scholarly journals Assessment of the Dissimilarities of EDI and SPI Measures for Drought Determination in South Africa

Water ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 82
Author(s):  
Omolola M. Adisa ◽  
Muthoni Masinde ◽  
Joel O. Botai
Keyword(s):  
South Africa ◽  
South African ◽  
Correlation Coefficient ◽  
Pearson Correlation ◽  
Standardized Precipitation Index ◽  
Drought Monitoring ◽  
Drought Indices ◽  
Drought Severity ◽  
Pearson Correlation Coefficient ◽  
Drought Duration

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.

A novel index for ecological drought monitoring based on ecological water deficit: a case study of Northwestern China

2021 ◽  
Author(s):  
Tianliang Jiang ◽  
Xiaoling Su
Keyword(s):  
Water Deficit ◽  
Time Scales ◽  
Drought Index ◽  
Vegetation Index ◽  
Standardized Precipitation Index ◽  
Northwestern China ◽  
Drought Monitoring ◽  
Drought Indices ◽  
Drought Severity ◽  
Different Time Scales

<p>Although the concept of ecological drought was first defined by the Science for Nature and People Partnership (SNAPP) in 2016, there remains no widely accepted drought index for monitoring ecological drought. Therefore, this study constructed a new ecological drought monitoring index, the standardized ecological water deficit index (SEWDI). The SEWDI is based on the difference between ecological water requirements and consumption, referred to as the standardized precipitation index (SPI) method, which was used to monitor ecological drought in Northwestern China (NWRC). The performances of the SEWDI and four widely-used drought indices [standardized root soil moisture index (SSI), self-calibrated Palmer drought index (scPDSI), standardized precipitation-evaporation drought index (SPEI), and SPI) in monitoring ecological drought were evaluated through comparing the Pearson correlations between these indices and the standardized normalized difference vegetation index (SNDVI) under different time scales, wetness, and water use efficiencies (WUEs) of vegetation. Finally, the rotational empirical orthogonal function (REOF) was used to decompose the SEWDI at a 12-month scale in the NWRC during 1982–2015 to obtain five ecological drought regions. The characteristics of ecological drought in the NWRC, including intensity, duration, and frequency, were extracted using run theory. The results showed that the performance of the SEWDI in monitoring ecological drought was highest among the commonly-used drought indices evaluated under different time scales [average correlation coefficient values (r) between SNDVI and drought indices: SEWDI<sub></sub>= 0.34, SSI<sub></sub>= 0.24, scPDSI<sub></sub>= 0.23, SPI<sub></sub>= 0.20, SPEI<sub></sub>= 0.18), and the 12-month-scale SEWDI was largely unaffected by wetness and WUE. In addition, the results of the monitoring indicated that serious ecological droughts in the NWRC mainly occurred in 1982–1986, 1990–1996, and 2005–2010, primarily in regions I, II, and V, regions II, and IV, and in region III, IV, and V, respectively. This study provides a robust approach for quantifying ecological drought severity across natural vegetation areas and scientific evidence for governmental decision makers.</p>

scholarly journals Drought Monitoring Using Rainfall, Evapotranspiration and Streamflow Data: A Case Study of Kaduna River Catchment Area (Nigeria)

2020 ◽  
pp. 133-144
Author(s):  
A. Dare ◽  
E. J. Zakka ◽  
Maikano Samson ◽  
A. O. Afolabi ◽  
S. O. Okechalu ◽  
...  
Keyword(s):  
Catchment Area ◽  
Drought Index ◽  
Meteorological Data ◽  
Standardized Precipitation Index ◽  
Hydrological Drought ◽  
Crop Damage ◽  
Drought Monitoring ◽  
Drought Indices ◽  
Drought Severity ◽  
Drought Conditions

Drought is defined as the lack of adequate precipitation, either rain or snow that causes reduced soil moisture or groundwater, diminished streamflow, crop damage and a general water shortage. The objective of this study focuses on meteorological and hydrological drought monitoring in river Kaduna catchment area. Standardized Precipitation Index (SPI) and Reconnaissance Drought Index (RDI) drought indices were used to characterize meteorological drought while Streamflow Drought Index (SDI) was used for hydrological drought monitoring for a period of 34 years (1967 – 2001). DrinC software, a drought indices calculator, was used for the calculation of SPI, RDI, and SDI respectively. The drought severity classification based on meteorological and hydrological drought indices gave 33% and 37% drought conditions period with the year 1967 – 2001. Based on these indexes, the drought characteristics of the catchment area were investigated by analyzing meteorological data from 1967 to 2001. The results of this analysis show that more non-drought/normal conditions were predominant than drought conditions. During the period under study (34 years), only one-year return period of extreme drought condition.

Drought monitoring incorporating precipitation and climate variables and its application for future drought projection

2020 ◽  
Author(s):  
Jeongeun Won ◽  
Sangdan Kim
Keyword(s):  
Drought Index ◽  
Potential Evapotranspiration ◽  
Standardized Precipitation Index ◽  
Management Program ◽  
Drought Monitoring ◽  
Drought Indices ◽  
Drought Severity ◽  
Climate Variables ◽  
Evaporative Demand ◽  
Monitoring Method

<p>In drought monitoring, it is very important to select climate variables to interpret drought. Most drought monitoring interprets drought as deficit in precipitation, so drought indices focused on the moisture supply side of the atmosphere have been mainly used. However, droughts can be caused not only by lack of rainfall, but also by various climate variables such as increase in temperature. In this regard, interest in potential evapotranspiration(PET), which is an moisture demand side of the atmosphere, is increasing and a PET-based drought index has been developed. However, complex droughts caused by various climate variables cannot be interpreted as a drought index that only considers precipitation or PET. In this study, we suggest a drought monitoring method that can reflect various future climate variables, including precipitation. In other words, copula-based joint drought index(CJDI), which incorporate standardized precipitation index(SPI) based on precipitation and evaporative demand drought index(EDDI) based on PET, is developed. CJDI, which considers both precipitation and PET, which are key variables related to drought, is able to properly monitor the drought events in Korea. In addition, future Drought severity – duration - frequency curves are derived to project future droughts compared to various drought indices. It is shown that CJDI can be used as a more reasonable drought index to establish the adaptation policy for future droughts by presenting the pattern of future droughts more realistically.</p><p><strong>Acknowledgment: </strong>This study was funded by the Korea Ministry of Environment (MOE) as Smart Urban Water Resources Management Program. (2019002950004)</p><p><strong>Keywords</strong>: Climate change; Copula; Drought; CJDI; Drought severity-duration-frequency curve</p>

scholarly journals The use of remote sensing to derive maize sowing dates for large-scale crop yield simulations

2020 ◽  
Author(s):  
Ehsan Eyshi Rezaei ◽  
Gohar Ghazaryan ◽  
Javier González ◽  
Natalie Cornish ◽  
Olena Dubovyk ◽  
...  
Keyword(s):  
South Africa ◽  
Remote Sensing ◽  
Correlation Coefficient ◽  
Large Scale ◽  
Pearson Correlation ◽  
Sowing Date ◽  
Spatiotemporal Variability ◽  
Pearson Correlation Coefficient ◽  
Crop Models ◽  
Sowing Dates

AbstractOne of the major sources of uncertainty in large-scale crop modeling is the lack of information capturing the spatiotemporal variability of crop sowing dates. Remote sensing can contribute to reducing such uncertainties by providing essential spatial and temporal information to crop models and improving the accuracy of yield predictions. However, little is known about the impacts of the differences in crop sowing dates estimated by using remote sensing (RS) and other established methods, the uncertainties introduced by the thresholds used in these methods, and the sensitivity of simulated crop yields to these uncertainties in crop sowing dates. In the present study, we performed a systematic sensitivity analysis using various scenarios. The LINTUL-5 crop model implemented in the SIMPLACE modeling platform was applied during the period 2001–2016 to simulate maize yields across four provinces in South Africa using previously defined scenarios of sowing dates. As expected, the selected methodology and the selected threshold considerably influenced the estimated sowing dates (up to 51 days) and resulted in differences in the long-term mean maize yield reaching up to 1.7 t ha−1 (48% of the mean yield) at the province level. Using RS-derived sowing date estimations resulted in a better representation of the yield variability in space and time since the use of RS information not only relies on precipitation but also captures the impacts of socioeconomic factors on the sowing decision, particularly for smallholder farmers. The model was not able to reproduce the observed yield anomalies in Free State (Pearson correlation coefficient: 0.16 to 0.23) and Mpumalanga (Pearson correlation coefficient: 0.11 to 0.18) in South Africa when using fixed and precipitation rule-based sowing date estimations. Further research with high-resolution climate and soil data and ground-based observations is required to better understand the sources of the uncertainties in RS information and to test whether the results presented herein can be generalized among crop models with different levels of complexity and across distinct field crops.

scholarly journals High-spatial resolution probability maps of drought duration and magnitude across Spain

2018 ◽  
Author(s):  
Fernando Domínguez-Castro ◽  
Sergio M. Vicente-Serrano ◽  
Miquel Tomás-Burguera ◽  
Marina Peña-Gallardo ◽  
Santiago Beguería ◽  
...  
Keyword(s):  
Standardized Precipitation Index ◽  
Generalized Pareto Distribution ◽  
Value Theory ◽  
Mitigation Measures ◽  
Drought Indices ◽  
Drought Severity ◽  
Drought Event ◽  
Drought Duration ◽  
Drought Assessment ◽  
Peak Over Threshold

Abstract. We mapped – for the first time – the probability of occurrence of drought over Spain, with the overriding aim of improving current drought assessment, management and mitigation measures and strategies across the region. We employed two well-established drought indices: the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). Drought characteristics (i.e. duration and severity) were characterised at 1-, 3-, 6- and 12-month, implying that drought event is attained only when the index values are lower than zero. We applied the extreme value theory to map drought hazard probability. Following this procedure, we tested different thresholds to generate the peak-over-threshold drought severity and magnitude series, besides evaluating different three-parametric distributions and thresholds to fit these series. Our results demonstrate that the Generalized Pareto distribution performs well in estimating the frequencies of drought magnitude and duration, with good agreement between the observed and modelled data when using upper percentiles to generate the peak-over-threshold series. Spatially, our estimations suggest a higher probability of extreme drought events in southern and central areas of Spain, compared to northern and eastern regions. Nevertheless, there are strong differences in drought probability estimations between drought indices (i.e. SPI and SPEI), as well as among drought timescales.

scholarly journals Indices-Based Evaluation of Spatiotemporal Distribution of Drought Within Derbendkhan Dam Watershed

2021 ◽  
Vol 39 (6) ◽  
pp. 893-914
Author(s):  
Mahmoud S. Al- Khafaji ◽  
Rusul A.H. Al- Ameri
Keyword(s):  
Drought Index ◽  
Standardized Precipitation Index ◽  
Temporal Variations ◽  
Weather Data ◽  
Drought Indices ◽  
Drought Severity ◽  
Environmental Damage ◽  
Eastern Region ◽  
Strong Impact ◽  
Drought Duration

Drought is one of the most significant natural disasters in Iraq. It has a strong impact on the water resources in Iraq. Consequently, it causes massive environmental damage, economic deficiency, and social problems to the country. Therefore, more considerations towards the study and management of drought has become of vital importance in recent decades. In this paper, three drought indices (DIs) were computed for evaluation of the spatiotemporal of drought within Derbendikhan Dam Watershed (DDW) in the Diyala River Basin, Iraq. Based on the monthly weather data for the period (1984 – 2013) downloaded from the Climate Forecast System Reanalysis (CFSR) for eight stations located within DDW. The Reconnaissance Drought Index (RDI), standardized precipitation index (SPI) and Streamflow Drought Index (SDI) at 12-month time scale were computed to assess droughts in the DDW. For each index, the temporal variations of the drought severity and Drought Frequency Patterns (DFPs) for the period (1984 – 2013) were computed and analyzed. In addition, spatial distributions of the drought severity for each index were mapped and investigated. Accordingly, the DFPs were compared to specify the dominant and/or more frequent DFPs. The results show that the performances of different DIs are strongly correlated with the dominant factors of droughts and drought duration. Also, the SPI and SDI are less accurate than the RDI when both precipitation and evaporation are the main factors controlling the drought events. However, the SPI and SDI indices are identical in the same proportions of the dry years which are less than the ratio of dry years to an RDI, but the severity of the drought from the SDI results is higher than the severity of the drought relative to the SPIand RDI. The three indices indicate that the Eastern region is drier than the Western region, which is somewhat wet.

scholarly journals Drought Monitoring in Northern Nigeria Using Four (4) Indices.

2021 ◽  
Vol 8 (1) ◽  
pp. 13-31
Author(s):  
Adeyemi Joshua OLASORE ◽  
Adebayo Ebenezer OLAGBAIYE ◽  
Taiwo Adedayo AJAYI ◽  
Peter Oluwatobi ALABI
Keyword(s):  
Correlation Coefficient ◽  
Time Scale ◽  
Standardized Precipitation Index ◽  
Drought Monitoring ◽  
Drought Indices ◽  
Analytic Hierarchy ◽  
Ecological Zones ◽  
The Standardized Precipitation Index ◽  
Hierarchy Process ◽  
Agro Ecological Zones

Drought can generally be defined as the extreme persistence of precipitation deficit over a region for a specific period. Eight study locations were picked from the Sudano-Sahelian agro-ecological zones of Nigeria (Bauchi, Bida. Kaduna, Kano, Maiduguri. Sokoto, Nguru, and Katsina) from 1981 to 2015. The Standardized Precipitation Index (SPI), Standardized Precipitation Evaporation Index- Thornthwaite (SPEI.T), Standardized Precipitation Evaporation Index-Hargreaves (SPEI-H) and Standardized Precipitation Evaporation Index-penman (SPEI-P) were used as the primary indicators of meteorological and agricultural droughts. The correlation coefficient shows an increasing correlation among the indices with increasing time scale, with SPI and SPEI-H having the highest correlation. The regression analysis shows a monotonic increasing relationship between indices while SPI vs SPEI-H has the highest correlation coefficient. The number of drought occurrences captured by the indices also increases with increasing time scale with SPEI-P detecting the highest number of drought events. All the drought indices reflect the historical drought periods between 1982-1989, 1992-2002, and 2008-2011. SPI, SPEI-P, and SPEI-H detected similar duration and intensity for the historical drought between 1982 and 1989 while SPEI-P showed the highest intensity and duration for the historical droughts between 1992 and 2002 and between 2008 and 2011.Analytic Hierarchy Process (AHP) evaluated that SPEI-P was more robust and sophisticated, SPI and SPEI-P had the same score for tractability while SPEI-H being the least tractable, and SPI had the highest for transparency and extendibility.

scholarly journals Drought detection in Java Island based on Standardized Precipitation and Evapotranspiration Index (SPEI)

2021 ◽  
Author(s):  
Suroso ◽  
Dede Nadhilah ◽  
Ardiansyah ◽  
Edvin Aldrian
Keyword(s):  
Correlation Coefficient ◽  
Standardized Precipitation Index ◽  
Temporal Variations ◽  
Drought Indices ◽  
Drought Severity ◽  
Drought Risk ◽  
Conservative Approach ◽  
Temporal Scales ◽  
Drought Analysis ◽  
Kolmogorov Smirnov

Abstract This study reports a drought analysis which was carried out using the Standardized Precipitation and Evapotranspiration Index (SPEI) to determine the spatial and temporal level of drought risk in Java, Indonesia. Apart from using the SPEI, this study also used the SPI (Standardized Precipitation Index) as a comparison in detecting drought and also validated with historical drought occurrences. Temporal variations of SPI and SPEI values were discussed by considering different timescales (monthly to yearly). Pearson's correlations between both drought indices were calculated to see how similar both indices were. Also, the Kolmogorov–Smirnov tests were used for the similarity test of two kinds of distributions. The results obtained from this analysis showed that the correlation coefficient between the SPI and SPEI models was relatively high on a monthly scale and consistently increased along with the increase of temporal scales but had a decreasing trend during the dry season. However, the SPI detected drought severity with an excessively high estimate in comparison with the SPEI. Greater spatial extents of drought estimation were also generated by SPI followed by SPEI in comparison to factual drought occurrences. As a consequence, SPEI becomes more moderate and SPI as a conservative approach for estimating drought events.

Relationship between Invasive and Non-Invasive Hemodynamic Measures in Experimental Pulmonary Hypertension

2020 ◽  
Vol 16 (1) ◽  
pp. 47-53
Author(s):  
Vicente Benavides-Córdoba ◽  
Mauricio Palacios Gómez
Keyword(s):  
Heart Rate ◽  
Pulmonary Hypertension ◽  
Ejection Fraction ◽  
Right Ventricle ◽  
Correlation Coefficient ◽  
Pearson Correlation ◽  
Systolic Pressure ◽  
Control Group ◽  
Pearson Correlation Coefficient ◽  
Non Invasive

Introduction: Animal models have been used to understand the pathophysiology of pulmonary hypertension, to describe the mechanisms of action and to evaluate promising active ingredients. The monocrotaline-induced pulmonary hypertension model is the most used animal model. In this model, invasive and non-invasive hemodynamic variables that resemble human measurements have been used. Aim: To define if non-invasive variables can predict hemodynamic measures in the monocrotaline-induced pulmonary hypertension model. Materials and Methods: Twenty 6-week old male Wistar rats weighing between 250-300g from the bioterium of the Universidad del Valle (Cali - Colombia) were used in order to establish that the relationships between invasive and non-invasive variables are sustained in different conditions (healthy, hypertrophy and treated). The animals were organized into three groups, a control group who was given 0.9% saline solution subcutaneously (sc), a group with pulmonary hypertension induced with a single subcutaneous dose of Monocrotaline 30 mg/kg, and a group with pulmonary hypertension with 30 mg/kg of monocrotaline treated with Sildenafil. Right ventricle ejection fraction, heart rate, right ventricle systolic pressure and the extent of hypertrophy were measured. The functional relation between any two variables was evaluated by the Pearson correlation coefficient. Results: It was found that all correlations were statistically significant (p <0.01). The strongest correlation was the inverse one between the RVEF and the Fulton index (r = -0.82). The Fulton index also had a strong correlation with the RVSP (r = 0.79). The Pearson correlation coefficient between the RVEF and the RVSP was -0.81, meaning that the higher the systolic pressure in the right ventricle, the lower the ejection fraction value. Heart rate was significantly correlated to the other three variables studied, although with relatively low correlation. Conclusion: The correlations obtained in this study indicate that the parameters evaluated in the research related to experimental pulmonary hypertension correlate adequately and that the measurements that are currently made are adequate and consistent with each other, that is, they have good predictive capacity.

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