Nonlinear Evapotranspiration Modeling Using Artificial Neural Networks

Reference evapotranspiration (ETo) is an important and one of the most difficult components of the hydrologic cycle to quantify accurately. Estimation/measurement of ETo is not simple as there are number of climatic parameters that can affect the process. There exists copious conventional (direct and indirect) and non conventional/soft computing (artificial neural networks, ANNs) methods for estimating ETo. Direct methods have the limitations of measurement errors, expensive, impracticality of acquiring point measurements for spatially variable locations, whereas the indirect methods have the limitations of unavailability of all necessary climate data and lack of generalizability (needs local calibration). In contrast to conventional methods, soft computing models can estimate ETo accurately with minimum climate data which have advantages over limitations of conventional ETo methods. This chapter reviews the application of ANN methods in estimating ETo accurately for 15 locations in India using six climatic variables as input. The performance of ANN models were compared with the multiple linear regression (MLR) models in terms of root mean squared error, coefficient of determination and ratio of average output and target ETo values. The results suggested that the ANN models performed better as compared to MLR for all locations

Development of Smart Automated Irrigation System

This study is designed to develop an automatic irrigation system that switches (ON/OFF) a pump motor by sensing the moisture content of the soil using wireless technology. Through GSM Modem, the sensed moisture content data will be sent as an SMS to the user. The project uses 8051 series microcontroller, which is programmed to receive the input signal of varying moistures of the soil through sensors. This is achieved by using an op-amp as comparator which acts as interface between the sensing device and the microcontroller. Once the controller receives the signal, it generates an output that drives a relay for operating the water pump. It also sends an SMS to the concerned number using GSM modem. An LCD display is also interfaced to the microcontroller to display the status of the soil and water pump ON/Off condition. The sensing arrangement is made using two stiff metallic rods inserted to the agricultural field required to be in control. Connections from the metallic rods are interfaced to the control unit. This concept can also be enhanced by integrating XBEE/Bluetooth technology, such that whenever the water pump switches ON/OFF, the information is sent to a smart mobile phone or XBEE transceiver module regarding the status of the pump

Estimation of wheat crop evapotranspiration using NDVI vegetation index

The evapotranspiration of the wheat crop grown in Tarafeni South Main Canal (TSMC) irrigation command area of West Bengal, India was estimated based on Normalized Difference Vegetation Index (NDVI) from LANDSAT images. The crop evapotranspiration (ETc) of wheat crop was estimated using the crop coefficient (Kc) maps and the reference evapotranspiration (ETo) in the TSMC irrigation command area. The ETo was estimated from the well known temperature based ETo estimation method, i.e. FAO-24 modified Blaney-Criddle method using measured maximum and minimum air temperatures data during January 2011 in the command area. The Kc maps were mapped in ARC GIS software using procured LANDSAT images for the study period. The area under wheat crop was clipped from land use/land cover map generated from LANDSAT image of January, 2011 for winter season. Further, the crop evapotranspiration map was obtained by multiplying Kc map with the estimated ETo value i.e., 5.76 mm/day for a particular day. The maximum crop evapotranspiration computed for Rabi crop was 5.57 mm/ day, whereas minimum was 1.59 mm/day for the TSMC command area

Modelling Nonlinear Daily Evapotranspiration using Variable Infiltration Capacity Model and Artificial Neural Network

Evapotranspiration (ET) is a key variable for hydrologic, climatic and agricultural studies. Accurate quantification of this variable is of utmost importance for irrigation management and crop productivity. With the availability of only meteorological variables in climatic stations, reference gross evapotranspiration (ETo) estimation is becoming a challenging task. Hence, there is a scope to estimate the ETo using various physical and empirical methods. Among physical methods, FAO-56 PM method is best and Artificial Neural Network (ANN) models are accurate empirical methods. Further, ETo can also be estimated using a water budget approach i.e. variable infiltration capacity (VIC) model, which accounts for the sub-grid variability of land use and land cover and soil moisture in a better way. In this study, the ETo was estimated by two different methods, namely, VIC and ANN for Mohanpur climatic location in India. The results reveal that VIC- ETo showed the correlation coefficient, r = 0.853, coefficient of determination, R2 = 0.727 and index of agreement, d = 0.924; while ANN models showed better agreement with r = 0.999, R2 = 0.998 and d = 0.999 with the FAO-56 PM method. Hence, it is concluded that the ANN showed better results as compared to VIC model for ETo estimation in Mohanpur climatic location

Comparative Evaluation of ANNs and Hargreaves Method to Model ETo

This review goes for creating counterfeit neural system (ANN) based reference evapotranspiration (ETo) models comparing to Hargreaves (HG) strategy. The ANN models were created utilizing pooled atmosphere information of various areas under four agro-environmental locales (semi-dry, dry, sub-damp, and muggy) in India. The inputs for the development of ANN models include daily climate data of minimum, maximum air temperatures and extra terrestrial radiation and the target consists of the FAO-56 PM estimated ETo. Comparison of developed ANN models with the conventional HG method. The performance indices used for comparison include root mean squared error (RMSE) and coefficient of determination (R2). Based on the comparisons, it is concluded that the ANN models performed better than conventional HG method.

Temperature based generalized wavelet-neural network models to estimate evapotranspiration in India

In this paper, generalized wavelet-neural network (WNN) based models were developed for estimating reference evapotranspiration (ETo) corresponding to Hargreaves (HG) method for different agro-ecological regions (AERs): semi-arid, arid, sub-humid, and humid in India. The input and target to the WNN models are climate data (minimum and maximum air temperature) and ETo (estimated from FAO-56 Penman Monteith method), respectively. The developed WNN models were compared with the various generalized conventional models such as artificial neural networks (ANN), linear regression (LR), wavelet regression (WR), and HG method to test the best performed model. The performance indices used for the comparison include root mean squared error (RMSE), Nash-Sutcliffe efficiency (NSE), the ratio of average output to the average target ETo values (Rratio), and relative percentage (RP). The WNN and ANN models were performed better as compared to LR, WR and HG methods. Further, the best performed WNN and ANN models were tested on locations, which were not included in training to test their generalizing capability. It is concluded that the WNN and ANN models were shown good generalizing capability for the tested locations as compared to HG method

Hydrologic Calculator: An Educational Interface for Hydrological Processes Analysis

Hydrology, which deals with the study of water, is one of the fundamental courses to the undergraduate program of many disciplines: civil engineering, agricultural engineering, earth sciences, environmental sciences, geography, etc.  This course covers various events of the hydrological cycle, namely, rainfall, runoff, hydrograph, infiltration, evapotranspiration, and flood routing. These events involve a large number of techniques and methods for the analysis, which are time-consuming.  To enhance the learning, this study presents a tool called ‘Hydrologic Calculator’, an educational interface with eight modules for analyzing the various hydrological related events. In addition, ‘Help’ module in ‘Hydrologic Calculator’ provides a thorough understanding of the theory and methodology adopted for solving the different hydrological problems. Hydrologic Calculator includes a graphical user interface, which helps in input data preparation and output display in both graphical and tabular forms. Besides, it also provides detailed results in log (.txt) format. All the eight modules of the software were tested using the available published data. The validation results obtained using Hydrologic Calculator were in good agreement with the respective results given in the source. Thus, Hydrologic Calculator can be used as a professional computer tool for teaching and analyzing different hydrological processes.

Not Available

Enhancing nitrogen removal efficiency of domestic wastewaterThe temperatures of sewage water were too low in cold climatic regions of Baltic Sea, which resulted in inefficiency of denitrification in sewage treatment process (STP). This is not prescribed to meet the effluent nitrogen levels (<10 mg/l) as per Urban Wastewater Treatment Directive 98/15/EC. In order to improve the denitrification efficiency and the subsequent removal of nitrogen from the municipal wastewater as per the above European Commission guidelines, modified process was formulated with pre-anaerobic and post-aerobic activated sewage treatment processes. The modified process includes the rise in ambient temperature up to 20 ± 2 C by using heat exchangers in Increased Technology and Efficiency in Sewage Treatment (ITEST) pilot plant at the Swedish Environmental Research Institute (IVL) laboratory. The experiments were conducted with the modified process of sewage water in one line (treatment line (TL)) and the existing process in another line (reference line (RL)) of the pilot plant. The physical (such as Temperature, Suspended solids and Sludge volume) and chemical (ammonium-nitrate (NH4 +-N), nitrate-nitrogen (NO3 -N) and total-nitrogen (TN)) parameters were analyzed. The results concluded that the NH4 +-N, NO3 -N and TN concentrations of treated waste water were satisfactory with a concentration of <10 mg/l as per the European Directives 98/15/EEC at treatment line as compared to influent and reference lines. The average nitrogenouscompounds’ removal efficiencies were 84% and 76% of NH4 +, 80% and 65% of NO3 , 78% and 62% of TN for TL and RL, respectively. 2017 The Gulf Organisation for Research and Development. Production and hosting by Elsevier B.V.Not Availabl

Aboriginal Tribe’s Knowledge of the Endangered Freshwater Turtle Cuora amboinensis in Car Nicobar, a Remote Oceanic Island in the Bay of Bengal

Freshwater turtles are among the least studied faunas in the Andaman and Nicobar Islands, India. Here, we report the presence of freshwater turtles (Cuora amboinensis) from Car Nicobar, a small remote island in the Nicobar archipelago comprising the Andaman and Nicobar Islands. Semi-structured interviews were conducted with the people belonging to Nicobarese tribes (n = 233) to gather their local ecological knowledge as supportive information to obtain a better understanding of the status of turtles in Car Nicobar. Most interviewees (90%) opined that freshwater turtles are found to be rare or very rare on the Island. All the respondents (100%) expressed willingness to contribute to future conservation projects. Community-level awareness emerged as a prominent issue for future conservation using the Garrett ranking method. A stream network map was prepared using the digital elevation model to visualize streams and potential habitats of turtles. This report on the freshwater turtles is essential from an ecological perspective since information is scarce on the freshwater turtles in Car Nicobar. This study emphasizes the importance of the engagement of stakeholders in conservation projects and recommends providing adequate attention to the conservation and protection of freshwater turtle diversity in Car Nicobar