Faculty Publications
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Item Bivariate Drought Characterization of Two Contrasting Climatic Regions in India Using Copula(American Society of Civil Engineers (ASCE), 2021) Sajeev, A.; Deb Barma, S.; Mahesha, A.; Shiau, J.-T.This study aims to construct the multiple time-scale joint distributions of drought duration and severity using two-dimensional copulas and compare the drought characteristics in India's two contrasting climate regions: the arid Rajasthan and humid, tropical Kerala. The drought occurrences were defined by the standardized precipitation index (SPI) with a threshold below -0.8 at time scales of 3, 6, 12, and 24 months for 1900-2016. Significant correlations were noted between the drought severity and drought duration in both regions. The Clayton copula gave a better fit than other copulas for modeling the dependence among the observed drought duration and severity. The results indicate that the probability of short-term droughts (SPI-3 and SPI-6) is more significant than those of long-term droughts (SPI-12 and SPI-24) for an identical drought event in both regions. Also, the probability of severe drought events with greater duration and severity for long-term droughts (SPI-12 and SPI-24) is higher in Kerala than that in western Rajasthan. For all the time-scale SPIs, the conditional probability of drought severity for a given duration exceeding a threshold showed an increasing trend in both regions. Furthermore, the conditional probability of the drought duration given the severity for short-term droughts is greater than that of the long-term droughts for the same drought event. For short-term droughts, the conditional return period of an identical drought event is lower in Kerala than in western Rajasthan. In contrast, the conditional return period of long-term droughts is lower in western Rajasthan. Additionally, copula-based nonexceedance conditional distributions for the major crops were established based on rainfall. © 2020 American Society of Civil Engineers.Item Long-Term Climate Variability and Drought Characteristics in Tropical Region of India(American Society of Civil Engineers (ASCE), 2021) Vijay, A.; Sivan, S.D.; Mudbhatkal, A.; Mahesha, A.This work reports climate change signals and long-Term trend analysis of climate variables, meteorological drought, and extreme climate indexes over the tropical state of Kerala in India. The trend analysis reveals statistically significant decrease of annual and southwest monsoon rainfall (as much as 63 mm and 55 mm per decade, respectively). A decrease in number of annual rainy days (up to 2.8 days/decade) is also reported. Temperature trend analysis indicates an increasing trend with as high as 1.3°C/decade. The spatio-Temporal variation of extreme climate indexes across Kerala shows a decreasing trend of extreme precipitation indexes and an increasing trend of extreme temperature indexes. R95 and R95p decreased in northern and southern Kerala whereas R5 index increased in central and southern regions. Warm days have significantly increased whereas cold days exhibit a decreasing trend across the state. The increase in warmer nights is statistically significant whereas colder nights are decreasing in central and southern regions. Meteorological drought using Standardized Precipitation Index (SPI) reveals increasing occurrence of droughts in Kerala with higher frequencies over southern and central Kerala. © 2021 American Society of Civil Engineers.Item Spatiotemporal Analysis of Compound Agrometeorological Drought and Hot Events in India Using a Standardized Index(American Society of Civil Engineers (ASCE), 2021) Muthuvel, D.; Mahesha, A.Meteorological droughts abetted by hot events could instigate an agricultural drought that eventually affects crop yield. Different types of droughts may coexist or occur in succession. A single index based on one particular variable may not be sufficient to quantify such compound drought events. Therefore, this study embedded drought indexes ofstandardized precipitation index (SPI), standardized soil-moisture index (SSI), and standardized temperature index (STI) with Gaussian copula functions to study compound agrometeorological drought and hot events in India from 1948 to 2014. By standardizing the joint probability of the SPI, SSI, and STI time series, the standardized compound drought and hot index (SCDHI) was developed. The SCDHI values in the monsoon months of different climatic zones have a strong correlation of about 0.95 with other well-established indexes such as the standardized compound event indicator (SCEI), which incorporates SPI and STI, and the multivariate standardized drought index (MSDI), which incorporates SPI and SSI. Based on the areal extent, 1965-1966, 1972, 1987, and 2002 were identified as significant compound drought years in India. The index also identified three successive compound events of the 2012-2014 northest monsoon in the southern peninsular region. A notable increase in the frequency of compound drought and hot events was found post-2000. The case studies of the major drought events and the dependent pattern of SCDHI on its constituent indexes indicate that SCDHI performs well as an indicator of compound agrometeorological and hot events across different climatic regions and in both southwest and northeast monsoons. © 2021 American Society of Civil Engineers.Item Future global concurrent droughts and their effects on maize yield(Elsevier B.V., 2023) Muthuvel, D.; Sivakumar, B.; Mahesha, A.Droughts are one of the most devastating natural disasters. Droughts can co-exist in different forms (e.g. meteorological, hydrological, and agricultural) as concurrent droughts. Such concurrent droughts can have far reaching implications for crop yield and global food security. The present study aims to assess global concurrent drought traits and their effects on maize yield under climate change. The standardized indices of precipitation, runoff, and soil moisture incorporated as multivariate standardized drought index (MSDI) using copula functions are used to quantify the concurrent droughts. The ensemble data of several General Circulation Models (GCMs) considering the high emission scenario of Coupled Model Intercomparison Project phase 6 (CMIP6) are utilized. Applying run theory on a time series (1950–2100) of MSDI values, the duration, severity, areal coverage, and average areal intensity of concurrent droughts are computed. The temporal evolution of drought duration and severity are compared among historical (1950–2014), near future (2021–2060), and far future (2061–2100) timeframes. The results indicate that the most vulnerable regions in the late 21st century are Central America, the Mediterranean, Southern Africa, and the Amazon basin. The indices and spatial extent of the individual droughts are used as predictor variables to predict the country-level crop index of the top seven producers of maize. The historical dynamics between maize yield and different drought forms are projected using XGBoost (Extreme Gradient Boosting) algorithms. The future temporal changes in drought-crop yield dynamics are tracked using probabilities of various drought forms under yield-loss conditions. The conditional concurrent drought probabilities are as high as 84 %, 64 %, and 37 % in France, Mexico, and Brazil, revealing that concurrent drought affects the maize yield tremendously in the far future. This approach of applying statistical and soft-computing techniques could aid in drought mitigation under changing climatic conditions. © 2022 Elsevier B.V.Item Fortnightly Standardized Precipitation Index trend analysis for drought characterization in India(Springer, 2024) Benny, B.; Vinod, D.; Mahesha, A.Climate change is a major concern, as it profoundly affects many facets of our lives. It has brought about several issues, including declining water supply, reduced agricultural yields, increased drought occurrences, and increased heat waves. Amidst these challenges, the influence of short-term drought events on plant growth and irrigation schedule emerges as a critical concern. However, despite these evident consequences, a nuanced understanding of the intricate relationship between the severity and duration of short-period drought/deficit events still needs to be explored. This paper analyses fortnightly water deficit periods over different regions of India, which would be more relevant to re-scheduling the irrigation events than monthly or longer duration in preventing crops from reaching the permanent wilting point. Hence, this work considers analyzing 15-day Standardized Precipitation Index (SPI) trends and drought characteristics using conventional methods and Innovative Trend Analysis (ITA) techniques. The analysis uses gridded rainfall data from the India Meteorological Department (IMD), which has a spatial resolution of 0.250-E and 0.250-N. The data spans the period from 1970 to 2021. The ITA and Mann Kendall (MK) displayed nearly identical areas of increasing and decreasing trends, but ITA effectively identified significant trends. While MK and Modified Mann Kendall (MMK) could only indicate significant trends for 12.94%, 9.57%, and 9.9% of grid points for SPI, drought severity, and duration, respectively, ITA was able to identify significant trends at 44.31%, 10.9%, and 10.1% on an annual scale. The ITA method effectively identified the significant trends and magnitudes of fortnightly SPI and drought characteristics. The Tropical monsoon (Am), Tropical savannah (Aw), Arid desert hot (BWh), Arid steppe hot (BSh), and Temperate dry winter warm summer (Cwb) climatic zones have shown a significant increase in annual drought severity. Similarly, a significant increase in monsoon drought severity is observed across several states, including Gujarat and Mizoram, impacting diverse geographic extents. The present study can help policymakers and water resource managers decide on water allocation, irrigation, and crop management practices. © The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2024.Item Modeling of short-term meteorological drought under changing climate in Gujarat, India(Springer, 2025) Renuka, S.; Vinod, D.; Mahesha, A.Climate change exacerbates droughts globally, challenging traditional stationary methods in identifying natural hazards like droughts. This study examines short-term drought characteristics over Gujarat using three indices: Standardised Precipitation Evapotranspiration Index (SPEI), Standardised Precipitation Index (SPI), and Reconnaissance Drought Index (RDI). Non-stationary models were developed using the Generalised Additive Models for Location, Scale, and Shape (GAMLSS) framework, incorporating local and large-scale climatic covariates and time across 11,700 model combinations. Drought patterns were analysed at fortnightly, monthly, and three-month timescales over 60 grid points. Results indicate that non-stationary droughts are more frequent, severe, and localised than stationary cases. The agreement between stationary and non-stationary methods improves with longer timescales. Among local covariates, diurnal temperature range (DTR) has the highest impact on drought characteristics across all indices and timescales. The Kutch region experiences the highest drought frequency with significantly reduced rainfall, with index values often below ? 1. This study highlights the critical role of non-stationary methods in accurately assessing drought patterns in climatically variable regions like Gujarat. The findings emphasise the need for advanced statistical approaches to enhance drought management and mitigation strategies by incorporating local and large-scale climate influences. © The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2025.