Faculty Publications
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Item Associative study of NDVI and precipitation in Indian region during monsoon season using satellite and ground measurements [2000-2013](Institute of Electrical and Electronics Engineers Inc., 2016) Mehta, M.; Dubey, S.Natural vegetation cover and crop yield vary spatially and temporally in a diverse manner. Understanding this variation requires a robust analysis of important climatic factors such as rainfall, temperature, sunshine hours etc., along with LULC dynamics. In this study, NDVI has been used as an indicator of vegetative greenness and productivity. Based on 0.5°×0.5° spatial resolution data of NDVI obtained from MISR, correlation between NDVI and average seasonal precipitation has been analyzed. The precipitation data used is obtained from two sources, TRMM 3B42-V7 and IMD gridded data, both at spatial resolution of 0.25°×0.25°. The TRMM and IMD data have also been mutually correlated. Data was acquired for the months of June, July, August and September (JJAS) i.e. monsoon season for 14 years, 2000 to 2013. The correlation coefficients thus obtained are reported significant at a confidence level of 99% (p<0.001). © 2015 IEEE.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 Quantifying aquifer properties and freshwater resource in coastal barriers: A hydrogeophysical approach applied at Sasihithlu (Karnataka state, India)(2012) Vouillamoz, J.-M.; Hoareau, J.; Grammare, M.; Caron, D.; Nandagiri, L.; Legchenko, A.Many human communities living in coastal areas in Africa and Asia rely on thin freshwater lenses for their domestic supply. Population growth together with change in rainfall patterns and sea level will probably impact these vulnerable groundwater resources. Spatial knowledge of the aquifer properties and creation of a groundwater model are required for achieving a sustainable management of the resource. This paper presents a ready-to-use methodology for estimating the key aquifer properties and the freshwater resource based on the joint use of two non-invasive geophysical tools together with common hydrological measurements.
We applied the proposed methodology in an unconfined aquifer of a coastal sandy barrier in South-Western India. We jointly used magnetic resonance and transient electromagnetic soundings and we monitored rainfall, groundwater level and groundwater electrical conductivity. The combined interpretation of geophysical and hydrological results allowed estimating the aquifer properties and mapping the freshwater lens. Depending on the location and season, we estimate the freshwater reserve to range between 400 and 700 L m??'2 of surface area (A± 50%). We also estimate the recharge using time lapse geophysical measurements with hydrological monitoring. After a rainy event close to 100% of the rain is reaching the water table, but the net recharge at the end of the monsoon is less than 10% of the rain. Thus, we conclude that a change in rainfall patterns will probably not impact the groundwater resource since most of the rain water recharging the aquifer is flowing towards the sea and the river. However, a change in sea level will impact both the groundwater reserve and net recharge. © Author(s) 2012.Item Comparison of Oceansat-2 scatterometer- to buoy-recorded winds and spatial distribution over the Arabian Sea during the monsoon period(Taylor and Francis Ltd. michael.wagreich@univie.ac.at, 2015) Gadad, S.; Deka, P.C.For this wind resource assessment (WRA) study, wind speed and direction are the fundamental inputs. Also, these studies are data driven and require large historical wind speed data sets available on the site. This work explores the application of space-based scatterometer winds for assimilation into WRA studies towards the development of offshore wind energy. This article focuses on estimating the performance of Oceansat-2 scatterometer (OSCAT)-derived wind vector using in situ data from buoys at different locations in the Arabian Sea. A comparative study between three methods for estimating the equivalent neutral winds (ENW) for buoys is carried out. OSCAT winds were closest to ENW estimated by the Liu–Katsaros–Businger (LKB) method. The spatial and temporal windows for comparison were 0.5° and ±60 minutes, respectively. The monsoon months (June–September) of 2011 were selected for study. The root mean square deviation for wind speed is less than 2.5 m s?1 and wind direction is less than 20°, and a small positive bias is observed in the OSCAT wind values. From the analysis, the OSCAT wind values are consistent with in situ-observed values. Furthermore, wind atlas maps were developed with OSCAT winds, representing the spatial distribution of winds at a height of 10 m over the Arabian Sea. © 2015 Taylor & Francis.Item Prediction model for peninsular Indian summer monsoon rainfall using data mining and statistical approaches(Elsevier Ltd, 2017) Vathsala, H.; Koolagudi, S.G.In this paper we discuss a data mining application for predicting peninsular Indian summer monsoon rainfall, and propose an algorithm that combine data mining and statistical techniques. We select likely predictors based on association rules that have the highest confidence levels. We then cluster the selected predictors to reduce their dimensions and use cluster membership values for classification. We derive the predictors from local conditions in southern India, including mean sea level pressure, wind speed, and maximum and minimum temperatures. The global condition variables include southern oscillation and Indian Ocean dipole conditions. The algorithm predicts rainfall in five categories: Flood, Excess, Normal, Deficit and Drought. We use closed itemset mining, cluster membership calculations and a multilayer perceptron function in the algorithm to predict monsoon rainfall in peninsular India. Using Indian Institute of Tropical Meteorology data, we found the prediction accuracy of our proposed approach to be exceptionally good. © 2016 Elsevier LtdItem Long-range prediction of Indian summer monsoon rainfall using data mining and statistical approaches(Springer-Verlag Wien michaela.bolli@springer.at, 2017) Vathsala, H.; Koolagudi, S.G.This paper presents a hybrid model to better predict Indian summer monsoon rainfall. The algorithm considers suitable techniques for processing dense datasets. The proposed three-step algorithm comprises closed itemset generation-based association rule mining for feature selection, cluster membership for dimensionality reduction, and simple logistic function for prediction. The application of predicting rainfall into flood, excess, normal, deficit, and drought based on 36 predictors consisting of land and ocean variables is presented. Results show good accuracy in the considered study period of 37years (1969–2005). © 2016, Springer-Verlag Wien.Item Spatio-temporal precipitation variability over Western Ghats and Coastal region of Karnataka, envisaged using high resolution observed gridded data(Springer Science and Business Media Deutschland GmbH, 2017) Doranalu Chandrashekar, V.; Shetty, A.; Singh, B.B.; Sharma, S.Climatic changes in the recent decades have led to large variations in precipitation over the different geographical regions of the globe. Changes in precipitation pattern over the space and time can severely affect the country like India, which has a large spatio-temporal variability in the precipitation. Any shift in the mean precipitation pattern pose a challenge to economy, agricultural farming and the ecosystem of these regions. In the present study, we analyze the seasonal spatio-temporal variation in trends of long term (1901–2013) observed high resolution (0.25° × 0.25°) gridded daily precipitation data of the Indian Meteorological Department over Western Ghats and coastal region of Karnataka, vulnerable to the risks of climate change. Our analysis shows increasing trend in seasonal ratio of precipitation over the Southern coastal plains and the adjacent Western Ghats region during pre-monsoon (MAM) while the southern coastal plains show decreasing trend in monsoon period (JJAS). Daily intensity index of precipitation during monsoon shows increasing trend in northern plains with decreasing trend in the medium precipitation events. Our study finds that different topographic regions of Karnataka have different responses in the trends of precipitation, particularly the response of plains is quite different to that of the higher elevated Ghat region. © 2017, Springer International Publishing AG, part of Springer Nature.Item Occurrence and environmental risks of nonsteroidal anti-inflammatory drugs in urban wastewater in the southwest monsoon region of India(Springer, 2020) Thalla, A.K.; Vannarath, A.S.Municipal wastewater treatment plants (MWWTPs) are considered to reduce the amount of pollutants that enter water reservoirs as a result of wastewater disposal. An assessment of the occurrence and removal of pharmaceutical compounds, mainly nonsteroidal anti-inflammatory drugs (NSAIDs), in wastewater from the Kavoor MWWTP (southwest monsoon region), India, is presented in this paper. The performance of the MWWTP was monitored in the summer (May) and monsoon (September) periods. The highest inlet concentrations of diclofenac, naproxen, ibuprofen, ketoprofen, and acetylsalicylic acid in the wastewater were observed in May and were 721.37, 2132.48, 2109.875, 2747.29, and 2213.36 ?g/L, respectively. The ketoprofen content was found to be higher than that of other NSAIDs in the influent in both seasons, whereas the diclofenac content was found to be the lowest. The removal efficiency (RE) of the target NSAIDs in the Kavoor secondary treatment plant varied from 81.82–98.92% during the summer season. During the monsoon season, the influent NSAID concentration level dropped, probably because of infiltration in old sewer pipes. In addition, a 100% RE was achieved for all the target NSAIDs in the wastewater of the MWWTP. The results showed that secondary treatment plants have the potential to remove NSAID compounds from municipal sewage with consistent performance. The environmental hazards caused by the accumulation of such compounds in water reservoirs are due to open discharge. The environmental risk levels of these compounds were also studied by the environmental risk assessment (ERA) using the European Agency for Evaluation of Medicines approach. © 2020, Springer Nature Switzerland AG.Item Bivariate Modeling of Hydroclimatic Variables in Humid Tropical Coastal Region Using Archimedean Copulas(American Society of Civil Engineers (ASCE) onlinejls@asce.org 1801 Alexander Bell DriveGEO Reston VA 20191 Alabama, 2020) Uttarwar, S.B.; Deb Barma, S.; Mahesha, M.The present study focuses on the dependence modeling of hydroclimatic variables such as the El Niño-Southern Oscillation (ENSO) index, precipitation, tidal height, and groundwater level (GWL) in humid tropical coastal region of India. The rank-based correlation coefficient was used to determine the dependence between the pairs of cumulative monsoon precipitation of June-July-August-September (P_JJAS) and the postmonsoon groundwater level (PMGWL), ENSO-P_JJAS, ENSO-PMGWL, and GWL-tidal height. The results indicated that P_JJAS-PMGWL, ENSO-PMGWL, and GWL-tidal height had significant dependence, whereas P_JJAS-ENSO had no significant dependence. The best fit distributions for P_JJAS, PMGWL, and tidal height were found to be lognormal, extreme value, and generalized extreme value distributions, respectively, whereas for the ENSO index, it was the normal kernel-density function. The Archimedean families of copulas were used for dependence modeling, and it was observed that the ENSO-PMGWL was best modeled by the Frank copula, the P_JJAS-PMGWL by the Gumbel-Hougaard copula, and the GWL-tidal height by the Frank copula. The copula-based conditional probability for the Gumbel-Hougaard and Frank copulas for GWL were obtained to understand the risk associated with other hydroclimatic variables. Thus, copula-based dependence modeling could be useful for understanding the risk among hydroclimatic variables including groundwater. © 2020 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.