Faculty Publications
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Item Bias correction methods for hydrologic impact studies over India's Western Ghat basins(American Society of Civil Engineers (ASCE) onlinejls@asce.org, 2018) Mudbhatkal, A.; Mahesha, M.The regional climate models (RCMs) used in the analysis of the impact of climate variables on the hydrology of river basins needs appropriate preprocessing (bias correction) to represent and reproduce future climate with a fair degree of accuracy. The performance of bias corrections methods was assessed in this investigation on the basis of their ability to minimize error on climate variables and streamflow. This work compares the performance of five bias correction methods applied for precipitation and four methods for temperature in modeling the hydrology of the river catchments of theWestern Ghats of India. TheWestern Ghats are a mountainous forest range along the entire west coast of India that plays a major role in the distribution of Indian monsoon rains. Simulations were used to evaluate the performance of the bias correction methods. Using raw RCM, bias corrected precipitation and temperature time series, streamflows were estimated by the soil and water assessment tool (SWAT) hydrological model. The results indicated that the raw RCM-simulated precipitation was biased by 42% and the temperature was biased by 12% across the catchments investigated. Subsequently, a bias of 65% was found in the streamflow. The performance of the delta change correction method was consistently better for precipitation (with Nash-Sutcliffe efficiency, NSE > 0.75 for 5 catchments) and temperature (NSE = 1) compared with other methods. Good performance was observed between the observed and bias corrected streamflow (daily time scale) for the catchments Purna (NSE = 0.97), Ulhas (NSE = 0.64), Aghanashini (NSE = 0.82), Netravathi (NSE = 0.89), and Chaliyar (NSE = 0.90); low performance with an NSE of 0.3 was observed for the catchments Kajvi and Vamanapuram. The methods failed for Malaprabha and Tunga catchments. The results indicate that the delta change correction method performed best in analyzing the hydrological impact of climate variables on the windward side of Western Ghats of India. © 2017 American Society of Civil Engineers.Item Regional climate trends and topographic influence over the Western Ghat catchments of India(John Wiley and Sons Ltd vgorayska@wiley.com Southern Gate Chichester, West Sussex PO19 8SQ, 2018) Mudbhatkal, A.; Mahesha, M.This study investigates the role of elevation stratification and climate change on the hydrology of Western Ghat catchments during the period from 1951 to 2013 using gridded data. The trend analysis of rainfall and temperature was conducted using the Mann–Kendall trend test, and the hydrological modelling of the rivers was conducted using the Soil and Water Assessment Tool (SWAT) model. To characterize the spatial distribution of rainfall and streamflow based on elevation stratification, contemporary rainfall zones were delineated and the response of each zone was evaluated. The results indicated that the maximum rainfall occurs at certain distance on the windward side from the crest of the Western Ghats. On the leeward side (eastern plateau), the rainfall is maximum at crest (Western Ghats) and decreases with distance. The rivers in the southern portion of the Western Ghats of India were highly vulnerable to changing climate followed by the central portion. The annual and monsoon rainfall in the southern river decreased at 0.43 and 0.30% decade?1 (1% significance level), respectively. The summer rainfall in the river of the central portion (Netravathi River) decreased at 0.44% decade?1. The annual air temperature of the southern river catchment (Vamanapuram) increased at the rate of 0.12 °C decade?1 (at 0.1% significance level), and the air temperature of the central rivers increased at the rate of 0.09, 0.08, and 0.07 °C (0.1% significance level), respectively. The streamflow response of the southern and central rivers was discernible as the monsoon flow decreased at 37% decade?1 (0.1% significance level) in the southern river and 10% decade?1 (5% significance level) in the central river. Interestingly, the pristine Aghanashini River demonstrated resilience to climate change with an increase in annual rainfall and streamflow at 115 mm decade?1 (5% significance level) and 0.71 Mm3 decade?1 (0.1% significance level), respectively. © 2017 Royal Meteorological SocietyItem Assessing climate change impacts on river hydrology – A case study in the Western Ghats of India(Springer, 2018) Sharannya, T.M.; Mudbhatkal, A.; Mahesha, M.The objective of this study is to evaluate the hydrological impacts of climate change on rainfall, temperature and streamflow in a west flowing river originating in the Western Ghats of India. The long-term trend analysis for 110 yr of meteorological variables (rainfall and temperature) was carried out using the modified Mann–Kendall trend test and the magnitude of the trend was quantified using the Sen’s slope estimator. The Regional Climate Model (RCM), COordinated Regional climate Downscaling EXperiment (CORDEX) simulated daily weather data of baseline (1951–2005) and future RCP 4.5 scenarios (2006–2060) were used to run the hydrological model, Soil and Water Assessment Tool (SWAT), in order to evaluate the effect of climate change on rainfall, temperature and streamflow. Significant changes were observed with regard to rainfall, which have shown decreasing trend at the rate of 2.63 mm per year for the historical and 8.85 mm per year for RCP 4.5 future scenarios. The average temperature was found to be increasing at 0.10?C per decade for both historical and future scenarios. The impact of climate change on the annual streamflow yielded a decreasing trend at the rate of 1.2Mm3 per year and 2.56 Mm 3, respectively for the past and future scenarios. The present work also investigates the capability of SWAT to simulate the groundwater flow. The simulated results are compared with the recession limb of the hydrograph and were found to be reasonably accurate. © 2018, Indian Academy of Sciences.Item Estimating anisotropic heterogeneous hydraulic conductivity and dispersivity in a layered coastal aquifer of Dakshina Kannada District, Karnataka(Elsevier B.V., 2018) Priyanka, B.N.; Kumar, M.S.; Mahesha, M.The solution for the inverse problem of seawater intrusion at an aquifer scale has not been studied as extensively as forward modeling, because of the conceptual and computational difficulties involved. A three-dimensional variable-density conceptual phreatic model is developed by constraining with real-field data such as layering, aquifer bottom topography and appropriate initial conditions. The initial aquifer parameters are layered heterogeneous and spatially homogeneous that are based on discrete field measurements. The developed conceptual model shows poor correlation with observed state variables (hydraulic head and solute concentration), signifying the importance of spatial heterogeneity in hydraulic conductivity and dispersivity of all the layers. The conceptual model is inverted to estimate the anisotropic spatially varying hydraulic conductivity and the longitudinal dispersivity at the pilot points by minimizing the least square error of state variables across the observation wells. The inverse calibrated model is validated for the hydraulic head at validation wells and the solute concentration is validated with equivalent solute concentration derived from the electrical resistivity, which shows good results against the field measurements. The verification of estimated anisotropic hydraulic conductivity with the electrical resistivity tomography image shows good agreement. This investigation gives an insight about constraining the highly parameterized inverse model with real-field data to estimate spatially varying aquifer parameters for an effective simulation of the seawater intrusion in a layered coastal aquifer. © 2018 Elsevier B.V.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 Evaluation of satellite precipitation products in simulating streamflow in a humid tropical catchment of india using a semi-distributed hydrological model(MDPI, 2020) Sharannya, T.M.; Al-Ansari, N.; Deb Barma, S.; Mahesha, M.Precipitation obtained from rain gauges is an essential input for hydrological modelling. It is often sparse in highly topographically varying terrain, exhibiting a certain amount of uncertainty in hydrological modelling. Hence, satellite rainfall estimates have been used as an alternative or as a supplement to station observations. In this study, an attempt was made to evaluate the Tropical Rainfall Measuring Mission (TRMM) and Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), employing a semi-distributed hydrological model, i.e., Soil and Water Assessment Tool (SWAT), for simulating streamflow and validating them against the flows generated by the India Meteorological Department (IMD) rainfall dataset in the Gurupura river catchment of India. Distinct testing scenarios for simulating streamflow were made to check the suitability of these satellite precipitation data. The TRMM was able to better estimate rainfall than CHIRPS after performing categorical and continuous statistical results with respect to IMD rainfall data. While comparing the performance of model simulations, the IMD rainfall-driven streamflow emerged as the best followed by the TRMM, CHIRPS-0.05, and CHIRPS-0.25. The coefficient of determination (R2), Nash–Sutcliffe efficiency (NSE), and percent bias (PBIAS) were in the range 0.63 to 0.86, 0.62 to 0.86, and ?14.98 to 0.87, respectively. Further, an attempt was made to examine the spatial distribution of key hydrological signature, i.e., flow duration curve (FDC) in the 30–95 percentile range of non-exceedance probability. It was observed that TRMM underestimated the flow for agricultural water availability corresponding to 30 percent, even though it showed a good performance compared to the other satellite rainfall-driven model outputs. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.Item Simulation of coastal aquifer using mSim toolbox and COMSOL multiphysics(Springer, 2020) Kumar, S.S.; Deb Barma, S.; Mahesha, M.Fluctuations in groundwater levels along the coast have a significant impact on the extent of saltwater intrusion into freshwater aquifers. This study aims to simulate the groundwater flow and solute transport in the region by using the mSim toolbox in the MATLAB and COMSOL Multiphysics. The investigation is focussed on a micro-basin of Pavanje river located along the west coast of India. The model results are calibrated and validated against the field observations. The results show that the variation of the water table over the year is significant and range from about 3–14 m. There exists a reasonable correlation between the simulated and observed values of groundwater level and salinity. The wells that are most vulnerable to seawater intrusion in the region are identified. The COMSOL model estimated a salinity range of 0–20 mol/m3. Additionally, the model is used to understand the response of coastal aquifer to various stress scenarios. The study reveals that reduced recharge rate with increased pumping has a serious impact on aquifer system. © 2020, Indian Academy of Sciences.Item Multivariate analysis of concurrent droughts and their effects on Kharif crops—A copula-based approach(John Wiley and Sons Ltd, 2022) Muthuvel, D.; Mahesha, M.Apart from creating an ecological imbalance, drought events could affect an agrarian country's economy and food security by reducing crop yields. The antecedent meteorological droughts could prolong into hydrological and (or) agricultural droughts and may co-exist as concurrent droughts. The current study aims to comprehensively study Indian concurrent droughts, their effects on crop yield, and possible teleconnection with ENSO (El Niño–Southern Oscillation), adopting a copula-based multivariate approach. The copula functions can replicate the correlation among the variables and keep the dependence structure intact. The concurrent drought characteristics are computed using a multivariate standardized drought index that incorporates the three primary drought indices using the Gaussian copula. Some of the severe concurrent drought years such as 2002, 1987, 1972, and 1965 caused considerable yield losses in Kharif season crops of groundnut, millet, and rice. This prompts to construct quad-variate models involving the crop yield and the three drought indices using the vine copulas that perform better than the elliptical and symmetric Archimedean copula. Though the isolated forms of droughts could cause mild yield losses, the probability of concurrent droughts causing high to exceptional losses is more. Further, the ENSO teleconnection with the concurrent monsoon droughts is analysed and mapped. The above-normal warming of the Nino 3.4 region over the tropical Pacific during the months leading up to the monsoon could signal concurrent monsoon droughts in the areas under the Ganga-Brahmaputra basin at a probability of around 45%. These results could be helpful in drought mitigation measures and policymaking. © 2021 Royal Meteorological Society.Item Regional Trends and Spatiotemporal Analysis of Rainfall and Groundwater in the West Coast Basins of India(American Society of Civil Engineers (ASCE), 2022) Krishnan, C.; Mahesha, M.The present study investigates the spatiotemporal variabilities of long-term (1950-2016) rainfall and regional groundwater levels for annual and seasonal periods over the west coast of India. The study area is a narrow strip of land between Western Ghats (mountainous terrain) and the Arabian Sea, extending over 1,500 km from south to north. The Mann Kendall (MK) and Sen's slope estimator established the long-term trend and magnitude of rainfall and groundwater. The nature of trends in the time series of hydroclimatic variables was identified through singular spectrum analysis (SSA). The SSA extracted nonlinear trends along with the shape for both increasing and decreasing trends. Annual and southwest monsoon rainfall exhibited prominent decreasing trends. The percentage departure analysis of rainfall revealed that earlier decades (1950-1980) were the wettest, followed by the drier decades (1980-2016) for Periyar, Varrar, and Netravati and vice versa for Vasishti and Bhatsol. The wavelet spectra for rainfall indicated short- and long-term modulations. The long-term groundwater level trends of 725 wells on the entire west coast showed a significant decline in 13% of wells, and 6% of wells indicated increasing trends. The Monte Carlo-based numerical investigations on the modified MK (mMK) test power indicated the influence of parent distributions on trend detection. The field significance of trends at a 5% significance level was examined using the bootstrap test. The precipitation data were then compared with groundwater level variation at each site, and correlations were established. The declining southwest monsoon rains and their uneven spatial distribution could be attributed to a subsequent decline in the region's postmonsoon groundwater levels. © 2022 American Society of Civil Engineers.Item Enhanced streamflow simulations using nudging based optimization coupled with data-driven and hydrological models(Elsevier B.V., 2022) Sharannya, S.; Venkatesh, V.; Mahesha, M.; Acharya, T.D.Study region: Varahi River originating from the Western Ghats of India. Study focus: We developed a hybrid model that integrates process-based hydrological model (PHM) and data-driven (DD) techniques to generate streamflow simulations precisely. The hybrid modeling framework is practical as it respects hydrological processes through the PHM while considering the advantage of the DD model's ability to simulate the complex relationship between residuals and input variables. Further, we have proposed an optimization-based nudging scheme for post-processing the hybrid model simulated streamflow to overcome the limitations in PHM and DD. New hydrological insights for the region: We formulated two approaches for simulating streamflow ensembles using DD and PHM models. In approach− 1, DD models are initially used to ensemble meteorological variables and then use the ensembles in a PHM to simulate streamflows. In approach− 2, PHM is forced with different sets of meteorological variables to simulate multiple streamflow sets and then use DD models to ensemble the PHM-derived streamflows. Random forest exhibited better performance for ensembling precipitation, temperature, and streamflow datasets compared to the other five DD algorithms in the study. Streamflows generated using approach− 2 showed reliable estimates when compared against observed streamflow values. However, post-processing the hybrid streamflows using an optimization-based nudging scheme outperformed the streamflows generated in approach− 1 and approach− 2 with better model fit statistics (R2 and NSE of 0.69 and 0.66). The output from the nudging scheme was further utilized for streamflow predictions under the combined impact of land use/cover (LULC) and climate change (CC) under the Representative Concentration Pathway 4.5 scenario. It depicted a decrease in monthly and seasonal stream flows with − 22.65 %, − 31.77 %, − 11.81 % for winter, summer, and monsoon seasons, respectively. These results suggest that water availability will decline, and water scarcity will increase in the study region. These variations in streamflow might negatively impact agriculture and natural ecosystems and even lead to water restrictions in the region. © 2022 The Authors