scholarly journals Evaluation of the similarity between drought indices by correlation analysis and Cohen's Kappa test in a Mediterranean area

2021 ◽  
Author(s):  
L. Vergni ◽  
F. Todisco ◽  
B. Di Lena

AbstractIn the literature, numerous papers report comparative analyses of drought indices. In these types of studies, the similarity between drought indices is usually evaluated using the Pearson correlation coefficient, r, calculated between corresponding severity time series. However, it is well known that the correlation does not describe the strength of agreement between two variables. Two drought indices can exhibit a high degree of correlation but can, at the same time, disagree substantially, for example, if one index is consistently higher than the other. From an operational point of view, two indices can be considered in agreement when they indicate the same severity category for a given period (e.g. moderate drought). In this work, we compared six meteorological drought indices based on both correlation analysis and Cohen's Kappa test. This test is typically used in medical or social sciences to obtain a quantitative assessment of the degree of agreement between different methods or analysts. The indices considered are five timescale-dependent indices, i.e. the Percent of Normal Index, the Deciles Index, the Percentile Index, the Rainfall Anomaly Index, and the Standardised Precipitation Index, computed at the 1-, 3-, and 6-month timescales, and the Effective Drought Index, a relatively new index, which has a self-defined timescale. The indices were calculated for 15 stations in the Abruzzo region (central Italy) during 1951–2018. We found that the strength of agreement depends on both the criteria of drought severity classification and the different indices' calculation method. The Cohen's Kappa test indicates a prevailing moderate or fair agreement among the indices considered, despite the generally very high correlation between the corresponding severity times series. The results demonstrate that the Cohen's Kappa test is more effective than the correlation analysis in discriminating the actual strength of agreement/disagreement between drought indices.

2016 ◽  
Vol 31 (1) ◽  
pp. 33-41 ◽  
Author(s):  
Fayçal Djellouli ◽  
Abderrazak Bouanani ◽  
Kamila Baba-Hamed

AbstractDrought is an insidious hazard of nature in many parts of the world. It originates from persistent shortage of precipitation over a specific region for a specific period of time and has a conceptual and operational definition. Drought impact on some activity, group, or environmental sector depends on the extent of water shortage and ground conditions. Algeria and especially the western region has experienced several periods of drought over the last century, since 1975 to the present day. The most recent drought in 1981, 1989, 1990, 1992, 1994 and 1999 was characterized by its intensity and spatial extent. Drought is identified using various drought indices (meteorological, hydrological and agricultural). In this research, we focus on the meteorological drought, to assess the reliability of these indices under changing climatic conditions. Data was recorded for the period of 1980–2009 at wadi Louza catchment (NW-Algeria). For describing and monitoring drought severity periods, we calculated the correlation between both meteorological drought indices: Standardised Precipitation Index (SPI) and Effective Drought Index (EDI). The results show that the watershed of wadi Louza has experienced a severe meteorological drought. The correlation between meteorological drought indices was good for all time steps and the best was found for 9-month time step. The obtained results may provide some scientific support for fighting against droughts.


Water ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 82
Author(s):  
Omolola M. Adisa ◽  
Muthoni Masinde ◽  
Joel O. Botai

This study examines the (dis)similarity of two commonly used indices Standardized Precipitation Index (SPI) computed over accumulation periods 1-month, 3-month, 6-month, and 12-month (hereafter SPI-1, SPI-3, SPI-6, and SPI-12, respectively) and Effective Drought Index (EDI). The analysis is based on two drought monitoring indicators (derived from SPI and EDI), namely, the Drought Duration (DD) and Drought Severity (DS) across the 93 South African Weather Service’s delineated rainfall districts over South Africa from 1980 to 2019. In the study, the Pearson correlation coefficient dissimilarity and periodogram dissimilarity estimates were used. The results indicate a positive correlation for the Pearson correlation coefficient dissimilarity and a positive value for periodogram of dissimilarity in both the DD and DS. With the Pearson correlation coefficient dissimilarity, the study demonstrates that the values of the SPI-1/EDI pair and the SPI-3/EDI pair exhibit the highest similar values for DD, while the SPI-6/EDI pair shows the highest similar values for DS. Moreover, dissimilarities are more obvious in SPI-12/EDI pair for DD and DS. When a periodogram of dissimilarity is used, the values of the SPI-1/EDI pair and SPI-6/EDI pair exhibit the highest similar values for DD, while SPI-1/EDI displayed the highest similar values for DS. Overall, the two measures show that the highest similarity is obtained in the SPI-1/EDI pair for DS. The results obtainable in this study contribute towards an in-depth knowledge of deviation between the EDI and SPI values for South Africa, depicting that these two drought indices values are replaceable in some rainfall districts of South Africa for drought monitoring and prediction, and this is a step towards the selection of the appropriate drought indices.


Author(s):  
A. T. Lennard ◽  
N. Macdonald ◽  
J. Hooke

Abstract. Droughts are a reoccurring feature of the UK climate; recent drought events (2004–2006 and 2010–2012) have highlighted the UK’s continued vulnerability to this hazard. There is a need for further understanding of extreme events, particularly from a water resource perspective. A number of drought indices are available, which can help to improve our understanding of drought characteristics such as frequency, severity and duration. However, at present little of this is applied to water resource management in the water supply sector. Improved understanding of drought characteristics using indices can inform water resource management plans and enhance future drought resilience. This study applies the standardised precipitation index (SPI) to a series of rainfall records (1962–2012) across the water supply region of a single utility provider. Key droughts within this period are analysed to develop an understanding of the meteorological characteristics that lead to, exist during and terminate drought events. The results of this analysis highlight how drought severity and duration can vary across a small-scale water supply region, indicating that the spatial coherence of drought events cannot be assumed.


2020 ◽  
Vol 21 (7) ◽  
pp. 1513-1530 ◽  
Author(s):  
Lingcheng Li ◽  
Dunxian She ◽  
Hui Zheng ◽  
Peirong Lin ◽  
Zong-Liang Yang

AbstractThis study elucidates drought characteristics in China during 1980–2015 using two commonly used meteorological drought indices: standardized precipitation index (SPI) and standardized precipitation–evapotranspiration index (SPEI). The results show that SPEI characterizes an overall increase in drought severity, area, and frequency during 1998–2015 compared with those during 1980–97, mainly due to the increasing potential evapotranspiration. By contrast, SPI does not reveal this phenomenon since precipitation does not exhibit a significant change overall. We further identify individual drought events using the three-dimensional (i.e., longitude, latitude, and time) clustering algorithm and apply the severity–area–duration (SAD) method to examine the drought spatiotemporal dynamics. Compared to SPI, SPEI identifies a lower drought frequency but with larger total drought areas overall. Additionally, SPEI identifies a greater number of severe drought events but a smaller number of slight drought events than the SPI. Approximately 30% of SPI-detected drought grids are not identified as drought by SPEI, and 40% of SPEI-detected drought grids are not recognized as drought by SPI. Both indices can roughly capture the major drought events, but SPEI-detected drought events are overall more severe than SPI. From the SAD analysis, SPI tends to identify drought as more severe over small areas within 1 million km2 and short durations less than 2 months, whereas SPEI tends to delineate drought as more severe across expansive areas larger than 3 million km2 and periods longer than 3 months. Given the fact that potential evapotranspiration increases in a warming climate, this study suggests SPEI may be more suitable than SPI in monitoring droughts under climate change.


2015 ◽  
Vol 16 (3) ◽  
pp. 1397-1408 ◽  
Author(s):  
Hongshuo Wang ◽  
Jeffrey C. Rogers ◽  
Darla K. Munroe

Abstract Soil moisture shortages adversely affecting agriculture are significantly associated with meteorological drought. Because of limited soil moisture observations with which to monitor agricultural drought, characterizing soil moisture using drought indices is of great significance. The relationship between commonly used drought indices and soil moisture is examined here using Chinese surface weather data and calculated station-based drought indices. Outside of northeastern China, surface soil moisture is more affected by drought indices having shorter time scales while deep-layer soil moisture is more related on longer index time scales. Multiscalar drought indices work better than drought indices from two-layer bucket models. The standardized precipitation evapotranspiration index (SPEI) works similarly or better than the standardized precipitation index (SPI) in characterizing soil moisture at different soil layers. In most stations in China, the Z index has a higher correlation with soil moisture at 0–5 cm than the Palmer drought severity index (PDSI), which in turn has a higher correlation with soil moisture at 90–100-cm depth than the Z index. Soil bulk density and soil organic carbon density are the two main soil properties affecting the spatial variations of the soil moisture–drought indices relationship. The study may facilitate agriculture drought monitoring with commonly used drought indices calculated from weather station data.


2016 ◽  
Vol 2 (2) ◽  
pp. 56
Author(s):  
Paisal Paisal ◽  
Mukhlis Zuardi ◽  
Reni Herman

<p style="text-align: justify;">The incidence of dengue disease in the world is estimated at 390 million cases per year. In Indonesia, during 2013 there were 35-40 cases per 100.000 population, with a mortality rate of 0.73%. This study aimed to determine the suitability and the percentage of RT-PCR, RDT NS1, and RDT IgM detection examination. Samples were obtained from hospitals in Aceh province during 2012. The research samples reached 100 collected samples, it was only 82 samples that fulfill the analysis criteria. Cohen’s Kappa test result showed there was moderate suitability between RT-PCR and RDT NS1 (K=0,404, p = 0,000), and weak suitability between RT-PCR began RDT IgM (K=0,139, p = 0,046). While the percentage of detection for RT-PCR, RDT NS1, dan RDT IgM were 16%, 10%, and 60%. RDT IgM is the best alternative for laboratory examination in the hospital.


Precipitation over the Upper Blue Nile Basin in Ethiopia contributes with 85% of the Nile river which provides 93% of Egypt’s conventional water resources. This study aims at assessing the meteorological drought in different locations in the Upper Blue Nile Basin and their relationship with the hydrological drought of Nile river in Egypt. The metrological drought was calculated by the Standard Precipitation Index (SPI) at five stations inside and close to the Upper Blue Nile Basin in Ethiopia, whereas the hydrological drought was calculated by the Streamflow Drought Index (SDI) at Dongola station at Nasser lake entrance. Both indices were calculated using the Drought Indices Calculator (DrinC) software. The selected study period was from 1973 to 2017 based on the availability of recorded data for meteorological stations in Ethiopia, and the streamflow for Dongola station. The data was categorized for each station by considering time periods of 1, 3, 6, 9, and 12 months based on their homogeneity. The correlation between SPI and SDI was evaluated using the Pearson correlation coefficient. The results showed a correlation between SPI for the five stations in the Upper Blue Nile Basin and SDI for Dongola station, where Gore station represented the highest frequency of significance at different time scales especially at the 3-months’ scale. The results confirm the relationship between SPI at Gore Station and SDI at Dongola Station, which means that the hydrological drought in Egypt is highly affected by the meteorological drought in the area surrounding Gore station. The paper recommends improving techniques for monitoring and overseeing drought hazards and assessing more meteorological stations to accurately predict climate change variations in Upper Blue Nile Basin and its effect on Egypt’s water resources.


Author(s):  
L. Sathya ◽  
R. Lalitha

Droughts are regional phenomena, which are considered as one of the major natural environmental hazards and severely affect the water resources. Climate variability may result in harmful drought periods in semiarid regions. Meteorological drought indices are considered as important tools for drought monitoring, they are embedded with different theoretical and experimental structures. This study compares the performance of three indices of Standardized Precipitation Index (SPI), Rainfall Anomaly Index (RAI) End Palmer Drought Severity Index (PNPI) to predict long-term drought events using the Thomas-Feiring Model and historical data. For studies of areal drought extent, the 61 years (1951-2011) historical rainfall data of Trichy District were utilized to generate 58 years (2012-2070) synthetic data series so that the characteristics of long-term drought might be determined and the performance of those three indices might be analyzed and compared. The results show that SPI and PNPI perform similarly with regard to drought identification and detailed analysis to determine the characteristics of long-term drought. Finally, the RAI indicated significant deviations from normalized natural processes.


2017 ◽  
Vol 5 (5) ◽  
pp. 592-594
Author(s):  
Lyudmila Akhmaltdinova ◽  
Alyona Lavrinenko ◽  
Ilya Belyayev

Antibacterial drugs are the most consumed group of drugs in the modern hospitals. Standard methods of antibiotic sensitivity are labour and time-consuming, taking up to 24 hours after the pure culture is isolated (the analysis typically lasts up to 72 hours). Working out express diagnostic methods is of importance, and studies are made in various directions. Flow cytometry in detecting resistant E.coli strains was used. Flow cytometry fluorescent dyes were used to stain viable and dead cells. For method validation, relative accuracy, relative susceptibility, relative specificity and Cohen’s kappa test were determined compared to the delusion test. Cytometry method showed acceptable results on the model of E.coli. Relative accuracy comprised 88.8%, sensitivity - 85.7%, specificity was 88.8%, Cohen’s kappa test showed value 0.524, which is a medium agreement between the measurements by different methods.


2013 ◽  
Vol 17 (6) ◽  
pp. 2339-2358 ◽  
Author(s):  
I. H. Taylor ◽  
E. Burke ◽  
L. McColl ◽  
P. D. Falloon ◽  
G. R. Harris ◽  
...  

Abstract. Drought is a cumulative event, often difficult to define and involving wide-reaching consequences for agriculture, ecosystems, water availability, and society. Understanding how the occurrence of drought may change in the future and which sources of uncertainty are dominant can inform appropriate decisions to guide drought impacts assessments. Our study considers both climate model uncertainty associated with future climate projections, and future emissions of greenhouse gases (future scenario uncertainty). Four drought indices (the Standardised Precipitation Index (SPI), Soil Moisture Anomaly (SMA), the Palmer Drought Severity Index (PDSI) and the Standardised Runoff Index (SRI)) are calculated for the A1B and RCP2.6 future emissions scenarios using monthly model output from a 57-member perturbed parameter ensemble of climate simulations of the HadCM3C Earth System model, for the baseline period 1961–1990, and the period 2070–2099 ("the 2080s"). We consider where there are statistically significant increases or decreases in the proportion of time spent in drought in the 2080s compared to the baseline. Despite the large range of uncertainty in drought projections for many regions, projections for some regions have a clear signal, with uncertainty associated with the magnitude of change rather than direction. For instance, a significant increase in time spent in drought is generally projected for the Amazon, Central America and South Africa whilst projections for northern India consistently show significant decreases in time spent in drought. Whilst the patterns of changes in future drought were similar between scenarios, climate mitigation, represented by the RCP2.6 scenario, tended to reduce future changes in drought. In general, climate mitigation reduced the area over which there was a significant increase in drought but had little impact on the area over which there was a significant decrease in time spent in drought.


Sign in / Sign up

Export Citation Format

Share Document