Faculty Publications
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Item Discrete wavelet-Ann approach in time series flow forecasting-a case study of Brahmaputra river(2012) Deka, P.C.; Haque, L.; Banhatti, A.G.This paper deals with the prediction of hydrologic behavior of the runoff for the one of the largest discharge carrier International River, Brahmaputra, located in Assam (India) at the Pandu station, by using daily time unit. The flow regime dominated by high data non-stationary and seasonal irregularity due to Himalayan climate fallout. The influence of data preprocessing through wavelet transforms has been investigated. For this, the main time series of flow data were decomposed to multi resolution time series using discrete wavelet transformations. Then these decomposed data were used as input to Artificial Neural Network (ANN) for multiple lead time flow forecasting. Various types of wavelets were used to evaluate the optimal performance of models developed. The forecasting accuracy of the models has been tested for multiple lead time upto 4 days using different decomposition levels. The performance of the proposed hybrid model has been evaluated based on the performance indices such as root mean square error (RMSE), coefficient of efficiency (CE) and mean relative error (MRE).The results shows the better forecasting accuracy by the proposed combined hybrid model over the single ANN model in hydrological time series forecasting. © 2012 CAFET-INNOVA TECHNICAL SOCIETY.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 Evaluating uncertainty of the soil and water assessment tool (SWAT) model in the upper cauvery basin, Karnataka, India(CAFET INNOVA Technical Society 1-2-18/103, Mohini Mansion, Gagan Mahal Road, Domalguda, Hyderabad 500029, 2015) Kumar Raju, B.C.; Nandagiri, L.Quantification of uncertainties associated with hydrological models are essential for accurate assessment of water balance components and optimal planning and management of water and land resources at basin-scale. The present study was taken up to evaluate the uncertainties associated with the Soil and Water Assessment Tool (SWAT) model using for two different techniques: i) Generalized Likelihood Uncertainty Estimation (GLUE) and ii) Sequential Uncertainty Fitting (SUFI-2) techniques. The study was carried out in the Upper Cauvery River basin (36,682 km2) located in the humid to sub-humid region of Karnataka State, India. The calibration of the model was carried out using the Nash – Sutcliffe (NS) coefficient as the objective function for both GLUE and SUFI-2 techniques. The P-factor was 67% and 71% of observed streamflow data bracketed by the 95% prediction uncertainty (95PPU) for GLUE and SUFI-2 respectively during calibration period and corresponding values of 54% and 61% during validation period. Overall results indicate the applicability of SWAT model with moderate levels of uncertainty in large basins located in the humid tropics. The calibrated SWAT model can be used for assessment of water balance components and land use management scenarios in the Upper Cauvery Basin. © 2015 CAFET-INNOVA TECHNICAL SOCIETY. All rights reserved.Item Identification and Apportionment of Pollution Sources to Groundwater Quality(Springer Basel info@birkhauser-science.com, 2016) Gulgundi, M.S.; Shetty, A.Characterizing groundwater quality and apportionment of pollution sources to groundwater pollution is important for managing water resources effectively. Owing to rapid industrialization and population growth in Bengaluru city, the groundwater quality is getting deteriorated. Receptor modeling by Multi-Linear Regression of the Absolute Principal Component Scores (APCS-MLR) has been used to evaluate the source apportionment of groundwater pollution in order to recognize and quantify the pollution sources. Groundwater quality data measured for pre-monsoon and post-monsoon in the year 2014, comprising 14 physico-chemical parameters from 68 sites distributed across the study area, have been used. Principal component analysis identified four factors explaining 79.2 % of the total variance. Receptor modeling using APCS-MLR provided apportionment of different sources responsible for the groundwater quality along with percentage contribution of the recognized sources to each parameter. Results revealed that most of the variables were primarily affected by rock water interactions, seepage of sewage and industrial effluent. It was also found that few parameters gained significant contribution from the unidentified sources. Finally, the model performance was evaluated based on the ratio of estimated mean to measured mean (E/M). It was found that except for Fe with (E/M) ratio as high as 7.1, the model showed moderate strength with (E/M) values ranging from 0.51 to 2.83 of all the other parameters. © 2016, Springer International Publishing Switzerland.Item Daily pan evaporation modeling in climatically contrasting zones with hybridization of wavelet transform and support vector machines(Springer Verlag service@springer.de, 2017) Pammar, L.; Deka, P.C.The estimation of evaporation has been under surveillance, which is being carried out by many researchers toward applications in the fields related to hydrology and water resources management. Due to complexities associated with its estimation, research has employed several modes via direct and indirect methods to estimate. Accurate estimations are still the thrust area of research in these fields. The pan evaporation estimations with the help of data modeling techniques have provided better results in the recent past. The advancement in the field of data modeling has introduced several techniques which can best fit the data type and provide accurate estimations. The novel gamma test (GT) was used to decide the best input–output combination. Parameter optimization was carried out by grid search. The developed models gave better estimations of pan evaporation, but exhibited some limitations with nonlinearity, and sparse and noisy data. These limitations paved way for data pre-processing techniques such as wavelet transform. This study made an attempt to explore hybrid modeling using discrete wavelet transform (DWT) and support vector machines (SVR) for pan evaporation estimation. Two stations representing contrasting climatic zones namely ‘Bajpe’ and ‘Bangalore’ located in the state of Karnataka, India, are selected in this study. The meteorological datasets recorded at these stations are analyzed using gamma test and grid search to use the best input–output combinations for the models. The modeled pan evaporation estimations are very promising toward ever demanding accuracy expected in the associated fields. © 2017, The International Society of Paddy and Water Environment Engineering and Springer Japan.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 Assessment of variable source area hydrological models in humid tropical watersheds(Taylor and Francis Ltd. michael.wagreich@univie.ac.at, 2018) Kumar Raju, B.C.K.; Nandagiri, L.The objective of this study was to compare the performances of hydrological models that incorporate the Variable Source Area (VSA) mechanism of runoff generation with that of the Soil and Water Assessment Tool (SWAT), which uses the infiltration-excess mechanism. One of the VSA-based model used, SWAT–VSA, has been proposed as a re-conceptualization of the SWAT and uses a topography-based wetness index to identify source areas. In this study, the topography-based wetness index was replaced with a Modified Normalized Difference Water Index (MNDWI) derived from satellite imagery resulting in the SWAT–MNDWI model. Model performances were evaluated through their application in two humid tropical watersheds (Hemavathi–2974 km2; Harangi–538.8 km2) located in the Upper Cauvery River Basin, India. Using relevant data inputs, the three models were applied separately to both watersheds. Models were calibrated for the historical period 2000–2003 and validated for the period 2004–2006 using observed daily observed streamflow records at the watershed outlets. Overall, the SWAT–MNDWI model was the best one in simulating daily streamflow with Nash–Sutcliffe efficiency of 0.85, coefficient of determination of 0.88, percentage bias of 13.2% and root mean square error of 37.48 m3/s for the Hemavathi watershed and corresponding values of 0.88, 0.88, 1.09% and 16.67 m3/s for the Harangi watershed. The spatial patterns of surface runoff generation were similar for the SWAT–VSA and SWAT–MNDWI models, but completely different for the SWAT model. Overall results have demonstrated that models incorporating VSA hydrology, and in particular the proposed SWAT–MNDWI model, provide accurate and convenient tools for distributed hydrologic modelling in humid tropical watersheds. © 2017 International Association for Hydro-Environment Engineering and Research.Item Improved vegetation parameterization for hydrological model and assessment of land cover change impacts on flow regime of the Upper Bhima basin, India(Springer International Publishing kasia@cesj.com, 2018) Mohaideen, M.M.D.; Varija, K.This study investigates the potential and applicability of variable infiltration capacity (VIC) hydrological model to simulate different hydrological components of the Upper Bhima basin under two different Land Use Land Cover (LULC) (the year 2000 and 2010) conditions. The total drainage area of the basin was discretized into 1694 grids of about 5.5 km by 5.5 km: accordingly the model parameters were calibrated at each grid level. Vegetation parameters for the model were prepared using temporal profile of Leaf Area Index (LAI) from Moderate-Resolution Imaging Spectroradiometer and LULC. This practice provides a methodological framework for the improved vegetation parameterization along with region-specific condition for the model simulation. The calibrated and validated model was run using the two LULC conditions separately with the same observed meteorological forcing (1996–2001) and soil data. The change in LULC has resulted to an increase in the average annual evapotranspiration over the basin by 7.8%, while the average annual surface runoff and baseflow decreased by 18.86 and 5.83%, respectively. The variability in hydrological components and the spatial variation of each component attributed to LULC were assessed at the basin grid level. It was observed that 80% of the basin grids showed an increase in evapotranspiration (ET) (maximum of 292 mm). While the majority of the grids showed a decrease in surface runoff and baseflow, some of the grids showed an increase (i.e. 21 and 15% of total grids—surface runoff and baseflow, respectively). © 2018, Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences.Item 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 Evaluating the Performance of Secondary Precipitation Products through Statistical and Hydrological Modeling in a Mountainous Tropical Basin of India(Hindawi Limited, 2020) Venkatesh, K.; Krakauer, N.Y.; Sharifi, E.; Ramesh, H.This paper investigates the performance of gridded rainfall datasets for precipitation detection and streamflow simulations in Indias Tungabhadra river basin. Sixteen precipitation datasets categorized under gauge-based, satellite-only, reanalysis, and gauge-adjusted datasets were compared statistically against the gridded Indian Meteorological Dataset (IMD) employing two categorical and three continuous statistical metrics. Further, the precipitation datasets' performance in simulating streamflow was assessed by using the Soil and Water Assessment Tool (SWAT) hydrological model. Based on the statistical metrics, Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation (APHRODITE) furnished very good results in terms of detecting rainfall, followed by Climate Hazards Group Infrared Precipitation (CHIRP), National Centres for Environmental Prediction-Climate Forecast System Reanalysis (NCEP CFSR), Tropical Rainfall Measurement Mission (TRMM) 3B42 v7, Global Satellite Mapping of Precipitation Gauge Reanalysis v6 (GSMaP_Gauge_RNL), and Multisource Weighted Ensemble Precipitation (MSWEP) datasets which had good-to-moderate performances at a monthly time step. From the hydrological simulations, TRMM 3B42 v7, CHIRP, CHIRPS 0.05°, and GSMaP_Gauge_RNL v6 produced very good results with a high degree of correlation to observed streamflow, while Soil Moisture 2 Rain-Climate Change Initiative (SM2RAIN-CCI) dataset exhibited poor performance. From the extreme flow event analysis, it was observed that CHIRP, TRMM 3B42 v7, Global Precipitation Climatology Centre v7 (GPCC), and APHRODITE datasets captured more peak flow events and hence can be further implemented for extreme event analysis. Overall, we found that TRMM 3B42 v7, CHIRP, and CHIRPS 0.05° datasets performed better than other datasets and can be used for hydrological modeling and climate change studies in similar topographic and climatic watersheds in India. © 2020 Kolluru Venkatesh et al.