Faculty Publications
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Item Tropical, Seasonal River Basin Development: Hydrogeological Analysis(2011) Shetkar, R.V.; Mahesha, A.This study presents a hydrogeological analysis of a humid tropical, seasonal river in the context of climate change, increasing demand for water, and uneven distribution of rainfall. We investigate the Netravathi basin, a tropical river basin of south India. The climate change effect on the basin was evident in terms of increasing trend in temperature by about 0.7°C/100 years and decreasing trend in the river flow during the monsoon by about 0.8% of average annual flow per year using the Mann-Kendall trend test. Even though rainfall was found to be decreasing, no significant trend could be established. From the trend analysis of the river flow, it was found that there is an overall declining trend with longer scarcity periods. In addition, the trends of magnitude and frequency of high flows are declining. Even though the region receives an average annual rainfall of about 3,930 mm, it has nonuniform distribution with most of the rainfall confining to a few months of a year. In view of this, the region suffers from a prolonged dry period during February to May. The projected domestic water demand of the region for the next 25 years is estimated to be increasing from the present 0.09 mm3 to 0.25 mm3 per day because of rapid urbanization and industrialization. The purpose of this investigation is to highlight the effects of climate change and uneven distribution of rainfall in the river basin. This may assist in proper planning of the basin through strategies such as river water harvesting, which is investigated in the companion paper. Because the Netravathi River is a seasonal and tidal river, and saltwater intrusion along the river during the summer months is affecting the development of the basin. It was found that the river water is affected up to distance of about 22,000 m from the Arabian sea and the wells on the banks of the river are found to be highly vulnerable to saltwater intrusion during the summer period (March to May). © 2011 American Society of Civil Engineers.Item 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.Item Impacts of climate change on varied River-Flow regimes of southern india(American Society of Civil Engineers (ASCE) onlinejls@asce.org, 2017) Mudbhatkal, A.; Raikar, R.V.; Venkatesh, B.; Mahesha, A.This paper assesses the possible impact of climate change on the hydrology of the subhumid and perhumid river regimes originating from the western mountain range (Western Ghats) of India. The modified Mann-Kendall test evaluates the trend of observed data (1975-2004) and RCP 4.5 data (2006-2070) of climatic variables. The results indicate a decreasing trend for annual rainfall over the Malaprabha River catchment (26 mm per year at the 5% significance level), whereas no trend is observed over the Netravathi River catchment at the 10% level. Indian southwestern monsoon rainfall shows a decreasing trend from 84 to 80% of total rainfall in the Malaprabha River catchment and from 80 to 77% in the Netravathi River catchment. Summer rains are found to be increasing in the Malaprabha River catchment (3-4.5% of total rainfall), whereas there is no significant trend for the Netravathi River catchment. Furthermore, the postmonsoon rainfall also shows a significant increase in the Malaprabha catchment (40 mm per decade at the 5% significance level) and the Netravathi catchment (30 mm per decade at the 10% significance level). The Netravathi River shows a decreasing trend for annual flow (0.22 Mm3 per year at the 10% significance level). However, for both catchments the temperature is found to be increasing by 0.2-0.8°C per decade. The soil and water assessment tool (SWAT) model is used to simulate the river catchments and exhibits a Nash-Sutcliffe efficiency of 0.831 and 0.857 for the Malaprabha and Netravathi River catchments, respectively. In addition, a decreasing trend in the high flow is estimated for Netravathi, whereas the trend is increasing for Malaprabha. Thus the impacts of climate change over the Western Ghats are very evident, but the flow of each river responds differently. © 2017 American Society of Civil Engineers.Item 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.Item 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.Item Characterizing extreme rainfall using Max-Stable Processes under changing climate in India(Elsevier B.V., 2025) Vinod, D.; Mahesha, A.Climate change has markedly intensified the frequency and intensity of extreme rainfall events globally over recent decades. The present investigation introduces a novel approach to modeling Intensity-Duration-Frequency (IDF) curves for major river basins in India using max-stable processes (MSPs). In contrast to earlier studies that mainly dealt with univariate extreme value theory and point-based IDF curves, this work uses a variety of MSP characterizations, such as Brown-Resnick, Schlather, Geometric Gaussian, and Extremal-t, to capture the spatial dependencies and non-stationary characteristics of extreme rainfall. This comprehensive two-stage modeling approach incorporates geographical covariates to capture spatial variation in extreme rainfall, followed by additional climate-informed covariates. One hundred fifty-six surface response models are analyzed across nine hourly extreme rainfall durations over 11 river basins. The Brown-Resnick process effectively captured spatiotemporal dependencies across all durations in the annual timeframe, while the Geometric Gaussian process also demonstrated strong performance. During the Indian Monsoon season, distinct covariates such as the Southern Oscillation Index (SOI) and Global Temperature Anomaly (GTA) significantly influenced extreme rainfall patterns. The analysis reveals that the Brahmaputra basin consistently exhibits the highest short-duration extreme rainfall, while the Indus basin shows the lowest. Long-term projections indicate alarming trends, with potential short-duration extreme rainfall reaching 338.9 mm for a 100-year return period in the Godavari basin. The findings highlight the importance of updating IDF relationships in climate variability, providing insights that could lead to disaster preparedness and resilience planning for vulnerable communities across India. © 2025 Elsevier B.V.