scholarly journals Assessment of Drought Event, its Trend and Teleconnected Factors Over Burundi, Central East Africa

2021 ◽  
Author(s):  
Athanase Nkunzimana ◽  
Bi Shuoben ◽  
Wang Guojie ◽  
Ahmed Alriah Mohamed Abdallah ◽  
Isaac Sarfo ◽  
...  
Keyword(s):  
Time Scales ◽  
Standardized Precipitation Index ◽  
Drought Event ◽  
Drought Assessment ◽  
The North ◽  
Increasing Trend ◽  
The Indian Ocean ◽  
Short Rains ◽  
The Standardized Precipitation Index ◽  
Very High

Abstract This study assessed the drought events across Burundi for 37 years ranging from 1981 to 2017. The drought assessment was conducted using the Standardized Precipitation Index (SPI) at 1, 3, 6 and 12-month time scales. The Mann Kendall and Modified Mann Kendall trend tests and Sen’s slope statistic tests were used to analyse the spatiotemporal drought trend. The overall analysis of SPI-3, SPI-6 and SPI-12 outputs revealed that the Northern part of Burundi was the most threatened by dry events, and more than 80% of the extremely and severely dry events occurred within the period 1993–2000. The drought magnitude varied highly in the short rains season (SOND) than during the long rains season (MAM) specifically during the 1990s decade. The cumulative frequency of extremely dry events was very high in the North with 5.2%, 6.1% and 7.4 % at 3, 6 and 12-month time scales respectively. Likewise, the northern part experienced both short, medium and long dry periods, thus 88 consecutive dry months within only 8 years. The North and East regions exhibited a positive increasing trend over annual and seasonal time scales at both 3, 6, and 12 months of SPI analysis while the mountainous region and the South experienced a significant decreasing trend. The first abrupt point issued by forward and backward sequential statistics occurred in 1990, the year corresponding to the beginning of the driest period. Dry years are associated with circulation anomalies over the Indian Ocean and La Nina events.

scholarly journals Dry and Wet Events in Andean Populations of Northern Peru: A Case Study of Chachapoyas, Peru

2021 ◽  
Vol 9 ◽  
Author(s):  
Jesús Rascón ◽  
Wildor Gosgot Angeles ◽  
Lenin Quiñones Huatangari ◽  
Manuel Oliva ◽  
Miguel Ángel Barrena Gurbillón
Keyword(s):  
Anthropogenic Activities ◽  
Standardized Precipitation Index ◽  
Population Increase ◽  
Severe Drought ◽  
Drought Event ◽  
Climatic Data ◽  
Economic Activities ◽  
The North ◽  
Moderate Drought ◽  
The Standardized Precipitation Index

Climate change and population growth have heavily impacted the ecosystem’s water resources, essential for anthropogenic activities. These also apply to the Andean city of Chachapoyas, located in the north of Peru, which has gone through a substantial population increase in recent years, therefore increasing its water demand. This research aimed to assess dry and wet events from 1981 to 2019 that have taken place in Chachapoyas, by applying the Standardized Precipitation Index (SPI), and the Standardized Precipitation Evapotranspiration Index (SPEI). These events were periodically characterized, and the index relationship was determined at different timescales. The SPI and SPEI indices were calculated at the city’s only weather station for timescales of 3, 6, 12, and 24 months using climatic data. The indices showed a remarkably consistent behavior for timescales of 12 and 24 months detecting an extreme drought event in 1993, while for timescales of 3 and 6 months a severe drought event was detected in the same year. Contrastingly, there has been an increase in extreme wet events in the last decade, hence Chachapoyas is categorized between "moderate drought" and “moderate wet”. It should be noted that the indices have a high correlation between them when calculated for the same timescale. The results were statistically significant (p < 0.05). Considering the results obtained related to dry and wet events and their relation with economic activities such as environmental management, we can conclude that the SPI and SPEI indices are useful and valuable tools for local and regional governments.

scholarly journals Drought Assessment using GRACE Terrestrial Water Storage Deficit in Mongolia from 2002 to 2017

Water ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 1301 ◽  
Author(s):  
Yu ◽  
Li ◽  
Cao ◽  
Schillerberg
Keyword(s):  
Standardized Precipitation Index ◽  
Water Storage ◽  
Drought Severity ◽  
Severe Drought ◽  
Drought Event ◽  
Terrestrial Water Storage ◽  
Water Shortages ◽  
Drought Assessment ◽  
Terrestrial Water ◽  
The Standardized Precipitation Index

Climate warming can result in increases in the frequency and magnitude of drought events, leading to water shortages and socioeconomic losses. Gravity Recovery and Climate Experiment (GRACE) satellite data have been used to monitor and estimate drought events. However, there is little information on detecting the characteristics of droughts in Mongolia due to sparse observations. In this study, we estimate the drought conditions in Mongolia using GRACE terrestrial water storage data during 2002–2017. Water storage deficit (WSD) is used to identify the drought event and calculate the water storage deficit index (WSDI). The WSDI was compared with the standardized precipitation index (SPI) and the standardized precipitation evapotranspiration index (SPEI). The results showed that there were two turning points of WSD in 2007 and 2012. Eight drought events were identified and the most severe drought occurred in 2007–2009 lasting for 38 months with a WSDI of −0.98 and a total WSD of −290.8 mm. Overall, the WSD and WSDI were effective in analyzing and assessing the drought severity in a region where hydrological observations are lacking.

scholarly journals Positive and Negative Phases of the Wintertime North Atlantic Oscillation and Drought Occurrence over Europe: A Multitemporal-Scale Approach

2008 ◽  
Vol 21 (6) ◽  
pp. 1220-1243 ◽  
Author(s):  
J. Ignacio López-Moreno ◽  
Sergio M. Vicente-Serrano
Keyword(s):  
Twentieth Century ◽  
North Atlantic Oscillation ◽  
Time Scales ◽  
North Atlantic ◽  
Standardized Precipitation Index ◽  
Opposite Pattern ◽  
The North ◽  
The Standardized Precipitation Index ◽  
Drought Occurrence ◽  
Different Time Scales

Abstract In this study, droughts are analyzed using the standardized precipitation index (SPI) at different time scales for all of Europe over the period 1901–2000. The SPI is calculated at different time scales (1–12 months), as are the average values that correspond to negative and positive phases of the North Atlantic Oscillation (NAO). The responses of droughts to the phases of the NAO vary spatially, but the response also depends on the month of the year and the time scale of the analysis. During the positive/negative phases, negative/positive SPI values are generally recorded in southern Europe, with the opposite pattern recorded in northern Europe. In certain regions, significant differences in the SPI are also recorded during spring, summer, and even autumn. In several regions, the magnitude of the average SPI anomalies is noticeably different for the positive and negative phases of the NAO, indicating the asymmetric response of droughts to the NAO. The unstable response of drought occurrence is also demonstrated, at different time scales, to positive and negative phases of the NAO throughout the twentieth century. During the second half of the twentieth century, there is a strengthening of the influence of the positive phases of the NAO on droughts. In contrast, the negative phases show a weaker influence on the SPI during the second half of the twentieth century. This pattern is related to changes in the wintertime sea level pressure fields associated with positive and negative phases of the NAO.

scholarly journals Hydrological response to different time scales of climatological drought: an evaluation of the Standardized Precipitation Index in a mountainous Mediterranean basin

2005 ◽  
Vol 9 (5) ◽  
pp. 523-533 ◽  
Author(s):  
S. M. Vicente-Serrano ◽  
J. I. López-Moreno
Keyword(s):  
Time Scales ◽  
Hydrological Cycle ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Drought Indices ◽  
Long Time ◽  
The Standardized Precipitation Index ◽  
Hydrological Droughts ◽  
Different Time Scales

Abstract. At present, the Standardized Precipitation Index (SPI) is the most widely used drought index to provide good estimations about the intensity, magnitude and spatial extent of droughts. The main advantage of the SPI in comparison with other indices is the fact that the SPI enables both determination of drought conditions at different time scales and monitoring of different drought types. It is widely accepted that SPI time scales affect different sub-systems in the hydrological cycle due to the fact that the response of the different water usable sources to precipitation shortages can be very different. The long time scales of SPI are related to hydrological droughts (river flows and reservoir storages). Nevertheless, few analyses empirically verify these statements or the usefulness of the SPI time scales to monitor drought. In this paper, the SPI at different time scales is compared with surface hydrological variables in a big closed basin located in the central Spanish Pyrenees. We provide evidence about the way in which the longer (>12 months) SPI time scales may not be useful for drought quantification in this area. In general, the surface flows respond to short SPI time scales whereas the reservoir storages respond to longer time scales (7–10 months). Nevertheless, important seasonal differences can be identified in the SPI-usable water sources relationships. This suggests that it is necessary to test the drought indices and time scales in relation to their usefulness for monitoring different drought types under different environmental conditions and water demand situations.

scholarly journals Using integrated meteorological and hydrological indices to assess drought characteristics in southern Taiwan

2019 ◽  
Vol 50 (3) ◽  
pp. 901-914 ◽  
Author(s):  
Hsin-Fu Yeh
Keyword(s):  
River Basin ◽  
Drought Index ◽  
Standardized Precipitation Index ◽  
Assessment Method ◽  
Drought Indices ◽  
Trend Test ◽  
Integrated Analysis ◽  
Drought Assessment ◽  
Southern Taiwan ◽  
The Standardized Precipitation Index

Abstract Numerous drought index assessment methods have been developed to investigate droughts. This study proposes a more comprehensive assessment method integrating two drought indices. The Standardized Precipitation Index (SPI) and the Streamflow Drought Index (SDI) are employed to establish an integrated drought assessment method to study the trends and characteristics of droughts in southern Taiwan. The overall SPI and SDI values and the spatial and temporal distributions of droughts within a given year (November to October) revealed consistent general trends. Major droughts occurred in the periods of 1979–1980, 1992–1993, 1994–1995, and 2001–2003. According to the results of the Mann–Kendall trend test and the Theil–Sen estimator analysis, the streamflow data from the Sandimen gauging station in the Ailiao River Basin showed a 30% decrease, suggesting increasing aridity between 1964 and 2003. Hence, in terms of water resources management, special attention should be given to the Ailiao River Basin. The integrated analysis showed different types of droughts occurring in different seasons, and the results are in good agreement with the climatic characteristics of southern Taiwan. This study suggests that droughts cannot be explained fully by the application of a single drought index. Integrated analysis using multiple indices is required.

scholarly journals Computation of the Standardized Precipitation Index (SPI) and Its Use to Assess Drought Occurrences in Cameroon over Recent Decades

2014 ◽  
Vol 53 (10) ◽  
pp. 2310-2324 ◽  
Author(s):  
Guy Merlin Guenang ◽  
F. Mkankam Kamga
Keyword(s):  
Time Scales ◽  
Goodness Of Fit ◽  
Standardized Precipitation Index ◽  
Research Unit ◽  
Distribution Functions ◽  
Precipitation Index ◽  
Severe Drought ◽  
East Anglia ◽  
The Standardized Precipitation Index ◽  
Short Time

AbstractThe standardized precipitation index (SPI) is computed and analyzed using 55 years of precipitation data recorded in 24 observation stations in Cameroon along with University of East Anglia Climate Research Unit (CRU) spatialized data. Four statistical distribution functions (gamma, exponential, Weibull, and lognormal) are first fitted to data accumulated for various time scales, and the appropriate functions are selected on the basis of the Anderson–Darling goodness-of-fit statistic. For short time scales (up to 6 months) and for stations above 10°N, the gamma distribution is the most frequent choice; below this belt, the Weibull distribution predominates. For longer than 6-month time scales, there are no consistent patterns of fitted distributions. After calculating the SPI in the usual way, operational drought thresholds that are based on an objective method are determined at each station. These thresholds are useful in drought-response decision making. From SPI time series, episodes of severe and extreme droughts are identified at many stations during the study period. Moderate/severe drought occurrences are intra-annual in short time scales and interannual for long time scales (greater than 9 months), usually spanning many years. The SPI calculated from CRU gridded precipitation shows similar results, with some discrepancies at longer scales. Thus, the spatialized dataset can be used to extend such studies to a larger region—especially data-scarce areas.

scholarly journals Meteorological Drought Analysis and Return Periods over North and West Africa and Linkage with El Niño–Southern Oscillation (ENSO)

2021 ◽  
Vol 13 (23) ◽  
pp. 4730
Author(s):  
Malak Henchiri ◽  
Tertsea Igbawua ◽  
Tehseen Javed ◽  
Yun Bai ◽  
Sha Zhang ◽  
...  
Keyword(s):  
West Africa ◽  
Large Scale ◽  
Southern Oscillation ◽  
Standardized Precipitation Index ◽  
Joint Probability ◽  
Meteorological Drought ◽  
Socioeconomic Impacts ◽  
The North ◽  
The Standardized Precipitation Index ◽  
The North Atlantic Oscillation

Droughts are one of the world’s most destructive natural disasters. In large regions of Africa, droughts can have strong environmental and socioeconomic impacts. Understanding the mechanism that drives drought and predicting its variability is important for enhancing early warning and disaster risk management. Taking North and West Africa as the study area, this study adopted multi-source data and various statistical analysis methods, such as the joint probability density function (JPDF), to study the meteorological drought and return years across a long term (1982–2018). The standardized precipitation index (SPI) was used to evaluate the large-scale spatiotemporal drought characteristics at 1–12-month timescales. The intensity, severity, and duration of drought in the study area were evaluated using SPI–12. At the same time, the JPDF was used to determine the return year and identify the intensity, duration, and severity of drought. The Mann-Kendall method was used to test the trend of SPI and annual precipitation at 1–12-month timescales. The pattern of drought occurrence and its correlation with climate factors were analyzed. The results showed that the drought magnitude (DM) of the study area was the highest in 2008–2010, 2000–2003, and 1984–1987, with the values of 5.361, 2.792, and 2.187, respectively, and the drought lasting for three years in each of the three periods. At the same time, the lowest DM was found in 1997–1998, 1993–1994, and 1991–1992, with DM values of 0.113, 0.658, and 0.727, respectively, with a duration of one year each time. It was confirmed that the probability of return to drought was higher when the duration of drought was shorter, with short droughts occurring more regularly, but not all severe droughts hit after longer time intervals. Beyond this, we discovered a direct connection between drought and the North Atlantic Oscillation Index (NAOI) over Morocco, Algeria, and the sub-Saharan countries, and some slight indications that drought is linked with the Southern Oscillation Index (SOI) over Guinea, Ghana, Sierra Leone, Mali, Cote d’Ivoire, Burkina Faso, Niger, and Nigeria.

scholarly journals Drought monitoring and prediction using SPI, SPEI, and random forest model in various climates of Iran

2021 ◽  
Author(s):  
Morteza Lotfirad ◽  
Hassan Esmaeili-Gisavandani ◽  
Arash Adib
Keyword(s):  
Random Forest ◽  
Correlation Coefficient ◽  
Potential Evapotranspiration ◽  
Standardized Precipitation Index ◽  
Monthly Precipitation ◽  
Model Combination ◽  
The North ◽  
Drought Prediction ◽  
Lag Times ◽  
The Standardized Precipitation Index

Abstract The aim of this study is to select the best model (combination of different lag times) for predicting the standardized precipitation index (SPI) and the standardized precipitation and evapotranspiration index (SPEI) in next time. Monthly precipitation and temperature data from 1960 to 2019 were used. In temperate climates, such as the north of Iran, the correlation coefficient of SPI and SPEI was 0.94, 0.95, and 0.81 at the time scales of 3, 12, and 48 months, respectively. Besides, this correlation coefficient was 0.47, 0.35, and 0.44 in arid and hot climates, such as the southwest of Iran because potential evapotranspiration (PET) depends on temperature more than rainfall. Drought was predicted using the random forest (RF) model and applying 1–12 months lag times for next time. By increasing of time scale, the prediction accuracy of SPI and SPEI will improve. The ability of SPEI is more than SPI for drought prediction, because the overall accuracy (OA) of prediction will increase, and the errors (i.e., overestimate (OE) and underestimate (UE)) will reduce. It is recommended for future studies (1) using wavelet analysis for improving accuracy of predictions and (2) using the Penman–Monteith method if ground-based data are available.

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