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

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.

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

Advances in Meteorology ◽

10.1155/2016/9472605 ◽

2016 ◽

Vol 2016 ◽

pp. 1-10 ◽

Cited By ~ 14

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.

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Reliability Assessment of Agricultural Reservoirs for Water Supply under Climate Change

Korean Society of Hazard Mitigation ◽

10.9798/kosham.2020.20.1.53 ◽

2020 ◽

Vol 20 (1) ◽

pp. 53-60

Author(s):

Dasang Ko ◽

Yeongcheol Joo ◽

Taesam Lee

Keyword(s):

Climate Change ◽

Standardized Precipitation Index ◽

Precipitation Index ◽

Severe Drought ◽

Water Shortages ◽

The Future ◽

Storage Rate ◽

The Standardized Precipitation Index ◽

Agricultural Areas

Recently, the frequency of drought occurrence and the resulting damage has increased due to climate change. Frequent severe droughts induce water shortages in agricultural reservoirs. The role of drought monitoring and prediction is critical for mitigating the effects of severe drought in agricultural areas. In this study, a compound standardized storage and precipitation index (CSSPI) was developed that adapted the existing drought index-the standardized precipitation index (SPI)-by adding hydrological data on storage rate. Furthermore, the future storage rate was simulated using autoregressive models (AR) to estimate the future CSSPI. A dataset containing records of reservoirs and precipitation at the three areas of Jungbu, Youngnam, and Honam was applied to estimate the current and future status of the CSSPI. The results indicate that the CSSPIs generated accurately present the past pattern of the observed data and that they can be considered as inputs for predicting future drought conditions.

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Spatio-temporal evaluation of drought characteristics in the Dhasan basin

MAUSAM ◽

10.54302/mausam.v69i4.423 ◽

2021 ◽

Vol 69 (4) ◽

pp. 589-598

Author(s):

SASWAT KUMAR KAR ◽

R. M. SINGH ◽

T. THOMAS

Keyword(s):

Time Scale ◽

Monsoon Season ◽

Standardized Precipitation Index ◽

Rain Gauge ◽

Drought Severity ◽

Severe Drought ◽

Multiple Time ◽

Drought Duration ◽

Drought Characteristics ◽

Drought Conditions

ABSTRACT. The meteorological drought characteristics including onset, departure, duration, severity as well as intensity have been evaluated mainly for monsoon season at all the three rain gauge stations located in Dhasan basin. The Standardized Precipitation Index (SPI) has been applied to understand and quantify the drought severity on multiple time scale (1, 3, 6, 12 and 24 months). The spatiotemporal analysis of drought based on 3-month SPI has also carried out to identify drought years and the regions of the study area which is under the grip of continuous drought events. Based on the 3-month SPI, major drought events have been identified. The maximum drought severity of -11.17 occurred during November 1991 to August 1992 having the longest duration of 10 months, in the area under Sagar rain gauging station. The onset of most of the drought events in the basin take place during the beginning of Kharif season and terminate by the end of August or September, so affect the agricultural crops severely. The spatial variation indicates that during June 2002, about 55.74% of basin area was experiencing severe drought conditions, followed by 35.29% area under moderate drought condition and only 8.97% area faced mild drought conditions. The inter-relationship among the drought duration, number of drought events, drought severity and time scale have been studied.

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Drought planning and management: experience in the Seyhan River Basin, Turkey

Water Policy ◽

10.2166/wp.2016.019 ◽

2016 ◽

Vol 18 (S2) ◽

pp. 177-209 ◽

Cited By ~ 3

Author(s):

Ismail Kaan Tuncok

Keyword(s):

River Basin ◽

Eastern Mediterranean ◽

Methodological Approach ◽

Standardized Precipitation Index ◽

Agricultural Drought ◽

Drought Indices ◽

Drought Planning ◽

Planning And Management ◽

Drought Conditions ◽

The Standardized Precipitation Index

The focus of this study was to integrate drought planning and management into local and regional decision-making processes in the Seyhan River Basin, which is the second-largest basin after the Nile in the Eastern Mediterranean and agriculturally one of the most productive regions in Turkey and Europe. The methodological approach consisted of two steps: Step 1 – review and analyse historical data sets to evaluate and characterize water resources and drought-driven elements; Step 2 – evaluate drought indices to characterize drought conditions through use of the Standardized Precipitation Index and Standardized Precipitation Evapotranspiration Index. Historical and future expected drought periods were identified in the context of hydrologic, meteorologic and agricultural drought conditions.

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

Water ◽

10.3390/w11061301 ◽

2019 ◽

Vol 11 (6) ◽

pp. 1301 ◽

Cited By ~ 6

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.

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A Probabilistic Approach for Assessment of Future Drought in Bagmati River Basin, Nepal

Nepalese Journal of Statistics ◽

10.3126/njs.v2i0.21156 ◽

2018 ◽

Vol 2 ◽

pp. 75-88

Author(s):

Rajendra Man Shrestha ◽

Azaya Bikram Sthapit ◽

Srijan Lal Shrestha

Keyword(s):

River Basin ◽

Probabilistic Approach ◽

Standardized Precipitation Index ◽

Severe Drought ◽

Summer Drought ◽

The Future ◽

Moderate Drought ◽

Extreme Distribution ◽

Bagmati River

Background: The Bagmati River is the rain-fed river in the basin of Nepal. The climate change in rainfall patterns may lead to drought or flashflood in this basin. Drought is a silent and pervasive hazard due to the deficit of water availability. It may have adverse impact on society leading to impact on environment, culture, political and other functions of the region.Objective: This study aims to assess the future drought in the Bagmati River Basin, Nepal.Materials and Methods: Providing Regional Climates for Impact Studies precipitation data was obtained from Department of Hydrology and Meteorology, Kathmandu. The Generalized Extreme Distribution was fitted to respective total precipitations in 3 time-scales using EasyFit software. Standardized Precipitation Index (SPI) method was used to derive SPI for winter drought, SPI for summer drought and SPI for long-term (annual) drought.Results: The results of data analysis showed that winter moderate drought episodes may occur in years 2035, 2042, 2048, 2049, 2051 and 2053. Likewise, summer severe drought episode may occur in 2046. The year 2046 also indicated long-term extreme drought. Moreover, 2030, 2031, 2035, 3040 and 2053 may be long-term moderate drought episodes years in future.Conclusion: There may be winter moderate drought, summer severe drought and a long-term extreme as well as moderate drought during the future period 2030-2060.Nepalese Journal of Statistics, Vol. 2, 75-88

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DROUGHT OCCURRENCE UNDER LITHUANIAN CLIMATIC CONDITIONS

Proceedings of the 7th International Scientific Conference Rural Development 2015 ◽

10.15544/rd.2015.059 ◽

2015 ◽

Cited By ~ 1

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.

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Developing Objective Operational Definitions for Monitoring Drought

Journal of Applied Meteorology and Climatology ◽

10.1175/2009jamc2088.1 ◽

2009 ◽

Vol 48 (6) ◽

pp. 1217-1229 ◽

Cited By ~ 88

Author(s):

Steven M. Quiring

Keyword(s):

Water Conservation ◽

Standardized Precipitation Index ◽

Meteorological Drought ◽

Severity Index ◽

Decision Makers ◽

Drought Severity ◽

Specific Method ◽

The Standardized Precipitation Index ◽

Spatially Variant ◽

Objective Methodology

Abstract Drought is a complex phenomenon that is difficult to accurately describe because its definition is both spatially variant and context dependent. Decision makers in local, state, and federal agencies commonly use operational drought definitions that are based on specific drought index thresholds to trigger water conservation measures and determine levels of drought assistance. Unfortunately, many state drought plans utilize operational drought definitions that are derived subjectively and therefore may not be appropriate for triggering drought responses. This paper presents an objective methodology for establishing operational drought definitions. The advantages of this methodology are demonstrated by calculating meteorological drought thresholds for the Palmer drought severity index, the standardized precipitation index, and percent of normal precipitation using both station and climate division data from Texas. Results indicate that using subjectively derived operational drought definitions may lead to over- or underestimating true drought severity. Therefore, it is more appropriate to use an objective location-specific method for defining operational drought thresholds.

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Evaluation of a High-Resolution SPI for Monitoring Local Drought Severity

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-16-0106.1 ◽

2016 ◽

Vol 55 (10) ◽

pp. 2247-2262 ◽

Cited By ~ 4

Author(s):

Rebecca V. Cumbie-Ward ◽

Ryan P. Boyles

Keyword(s):

United States ◽

High Resolution ◽

Standardized Precipitation Index ◽

Stage Iv ◽

Drought Severity ◽

Cluster Solution ◽

Historical Distribution ◽

Drought Conditions ◽

Hydrologic Prediction ◽

Strong Agreement

AbstractA standardized precipitation index (SPI) that uses high-resolution, daily estimates of precipitation from the National Weather Service over the contiguous United States has been developed and is referred to as HRD SPI. There are two different historical distributions computed in the HRD SPI dataset, each with a different combination of normals period (1971–2000 or 1981–2010) and clustering solution of gauge stations. For each historical distribution, the SPI is computed using the NCEP Stage IV and Advanced Hydrologic Prediction Service (AHPS) gridded precipitation datasets for a total of four different HRD SPI products. HRD SPIs are found to correlate strongly with independently produced SPIs over the 10-yr period from 2005 to 2015. The drought-monitoring utility of the HRD SPIs is assessed with case studies of drought in the central and southern United States during 2012 and over the Carolinas during 2007–08. A monthly comparison between HRD SPIs and independently produced SPIs reveals generally strong agreement during both events but weak agreement in areas where radar coverage is poor. For both study regions, HRD SPI is compared with the U.S. Drought Monitor (USDM) to assess the best combination of precipitation input, normals period, and station clustering solution. SPI generated with AHPS precipitation and the 1981–2010 PRISM normals and associated cluster solution is found to best capture the spatial extent and severity of drought conditions indicated by the USDM. This SPI is also able to resolve local variations in drought conditions that are not shown by either the USDM or comparison SPI datasets.

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The Bolivian Drought Monitor: an operational tool, calibrated on impact records, to identify and communicate drought severity conditions.

10.5194/egusphere-egu21-8480 ◽

2021 ◽

Author(s):

Lauro Rossi ◽

Alessandro Masoero ◽

Anna Mapelli ◽

Fabio Castelli

Keyword(s):

Remote Sensing ◽

Early Warning ◽

Warning System ◽

Drought Severity ◽

Severe Drought ◽

Drought Event ◽

Context Analysis ◽

Management Platform ◽

Drought Conditions ◽

Civil Defence

Within the framework of the CIF financed &#8220;Pilot Program for Climate Resilience&#8221;, the Drought Monitoring and Early Warning System for Bolivia was developed and implemented. The system is operational since July 2020 and aims at detecting emerging severe drought conditions in the country, in order to trigger timely warnings to stakeholders and the general public.The Bolivian Drought Monitor has two main components: a technical one (data gathering and analysis, performed through the multi-hazard early warning &#8220;myDEWETRA&#8221; platform) and an institutional one (creating consensus and disseminating warnings). The system design followed a participatory approach, involving since the early stages the Ministry for Water and Environment (MMAyA), the National Hydrometeorological Service (SENAMHI), the Vice-Ministry for Civil Defence (VIDECI). These institutions actively contribute to the monthly edition of the drought bulletin, each one for its own sector of competence, through a dedicated IT tool for synchronous compilation. Ongoing drought conditions are reported in a national bulletin, issued monthly and published on a dedicated public website: http://monitorsequias.senamhi.gob.bo/Given the Bolivian data-poor context, analysis strongly relies on a large variety of multi-source satellite products, spanning from well consolidated ones in the operational practice to more experimental ones such as from the SMAP mission. This information is used to monthly refresh the spatial maps of 17 indexes covering meteorological, hydrological and agricultural droughts for different aggregation periods (from 1 to 12 months). Simulation of the system performance over a long period (2002-2019) and comparison with recorded socio-economic drought impacts&#160; from the National Disaster Observatory (Observatorio Nacional de Desastres- OND) of the Vice-Ministry of Civil Defence (VIDECI) was used to define a most representative compound index, based on a weighted combination of a selection of 4 indexes with their related thresholds. The combination of 3-month SPEI, 2-month SWDI, 1-month VHI and 1-month FAPAR indexes performed the best in the comparison with impact records. This combination encompasses both the medium-term effects of meteorological and hydrological deficits (3-month SPEI and SWDI), both the short-term effects on vegetation (1-month VHI and FAPAR). This set of indexes proved to be a solid proxy in estimating possible impacts on population of ongoing or incoming drought spells, as happened for most significant recent drought events occurred in Bolivia, such as the 2010 event in the Chaco region and the 2016 drought event in the Altiplano and Valles regions, that heavily affected the water supply in several major cities (La Paz, Sucre, Cochabamba, Oruro and Potos&#237;).The design of the monitoring and bulletin management platform, together with its strong remote-sensing base, give to the system a high potential for easy export to other regional and national contexts. Also, the variety of the different computed drought indexes and the replicability of the procedure for the best compound index identification will allow for efficient evolutionary maintenance as new remote-sensing products will be available in the future.

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