scholarly journals A Bayesian Network-Based Probabilistic Framework for Drought Forecasting and Outlook

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Ji Yae Shin ◽  
Muhammad Ajmal ◽  
Jiyoung Yoo ◽  
Tae-Woong Kim
Keyword(s):  
Bayesian Network ◽  
Standardized Precipitation Index ◽  
Severe Drought ◽  
Drought Condition ◽  
Probabilistic Framework ◽  
Drought Forecasting ◽  
Probabilistic Forecasting ◽  
The Past ◽  
Drought Conditions ◽  
The Standardized Precipitation Index

Reliable drought forecasting is necessary to develop mitigation plans to cope with severe drought. This study developed a probabilistic scheme for drought forecasting and outlook combined with quantification of the prediction uncertainties. The Bayesian network was mainly employed as a statistical scheme for probabilistic forecasting that can represent the cause-effect relationships between the variables. The structure of the Bayesian network-based drought forecasting (BNDF) model was designed using the past, current, and forecasted drought condition. In this study, the drought conditions were represented by the standardized precipitation index (SPI). The accuracy of forecasted SPIs was assessed by comparing the observed SPIs and confidence intervals (CIs), exhibiting the associated uncertainty. Then, this study suggested the drought outlook framework based on probabilistic drought forecasting results. The overall results provided sufficient agreement between the observed and forecasted drought conditions in the outlook framework.

scholarly journals Evaluation of temporal drought variation and projection in a tropical river basin of Kerala

2020 ◽  
Vol 11 (S1) ◽  
pp. 115-132 ◽  
Author(s):  
M. A. Jincy Rose ◽  
N. R. Chithra
Keyword(s):  
River Basin ◽  
Standardized Precipitation Index ◽  
Drought Severity ◽  
Climate Projections ◽  
Severe Drought ◽  
Tropical River ◽  
The Past ◽  
Drought Conditions ◽  
The Future ◽  
The Standardized Precipitation Index

Abstract Temperature is an indispensable parameter of climate that triggers evapotranspiration and has vital importance in aggravating drought severity. This paper analyses the existence and persistence of drought conditions which are said to prevail in a tropical river basin which was once perennial. Past observed data and future climate projections of precipitation and temperature were used for this purpose. The assessment and projection of this study employ the Standardized Precipitation Evapotranspiration Index (SPEI) compared with that of the Standardized Precipitation Index (SPI). The results indicate the existence of drought in the past and the drought conditions that may persist in the future according to RCP 4.5 and 8.5 scenarios. The past drought years identified in the study were compared with the drought declared years in the state and were found to be matching. The evaluation of the future scenarios unveils the occurrence of drought in the basin ranging from mild to extreme conditions. It has been noted that the number of moderate and severe drought months has increased based on SPEI compared to SPI, indicating the importance of temperature in drought studies. The study can be considered as a plausible scientific remark helpful in risk management and application decisions.

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.

DROUGHT OCCURRENCE UNDER LITHUANIAN CLIMATIC CONDITIONS

2015 ◽  
Author(s):  
Laima TAPARAUSKIENĖ ◽  
Veronika LUKŠEVIČIŪTĖ
Keyword(s):  
Meteorological Data ◽  
Standardized Precipitation Index ◽  
Vegetation Period ◽  
Climatic Conditions ◽  
Precipitation Record ◽  
Calculation Step ◽  
Drought Conditions ◽  
The Standardized Precipitation Index ◽  
June July

This study provides the analysis of drought conditions of vegetation period in 1982-2014 year in two Lithuanian regions: Kaunas and Telšiai. To identify drought conditions the Standardized Precipitation Index (SPI) was applied. SPI was calculated using the long-term precipitation record of 1982–2014 with in-situ meteorological data. Calculation step of SPI was taken 1 month considering only vegetation period (May, June, July, August, September). The purpose of investigation was to evaluate the humidity/aridity of vegetation period and find out the probability of droughts occurrence under Lithuanian climatic conditions. It was found out that according SPI results droughts occurred in 14.5 % of all months in Kaunas region and in 15.8 % in Telšiai region. Wet periods in Kaunas region occurred in 15.8 %, and in Telšiai region occurrence of wet periods was – 18.8 % from all evaluated months. According SPI evaluation near normal were 69.7 % of total months during period of investigation in Kaunas and respectively – 65.5 % in Telšiai. The probability for extremely dry period under Lithuania climatic conditions are pretty low – 3.0 % in middle Lithuania and 2.4 % in western part of Lithuania.

scholarly journals Analysis of Drought in the Northern Region of Bangladesh Using Standardized Precipitation Index (SPI)

2019 ◽  
Vol 11 (1-2) ◽  
pp. 199-216
Author(s):  
R Afrin ◽  
F Hossain ◽  
SA Mamun
Keyword(s):  
Standardized Precipitation Index ◽  
Extended Period ◽  
Northern Region ◽  
Precipitation Index ◽  
Rainfall Data ◽  
Extreme Drought ◽  
Severe Drought ◽  
Drought Analysis ◽  
Dry Conditions ◽  
The Standardized Precipitation Index

Drought is an extended period when a region notes a deficiency in its water supply. The Standardized Precipitation Index (SPI) method was used in this study to analyze drought. Northern region of Bangladesh was the area of study. Monthly rainfall data of northern region of Bangladesh was obtained from the Meteorological Department of Bangladesh. Obtained rainfall data was from 1991 to 2011 and values from 2012 to 2026 were generated using Markov model. Then SPI values from 1991 to 2026 were calculated by using SPI formula for analyzing drought. Analysis with SPI method showed that droughts in northern region of Bangladesh varied from moderately dry to severely dry conditions and it may vary from moderately dry to severely dry conditions normally in future but in some cases extreme drought may also take place. From the study, it is observed that the northern region of Bangladesh has already experienced severe drought in 1991, 1992, 1994, 1995, 1997, 1998, 2000, 2003, 2005, 2007, 2009 and 2010. The region may experience severe drought in 2012, 2015, 2016, 2018, 2019, 2021, 2022, 2023, 2024, 2025 and 2026 and extreme drought in 2012, 2014, 2016, 2023 and 2024. J. Environ. Sci. & Natural Resources, 11(1-2): 199-216 2018

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 Droughts and corruption

Public Choice ◽  
2020 ◽  
Author(s):  
Daniela Wenzel
Keyword(s):  
Public Sector ◽  
Natural Disasters ◽  
Good Governance ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Developed Countries ◽  
Severe Drought ◽  
Specific Analysis ◽  
Short And Long Term ◽  
The Standardized Precipitation Index

Abstract Natural disasters are challenges for good governance. That conclusion follows from recent research investigating the effects of natural disasters on one important force hostile to good governance: public sector corruption. However, a specific analysis of droughts is so far neglected in the still-young relevant strand of the literature. The present paper fills that gap by analyzing the short- and long-term influence of droughts on public sector corruption within a unified panel estimation approach for 120 countries during the period 1985–2013. Relying on a meteorological drought measure, the Standardized Precipitation Index, we show that more severe drought exposure is followed by more corruption. The effect holds for subsamples of developing and developed countries. The robustness of the results is supported by a variety of stability tests. Furthermore, we provide initial evidence on the transmission paths of drought-induced corruption, which differ depending on the countries’ level of development. Whereas droughts increase corruption risk in developing countries by triggering significantly larger aid inflows and less democratic accountability and transparency, corruption in developed countries rises as a consequence of governmental drought relief payments.

scholarly journals Trends and Extremes of Drought Episodes in Vietnam Sub-Regions during 1980–2017 at Different Timescales

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 813 ◽  
Author(s):  
Milica Stojanovic ◽  
Margarida L.R. Liberato ◽  
Rogert Sorí ◽  
Marta Vázquez ◽  
Tan Phan-Van ◽  
...  
Keyword(s):  
Large Scale ◽  
Root Zone ◽  
Southern Oscillation ◽  
Standardized Precipitation Index ◽  
Lower Troposphere ◽  
Severe Drought ◽  
Positive Trend ◽  
Drought Conditions ◽  
Northern Regions ◽  
Dry Conditions

This study investigated the temporal occurrence of dry conditions in the seven climatic sub-regions of Vietnam during the 1980–2017 period. This assessment was performed using the Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Precipitation Index (SPI) at 1 to 24 months timescales. Results show that the main periods of extreme drought occurred simultaneously throughout the country in 1992–1993 and 2003–2004, except for 2015–2016, when it was not identified in the southern region. In addition, a slight temporal lag was identified latitudinally (north–south) at the beginning of dry conditions, revealing the largest difference between the northern and southern regions. A positive trend in the time series of both indices (SPEI and SPI) prevailed in all sub-regions, with the SPEI minus SPI difference always being negative, suggesting the importance of temperature and evapotranspiration for this trend. Further detailed analyses were then performed using SPEI at 1-month and 12-months timescales for all climate sub-regions, as well as the main indicators to characterize duration and severity. Results show that the number of drought episodes did not vary much between regions, but they did vary in duration and severity at the annual scale. Moreover, changes in the soil root zone are largely associated with dry and wet conditions not only from season to season, but also in longer accumulation periods and more strongly in the northern regions of Vietnam. Indeed, a study of the most severe drought episodes also revealed the occurrence of negative anomalies of the root-soil moisture in the subsequent four or more months. Dynamic atmospheric conditions associated with the peak of most severe drought episodes show the crucial role of subsidence of dry air in the middle and high atmosphere, which prevents convection in the lower troposphere. Finally, the linkages between drought conditions in Vietnam and large-scale atmospheric and oceanic teleconnection patterns were revealed to be quite different among northern and southern sub-regions. During the positive phase of El Niño–Southern Oscillation (ENSO), drought episodes at different timescales were identified in the southern climate sub-regions, while the negative phase was associated with drought conditions in the northern regions.

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 Drought Monitoring for Washington State: Indicators and Applications

2011 ◽  
Vol 12 (1) ◽  
pp. 66-83 ◽  
Author(s):  
Shraddhanand Shukla ◽  
Anne C. Steinemann ◽  
Dennis P. Lettenmaier
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Snow Water Equivalent ◽  
Standardized Precipitation Index ◽  
Land Surface Model ◽  
Washington State ◽  
Drought Monitoring ◽  
Surface Model ◽  
Drought Conditions ◽  
The Standardized Precipitation Index

Abstract A drought monitoring system (DMS) can help to detect and characterize drought conditions and reduce adverse drought impacts. The authors evaluate how a DMS for Washington State, based on a land surface model (LSM), would perform. The LSM represents current soil moisture (SM), snow water equivalent (SWE), and runoff over the state. The DMS incorporates the standardized precipitation index (SPI), standardized runoff index (SRI), and soil moisture percentile (SMP) taken from the LSM. Four historical drought events (1976–77, 1987–89, 2000–01, and 2004–05) are constructed using DMS indicators of SPI/SRI-3, SPI/SRI-6, SPI/SRI-12, SPI/SRI-24, SPI/SRI-36, and SMP, with monthly updates, in each of the state’s 62 Water Resource Inventory Areas (WRIAs). The authors also compare drought triggers based on DMS indicators with the evolution of drought conditions and management decisions during the four droughts. The results show that the DMS would have detected the onset and recovery of drought conditions, in many cases, up to four months before state declarations.

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