Academic literature on the topic 'Standardized Precipitation Index (SPI)'
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Journal articles on the topic "Standardized Precipitation Index (SPI)"
Isia, Ismallianto, Tony Hadibarata, Muhammad Noor Hazwan Jusoh, Rajib Kumar Bhattacharjya, Noor Fifinatasha Shahedan, Aissa Bouaissi, Norma Latif Fitriyani, and Muhammad Syafrudin. "Drought Analysis Based on Standardized Precipitation Evapotranspiration Index and Standardized Precipitation Index in Sarawak, Malaysia." Sustainability 15, no. 1 (December 31, 2022): 734. http://dx.doi.org/10.3390/su15010734.
Full textPandya, Parthsarthi, Rohit Kumarkhaniya, Ravina Parmar, and Piyush Ajani. "Meteorological Drought Analysis Using Standardized Precipitation Index." Current World Environment 15, no. 3 (December 30, 2020): 477–86. http://dx.doi.org/10.12944/cwe.15.3.12.
Full textLucas, Matthew P., Clay Trauernicht, Abby G. Frazier, and Tomoaki Miura. "Long-Term, Gridded Standardized Precipitation Index for Hawai‘i." Data 5, no. 4 (November 26, 2020): 109. http://dx.doi.org/10.3390/data5040109.
Full textAriyanto, Dwi Priyo, Abdul Aziz, Komariah Komariah, Sumani Sumani, and Magarsa Abara. "Comparing the accuracy of estimating soil moisture using the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI)." SAINS TANAH - Journal of Soil Science and Agroclimatology 17, no. 1 (June 29, 2020): 23. http://dx.doi.org/10.20961/stjssa.v17i1.41396.
Full textSalmin, A. S., I. F. Asaulyak, and A. I. Belolyubtsev. "ANALYSING TIME SERIES OF STANDARDIZED PRECIPITATION INDEX (SPI)." Успехи современного естествознания (Advances in Current Natural Sciences), no. 5 2021 (2021): 101–9. http://dx.doi.org/10.17513/use.37630.
Full textKumar, Rohini, Jude L. Musuuza, Anne F. Van Loon, Adriaan J. Teuling, Roland Barthel, Jurriaan Ten Broek, Juliane Mai, Luis Samaniego, and Sabine Attinger. "Multiscale evaluation of the Standardized Precipitation Index as a groundwater drought indicator." Hydrology and Earth System Sciences 20, no. 3 (March 15, 2016): 1117–31. http://dx.doi.org/10.5194/hess-20-1117-2016.
Full textKumar, R., J. L. Musuuza, A. F. Van Loon, A. J. Teuling, R. Barthel, J. Ten Broek, J. Mai, L. Samaniego, and S. Attinger. "Multiscale evaluation of the standardized precipitation index as a groundwater drought indicator." Hydrology and Earth System Sciences Discussions 12, no. 8 (August 5, 2015): 7405–36. http://dx.doi.org/10.5194/hessd-12-7405-2015.
Full textZuo, Dongdong, Wei Hou, Hao Wu, Pengcheng Yan, and Qiang Zhang. "Feasibility of Calculating Standardized Precipitation Index with Short-Term Precipitation Data in China." Atmosphere 12, no. 5 (May 6, 2021): 603. http://dx.doi.org/10.3390/atmos12050603.
Full textAripbilah, Safrudin Nor, and Heri Suprapto. "ANALISIS KEKERINGAN DI KABUPATEN SRAGEN DENGAN METODE PALMER, THORNTHWAITE, DAN STANDARDIZED PRECIPITATION INDEX." JURNAL SUMBER DAYA AIR 17, no. 2 (November 30, 2021): 111–24. http://dx.doi.org/10.32679/jsda.v17i2.742.
Full textBlain, Gabriel Constantino. "Standardized precipitation index based on pearson type III distribution." Revista Brasileira de Meteorologia 26, no. 2 (June 2011): 167–80. http://dx.doi.org/10.1590/s0102-77862011000200001.
Full textDissertations / Theses on the topic "Standardized Precipitation Index (SPI)"
Edossa, D. C., Y. E. Woyessa, and W. A. Welderufael. "Comparison between two meteorological drought indices in the central region of South Africa." Interim : Interdisciplinary Journal, Vol 13, Issue 3: Central University of Technology Free State Bloemfontein, 2013. http://hdl.handle.net/11462/309.
Full textThe objective of this study was to characterize meteorological droughts in the Central Region of South Africa, Modder River Basin, C52A quaternary catchment using two popular drought indices: Standardized Precipitation Index (SPI) and Standardized Precipitation-Evapotranspiration Index (SPEI) and to compare the two indices. Drought events were characterized based on their frequency, duration, magnitude and intensity. The indices were computed for the time-scales that are important for planning and management of water resources, i.e. 3-, 6- and 12-month time-scales. The basic meteorological input data used in the computation of these indices were 57 years (1950-2007) of monthly precipitation and monthly temperature data which were recorded at The Cliff weather station in the quaternary catchment. It was found that both SPI and SPEI responded to drought events in similar fashion in all time-scales. During the analysis period, a total of 37, 26 and 17 drought events were identified in the area based on 3-, 6-, and 12-month times-scales, respectively. Considering event magnitude as severity parameter, results from both indices identified the periods 1984-1985, 1992-1993 and 2003-2005 as the severest drought periods in the area. However, when the effects of both drought duration and magnitude are considered (drought intensity), the most severest drought events were identified during the years 1982/83, 1966 and 1973 based on 3-, 6- and 12-month timescales, respectively. It was concluded that although the SPEI generally exhibits veracity over SPI by including, apart from precipitation, additional meteorological parameter, mean temperature, SPI should be adopted as an appropriate drought monitoring tool in an area, like Africa, where meteorological data are scarce.
Passos, Jacqueline Sobral de Araújo. "Variabilidade espaço-temporal da precipitação do Alto São Francisco (sub-40) utilizando dados do sensor PR/TRMM." Universidade Federal da Paraíba, 2015. http://tede.biblioteca.ufpb.br:8080/handle/tede/9123.
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The precipitation, due to its importance, is considered one of the main variables of the hydrological cycle. An alternative to collect rainfall data is using rainfall measurements by sensors/satellites. Among these kinds of alternative, the Tropical Rainfall Measuring Mission (TRMM) allows the collection with a spatial resolution 0.25º × 0.25º. Thus, the objective of the study is to understand, in more detail, the behavior and distribution of rainfall throughout the Upper São Francisco basin (Sub-40), in a recent period (1998-2013). The survey was conducted in the following steps: collection of TRMM rainfall data from 1998 to 2013 organizing them monthly and yearly; getting Três Marias reservoir in flow data; getting altimetry SRTM data; analyzing the correlation between the TRMM precipitation and the inflows to Três Marias reservoir; generating surface profiles to compare with the precipitation data, analyzing the number of consecutive dry days and consecutive wet days; computing the Standardized Precipitation Index - SPI for each point (169 points); spatial distribution of annual and monthly accumulated rainfall data, the correlation of rainfall and flow, of consecutive wet and dry days, the SPI index and cluster analysis. According to the results, it can be concluded that the years of highest and lowest value of annual rainfall depth was respectively 2009 and 2012. The driest months are June to August, and July is the driest one. In contrast, the wettest months are from November to January, and most rainy month is December. The annual and monthly precipitation depth showed that the northeast region of the basin rains less and the western and southern basin are wetter. The precipitation response to the inflow to the Três Marias reservoir is four days after the rainfall occurs. The relation between precipitation and altimetry shows that most of the annual rainfall depth is directly proportional to altimetry, but in some cases it shows little variability in the ground. Regarding the SPI, it was possible to calculate the beginning, end, intensity and magnitude of each dry and wet season. From the maps, SPI spatial information was produced in order to identify for each period the regions with highest and lowest values. By means of the map and dendrogram clusters, regions with higher and lower similarity between the monthly accumulated rainfall data were identified. Finally, the TRMM sensor proved useful in the analysis of spatial and temporal variability of precipitation over the studied basin, accounting satisfactorily dry and rainy periods. With easy acquisition and handling, satellite data is a viable alternative to collect precipitation data with spatial and temporal quality, especially in areas of difficult access or in developing countries.
A precipitação, pela sua importância, é considerada uma das principais variáveis do ciclo hidrológico. Uma alternativa para coletar dados de chuva é utilizar precipitações obtidas por sensores/satélites. Dentre estes, a Tropical Rainfall Measuring Mission (TRMM) permite a coleta com resolução espacial de 0,25º × 0,25º. Com isso, o objetivo do estudo é compreender, de forma mais detalhada, o comportamento e a distribuição da precipitação ao longo da bacia do Alto São Francisco (Sub-40), em período recente (1998−2013). A pesquisa foi realizada nas seguintes etapas: coleta de dados do TRMM para o período de 1998 a 2013 organizando-os em acumulados mensais e anuais; coleta dos dados de vazão do reservatório Três Marias; coleta de dados de altimetria SRTM; correlação diária entre os elementos de precipitação TRMM; analisar o comportamento da precipitação anual da Sub-40 frente aos dados altimétricos; identificar a quantidade de dias secos e úmidos consecutivos de cada ponto da grade utilizado; extração do Índice Padronizado de Precipitação - SPI para cada ponto (169 pontos); espacialização dos dados de precipitação acumulada anual e mensal, da correlação de chuva e vazão, dos dias secos e úmidos consecutivos, do Índice SPI e da análise de cluster. De acordo com os resultados obtidos, pode-se concluir que os anos de maior e menor valor de precipitações acumuladas anuais foram respectivamente os anos de 2009 e 2012. Os meses mais secos foram os de junho a agosto, sendo julho o mês mais seco. Em contrapartida, os meses mais úmidos foram de novembro a janeiro, com maior precipitação ocorrendo em dezembro. Os dados de precipitação acumuladas anuais e mensais mostraram que a região nordeste da bacia chove menos e que o oeste e sul da bacia são mais úmidos. O tempo de resposta da precipitação frente à vazão afluente ao reservatório Três Marias é de quatro dias após a ocorrência de chuvas. A relação entre a precipitação e altimetria mostra que a maioria dos dados de precipitações acumuladas anuais é diretamente proporcional à altimetria, mas que em alguns casos ela apresenta pouca variabilidade em relação ao terreno. Com relação ao SPI, a partir dos mapas, produziram-se informações de SPI de maneira espacializada identificando a cada período as regiões de maiores e menores valores. Observando os mapas de clusters e dendrograma identificaram-se as regiões com maior e menor similaridade entre os dados de precipitação acumulada mensal. Por fim, o sensor TRMM se mostrou hábil na análise da variabilidade espaço-temporal da precipitação sobre a bacia, representando de forma satisfatória os períodos secos e chuvosos. Com fácil aquisição e manuseio, os dados do satélite são uma alternativa viável para se coletar informações pluviométricas com qualidade espacial e temporal, principalmente em regiões de difícil acesso ou em países em desenvolvimento.
Chattopadhyay, Somsubhra. "IMPACT OF CLIMATE CHANGE ON EXTREME HYDROLOGICAL EVENTS IN THE KENTUCKY RIVER BASIN." UKnowledge, 2017. http://uknowledge.uky.edu/bae_etds/50.
Full textPieper, Patrick [Verfasser]. "Meteorological Drought - Universal Monitoring and reliable seasonal Prediction with the Standardized Precipitation Index / Patrick Pieper." Hamburg : Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky, 2020. http://d-nb.info/1227582404/34.
Full textRosa, Ricardo Granés Tavares Duarte. "Índices de seca. Aplicação ao continente português." Master's thesis, ISA/UTL, 2011. http://hdl.handle.net/10400.5/4488.
Full textThe Palmer Drought Severity Index (PDSI) was tested along with two indices resulting from modifying its original formulation, one concerning the replacement of the Thornthwaite equation to compute potential evapotranspiration (ETP) by the FAO Penman-Monteith method, and the other consisting in replacing the soil water balance model and the ETP computation that passes to correspond to the ETP of an olive orchard, generating a new index: the MedPDSI. A factor for the normalization of the index, the climate characteristic (K), was reviewed and the index was calibrated for each analyzed location. The Standardized Precipitation Index (SPI) for the 9 and 12 month time-scales was also tested and compared with the three variants of the PDSI. The results revealed that the modification of K improved the standardization of the PDSI and that the calibration produced statistically improved results. It was found that the MedPDSI anticipates the initiation of droughts over the original PDSI, either with ETP Thornthwaite or with ETP FAO Penman-Monteith, and tends to classify droughts more severely than the first. The use of 9 month time-scale in the SPI is the one that best relates to the PDSI, since it clearly anticipates the onset of droughts relative to the 12 month scale.
SANTOS, Marcos Suassuna. "Caracterização espaço-temporal de secas utilizando ondaletas e o Standardized Precipitation Index: uma aplicação para a parcela mineira da bacia Rio São Francisco." reponame:Repositório Institucional da CPRM, 2011. http://rigeo.cprm.gov.br/xmlui/handle/doc/1221.
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A pesquisa desenvolvida tem foco na análise espaço-temporal das secas, baseada em informações de chuvas. Para a obtenção das séries históricas representativas das secas e estudo espacial do fenômeno, foi empregada a análise regional de precipitações com momentos-L, além do índice de seca Standardized Precipitation Index (SPI). Para a análise de séries temporais de secas foi utilizada a transformada de ondaletas, uma alternativa à transformada de Fourier, a qual permite identificar periodicidades nas séries além de localizar variações dessas periodicidades ao longo do tempo. Procurou-se ainda investigar possíveis influências dos fenômenos El Niño Oscilação Sul (ENOS), por meio do Índice Oceânico Niño (ION) e do Índice de Oscilação Sul (IOS), e do fenômeno da Oscilação Decenal do Pacífico (ODP) sobre os índices de secas obtidos. Foi proposto incorporar a análise regional de frequência no cálculo das séries de SPI, com vistas a contribuir com a superação da crítica de que, para esse cálculo, longos registros históricos de chuvas são necessários, além de considerar apenas a possibilidade de uso da distribuição de probabilidades Gama. Reforça-se a necessidade de, no cálculo do SPI, considerar outras possibilidades além dessa distribuição e a análise local de frequências, uma vez que valores extremos de chuvas eventualmente distorcem significativamente as estimativas do índice. Além disso, a análise regional de frequência permitiu definir regiões estatisticamente homogêneas, as quais apresentaram abrangência geográfica inversamente proporcional aos totais precipitados médios anuais. Para a análise de séries temporais o uso da transformada de ondaletas não detectou aumento da frequência de ocorrência de secas na área de estudo nos últimos anos. Além disso, não possibilitou fazer uma conexão clara entre as secas na região de estudo e os índices climáticos IOS, ION e ODP. Ainda assim, de alguma forma, percebeu-se que esses fenômenos de grande escala influenciam a intensidade das secas em escala local, uma vez que foi persistente a observação das secas mais extremas na região em fase fria de ENOS e ODP, corroborando a tese de que extremos climáticos são mais intensos na América do Sul quando o ENOS e ODP estão em fase.
Santos, Marcus Suassuna. "Caracterização espaço-temporal de secas utilizando ondaletas e o standardized precipitation index: uma aplicação para a parecela mineira da Bacia do Rio São Francisco." Universidade Federal de Minas Gerais, 2011. http://hdl.handle.net/1843/REPA-8SBJYB.
Full textA pesquisa desenvolvida tem foco na análise espaço-temporal das secas, baseada em informações de chuvas. Para a obtenção das séries históricas representativas das secas e estudo espacial do fenômeno, foi empregada a análise regional de precipitações com momentos-L, além do índice de seca Standardized Precipitation Index (SPI). Para a análise de séries temporais de secas foi utilizada a transformada de ondaletas, uma alternativa à transformada de Fourier, a qual permite identificar periodicidades nas séries além de localizar variações dessas periodicidades ao longo do tempo. Procurou-se ainda investigar possíveis influências dos fenômenos El Niño Oscilação Sul (ENOS), por meio do Índice Oceânico Niño (ION) e do Índice de Oscilação Sul (IOS), e do fenômeno da Oscilação Decenal do Pacífico (ODP) sobre os índices de secas obtidos. Foi proposto incorporar a análise regional de frequência no cálculo das séries de SPI, com vistas a contribuir com a superação da crítica de que, para esse cálculo, longos registros históricos de chuvas são necessários, além de considerar apenas a possibilidade de uso da distribuição de probabilidades Gama. Reforça-se a necessidade de, no cálculo do SPI, considerar outras possibilidades além dessa distribuição e a análise local de frequências, uma vez que valores extremos de chuvas eventualmente distorcem significativamente as estimativas do índice. Além disso, a análise regional de frequência permitiu definir regiões estatisticamente homogêneas, as quais apresentaram abrangência geográfica inversamente proporcional aos totais precipitados médios anuais. Para a análise de séries temporais o uso da transformada de ondaletas não detectou aumento da frequência de ocorrência de secas na área de estudo nos últimos anos. Além disso, não possibilitou fazer uma conexão clara entre as secas na região de estudo e os índices climáticos IOS, ION e ODP. Ainda assim, de alguma forma, percebeu-se que esses fenômenos de grande escala influenciam a intensidade das secas em escala local, uma vez que foi persistente a observação das secas mais extremas na região em fase fria de ENOS e ODP, corroborando a tese de que extremos climáticos são mais intensos na América do Sul quando o ENOS e ODP estão em fase.
Moreira, Adriana Aparecida. "Análise da seca/estiagem no norte do estado de Minas Gerais a partir de dados MODIS." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2016. http://hdl.handle.net/10183/147931.
Full textThe drought that affects the north of Minas Gerais State causes severe socio-environment impacts. Changes on the precipitation distribution or even the reduction of the raining amount is enough reason for regional disorganization. In this context, this work analyzed the drought spatial-temporal distribution in the north of Minas Gerais State, between 2003 and 2014. The methodology consisted on the elaboration of time series of standardized anomaly NDWI using images of reflectance MOD13Q1/MODIS. For the analysis it was used the following basis: the abnormality decrees caused by drought, damage and losses data, precipitation and the water subsurface range on GRACE solution. Correlations were conducted between NDWI and precipitation, as well as between standardized anomaly NDWI and precipitation anomaly, considering data with and without 30 days of gap. It was applied average test, the Student t-test, for the standardized anomaly NDWI and precipitation anomaly, with a confidence range of 95%. Results demonstrated that standardized anomaly NDWI satisfactorily identified three seasons of drought in this region. It corroborates with emergency decrees and public calamity data, in what it was observed a higher number of decrees, especially in these periods. Two seasons identified as drought were reported as severe drought in the north of Minas Gerais State. This fact validates the standardized anomaly NDWI data with the situation occurred in the region. The quantity of affected areas drought, also evidences the same period of larger numbers of occurrences drought and disability in the distribution of precipitation. However, the use of standardized anomaly NDWI by itself on the identification of drought may not be enough evidence for this association, since the phenomenon can occur and cause damages and losses among a green landscape, as seen in 2010. Statistical analysis demonstrated that there are correlations with better intensity degrees between the NDWI and the precipitation with a gap of 30 days. This fact was also observed for the standardized anomaly NDWI and precipitation anomaly data, however, mild to moderate correlations were observed. Student t-test demonstrated differences between the averages only for the year of 2014. Despite for all other periods averages were not statistically different, they were observed p-value low values, with the exception of the period between 2008 and 2011, which are verified p-value between 0.4 and 0.9. Although statistical tests did not demonstrated a great significance, the temporal variation of standardized anomaly NDWI data and precipitation anomaly evidenciate a similar relationship between these data. Lastly, the comparison with data from GRACE solutions, identified the same periods verified with the standardized anomaly NDWI, being then observed that these data corroborates between them in the identification of draught in the north of Minas Gerais State.
CHHIN, Rattana. "Future Projection of Drought in the Indochina Region Based on the Optimal Ensemble Subset of CMIP5 Models." Kyoto University, 2019. http://hdl.handle.net/2433/242616.
Full textSOUSA, Edicarlos Pereira de. "Padrões climáticos de eventos extremos de chuva utilizando análise multivariada e de ondeletas no Estado de Minas Gerais." Universidade Federal de Campina Grande, 2016. http://dspace.sti.ufcg.edu.br:8080/jspui/handle/riufcg/1485.
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Capes
O estado de Minas Gerais, localizado na região Sudeste do Brasil, possui um território planáltico, com áreas mais elevadas situadas na porção sul. O clima é predominantemente tropical e tropical de altitude, com temperaturas oscilando, normalmente, entre 17 e 20°C. Tais características o tornam, muitas vezes, susceptível a fortes chuvas, provocando transtornos diversos à população. Desse modo, buscou-se analisar a variabilidade da chuva mineira através de técnicas que fossem capazes de definir padrões espaciais e temporais de eventos secos e chuvosos, assim como modulá-los nas escalas tempo-frequência. Para isso, calculou-se o Índice de Precipitação Normalizada (IPN) mensal e trimestral no período 1977-2012. A fim de encontrar padrões espaço-temporais e regiões homogêneas (RH) do IPN mensal e trimestral, utilizaram-se as técnicas da Análise em Componentes Principais (ACP) e Agrupamentos (AA). A técnica da Transformada de Ondeletas (TO) foi aplicada para algumas localidades das diferentes RH em diversas escalas. A TO possibilitou encontrar oscilações importantes no sinal da precipitação, mostrando as componentes dominantes da variabilidade da chuva na área pesquisada. Nos espectros de fase e global de energia da TO, para a chuva mensal, predominou o ciclo anual em todas as localidades. Além da escala anual, observaram-se interações com escalas inferiores a doze meses, possivelmente decorrentes da sazonalidade da precipitação. A TO da precipitação e da Radiação de Onda Longa (ROL) diárias evidenciou frequências maiores que as da chuva mensal. A análise dos espectros de fase e de energia global, nas regiões centro-sul e oeste, apresentou maior energia no início das séries da precipitação e de ROL. Contribuições mais elevadas ocorreram nas escalas sinóticas e intrassazonais, principalmente nas localidades de Viçosa, Bom Despacho, Ituiutaba e Lavras. Esses padrões temporais estão associados com a Oscilação de Madden-Julian (OMJ), intensificando a atuação de sistemas moduladores do clima de Minas Gerais. Oscilações em escalas menores que dez dias foram detectadas nos anos de 2011 e 2012 e podem estar associadas aos sistemas de curto prazo que contribuíram para a chuva mineira. No caso de 2011, os eventos de chuva observados em meados de janeiro foram modulados pelos episódios da Zona de Convergência do Atlântico Sul (ZCAS) e reforçados pela atuação da OMJ.
The state of Minas Gerais, located in southeastern Brazil, has a plateaux area, with higher areas in the southern part. The climate is predominantly tropical and tropical altitude, with temperatures ranging normally between 17 and 20°C. These characteristics make it often susceptible to heavy rains, causing many disorders the population. Thus, it sought to analyze the variability of the rain of Minas Gerais through techniques that were able to define spatial and temporal patterns of dry and wet events, and modulate them in the time-frequency ranges. For this, we calculated the Standardized Precipitation Index (SPI) monthly and quarterly in the period 1977-2012. In order to find spatiotemporal patterns and homogeneous regions (HR) of the monthly and quarterly SPI, we used the techniques of Principal Components Analysis (PCA) and Cluster Analysis (CA). The technique of Wavelets Transform (WT) has been applied to some locations of the different HR at various scales. The WT possible find important variations in rainfall signal, showing the dominant components of rainfall variability in the studied area. In phase spectra and global energy of WT, for the monthly rainfall, dominated the annual cycle in all locations. In addition to the annual scale, there were interactions with scales less than twelve months, possibly due to the seasonality of precipitation. The WT of precipitation and Outgoing Longwave Radiation (OLR) daily reported higher frequencies than the monthly rainfall. Analysis of phase spectra and global power, in south-central and western regions, showed higher energy at the beginning of the series of precipitation and OLR. Higher contributions occurred in the synoptic and intraseasonal scales, especially in the localities of Viçosa, Bom Despacho, Ituiutaba and Lavras. These temporal patterns are associated with the Madden-Julian Oscillation (MJO), intensifying the activity of modulators systems climate of Minas Gerais. Oscillations at smaller scales than ten days were detected in 2011 and 2012 and may be associated with short-term systems that contributed to the Minas Gerais rainfall. In the case of 2011 rain events observed in mid-January they were modulated by episodes of South Atlantic Convergence Zone (SACZ) and reinforced by the performance of MJO.
Book chapters on the topic "Standardized Precipitation Index (SPI)"
Almadani, Mohammad A. "Drought Assessment Using Standardized Precipitation Index (SPI) Case Study: Sulphur Springs Tampa FL." In Lecture Notes in Civil Engineering, 133–46. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-7920-9_16.
Full textBeg, Ayad Ali Faris, and Ahmed Hashem Al-Sulttani. "Spatial Assessment of Drought Conditions Over Iraq Using the Standardized Precipitation Index (SPI) and GIS Techniques." In Environmental Remote Sensing and GIS in Iraq, 447–62. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21344-2_18.
Full textParida, Suman Kalyani, Jyotiprakash Padhi, Paromita Chakraborty, and Bitanjaya Das. "Drought Characterization During Monsoon Months Based on Standardized Precipitation Index (SPI) in Nuapada District, Odisha, India." In Water Quality, Assessment and Management in India, 59–69. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95687-5_4.
Full textAyuso, J. L., P. Ayuso-Ruiz, A. P. García-Marín, J. Estévez, and E. V. Taguas. "Local Analysis of the Characteristics and Frequency of Extreme Droughts in Málaga Using the SPI (Standardized Precipitation Index)." In Lecture Notes in Management and Industrial Engineering, 167–79. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-12754-5_13.
Full textKostopoulou, E., C. Giannakopoulos, D. Krapsiti, and A. Karali. "Temporal and Spatial Trends of the Standardized Precipitation Index (SPI) in Greece Using Observations and Output from Regional Climate Models." In Perspectives on Atmospheric Sciences, 475–81. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-35095-0_68.
Full textTeixeira-Gandra, Claudia Fernanda Almeida, Gisele Machado da Silva, Rita De Cassia Fraga Damé, Maria Clotilde Carré Chagas Neta, Francisco Amaral Villela, Letícia Burkert Méllo, Emanuele Baifus Manke, and Rosiane Schwantz do Couto. "Evaluation of Droughts in the State of Rio Grande do Sul, Brazil, Using the Standardized Precipitation Index (SPI) and the Moreno Index (MI)." In INCREaSE 2019, 125–37. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30938-1_10.
Full textAmrit, Kumar, S. K. Mishra, and R. P. Pandey. "Coupling of Tennant Concept with Standardized Precipitation Index (SPI) for the Prediction of Environmental Flow Condition from Rainfall in Upper Narmada Basin." In Climate Change Impacts, 265–72. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-5714-4_20.
Full textDökmen, Funda, Zafer Aslan, and Ahmet Tokgözlü. "Standardized Precipitation Index Analyses with Wavelet Techniques at Watershed Basin." In Computational Science and Its Applications – ICCSA 2017, 127–41. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-62395-5_10.
Full textSahu, Smruti Ranjan, Kishan Singh Rawat, Sanjeev Kumar, Anil Kumar Mishra, and Sudhir Kumar Singh. "Monitoring Drought of Maharashtra, India by Using Standardized Precipitation Index." In Springer Proceedings in Energy, 201–8. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-6879-1_20.
Full textChervenkov, Hristo, and Valery Spiridonov. "Precipitation Pattern Estimation with the Standardized Precipitation Index in Projected Future Climate over Bulgaria." In Large-Scale Scientific Computing, 443–49. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73441-5_48.
Full textConference papers on the topic "Standardized Precipitation Index (SPI)"
Santos, J. F., M. M. Portela, M. Naghettini, J. P. Matos, and A. T. Silva. "Precipitation thresholds for drought recognition: a further use of the standardized precipitation index, SPI." In RIVER BASIN MANAGEMENT 2013. Southampton, UK: WIT Press, 2013. http://dx.doi.org/10.2495/rbm130011.
Full textTheophilou, M. K., and D. Serghides. "Drought in Nicosia using Standardized Precipitation Index SPI-n and BMDI drought index." In Third International Conference on Remote Sensing and Geoinformation of the Environment, edited by Diofantos G. Hadjimitsis, Kyriacos Themistocleous, Silas Michaelides, and Giorgos Papadavid. SPIE, 2015. http://dx.doi.org/10.1117/12.2196266.
Full textNg, Cia Yik, Wan Zurina Wan Jaafar, Faridah Othman, Sai Hin Lai, Yiwen Mei, and Juneng Liew. "Evaluation of Drought Conditions in Peninsular Malaysia during 1989-2018 using SPI and EDDI." In International Technical Postgraduate Conference 2022. AIJR Publisher, 2022. http://dx.doi.org/10.21467/proceedings.141.1.
Full textAkbari, H., G. R. Rakhshandehroo, A. H. Sharifloo, and E. Ostadzadeh. "Drought Analysis Based on Standardized Precipitation Index (SPI) and Streamflow Drought Index (SDI) in Chenar Rahdar River Basin, Southern Iran." In Watershed Management Symposium 2015. Reston, VA: American Society of Civil Engineers, 2015. http://dx.doi.org/10.1061/9780784479322.002.
Full textTAPARAUSKIENĖ, Laima, and Veronika LUKŠEVIČIŪTĖ. "DROUGHT OCCURRENCE UNDER LITHUANIAN CLIMATIC CONDITIONS." In Rural Development 2015. Aleksandras Stulginskis University, 2015. http://dx.doi.org/10.15544/rd.2015.059.
Full textEl Orfi, Tarik, Mohamed El Ghachi, and Sébastien Lebaut. "Characterization and Spatialization of Drought by the Standardized Precipitation Index (SPI) in the Upper Basin of the Oum ErRbia River." In GEOIT4W-2020: 4th Edition of International Conference on Geo-IT and Water Resources 2020, Geo-IT and Water Resources 2020. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3399205.3399211.
Full textŻARSKI, Jacek, Stanisław DUDEK, and Renata KUŚMIEREK-TOMASZEWSKA. "DRIP IRRIGATION AS A FACTOR MITIGATING DROUGHT IMPACT IN CORN CULTIVATION IN CENTRAL POLAND." In RURAL DEVELOPMENT. Aleksandras Stulginskis University, 2018. http://dx.doi.org/10.15544/rd.2017.167.
Full textZolotokrylin, Aleksandr, Tatyana Titkova, and Elena Cherenkova. "DRYNESS DYNAMICS OF THE SOUTH OF EUROPEAN RUSSIA IN THE SPRING - SUMMER PERIOD." In Land Degradation and Desertification: Problems of Sustainable Land Management and Adaptation. LLC MAKS Press, 2020. http://dx.doi.org/10.29003/m1697.978-5-317-06490-7/148-152.
Full textManganhar, Suhail, and Humayoon Sial. "Projection of Geographical Variability and Temporal Trends on Drought Characteristics Using Standardized Precipitation Evapotranspiration Index (SPEI) for Water Resource Management of Critical Zones in Sindh, Pakistan." In 5th International Electronic Conference on Water Sciences. Basel, Switzerland: MDPI, 2020. http://dx.doi.org/10.3390/ecws-5-08449.
Full textAnggono, W. S. P. Dwi, Kristoko Dwi Hartomo, and Eko Sediyono. "Standardized precipitation index web application mapping shiny model." In 2017 International Conference on Innovative and Creative Information Technology (ICITech). IEEE, 2017. http://dx.doi.org/10.1109/innocit.2017.8319131.
Full textReports on the topic "Standardized Precipitation Index (SPI)"
Krishnappa, Rakshith, and Vidhya Sivakumar. Characterization of Drought Vulnerability Assessment Using Standardized Precipitation Index (SPI): Merits and Limitations. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, September 2020. http://dx.doi.org/10.7546/crabs.2020.09.18.
Full textLeis, Sherry, and Lloyd Morrison. Plant community trends at Tallgrass Prairie National Preserve: 1998–2018. National Park Service, October 2022. http://dx.doi.org/10.36967/2294512.
Full textLeis, Sherry. Vegetation community monitoring trends in restored tallgrass prairie at Wilson’s Creek National Battlefield: 2008–2020. National Park Service, April 2022. http://dx.doi.org/10.36967/nrr-2293117.
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