scholarly journals Jointly Modeling Drought Characteristics with Smoothed Regionalized SPI Series for a Small Island

Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2489 ◽  
Author(s):  
Luis Angel Espinosa ◽  
Maria Manuela Portela ◽  
João Dehon Pontes Filho ◽  
Ticiana Marinho de Carvalho Studart ◽  
João Filipe Santos ◽  
...  
Keyword(s):  
Moving Average ◽  
Standardized Precipitation Index ◽  
Cumulative Distribution ◽  
Interarrival Time ◽  
Small Island ◽  
Drought Duration ◽  
Rain Gauges ◽  
Duration Magnitude ◽  
The Standardized Precipitation Index ◽  
Homogeneous Regions

The paper refers to a study on droughts in a small Portuguese Atlantic island, namely Madeira. The study aimed at addressing the problem of dependent drought events and at developing a copula-based bivariate cumulative distribution function for coupling drought duration and magnitude. The droughts were identified based on the Standardized Precipitation Index (SPI) computed at three and six-month timescales at 41 rain gauges distributed over the island and with rainfall data from January 1937 to December 2016. To remove the spurious and short duration-dependent droughts a moving average filter (MA) was used. The run theory was applied to the smoothed SPI series to extract the drought duration, magnitude, and interarrival time for each drought category. The smoothed series were also used to identify homogeneous regions based on principal components analysis (PCA). The study showed that MA is necessary for an improved probabilistic interpretation of drought analysis in Madeira. It also showed that despite the small area of the island, three distinct regions with different drought temporal patterns can be identified. The copulas approach proved that the return period of droughts events can differ significantly depending on the way the relationship between drought duration and magnitude is accounted for.

scholarly journals Drought Trends in the Iberian Peninsula over the Last 112 Years

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
P. Páscoa ◽  
C. M. Gouveia ◽  
A. Russo ◽  
R. M. Trigo
Keyword(s):  
Iberian Peninsula ◽  
Standardized Precipitation Index ◽  
Research Unit ◽  
Climatic Research Unit ◽  
Drought Indices ◽  
Drought Duration ◽  
Mean Intensity ◽  
Duration Magnitude ◽  
Northwestern Region ◽  
The Standardized Precipitation Index

The Iberian Peninsula (IP) is a drought-prone area located in the Mediterranean which presents a significant tendency towards dryness during the last decades, reinforcing the need for a continuous monitoring of drought. The long-term evolution of drought in the IP is analyzed, using the Standardized Precipitation Evaporation Index (SPEI) and the Standardized Precipitation Index (SPI), for the period of 1901–2012 and for three subperiods: 1901–1937, 1938–1974, and 1975–2012. SPI and SPEI were calculated with a 12-month time scale, using data from the Climatic Research Unit (CRU) database. Trends in the drought indices, precipitation, and reference evapotranspiration (ET0) were analysed and series of drought duration, drought magnitude, time between drought events, and mean intensity of the events were computed. SPI and SPEI significant trends show areas with opposite signals in the period 1901–2012, mainly associated with precipitation trends, which are significant and positive in the northwestern region and significant and negative in the southern areas. Additionally, SPEI identified dryer conditions and an increase in the area affected by droughts, which agrees with the increase in ET0. The same spatial differences were identified in the drought duration, magnitude, mean intensity, and time between drought events.

scholarly journals Early warning of drought in Europe using the monthly ensemble system from ECMWF

2015 ◽  
Vol 19 (7) ◽  
pp. 3273-3286 ◽  
Author(s):  
C. Lavaysse ◽  
J. Vogt ◽  
F. Pappenberger
Keyword(s):  
Large Scale ◽  
Standardized Precipitation Index ◽  
Seasonal Forecast ◽  
Cumulative Distribution ◽  
False Alarms ◽  
Negative Effects ◽  
European Continent ◽  
Probabilistic Forecasts ◽  
Extended Range ◽  
The Standardized Precipitation Index

Abstract. Timely forecasts of the onset or possible evolution of droughts are an important contribution to mitigate their manifold negative effects. In this paper we therefore analyse and compare the performance of the first month of the probabilistic extended range forecast and of the seasonal forecast from the European Centre for Medium-range Weather Forecasts (ECMWF) in predicting droughts over the European continent. The Standardized Precipitation Index (SPI-1) is used to quantify the onset or likely evolution of ongoing droughts for the next month. It can be shown that on average the extended range forecast has greater skill than the seasonal forecast, whilst both outperform climatology. No significant spatial or temporal patterns can be observed, but the scores are improved when focussing on large-scale droughts. In a second step we then analyse several different methods to convert the probabilistic forecasts of SPI into a Boolean drought warning. It can be demonstrated that methodologies which convert low percentiles of the forecasted SPI cumulative distribution function into warnings are superior in comparison with alternatives such as the mean or the median of the ensemble. The paper demonstrates that up to 40 % of droughts are correctly forecasted one month in advance. Nevertheless, during false alarms or misses, we did not find significant differences in the distribution of the ensemble members that would allow for a quantitative assessment of the uncertainty.

scholarly journals Forecasting droughts in East Africa

2013 ◽  
Vol 10 (8) ◽  
pp. 10209-10230 ◽  
Author(s):  
E. Mwangi ◽  
F. Wetterhall ◽  
E. Dutra ◽  
F. Di Giuseppe ◽  
F. Pappenberger
Keyword(s):  
East Africa ◽  
Standardized Precipitation Index ◽  
Drought Indices ◽  
Drought Event ◽  
East African ◽  
African Region ◽  
Drought Duration ◽  
Additional Information ◽  
Duration Magnitude ◽  
Rain Season

Abstract. The humanitarian crisis caused by the recent droughts (2008–2009 and 2010–2011) in the East African region have illustrated that the ability to make accurate drought predictions with adequate lead time is essential. The use of dynamical model forecasts and drought indices, such as Standardized Precipitation Index (SPI), promises to lead to a better description of drought duration, magnitude and spatial extent. This study evaluates the use of the European Centre for Medium-Range Weather Forecasts (ECMWF) products in forecasting droughts in East Africa. ECMWF seasonal precipitation shows significant skill for both rain seasons when evaluated against measurements from the available in-situ stations from East Africa. The October–December rain season has higher skill that the March–May season. ECMWF forecasts add value to the statistical forecasts produced during the Greater Horn of Africa Climate Outlook Forums (GHACOF) which is the present operational product. Complementing the raw precipitation forecasts with SPI provides additional information on the spatial extend and intensity of the drought event.

scholarly journals An analysis of drought evolution characteristics based on standardized precipitation index: a case study in Southwest Guizhou Autonomous Prefecture, China

2021 ◽  
Vol 21 (3) ◽  
pp. 327-335
Author(s):  
XU YANG ◽  
XIAOHOU SHAO ◽  
XINYU MAO ◽  
XIUNENG LI ◽  
RONGQI LI
Keyword(s):  
Drought Resistance ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Natural Ecosystems ◽  
Drought Duration ◽  
Agricultural Water Management ◽  
Evolution Characteristics ◽  
Drought Disaster ◽  
The Standardized Precipitation Index

Drought is a worldwide concerned issue which causes huge losses in agriculture, economic and damages in natural ecosystems. The precise assessment of drought evolution characteristics is essential for agricultural water management and drought resistance, while such work is rarely reported. Thus, eight meteorological stations located within the Southwest Guizhou Autonomous Prefecture (SGAP) were selected, and the Standardized Precipitation Index (SPI) was used to assess the drought evolution characteristics. The results revealed that the drought occurrences number in Pu'an station was the largest (23 droughts), and the average drought duration in Xingren station was the longest (48.75 months). Moreover, the drought characteristics of the eight stations have account for the largest proportion under normal conditions, was more than 60%, the frequency of drought disaster occurring in Xingren is the highest (30.05%), followed by Wangmo (23.73%). The results of this study will provide theoretical guidance for drought resistance and agricultural production in Southwest Guizhou Autonomous Prefecture of China.

scholarly journals Stochastic Model for Drought Forecasting in the Southern Taiwan Basin

Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2041 ◽  
Author(s):  
Hsin-Fu Yeh ◽  
Hsin-Li Hsu
Keyword(s):  
Water Resource Management ◽  
Moving Average ◽  
Arima Model ◽  
Standardized Precipitation Index ◽  
Warning System ◽  
Absolute Error ◽  
Drought Forecasting ◽  
Drought Conditions ◽  
Southern Taiwan ◽  
The Standardized Precipitation Index

The global rainfall pattern has changed because of climate change, leading to numerous natural hazards, such as drought. Because drought events have led to many disasters globally, it is necessary to create an early warning system. Drought forecasting is an important step toward developing such a system. In this study, we utilized the stochastic, autoregressive integrated moving average (ARIMA) model to predict drought conditions based on the standardized precipitation index (SPI) in southern Taiwan. We employed data from 1967 to 2006 to train the model and data from 2007 to 2017 for model validation. The results showed that the coefficients of determination (R2) were over 0.80 at each station, and the root-mean-square error and mean absolute error were sufficiently low, indicating that the ARIMA model is effective and adequate for our stations. Finally, we employed the ARIMA model to forecast future drought conditions from 2019 to 2022. The results yielded relatively low SPI values in southern Taiwan in future summers. In summary, we successfully constructed an ARIMA model to forecast drought. The information in this study can act as a reference for water resource management.

scholarly journals Drought Frequency Analysis Based on the Development of a Two-Variate Standardized Index (Rainfall-Runoff)

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2599 ◽  
Author(s):  
Gholamreza Nikravesh ◽  
Mohammad Aghababaei ◽  
Mohammad Nazari-Sharabian ◽  
Moses Karakouzian
Keyword(s):  
Standardized Precipitation Index ◽  
Drought Indices ◽  
Flow Index ◽  
Severe Drought ◽  
Drought Event ◽  
Rainfall Runoff ◽  
Drought Duration ◽  
Novel Approach ◽  
Standardized Index ◽  
The Standardized Precipitation Index

Drought is one of the most drastic events, which has imposed irreparable damages on human societies and may occur in any climate regime. To define drought, given its properties of multidimensionality and randomity, one cannot rely on a single variable/index (e.g., precipitation, soil moisture, and runoff). Accordingly, implementing a novel approach, this study investigated drought events in two basins with different climatic regimes, using multivariate frequency analyses of drought duration, severity, and severity peak, based on developing a Two-variate Standardized Index (TSI). The index was developed based on the concept of copula, by applying rainfall-runoff data (1974–2019) and comparing them with two popular drought indices, the Standardized Precipitation Index (SPI) and Standardized Stream Flow Index (SSFI), in terms of derived drought characteristics. The results show that TSI determined more severe drought conditions with fewer return periods than SPI and SSFI in a specific drought event. This implies that the disadvantages of SPI and SSFI might not be found in TSI. The developed index can be employed by policymakers and planners to protect water resources from drought.

scholarly journals Spatiotemporal Analysis of Droughts over Different Climate Regions using Hybrid Clustering Method

2021 ◽  
Author(s):  
Kiyoumars Roushangar ◽  
Roghayeh Ghasempour ◽  
Vahid Nourani
Keyword(s):  
Standardized Precipitation Index ◽  
Spatiotemporal Analysis ◽  
Mitigation Strategies ◽  
Drought Severity ◽  
Spatiotemporal Pattern ◽  
Discrete Wavelet ◽  
Drought Duration ◽  
Time Frequency ◽  
The North ◽  
The Standardized Precipitation Index

Abstract Drought spatiotemporal variations assessment is an efficient method for implementing drought mitigation strategies and reducing its negative impacts. In this study, the spatiotemporal pattern of short to long-term droughts was assessed for an area with different climates. 31 stations located in Iran were considered and the Standardized Precipitation Index (SPI) series with timescales of 3, 6, and 12 months were calculated during the 1951-2016 period. A hybrid methodology namely Maximal Overlap Discrete Wavelet Transform (MODWT) was applied to obtain the SPIs time-frequency properties and multiscale zoning was done via K-means clustering approach. The energy amounts of decomposed subseries via the MODWT were used as inputs for K-means approach. Also, the statistics in drought features (i.e. drought duration, severity, and peak) were assessed and the results showed that shorter term droughts (i.e. SPI-3 and -6) were more frequent and severe in the north parts where the lowest values of drought duration were obtained. It was observed that the regions with more droughts frequency had the highest energy values. For shorter term droughts a direct relationship was obtained between the energy values and mean SPI, drought severity, and drought peak, whereas an inverse relationship was obtained for longer term drought. It was found that with increasing the degree of SPI, the similarity of the stations of each cluster increased too and the homogeneity of stations for the SPI-12 was slightly higher than the SPI-3 and -6.

scholarly journals Extreme Droughts Change in the Mekong River Basin: A Multidisciplinary Analysis Based on Satellite Data

Water ◽  
2021 ◽  
Vol 13 (19) ◽  
pp. 2682
Author(s):  
Vo Tuong ◽  
Thanh-Van Hoang ◽  
Tien-Yin Chou ◽  
Yao-Min Fang ◽  
Chun-Tse Wang ◽  
...  
Keyword(s):  
River Basin ◽  
Regional Climate ◽  
Standardized Precipitation Index ◽  
Extreme Drought ◽  
Mekong River ◽  
Drought Duration ◽  
Mekong River Basin ◽  
Drought Period ◽  
Mk Test ◽  
The Standardized Precipitation Index

This study evaluates droughts in the Mekong River Basin (MKB) based on a multidisciplinary method, mainly using the Standardized Precipitation Index (SPI) and Mann–Kendall (MK) test. Precipitation data corresponding to the seasonality of the regional climate were retrieved from Integrated Multi-satellitE Retrievals for Global Precipitation Measurement from 2001 to 2020, at a monthly temporal scale and 0.1 degree spatial resolution. Drought events and their average interval, duration, and severity were determined based on Run theory. Our results revealed the most extreme drought period was in January 2014, at the time the lowest precipitation occurred. Spatial extreme drought results indicated that Zone 2 in the upstream MKB has the highest frequency of drought, with 44 events observed during 19 years, and experiences the most severe droughts, whereas Zone 24 in the downstream MKB has the most prolonged drought duration of seven months. The periods and locations of extreme drought were identified using the SPI, corresponding to historic droughts of the MKB. Furthermore, the MK test shows an increasing trend of droughts in the lower MKB and the cluster analysis identified six clusters of times series. Overall, our study provides essential findings for international and national water resource stakeholders in identifying trends of extreme drought in the MKB.

scholarly journals Drought Assessment Based on Fused Satellite and Station Precipitation Data: An Example from the Chengbi River Basin, China

2022 ◽  
Vol 11 (1) ◽  
pp. 48
Author(s):  
Chongxun Mo ◽  
Xuechen Meng ◽  
Yuli Ruan ◽  
Yafang Wang ◽  
Xingbi Lei ◽  
...  
Keyword(s):  
River Basin ◽  
Cumulative Distribution Function ◽  
Standardized Precipitation Index ◽  
Cumulative Distribution ◽  
Precipitation Data ◽  
Drought Assessment ◽  
Lack Of Information ◽  
Complex Calculation ◽  
The Standardized Precipitation Index

Drought poses a significant constraint on economic development. Drought assessment using the standardized precipitation index (SPI) uses only precipitation data, eliminating other redundant and complex calculation processes. However, the sparse stations in southwest China and the lack of information on actual precipitation measurements make drought assessment highly dependent on satellite precipitation data whose accuracy cannot be guaranteed. Fortunately, the Chengbi River Basin in Baise City is rich in station precipitation data. In this paper, based on the evaluation of the accuracy of IMERG precipitation data, geographically weighted regression (GWR), geographic difference analysis (GDA), and cumulative distribution function (CDF) are used to fuse station precipitation data and IMERG precipitation data, and finally, the fused precipitation data with the highest accuracy are selected to evaluate the drought situation. The results indicate that the accuracy of IMERG precipitation data needs to be improved, and the quality of CDF-fused precipitation data is higher than the other two. The drought analysis indicated that the Chengbi River Basin is in a cyclical drought and flood situation, and from October to December 2014, the SPI was basically between +1 and −1, showing a spatial pattern of slight flooding, normal conditions, and slight drought.

scholarly journals Utilizing Objective Drought Severity Thresholds to Improve Drought Monitoring

2020 ◽  
Vol 59 (3) ◽  
pp. 455-475 ◽  
Author(s):  
Zachary T. Leasor ◽  
Steven M. Quiring ◽  
Mark D. Svoboda
Keyword(s):  
Standardized Precipitation Index ◽  
Region Of Interest ◽  
Cumulative Distribution ◽  
Drought Severity ◽  
Study Region ◽  
South Central ◽  
Central United States ◽  
Systematic Biases ◽  
The Standardized Precipitation Index ◽  
Western Portion

AbstractDrought is a prominent climatic hazard in the south-central United States. Drought severity is frequently classified using the categories established by the U.S. Drought Monitor (USDM). This study evaluates whether the thresholds for the standardized precipitation index (SPI) used by the USDM accurately classify drought severity. This study uses the SPI based on PRISM precipitation data from 1900 to 2015 to evaluate drought severity in Texas, Oklahoma, and Kansas. The results show that the fixed SPI thresholds for the USDM drought categories may lead to a systematic underestimation of drought severity in arid regions. To address this issue, objective drought thresholds were developed at each location by fitting a cumulative distribution function at each location to ensure that the observed frequency of drought in each severity category (D0–D4) matched the theoretical expectations of the USDM. This approach reduces the systematic biases in drought severity across the western portion of the study region. Therefore, we recommend developing objective drought thresholds for each location and SPI time scale (e.g., 1, 3, and 6 months). This method can be used to develop objective drought thresholds for any drought index and climate region of interest.

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