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 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 Assessment of Bi-Decadal Groundwater Fluctuations in a Coastal Region Using Innovative Trends and Singular Spectrum Analysis(Springer, 2023) Krishnan, C.; Mahesha, A.Coastal areas are among the densely populated regions in the world with growing population and subsequent increasing demands for water. Understanding the long-term variations in available water resources aids in efficient water conservation, management and allocation strategies. The present study investigated the long-term trends in groundwater depths (GWDs) for pre-monsoon and post-monsoon seasons in the coastal district of Kollam during the period 1996∼2017, where groundwater is the primary source for domestic and agricultural uses during summer season. The trends examined using the modified Mann Kendall (mMK), innovative trend analysis (ITA) and Sen’s slope estimator indicated a decreasing pre-monsoon GWD trends at an average of −0.5m/decade in 63% of the wells, while increasing post-monsoon GWD trends at an average rate of +0.43m/decade in 72% of the wells at 5% significance level. The singular spectrum analysis (SSA) captured monotonic as well as non-monotonic trend trajectories for the GWDs. About 41% wells exhibited a correlation below — 0.5 (p<0.05) between post-monsoon GWDs and JJASO (June, July, August, September and October) rainfall totals. The increasing post-monsoon GWDs could be related to recent changes in the southwest monsoon patterns over the peninsular India. Adequate planning and management of existing water resources could impart better control on water conservation strategies under the scenario of climate change. © 2023, Geological Society of India, Bengaluru, India.Item 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.