Faculty Publications

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Author: search.filters.author.Mahesha, A.Subject: search.filters.subject.precipitation assessment

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    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.
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    Trends of seasonal and annual rainfall of semi-arid districts of Karnataka, India: application of innovative trend analysis approach
    (Springer, 2023) Chowdari, K.; Deb Barma, S.D.; Bhat, N.; Girisha, R.; Gouda, K.C.; Mahesha, A.
    Trend analysis of rainfall is often carried out in water resources management to understand its distribution over a given region. The cumulative seasonal and annual rainfall derived from monthly datasets spanning 102 years (1901–2002) for 11 districts of the semi-arid Karnataka, India, was used for the trend analysis. The two-step homogeneous test approach was carried out on all the time series. Then, lag-1 autocorrelation was conducted only on homogeneous time series. Only 78.18 % of the total time series data were detected as homogeneous, and 95.35% of time series data were found to have insignificant autocorrelation. Then, the Innovative Trend Analysis (ITA) method was applied to 43 homogeneous rainfall time series, as well as to 41 time series using the MK and SR tests, and to two time series using the mMK test. The MK and SR tests detected a significant trend in 14.63% of the time series, while the ITA method was able to detect a trend in 93.02% of the total time series data. The MK and SR tests revealed significant trends in winter and post-monsoon season precipitation for two districts, but only for one district in the case of summer and annual rainfall. No trend was identified for monsoon season precipitation. The mMK test showed a positive trend for the post-monsoon season in a district, while the ITA method revealed significant trends for all seasons in most districts. The sub-trend analysis revealed trends that traditional methods were unable to detect. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.
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    Evaluation of GPM IMERG satellite precipitation for rainfall–runoff modelling in Great Britain
    (Taylor and Francis Ltd., 2024) Gautam, J.; O, S.; Vinod, D.; Mahesha, A.
    Reliable hydrological simulations require accurate precipitation data. However, data uncertainties due to the indirect nature of satellite estimates can propagate through hydrological models and lead to simulation errors. This study assesses the accuracy of Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG) products, comparing them directly with ground-based precipitation data and evaluating their performance in rainfall–runoff modelling across Great Britain. Three IMERG V06 products (IMERG-Early, IMERG-Late, and IMERG-Final) are examined. Utilizing the simple water balance model (SWBM), the analysis covers 250 basins, revealing that the SWBM performs well in over 50% of the basins. Runoff estimations show that European Observation (E-OBS) ground-based data yield the highest Nash-Sutcliffe efficiency (NSE) score (0.91), followed by IMERG-Final (0.85), IMERG-Late (0.82), and IMERG-Early (0.73). The findings underscore IMERG’s utility in hydrological modelling for ungauged or poorly gauged basins. © 2024 IAHS.