ref_64 article-title: Agricultural drought periods analysis by using nonhomogeneous poisson models and regionalization of appropriate model parameters publication-title: Tellus A Dyn. Meteorol. Oceanogr. – ident: ref_31 – volume: 59 start-page: 1675 year: 2014 ident: ref_35 article-title: Combined analysis of precipitation and water deficit for drought hazard assessment publication-title: Hydrol. Sci. J. doi: 10.1080/02626667.2013.862335 – ident: ref_27 – volume: 22 start-page: 205 year: 1982 ident: ref_41 article-title: A Precise Method for Determining Contoured Surfaces publication-title: Aust. Pet. Explor. Assoc. J. – volume: 11 start-page: 107 year: 2011 ident: ref_34 article-title: Comparison and classification of precipitation conditions on the basis of Standardized Precipitation Index and Relative Precipitation Index publication-title: Water-Environ. Rural. Areas – volume: 260 start-page: 105687 year: 2021 ident: ref_25 article-title: Assessment of drought in SPI series using continuous wavelet analysis for Gediz Basin, Turkey publication-title: Atmos. Res. doi: 10.1016/j.atmosres.2021.105687 – volume: 102 start-page: E1099 year: 2021 ident: ref_6 article-title: Advances in Land surface models and indicators for drought monitoring and prediction publication-title: Bull. Am. Meteorol. Soc. doi: 10.1175/BAMS-D-20-0087.1 – volume: 106 start-page: 1 year: 2018 ident: ref_10 article-title: Drought monitoring and analysis: Standardised precipitation evapotranspiration index (SPEI) and standardised precipitation index (SPI) publication-title: Phys. Chem. Earth Parts A/B/C doi: 10.1016/j.pce.2018.07.001 – volume: 317 start-page: 115494 year: 2022 ident: ref_16 article-title: Evaluation of drought propagations with multiple indices in the Yangtze River basin publication-title: J. Environ. Manag. doi: 10.1016/j.jenvman.2022.115494 – volume: 42 start-page: 3418 year: 2022 ident: ref_20 article-title: The effects of non-stationarity on SPI for operational drought monitoring in Europe publication-title: Int. J. Climatol. doi: 10.1002/joc.7424 – volume: 38 start-page: 100505 year: 2022 ident: ref_7 article-title: Spatiotemporal characteristics of meteorological to hydrological drought propagation under natural conditions in China publication-title: Weather. Clim. Extrem. doi: 10.1016/j.wace.2022.100505 – ident: ref_23 doi: 10.3390/atmos13020292 – volume: 20 start-page: 203 year: 2018 ident: ref_60 article-title: Analysis of the vegetation process in a two-stage reservoir on the basis of satellite imagery–a case study: Radzyny Reservoir on the Sama River publication-title: Rocz. Ochr. Sr. – ident: ref_28 – ident: ref_53 – ident: ref_30 – volume: 34 start-page: 4703 year: 2020 ident: ref_62 article-title: Probabilistic analysis of long-term climate drought using steady-state Markov chain approach publication-title: Water Resour. Manag. doi: 10.1007/s11269-020-02683-5 – volume: 8 start-page: 273 year: 1982 ident: ref_51 article-title: Smooth Interpolation of Scattered Data by Local Thin Plate Splines publication-title: Comput. Math. Appl. doi: 10.1016/0898-1221(82)90009-8 – volume: 98 start-page: 822 year: 2022 ident: ref_68 article-title: Spatial and Temporal Pattern Assessment of Meteorological Drought in Tumakuru District of Karnataka during 1951–2019 using Standardized Precipitation Index publication-title: J. Geol. Soc. India doi: 10.1007/s12594-022-2073-3 – volume: 74 start-page: 102936 year: 2022 ident: ref_8 article-title: Evaluation of agricultural drought in South Korea using socio-economic drought information publication-title: Int. J. Disaster Risk Reduct. doi: 10.1016/j.ijdrr.2022.102936 – ident: ref_40 – volume: 37 start-page: 617 year: 1986 ident: ref_47 article-title: Choosing Functions for Semi-variograms of Soil Properties and Fitting Them to Sampling Estimates publication-title: J. Soil Sci. doi: 10.1111/j.1365-2389.1986.tb00392.x – volume: 123 start-page: 11569 year: 2018 ident: ref_58 article-title: Meteorological and hydrological drought on the Loess Plateau, China: Evolutionary characteristics, impact, and propagation publication-title: J. Geophys. Res. Atmos. doi: 10.1029/2018JD029145 – ident: ref_14 – ident: ref_3 doi: 10.3390/ijerph18094449 – volume: 57 start-page: 12 year: 2013 ident: ref_15 article-title: Multivariate standardized drought index: A parametric multi-index model publication-title: Adv. Water Resour. doi: 10.1016/j.advwatres.2013.03.009 – ident: ref_44 – volume: 79 start-page: 48 year: 2019 ident: ref_65 article-title: Construction of a drought monitoring model using deep learning based on multi-source remote sensing data publication-title: Int. J. Appl. Earth Obs. Geoinf. – volume: 190 start-page: 691 year: 2018 ident: ref_37 article-title: Monitoring of meteorological and hydrological droughts in the Vistula basin (Poland) publication-title: Environ. Monit. Assess. doi: 10.1007/s10661-018-7058-8 – volume: 2 start-page: 315 year: 1985 ident: ref_42 article-title: A Refinement of Inverse Distance Weighted Interpolation publication-title: Geoprocessing – volume: 130 start-page: 104951 year: 2019 ident: ref_12 article-title: Modified palmer drought severity index: Model improvement and application publication-title: Environ. Int. doi: 10.1016/j.envint.2019.104951 – volume: 35 start-page: 3253 year: 2021 ident: ref_22 article-title: Recommendations for modifying the Standardized Precipitation Index (SPI) for drought monitoring in arid and semi-arid regions publication-title: Water Resour. Manag. doi: 10.1007/s11269-021-02891-7 – ident: ref_29 – ident: ref_54 – volume: 2 start-page: 60 year: 1986 ident: ref_46 article-title: A Controlled Study of Some Two-Dimensional Interpolation Methods publication-title: COGS Comput. Contrib. – volume: 42 start-page: 2155 year: 2021 ident: ref_55 article-title: Geospatial analysis of meteorological drought impact on Southern Africa biomes publication-title: Int. J. Remote Sens. doi: 10.1080/01431161.2020.1851799 – ident: ref_38 doi: 10.3390/atmos12091098 – volume: 133 start-page: 108460 year: 2021 ident: ref_4 article-title: Influence of meteorological drought on environmental flows in mountain catchments publication-title: Ecol. Indic. doi: 10.1016/j.ecolind.2021.108460 – volume: 4 start-page: 313 year: 1990 ident: ref_48 article-title: Kriging: A Method of Interpolation for Geographical Information Systems publication-title: Int. J. Geogr. Inf. Syst. doi: 10.1080/02693799008941549 – ident: ref_45 doi: 10.1080/10106048609354060 – ident: ref_61 doi: 10.3390/cli7060082 – ident: ref_36 – ident: ref_43 – ident: ref_63 doi: 10.1016/B978-0-12-811689-0.00004-5 – volume: 14 start-page: 1329 year: 2021 ident: ref_21 article-title: Drought investigation and trend assessment in Macta watershed (Algeria) by SPI and ITA methodology publication-title: Arab. J. Geosci. doi: 10.1007/s12517-021-07670-7 – volume: 3 start-page: 509 year: 2015 ident: ref_2 article-title: The biggest drought events in Europe from 1950 to 2012 publication-title: J. Hydrol. Reg. Stud. doi: 10.1016/j.ejrh.2015.01.001 – volume: 347 start-page: 131248 year: 2022 ident: ref_17 article-title: Socioeconomic drought analysis by standardized water supply and demand index under changing environment publication-title: J. Clean. Prod. doi: 10.1016/j.jclepro.2022.131248 – volume: 11 start-page: 1280 year: 2021 ident: ref_24 article-title: Spatiotemporal drought analysis by the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) in Sichuan Province, China publication-title: Sci. Rep. doi: 10.1038/s41598-020-80527-3 |
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| SubjectTerms | 20th century Agricultural production Climate change Drought Droughts Groundwater Hydrology Meteorology Poland Precipitation Rain Regions Spatial Analysis Surface water Uncertainty Water shortages Water supply |
| Title | Uncertainty in Determination of Meteorological Drought Zones Based on Standardized Precipitation Index in the Territory of Poland |
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