Temat: standardized - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Weather drought index prediction using the support vector regression in the Ansegmir Watershed, Upper Moulouya, Morocco
Autorzy:: Bekri, My Hachem
El Hmaidi, Abdellah
Ousmana, Habiba
El Faleh, El Mati
Berrada, Mohamed
El Aissaoui, Kamal
Essahlaoui, Ali
El Ouali, Abdelhadi
Powiązania:: https://bibliotekanauki.pl/articles/1841959.pdf
Data publikacji:: 2021
Wydawca:: Instytut Technologiczno-Przyrodniczy
Tematy:: Ansgemir watershed
drought
forecast
modelling
standardized precipitation index
SPI
standardized precipitation-evapotranspiration index
SPEI
support vectors regression
SVR
Opis:: The purpose of this study is to develop mathematical models based on artificial intelligence: Models based on the support vectors regression (SVR) for drought forecast in the Ansegmir watershed (Upper Moulouya, Morocco). This study focuses on the prediction of the temporal aspect of the two drought indices (standardized precipitation index – SPI and standardized precipitation-evapotranspiration index – SPEI) using six hydro-climatic variables relating to the period 1979–2013. The model SVR3-SPI: RBF, ε = 0.004, C = 20 and γ = 1.7 for the index SPI, and the model SVR3-SPEI: RBF ε = 0.004, C = 40 and γ = 0.167 for the SPEI index are significantly better in comparison to other models SVR1, SVR2 and SVR4. The SVR model for the SPI index gave a correlation coefficient of R = 0.92, MSE = 0.17 and MAE = 0.329 for the learning phase and R = 0.90, MSE = 0.18 and MAE = 0.313 for the testing phase. As for the SPEI index, the overlay is slightly poorer only in the case of the SPI index between the observed values and the predicted ones by the SVR model. It shows a very small gap between the observed and predicted values. The correlation coefficients R = 0.88 for the learning, R = 0.86 for testing remain higher and corresponding to a quadratic error average MSE = 0.21 and MAE = 0.351 for the learning and MSE = 0.21 and MAE = 0.350 for the testing phase. The prediction of drought by SVR model remain useful and would be extremely important for drought risk management.
Źródło:: Journal of Water and Land Development; 2021, 50; 187-194
1429-7426
2083-4535
Pojawia się w:: Journal of Water and Land Development
Dostawca treści:: Biblioteka Nauki

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Tytuł:: Adaptacja wskaźnika SPI na potrzeby monitorowania suszy w wodach podziemnych
Adaptation of the Standardized Precipitation Index SPI for drought monitoring in groundwater
Autorzy:: Kowalczyk, A.
Powiązania:: https://bibliotekanauki.pl/articles/2075651.pdf
Data publikacji:: 2017
Wydawca:: Państwowy Instytut Geologiczny – Państwowy Instytut Badawczy
Tematy:: wskaźnik wód podziemnych
susza
standaryzowany wskaźnik opadu
SPI
standaryzowany wskaźnika wód podziemnych
groundwater levels
drought
Standardized Precipitation Index
Standardized Groundwater Level Index
Opis:: The Standardized Precipitation Index (SPI) proposed by Thomas McKee, Nolan Doesken i John Kleist in 1993 is currently one of the most common meteorological index applied in the assessment of drought intensity. It serves for the quantitative assessment ofprecipitation deficit within an agreed time scale. The advantage of the SPI is that it can be applied at different time scales and different climatic conditions. It provides an early warning information regarding droughts and is helpful in the assessment of its severity. The authors propose that the method can be applied in, apart from precipitation, assessments of river flows, depth of snow cover, water resources in reservoirs, soil wetness and groundwater levels. The article proposes an index formula that allows for the assessment of drought in groundwater. Gamma distribution, which is most commonly used in the SPI formula and does not describe the distribution of groundwater level properly, was replaced with the empirical distribution. In this way a new tool with the advantages inheritedfrom its progenitor was defined to assess the intensity of drought in groundwater. The new index has all needed attributes to be used to interpret the current hydrogeological situation on both regional and local scales. It can compete with indicators currently used for this purpose in Poland and abroad. The "new standardized groundwater level index” was applied to analyse the course of a groundwater drought that occurred in Poland in recent years (2015-2016).
Źródło:: Przegląd Geologiczny; 2017, 65, 11/2; 1301--1305
0033-2151
Pojawia się w:: Przegląd Geologiczny
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Investigation of Transition Possibilities between Drought Classifications Using Standardized Precipitation Index for Wet and Dry Periods – Lower Seyhan Plain, Türkiye Case
Autorzy:: Şimşek, Serin Değerli
Çapar, Ömer Faruk
Turhan, Evren
Powiązania:: https://bibliotekanauki.pl/articles/24201700.pdf
Data publikacji:: 2023
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:: wet period
drought period
SPI
Standardized Precipitation Index
drought classification
transition probability
Karaisalı
Turkey
Opis:: In this study, the Karaisalı region of Türkiye, which has a semi-arid climate and is known to contain the extensive plains and rich water resources of the Seyhan Basin, was preferred as a study area for investigating wet and drought periods for a long timescale. Forty-one years of total precipitation data, between 1980 and 2020, belonging to the closest precipitation observation station located in the Karaisalı region were used. By using the Standardized Precipitation Index (SPI), which is one of the frequently used meteorological drought indices, drought classification probabilities, expected first transition period and residence time in each drought severity class values were calculated for the 12-month time scale. As a result of the study, it was determined that the most drought period took place in 2012 according to the examined time duration. In addition, the most wet period was observed in 2001. When various time scales were considered, SPI-3 and SPI-6 have Near Normal Wet periods, while SPI-9 and SPI-12 have Near Normal Drought periods. Extremely Wet periods were more numerous, while Extremely Drought periods lasted longer. In addition, 3 months after the end of the drought categories, it can be seen that the Wet and Drought periods change into Near Normal Wet and Near Normal Drought periods.
Źródło:: Journal of Ecological Engineering; 2023, 24, 5; 201--209
2299-8993
Pojawia się w:: Journal of Ecological Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Assessment of agricultural drought based on CHIRPS data and SPI method over West Papua - Indonesia
Autorzy:: Faisol, Arif
Indarto, Indarto
Novita, Elida
Budiyono, Budiyono
Powiązania:: https://bibliotekanauki.pl/articles/2073723.pdf
Data publikacji:: 2022
Wydawca:: Instytut Technologiczno-Przyrodniczy
Tematy:: agricultural drought
CHIRPS
Climate Hazards Group Infrared Precipitation with Stations data
Standardized Precipitation Index method
SPI
West Papua
Indonesia
Opis:: This study aims to utilise Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data and Standardised Precipitation Index (SPI) method to assess agricultural drought in West Papua, Indonesia. The data used in this study is monthly CHIRPS data acquired from 1996 to 2019, daily precipitation data recorded from 1996 to 2019 from the five climatological stations in West Papua, Indonesia located at Sorong, Fakfak, Kaimana, Manokwari, and South Manokwari. 3-month SPI or quarterly SPI are used to assess agricultural drought, i.e., SPI January-March, SPI February-April, SPI March-May, SPI April-June, SPI May-July, SPI June-August, SPI July-September, SPI August-October, SPI September-November, and SPI October-December. The results showed that in 2019 agricultural drought in West Papua was moderately wet to severely dry. The most severely dry occurred in September-December periods. Generally, CHIRPS data and SPI methods have an acceptable accuracy in generating drought information in West Papua with an accuracy of 53% compared with climate data analysis. Besides, the SPI from CHIRPS data processing has a moderate correlation with climate data analysis with an average R2= 0.51.
Źródło:: Journal of Water and Land Development; 2022, 52; 44--52
1429-7426
2083-4535
Pojawia się w:: Journal of Water and Land Development
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

Tytuł:: Zmienność występowania susz w okresie wegetacyjnym w Polsce w latach 1966-2015
Variability of Drought Occurrence During Growing Season in Poland in Years 1966-2015
Autorzy:: Szyga-Pluta, K.
Powiązania:: https://bibliotekanauki.pl/articles/163756.pdf
Data publikacji:: 2018
Wydawca:: Polskie Towarzystwa Geofizyczne
Tematy:: susza
SPI
wskaźnik standaryzowanego opadu
RPI
wskaźnik względnego opadu
wskaźnik K Sielianinowa
okresy suszy w Polsce
drought
Standardized Precipitation Index
Relative Precipitation Index
K Sielianinov Index
periods of drought in Poland
Opis:: Suszę atmosferyczną określa się często poprzez analizę niedoboru opadów na danym obszarze w badanym przedziale czasowym. Do identyfikacji suszy służą różne wskaźniki, z których w niniejszym opracowaniu wybrano: wskaźnik standaryzowanego opadu SPI (ang. Standardized Precipitation Index), wskaźnik względnego opadu RPI (ang. Relative Precipitation Index) i wskaźnik hydrotermiczny K Sielianinowa. W opracowaniu wykorzystano dane dotyczące średniej dobowej temperatury powietrza oraz dobowej sumy opadów atmosferycznych z trzydziestu stacji IMGW-PIB w miesiącach od kwietnia do października z lat 1966-2015. Dokonano oceny okresu wegetacyjnego w kolejnych latach pod względem niedoboru opadów przy wykorzystaniu wybranych wskaźników w badanym okresie, przedstawiono liczbę miesięcy charakteryzujących się suszą o różnym stopniu nasilenia, ich udział w okresie wegetacyjnym oraz zróżnicowanie przestrzenne na badanym obszarze. Należy stwierdzić, że do wyznaczania występowania okresów suszy w kolejnych latach znaczenie wyboru wskaźnika jest mniejsze niż w przypadku wyznaczenia okresów o różnej intensywności suszy. Występowanie suszy atmosferycznej w Polsce w okresie wegetacyjnym jest bardzo zróżnicowane, stąd niekompletna i niewystarczająca jest ocena suszy na podstawie uśrednionych wartości wskaźników dla całego obszaru Polski.
Atmospheric drought is often referred to by analyzing the rainfall deficit in a given area for a specified period. Different indicators are used to identify the drought, from which the Standardized Precipitation Index (SPI), Relative Precipitation Index (RPI) and the hydrothermal K Sielianinov Index have been selected. The data of average daily air temperature and daily precipitation totals from 30 IMGW-PIB stations in April-October from years1966-2015 were used. An assessment of the growing period in the following years in terms of rainfall shortage using selected indicators over the analyzed period showed the number of months characterized by varying degrees of severity of drought, their share in the growing period and spatial variation in the studied area. It should be noted that to determine the occurrence of drought periods in subsequent years, the significance of the indicator choice is smaller than when drought intensities are determined. The occurrence of atmospheric drought in Poland during the vegetation period is very diverse, hence the drought assessment based on averaged values of indicators for the whole area of Poland is incomplete and insufficient.
Źródło:: Przegląd Geofizyczny; 2018, 1-2; 51-67
0033-2135
Pojawia się w:: Przegląd Geofizyczny
Dostawca treści:: Biblioteka Nauki

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