Faculty Publications

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Predictive Simulation of Seawater Intrusion in a Tropical Coastal Aquifer
(American Society of Civil Engineers (ASCE) onlinejls@asce.org, 2016) Lathashri, U.A.; Mahesha, A.
The solute transport in a tropical, coastal aquifer of southern India is numerically simulated considering the possible cases of aquifer recharge, freshwater draft, and seawater intrusion using numerical modeling software. The aquifer considered for the study is a shallow, unconfined aquifer with lateritic formations having good monsoon rains up to about 3,000 mm during June to September and the rest of the months almost dry. The model is calibrated for a two-year period and validated against the available dataset, which gave satisfactory results. The groundwater flow pattern during the calibration period shows that for the month of May a depleted water table and during the monsoon month of August a saturated water table was predicted. The sensitivity analysis of model parameters reveals that the hydraulic conductivity and recharge rate are the most sensitive parameters. Based on seasonal investigation, the seawater intrusion is found to be more sensitive to pumping and recharge rates compared to the aquifer properties. The water balance study confirms that river seepage and rainfall recharge are the major input to the aquifer. The model is used to forecast the landward movement of seawater intrusion because of the anticipated increase in freshwater draft scenarios in combination with the decreased recharge rate over a longer period. The results of the predictive simulations indicate that seawater intrusion may still confine up to a distance of approximately 450-940 m landward for the scenarios considered and thus are sustainable. © 2015 American Society of Civil Engineers.
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.
Large-scale atmospheric teleconnections and spatiotemporal variability of extreme rainfall indices across India
(Elsevier B.V., 2024) Vinod, D.; Mahesha, A.
Identifying trends in hydrometeorological time series during extreme weather events and their interactions with large-scale atmospheric teleconnections is crucial for climate change research. This study evaluates 14 precipitation-based indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI) across seven climatic zones of India using gridded daily rainfall data from the India Meteorological Department (IMD) for 120 years (1902–2021) utilised. Trend analysis was carried out using the Mann-Kendall (MK) test, Theil-slope Sen's estimator, Innovative Trend Analysis (ITA), and other statistical tools. Change point detection is established using the Pettitte test and Cumulative Sum algorithm. The relationships between large-scale atmospheric teleconnections and ETCCDI indices are also found, and Multiple Linear Regression (MLR) models are developed between them. The results show significant increasing trends in extreme rainfall indices in India's Ladakh region, located in the arid desert-cold climatic zone. The annual, Southwest Monsoon (SW-Monsoon), Northeast Monsoon (NE-Monsoon), and summer rainfall trends were positive, while winter rainfall had a negative trend across most climatic zones. Significant associations between large-scale atmospheric teleconnections, including Arctic Oscillation (AO), Pacific Decadal Oscillation (PDO), Global Temperature Anomaly (GTA), Southern Oscillation Index (SOI), SST of Niño 3.4 region, Oceanic Niño Index (ONI), and Dipole Mode Index (IOD) and ETCCDI indices were established across multiple climatic zones. Using MLR analysis, this study attempts to establish, for the first time, the relationship between teleconnections and ETCCDI indices across India. Extreme rainfall indices are influenced by climate change during the SW-Monsoon across most of the climatic zones of India. During the previous El Niño event (2014–2016), average annual rainfall decreased by 19.5%, SW-Monsoon rainfall decreased by 25.2%, and NE-Monsoon rainfall decreased by 64.1% in India. The findings may provide valuable insights into mitigation strategies to sustain the adverse effects of extreme weather conditions and enhance climate resilience. © 2023 Elsevier B.V.

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