Spatial analysis of drought severity and magnitude using the standardized precipitation index and streamflow drought index over the Upper Indus Basin, Pakistan

2021 ◽  
Author(s):  
Sohail Abbas ◽  
Shazia Kousar
Keyword(s):  
Spatial Analysis ◽  
Drought Index ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Indus Basin ◽  
Drought Severity ◽  
Upper Indus Basin ◽  
Streamflow Drought Index ◽  
The Standardized Precipitation Index

scholarly journals Long-Term, Gridded Standardized Precipitation Index for Hawai‘i

Data ◽  
2020 ◽  
Vol 5 (4) ◽  
pp. 109
Author(s):  
Matthew P. Lucas ◽  
Clay Trauernicht ◽  
Abby G. Frazier ◽  
Tomoaki Miura
Keyword(s):  
High Spatial Resolution ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Drought Indices ◽  
Drought Severity ◽  
Spatially Explicit ◽  
Historical Period ◽  
The Standardized Precipitation Index ◽  
Climatic Information

Spatially explicit, wall-to-wall rainfall data provide foundational climatic information but alone are inadequate for characterizing meteorological, hydrological, agricultural, or ecological drought. The Standardized Precipitation Index (SPI) is one of the most widely used indicators of drought and defines localized conditions of both drought and excess rainfall based on period-specific (e.g., 1-month, 6-month, 12-month) accumulated precipitation relative to multi-year averages. A 93-year (1920–2012), high-resolution (250 m) gridded dataset of monthly rainfall available for the State of Hawai‘i was used to derive gridded, monthly SPI values for 1-, 3-, 6-, 9-, 12-, 24-, 36-, 48-, and 60-month intervals. Gridded SPI data were validated against independent, station-based calculations of SPI provided by the National Weather Service. The gridded SPI product was also compared with the U.S. Drought Monitor during the overlapping period. This SPI product provides several advantages over currently available drought indices for Hawai‘i in that it has statewide coverage over a long historical period at high spatial resolution to capture fine-scale climatic gradients and monitor changes in local drought severity.

scholarly journals ANALISIS KEKERINGAN DI KABUPATEN SRAGEN DENGAN METODE PALMER, THORNTHWAITE, DAN STANDARDIZED PRECIPITATION INDEX

2021 ◽  
Vol 17 (2) ◽  
pp. 111-124
Author(s):  
Safrudin Nor Aripbilah ◽  
Heri Suprapto
Keyword(s):  
Drought Index ◽  
Southern Oscillation ◽  
Standardized Precipitation Index ◽  
Severity Index ◽  
Precipitation Index ◽  
Suitable Method ◽  
Drought Severity ◽  
Severe Drought ◽  
Drought Hazard ◽  
Dry Conditions

El Nino and La Nina in Indonesia are one of the reasons that caused climate changes, which has possibility of drought and flood disasters. Sragen Regency wherethe dry season occurs, drought happened meanwhile other areas experience floods and landslides. A study on drought needs to be carried out so as to reduce the risk of losses due to the drought hazard. This study is to determine the drought index in Sragen Regency based on several methods and the correlation of each methods and its suitability to the Southern Oscillation Index (SOI) and rainfall. Drought was analyzed using several methods such as Palmer Drought Severity Index (PDSI), Thornthwaite-Matter, and Standardized Precipitation Index (SPI) then correlated with SOI to determine the most suitable method for SOI. The variables are applied in this method are rainfall, temperature, and evapotranspiration. The results showed that the drought potential of the Palmer method is only in Near Normal conditions, which is 1%, Severe drought conditions are 29% for the Thornthwaite-Matter method, and Extreme Dry conditions only reach 1,11% for the SPI method. The PDSI and SPI methods are inversely proportional to the Thornthwaite-Matter method and the most suitable method for SOI values or rainfall is the SPI method. These three methods can be identified the potential for drought with only a few variables so that they could be applied if they only have those data.Keywords: Drought, PDSI, Thornthwaite-Matter, SPI, SOI

scholarly journals Flash Drought Response to Precipitation and Atmospheric Evaporative Demand in Spain

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 165
Author(s):  
Iván Noguera ◽  
Fernando Domínguez-Castro ◽  
Sergio M. Vicente-Serrano
Keyword(s):  
Drought Index ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Rapid Decline ◽  
Spatial And Temporal Patterns ◽  
Evaporative Demand ◽  
Main Driver ◽  
The Standardized Precipitation Index ◽  
High Degree

Flash drought is the result of strong precipitation deficits and/or anomalous increases in atmospheric evaporative demand (AED), which triggers a rapid decline in soil moisture and stresses vegetation over short periods of time. However, little is known about the role of precipitation and AED in the development of flash droughts. For this paper, we compared the standardized precipitation index (SPI) based on precipitation, the evaporative demand drought index (EDDI) based on AED, and the standardized evaporation precipitation index (SPEI) based on the differences between precipitation and AED as flash drought indicators for mainland Spain and the Balearic Islands for 1961–2018. The results show large differences in the spatial and temporal patterns of flash droughts between indices. In general, there was a high degree of consistency between the flash drought patterns identified by the SPI and SPEI, with the exception of southern Spain in the summer. The EDDI showed notable spatial and temporal differences from the SPI in winter and summer, while it exhibited great coherence with the SPEI in summer. We also examined the sensitivity of the SPEI to AED in each month of the year to explain its contribution to the possible development of flash droughts. Our findings showed that precipitation is the main driver of flash droughts in Spain, although AED can play a key role in the development of these during periods of low precipitation, especially in the driest areas and in summer.

scholarly journals A Hybrid Precipitation Index Inspired by the SPI, PDSI, and MCDI. Part I: Development of the Index

2020 ◽  
Vol 21 (9) ◽  
pp. 1945-1976 ◽  
Author(s):  
Dudley B. Chelton ◽  
Craig M. Risien
Keyword(s):  
Time Scale ◽  
Standardized Precipitation Index ◽  
Severity Index ◽  
Precipitation Index ◽  
Drought Severity ◽  
Fading Memory ◽  
Hybrid Index ◽  
Weighted Averages ◽  
The Standardized Precipitation Index ◽  
Exponentially Weighted

AbstractThe filtering properties of the standardized precipitation index (SPI), the Palmer drought severity index (PDSI), and the model calibrated drought index (MCDI) are investigated to determine their relations to past, present, and future precipitation anomalies in regions with a wide diversity of precipitation characteristics. All three indices can be closely approximated by weighted averages of precipitation, but with different weighting. The SPI is well represented by one-sided, uniformly weighted averages; the MCDI is well represented by one-sided, exponentially weighted averages; and the PDSI is well represented by two-sided, exponentially weighted averages with much higher weighting of past and present precipitation than future precipitation. Detailed analyses identify interpretational complications and other undesirable features in the SPI and PDSI. In addition, the PDSI and MCDI are each restricted to single regionally specific “intrinsic” time scales that can significantly differ between the two indices. Inspired by the strengths of the SPI, PDSI, and MCDI, a hybrid index is developed that consists of exponentially weighted averages of past and present precipitation that are implicit in the PDSI and MCDI. The explicit specification of the exponential weighting allows users to control the time scale of the hybrid index to investigate precipitation variability on any time scale of interest. This advantage over the PDSI and MCDI is analogous to the controllability of the time scale of the SPI, but the exponentially fading memory is more physical than the uniform weighting of past and present precipitation in the SPI.

scholarly journals Inadequacy of the gamma distribution to calculate the Standardized Precipitation Index

2015 ◽  
Vol 19 (12) ◽  
pp. 1129-1135 ◽  
Author(s):  
Gabriel C. Blain ◽  
Monica C. Meschiatti
Keyword(s):  
Normal Distribution ◽  
Gamma Distribution ◽  
Goodness Of Fit ◽  
Drought Index ◽  
Standardized Precipitation Index ◽  
Early Warning Systems ◽  
Precipitation Index ◽  
Calculation Algorithm ◽  
The Standardized Precipitation Index ◽  
Generalized Normal Distribution

ABSTRACT The Standardized Precipitation Index was developed as a probability-based index able to monitor rainfall deficit in a standardized or normalized way. Thus, the performance of this drought index is affected by the use of a distribution that does not provide an appropriate fit for the rainfall data. The goal of this study was to evaluate the adjustment of the gamma distribution for the rainfall amounts summed over several time scales (Pelotas, Rio Grande do Sul, Brazil), to assess the goodness-of-fit of alternative distributions to these rainfall series and to evaluate the normality assumption of the Standardized Precipitation Index series calculated from several distributions. Based on the Lilliefors test and on a normality test, it is verified that the gamma distribution is not suitable for calculating this Index in several timescales. The generalized normal distribution presented the best performance among all analysed distributions. It was also concluded that the drought early warning systems and the academic studies should re-evaluate the use of the gamma distribution in the Standardized Precipitation Index calculation algorithm. A computational code that allows calculating this drought index based on the generalized normal distribution has also been provided.

scholarly journals Identification of dry and wet 6 months’ period in eastern Slovakia using indices

2020 ◽  
Vol 310 ◽  
pp. 00047
Author(s):  
Patrik Nagy ◽  
Martina Zeleňáková ◽  
Slávka Galas ◽  
Helena Hlavatá ◽  
Dorota Simonová
Keyword(s):  
Water Resources ◽  
Drought Index ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Reconnaissance Drought Index ◽  
Time Period ◽  
Streamflow Drought Index

In the paper we evaluated dry and wet 6 months’ periods, which reflect changes in water resources of the country. We assessed Standardized Precipitation Index (SPI), Standardized Evapotranspiration Index (SPEI), Streamflow Drought Index (SDI), Reconnaissance Drought Index (RDI). The time period was 1960 - 2015 and the study area includes eastern Slovakia – selected water and climatic stations. The results indicate dry periods and wet periods. The results of work are presented in the table for separate evaluated indices.

A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index

2010 ◽  
Vol 23 (7) ◽  
pp. 1696-1718 ◽  
Author(s):  
Sergio M. Vicente-Serrano ◽  
Santiago Beguería ◽  
Juan I. López-Moreno
Keyword(s):  
Global Warming ◽  
Water Balance ◽  
Drought Index ◽  
Standardized Precipitation Index ◽  
Severity Index ◽  
Drought Severity ◽  
Standardized Precipitation Evapotranspiration Index ◽  
Drought Assessment ◽  
The Standardized Precipitation Index

Abstract The authors propose a new climatic drought index: the standardized precipitation evapotranspiration index (SPEI). The SPEI is based on precipitation and temperature data, and it has the advantage of combining multiscalar character with the capacity to include the effects of temperature variability on drought assessment. The procedure to calculate the index is detailed and involves a climatic water balance, the accumulation of deficit/surplus at different time scales, and adjustment to a log-logistic probability distribution. Mathematically, the SPEI is similar to the standardized precipitation index (SPI), but it includes the role of temperature. Because the SPEI is based on a water balance, it can be compared to the self-calibrated Palmer drought severity index (sc-PDSI). Time series of the three indices were compared for a set of observatories with different climate characteristics, located in different parts of the world. Under global warming conditions, only the sc-PDSI and SPEI identified an increase in drought severity associated with higher water demand as a result of evapotranspiration. Relative to the sc-PDSI, the SPEI has the advantage of being multiscalar, which is crucial for drought analysis and monitoring.

scholarly journals The Assessment of Climate Change Impact on Meteorological Draught Susceptability on Sampean Watershed

2021 ◽  
Vol 9 (4) ◽  
pp. 146
Author(s):  
Masita Ratih ◽  
Gusfan Halik ◽  
Retno Utami Agung Wiyono
Keyword(s):  
Climate Change ◽  
Atmospheric Circulation ◽  
Drought Index ◽  
Standardized Precipitation Index ◽  
Assessment Method ◽  
Precipitation Index ◽  
Climate Change Scenarios ◽  
Change Impact ◽  
The Standardized Precipitation Index ◽  
The Impact

Drought disasters that occur in the Sampean watershed from time to time have increased, both the intensity of events and the area affected by drought. The general objective of this research is to develop an assessment method for the impact of climate chan ge on vulnerability to drought disasters based on atmospheric circulation data. The specific objectives of this study are to model rainfall predictions based on atmospheric circulation data, predict rainfall in various climate change scenarios (Intergovernm ental Panel on Climate Change, IPCC – AR5), and assess vulnerability to drought disasters using a meteorological approach. The Standardized Precipitation Index (SPI) is one way to analyze the drought index in an area which was developed previous researcher. The Standardized Precipitation Index (SPI) is designed to quantitatively determine the rainfall deficit with various time scales. The advantage of the Standardized Precipitation Index (SPI) is that it is enough to use monthly rainfall data to compare drou ght levels between regions even with different climate types. To facilitate the presentation of the data base on the identification of d rought susceptibility, we need a system that can assist in building, storing, managing and displaying geographically ref erenced information in the form of spatial mapping. This research facilitates monitoring of the area of drought-prone areas, predicts drought levels, prevents future drought disasters, and prepares plans for rebuilding drought-prone areas in the Sampean watershed.

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