Faculty Publications
Permanent URI for this communityhttps://idr.nitk.ac.in/handle/123456789/18736
Publications by NITK Faculty
Browse
8 results
Search Results
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 Developing regression models for predicting pan evaporation from climatic data - A comparison of multiple least-squares, principal components, and partial least-squares approaches(2007) Kovoor, G.M.; Nandagiri, L.Regression models for predicting daily pan evaporation depths from climatic data were developed using three multivariate approaches: multiple least-squares regression (MLR), principal components regression (PCR), and partial least-squares (PLS) regression. The objective was to compare the prediction accuracies of regression models developed by these three approaches using historical climatic datasets of four Indian sites that are located in distinctly different climatic regimes. In all cases (three approaches applied to four climatic datasets), regression models were developed using a part of the data and subsequently validated with the remaining data. Results indicated that although performances of the regression models varied from one climate to another, more or less similar prediction accuracies were obtained by all three approaches, and it was difficult to identify the best approach based on performance statistics. However, the final forms of the regression models developed by the three approaches differed substantially from one another. In all cases, the models derived using PLS contained the smallest number of predictor variables; between two to three out of a possible maximum of six predictor variables. The MLR approach yielded models with three to six predictor variables, and PCR models included all six predictor variables. This implies that the PLS regression models are the most parsimonious in terms of input data required for estimating epan from climate variables, and yet yield predictions that are almost as accurate as the more data-intensive MLR and PCR models. © 2007 ASCE.Item Climate analysis for regional irrigation planning(2010) Nandagiri, L.; Nayali, S.Rainfall characteristics and potential evapotranspiration together determine the agro meteorological regime of a region and influence decisions concerning the magnitudes and timing of irrigation applications. In addition to rainfall input, an important aspect of the water balance model is the crop evapotranspiration (ETcrop), which is a main factor in determining irrigation schedule. The procedure for estimation of ET rates from agricultural crops is well established and involves as a first step, computation of reference crop evapotranspiration (ETcrop) using regular climatologically recorded data. ETcrop could be estimated by reference evapotranspiration (ET) and crop coefficient. ‘Moisture Availability Index’ (MAI), which is computed as the ratio of 75% dependable rainfall and potential evapotranspiration is used as an index to indicate dry and wet periods. An MAI value of 1.00 indicates that dependable precipitation equals potential evapotranspiration. A value of MAI of 0.33 or less for one month during the crop-growing season is considered to be a signal of water deficit, causing crop production to fall below an economic level. Obtained information on MAI is used to decide the selection of sowing period of crops so as to avoid water stress during crucial harvesting period. © 2010 Taylor & Francis Group, LLC.Item Characterization of climatic parameters in the perspective of irrigated agriculture in Uttar Kannada district of Karnataka, India(India Meteorological Department mausamps@gmail.com, 2020) Yallurkar, S.; Nayak, S.; Nandagiri, L.A rainfall and potential evapotranspiration characteristics together determine the agro-meteorological regime of a region and influences decision concerning the magnitudes and timing of irrigation application. In the present study, historical rainfall and climate data pertaining to the study area, Uttar Kannada district, Karnataka, was analyzed with a view to characterizing irrigation water requirements. In addition to rainfall input, an important aspect of the water balance model is the crop evapotranspiration (ETcrop), which is the main factor in determining the irrigation schedule. ETcrop could be estimated by reference evapotranspiration (ET0) and crop coefficient. Atmospheric demand for water is represented by ‘potential evapotranspiration’ (PET) and calculated from climatic variables which is crucial for irrigation planning. It has been reported that the Penman-Monteith method gives more consistently correct ET0 estimates to other ET0 methods. While recognizing the importance of both rainfall and PET, an effective measure is known as the ‘Moisture Availability Index’ (MAI), which is computed as the ratio of 75% dependable rainfall and potential evapotranspiration. An MAI value of 1.00 indicates that dependable precipitation is equal to potential evapotranspiration. An MAI value of 0.33 or less for one month during the crop growing season is considered to be a signal of water deficit resulting reduction in crop yield. The findings of this study on MAI are used to decide the selection of the sowing period of crops so as to avoid water stress during the critical harvesting period. © 2020, India Meteorological Department. All rights reserved.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 Effect of local calibration on the performance of the hargreaves reference crop evapotranspiration equation(IWA Publishing, 2021) Niranjan, S.; Nandagiri, L.Obtaining accurate estimates of reference crop evapotranspiration (ET0) using limited climatic inputs is essential in data-short situations where the preferred FAO-56 Penman–Monteith (PM) equation cannot be implemented. Among several available for ET0 estimation, the empirical temperature-based Hargreaves–Samani (HG) equation remains a popular alternative. However, accurate HG estimates can be obtained by local calibration and replacing the mean daily temperature with the effective daily temperature. Therefore, the present study was taken up to evaluate the effects of site-specific calibration of model parameters and the use of effective air temperature on the accuracy of ET0 estimates by the HG model. For this purpose, climate records for the historical period 2006–2016 of 67 stations located across 10 agro-climatic zones of Karnataka State, India, were used and the analysis was carried out using a monthly time step. Calibration and statistical performance evaluation was performed using FAO-56 PM ET0 estimates as a reference. Overall results showed significant improvement in HG estimates across all zones with the use of locally calibrated parameters, whereas the use of effective air temperature did not lead to any significant gain in prediction accuracies. The derived information on the spatial distribution of calibrated parameters will help obtain accurate ET0 estimates with only air temperature inputs. © 2021 The Authors.Item Development of daily gridded Penman-Monteith reference crop evapotranspiration data for Karnataka State, India(Taylor and Francis Ltd., 2024) Niranjan, S.; Nandagiri, L.Reference crop evapotranspiration (ET0) estimates are often unavailable at fine spatial resolutions due to the lack of dense climatic networks. The present study was taken up to develop a methodology for obtaining a gridded Penman-Monteith (PM) ET0 dataset for Karnataka State, India, through spatial interpolation of estimates obtained at climate stations. Three interpolation techniques, Inverse Distance Weighted (IDW), Kriging, and Point-Based Sentinel Hospitals Area Distance (P-BSHADE), were employed to derive PM ET0 estimates. Considering the historical climate records of 67 stations located in Karnataka State for the period of 2006–2016, the interpolation methodologies were evaluated using a cross-validation procedure. Results showed that the performance of IDW was better with significant error reduction at validation sites. Subsequently, the IDW algorithm was used to derive daily PM ET0 values at 0.25° × 0.25° grids over the Karnataka State, India. Finally, the comparative analysis of developed PM ET0 gridded data product against three global ET0 products indicated the developed gridded ET0 to be most accurate across different agroclimatic zones. Web links of the developed product have been created in an effort to share the data on ET0, which is a critical input in a variety of studies in earth sciences. © 2023 Indian Society for Hydraulics.