Faculty Publications
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Item Performance evaluation of reference evapotranspiration equations across a range of Indian climates(2006) Nandagiri, L.; Kovoor, G.M.Reference crop evapotranspiration (ET0) is a key variable in procedures established for estimation of evapotranspiration rates of agricultural crops. In recent years, there is growing evidence to show that the more physically based FAO-56 Penman-Monteith (PM) combination method yields consistently more accurate ET0 estimates across a wide range of climates and is being proposed as the sole method for ET0 computations. However, other methods continue to remain popular among Indian practitioners either because of traditional usage or because of their simpler input data requirements. In this study, we evaluated the performances of several ET0 methods in the major climate regimes of India with a view to quantify differences in ET0 estimates as influenced by climatic conditions and also to identify methods that yield results closest to the FAO-56 PM method. Performances of seven ET0 methods, representing temperature-based, radiation-based, pan evaporation-based, and combination-type equations, were compared with the FAO-56 PM method using historical climate data from four stations located one each in arid (Jodhpur), semiarid (Hyderabad), subhumid (Bangalore), and humid (Pattambi) climates of India. For each location, ET0 estimates by all the methods for assumed hypothetical grass reference crop were statistically compared using daily climate records extending over periods of 3-4 years. Comparisons were performed for daily and monthly computational time steps. Overall results while providing information on variations in FAO-56 PM ET0 values across climates also indicated climate-specific differences in ET0 estimates obtained by the various methods. Among the ET0 methods evaluated, the FAO-56 Hargreaves (temperature-based) method yielded ET0 estimates closest to the FAO-56 PM method both for daily and monthly time steps, in all climates except the humid one where the Turc (radiation-based) was best. Considering daily comparisons, the associated minimum standard errors of estimate (SEE) were 1.35, 0.78, 0.67, and 0.31 mm/day, for the arid, semiarid, subhumid, and humid locations, respectively. For monthly comparisons, minimum SEE values were smaller at 0.95, 0.59, 0.38, and 0.20 mm/day for arid, semiarid, subhumid, and humid locations, respectively. These results indicate that the choice of an alternative simpler equation in a particular climate on the basis of SEE is dictated by the time step adopted and also it appears that the simpler equations yield much smaller errors when monthly computations are made. In order to provide simple ET0 estimation tools for practitioners, linear regression equations for preferred FAO-56 PM ET0 estimates in terms of ET0 estimates by the simpler methods were developed and validated for each climate. A novel attempt was made to investigate the reasons for the climate-dependent success of the simpler alternative ET0 equations using multivariate factor analysis techniques. For each climate, datasets comprising FAO-56 PM ET0 estimates and the climatic variables were subject to factor analysis and the resulting rotated factor loadings were used to interpret the relative importance of climatic variables in explaining the observed variabilities in ET0 estimates. Results of factor analysis more or less conformed the results of the statistical comparisons and provided a statistical justification for the ranking of alternative methods based on performance indices. Factor analysis also indicated that windspeed appears to be an important variable in the arid climate, whereas sunshine hours appear to be more dominant in subhumid and humid climates. Temperature related variables appear to be the most crucial inputs required to obtain ET0 estimates comparable to those from the FAO-56 PM method across all the climates considered. © 2006 ASCE.Item Latent heat flux estimation using trapezoidal relationship between MODIS land surface temperature and fraction of vegetation-application and validation in a humid tropical region(Taylor and Francis Ltd., 2014) Laxmi, K.; Nandagiri, L.The present study was taken up with the objective of developing a methodology for estimation of actual evapotranspiration (AET) using only satellite data. Accordingly, an algorithm based on the popular Priestley-Taylor method was developed. While previous studies have assumed a triangular relationship between land surface temperature (LST) and fraction of vegetation (FV) to calculate the Priestley-Taylor parameter (?), a trapezoidal relationship was adopted in the present study to enable applications in forested regions in the humid tropics. The developed algorithm was applied to the humid tropical Mae Klong region, Thailand, and latent heat flux (ET) estimates were validated with measurements made at a flux tower located at the centre of the region. Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing satellite data products corresponding to the study area were used to derive various inputs required by the algorithm. Comparison of estimated and measured fluxes on five cloud-free days in 2003 yielded root mean square error (RMSE) of 64.73 W m-2 which reduced to 18.65 W m-2 when one day was treated as an outlier. The methodology developed in this study derived inputs only from satellite imagery and provided reasonably accurate estimates of latent heat flux at a humid tropical location. © 2014 Taylor & Francis.Item Streamflow response to land use-land cover change over the Nethravathi River Basin, India(American Society of Civil Engineers (ASCE), 2015) Babar, S.; Ramesh, H.Land use-land cover change (LULC) has considerable impacts on hydrologic response at the watershed level. Quantitative assessment of LULC impacts on runoff generations is vital for water resources development. The soil and water assessment tool (SWAT) model was used to study the effect of LULC change on streamflows. In addition to this, the present study proposed a newly developed flow-routing model called runoff coefficient routing model (RCRM). This new model is simple and requires limited data, such as precipitation, LULC and streamflows as compared to other models, which require meteorological and many more input data. The Nethravathi River basin was selected for testing the RCRM model with the SWAT model to study land use-land cover change on streamflows. The SWAT model and RCRM model have been calibrated for 2001-2005 and validated for 2006-2009 daily data. Results have shown that the simulated streams are well correlated with observed streamflows with a coefficient of correlation (R2) equal to 0.82 in calibration and 0.68 in validation period. Whereas, the RCRM model results have shown R2 of 0.81 and 0.66 in the calibration and validation period. Finally, the SWAT and RCRM results were compared. It is observed that the results of the RCRM model have shown a good agreement with SWAT model results of R2 equal to 0.99 and 0.98, respectively, in the calibration and validation period. The sensitivity analysis was also carried out based on Latin hypercube one factor-at-a-time (LH-OAT) method using the SWAT model and found 11 sensitive parameters out of 28 parameters. Model performance was carried out using the Nash-Sutcliffe model efficiency coefficient (NSE) and found 0.81 for calibration and 0.62 for the validation period in the SWAT model. RCRM has NSE of 0.79 and 0.63. The response of the streamflows for the year 2013 was simulated from the calibrated model. The results showed that the observed streamflows have shown good correlation with simulated streamflows with R2 values of 0.86 and NSE of 0.81. From the results, it is concluded that the runoff shows early response in the year 2013 compared to the year 2003. This is mainly due to changes in LULC, which shows the conversion of forest to agricultural area and increase in built-up area from 2003 to 2013. The effect of LULC change on the hydrological model parameters were calculated and observed a decrease in evapotranspiration (ET) of about 4.5%, an increase in runoff of about 0.9%, and an increase in groundwater of about 1.12%. In conclusion, the proposed RCRM in the present study simulates streamflows at par with the SWAT model with only few input data. Hence, the newly developed RCRM model would be used to study streamflows responses to LULC changes. © 2015 American Society of Civil Engineers.Item An extreme learning machine approach for modeling evapotranspiration using extrinsic inputs(Elsevier B.V., 2016) Patil, A.P.; Deka, P.C.Precise estimation of evapotranspiration is crucial for accurate crop-water estimation. Recently machine learning (ML) techniques like artificial neural network (ANN) are being widely used for modeling the process of evapotranspiration. However, ANN faces issues like trapping in local minima, slow learning and tuning of meta-parameters. In this study an improved extreme learning machine (ELM) algorithm was used to estimate weekly reference crop evapotranspiration (ETo). The study was carried out for Jodhpur and Pali meteorological weather stations located in the Thar Desert, India. The study evaluated the performance of three different input combinations. The first input combination used locally available maximum and minimum air temperature data while the second and third combination used ETo values from another station (extrinsic inputs) along with the locally available temperature data as inputs. The performance of ELM models was compared with the empirical Hargreaves equation, ANN and least-square support vector machine (LS-SVM) models. Root mean squared error (RMSE), Nash-Sutcliffe model efficiency coefficient (NSE) and threshold statistics (TS) were used for comparing the performance of the models. The performance of ELM model was found to be better than the Hargreaves and ANN model. The LS-SVM and ELM displayed similar performance. ELM3 models, with 36 and 33 neurons in hidden layer were found to be the best models (RMSE of 0.43 for Jodhpur and 0.33 for Pali station) for estimating weekly ETo at Jodhpur and Pali stations respectively. The results showed that ELM is a simple yet efficient algorithm which exhibited good performance; hence, can be recommended for estimating weekly ETo. Furthermore, it was also found that use of ETo values from another station can help in improving the efficiency of ML models in limited data scenario. © 2016 Elsevier B.V.Item Assessment of consumption and availability of water in the upper Omo-Gibe basin, Ethiopia(Springer, 2020) Nesru, M.; Nagaraj, M.K.; Shetty, A.Understanding water balance components is imperative for proper policy and decision making, specifically in the upper part of the Omo-Gibe basin (UOGB) Ethiopia. The objective of this study is to explore the possibility of assessing consumption and availability of water using freely available satellite data and secondary data. Using twenty-three rain gauge stations data, a spatial average of rainfall was computed using the Thiessen polygon approach. Actual evapotranspiration (ETa) was estimated through the Surface Energy Balance System (SEBS). Input data used are, 16 clouds free Moderate Resolution Imaging Spectroradiometer (MODIS) images covering the study area for estimation of the spatial distribution of actual evapotranspiration covering the whole cropping year from the months of November 2003 to October 2004. Additionally, Priestly and Taylor’s approach was used to estimate reference evapotranspiration (ET0). For the study period, the result of estimated precipitation and ETa showed that the UOGB received 41,080 mm3 of precipitation, while 24,135 mm3 become evapotranspired. The assessed outflow from the basin is 17.6% of the precipitation and demonstrated that water is a scares resource in the UOGB. © 2019, Saudi Society for Geosciences.Item Estimation of daily actual evapotranspiration using vegetation coefficient method for clear and cloudy sky conditions(Institute of Electrical and Electronics Engineers, 2020) Shwetha, H.R.; Nagesh Kumar, D.N.Actual evapotranspiration (AET) can be studied and estimated using remote-sensing-based methods at multiple spatial and temporal scales. Reflectance and Land surface temperature are essential in these methods. However optical and thermal sensors fail to provide these data under overcast conditions and this creates gap in the AET product. Besides, there is a necessity of the AET method that requires less data and estimates AET with better accuracy. In this regard, AET was estimated for all-sky conditions using the vegetation coefficient (VI-Kv) method utilizing microwave, thermal, and optical data. Essential reference evapotranspiration (ET0) under cloudy conditions was estimated using LST-based Penman-Monteith temperature (PMT) and Hargreaves-Samani equations. Furthermore, LST predicted using the microwave polarization difference index (PLST) and LST of moderate resolution imaging spectroradiometer (MODIS) cloud product (MLST) were evaluated with in-situ air temperature (Ta) under cloudy sky conditions. Results revealed that the PLST correlated better with Ta than MLST with correlation coefficient (r) values of 0.71 and 0.81 for day and night times, respectively. Hence, PLST-based solar radiation (Rs) estimation yielded better accuracy with observed Rs with r and root mean square error values of 0.864 and 0.07 for Berambadi station under cloudy conditions, respectively. PMT-based ET0 values corresponded well with the observed ET0 under cloudy sky condition during this study. In addition, AET estimated using the VI-Kv method was compared with the simple two-source energy balance (TSEB) method under clear sky conditions. It was found that the improved VI-Kv method performed better than the TSEB method and could also fairly estimate AET even under cloudy sky conditions. © 2008-2012 IEEE.Item A Penman-Monteith evapotranspiration model with bulk surface conductance derived from remotely sensed spatial contextual information(Taylor and Francis Ltd. michael.wagreich@univie.ac.at, 2020) Shekar N C, S.; Nandagiri, L.A novel approach involving the use of the contextual information in a scatter plot of Moderate Resolution Imaging Spectrometer (MODIS) derived Land Surface Temperature versus Fraction of Vegetation (LST vs. Fv) has been proposed in this study to obtain pixel-wise values of bulk surface conductance (Gs) for use in the Penman-Monteith (PM) model for latent heat flux (?ET) estimation. Using a general expression for Gs derived by assuming a two-source total ?ET (canopy transpiration plus soil evaporation) approach proposed by previous researchers, minimum and maximum values of Gs for a given region can be inferred from a trapezoidal scatter plot of pixel-wise values of LST and corresponding Fv. Using these as limiting values, Gs values for each pixel can be derived through interpolation and subsequently used with the PM model to estimate ?ET for each pixel. The proposed methodology was implemented in 5 km × 5 km areas surrounding each of four flux towers located in tropical south-east Asia. Using climate data from the tower and derived Gs values the PM model was used to obtain pixel-wise instantaneous ?ET values on six selected dates/times at each tower. Excellent comparisons were obtained between tower measured ?ET and those estimated by the proposed approach for all four flux tower locations (R2 = 0.85–0.96; RMSE = 18.27–33.79 W m–2). Since the LST- Fv trapezoidal method is simple, calibration-free and easy to implement, the proposed methodology has the potential to provide accurate estimates of regional evapotranspiration with minimal data inputs. © 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.Item Modelling stream flow and soil erosion response considering varied land practices in a cascading river basin(Academic Press, 2020) Venkatesh, K.; Ramesh, H.; Das, P.[No abstract available]Item Connection between Meteorological and Groundwater Drought with Copula-Based Bivariate Frequency Analysis(American Society of Civil Engineers (ASCE), 2021) Pathak, A.A.; Dodamani, B.M.Groundwater is a major resource of freshwater that provides additional resilience to agricultural drought during rainfall deficit and also helps in understanding the nature of the hydrological drought risk of an area. This study investigated the response of groundwater drought to meteorological drought and local aquifer properties by considering monthly groundwater levels of a tropical river basin in India. Further, bivariate frequency analysis was carried out for groundwater drought to develop severity-duration-frequency curves by considering the copula function. Long-term monthly groundwater levels were procured, and cluster analysis was performed on groundwater observations to classify the wells. Standardized Groundwater level Index (SGI) was used to evaluate groundwater drought for each cluster, and the same was compared with the meteorological drought of different association periods. The cluster analysis conveyed that wells can be grouped into three clusters optimally. Based on the comparison of groundwater drought with meteorological drought, it was inferred that SGI is well harmonized with the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) in humid and semiarid regions, respectively. Analysis of hydraulic diffusivity with the autocorrelation structure of SGI emphasizes the crucial role of aquifer characteristics in local groundwater droughts. The results of joint and conditional return periods obtained from bivariate frequency analysis conveyed that high severity and high-duration droughts were more frequent in the well of Clusters 1 as well as Cluster 3 and comparatively less for the well of Cluster 2. The outcome of the study will be helpful to design proactive drought mitigation and preparedness strategies by considering conjunctive use of surface and groundwater. It also provides a framework to evaluate groundwater drought risk in other parts of the world. © 2021 American Society of Civil Engineers.