R. K. Panda

Effect of irrigation scheduling on potato crop parameters under water stressed conditions

Field experiments were conducted on a local cultivar, Kufri-Jyoti, of potato crop during the four winter seasons of 1995?1996 through 1998?1999. Five irrigation treatments were maintained based on the maximum allowable depletion (MAD) of available soil water (ASW). The treatments were 10% (T1), 30% (T2), 45% (T3), 60% (T4) and 75% (T5) MAD of ASW during non-critical stages of crop growth. Measurements of fresh tuber yield, dry tuber yield, plant dry matter (including roots but not tubers), total dry matter and leaf area index were made at various stages of crop growth during all four crop experiments. Fresh tuber yield of potato was significantly higher under high frequency than low frequency irrigation. With delayed irrigation, the yield reduced significantly under T4 and T5, which resulted in minimum fresh tuber yield and total dry matter yield during all four experiments. With increase in MAD from 45 to 75%, the fresh tuber yield reduced considerably due to reduction in the availability of water. A similar trend was observed for other crop parameters. Crop production functions with respect to crop water use were developed for five measures of plant growth; they were found to be linear. Though the results of the study are applicable for sub-humid sub-tropical climatic conditions with sandy loam soils as that of the study area, the objective methodology developed has universal applicability. Author Keywords: Irrigation; Potato; Water stress; Deficit irrigation; Production functions

Application of neural network and adaptive neuro-fuzzy inference systems for river flow prediction

Abstract Appropriate outflow from a barrage should be maintained to avoid flooding on the downstream side during the rainy season. Due to the nonlinear and fuzzy behaviour of hydrological processes, and in cases of scarcity of relevant data, it is difficult to simulate the desired outflow using physically-based models. Artificial intelligence techniques, namely artificial neural networks (ANN) and an adaptive neuro-fuzzy inference system (ANFIS), were used in the reported study to estimate the flow at the downstream stretch of a river using flow data for upstream locations. Comparison of the performance of ANN and ANFIS was made by estimating daily outflow from a barrage located in the downstream region of Mahanadi River basin, India, using daily release data from the Hirakud Reservoir, located some distance upstream of the barrage. To obtain the best input—output mapping, five different models with various input combinations were evaluated using both techniques. The significance of the contribution of two upstream tributaries to barrage outflow estimation was also evaluated. Three feed-forward back-propagation training algorithms were used to train the models. Standard performance indices, such as correlation coefficient, index of agreement, root mean square error, modelling efficiency and percentage deviation in peak flow, were used to compare the performance of the models, as well as the training techniques. The results revealed that the neural network with conjugate gradient algorithm performs better than Levenberg-Marquardt and gradient descent algorithms. The model which considers as input the reservoir release up to three antecedent time steps produced the best results. It was found that barrage outflow could be better estimated by the ANFIS than by the ANN technique.

Simulation of river stage using artificial neural network and MIKE 11 hydrodynamic model

Simulation of water levels at different sections of a river using physically based flood routing models is quite cumbersome, because it requires many types of data such as hydrologic time series, river geometry, hydraulics of existing control structures and channel roughness coefficients. Normally in developing countries like India it is not easy to collect these data because of poor monitoring and record keeping. Therefore, an artificial neural network (ANN) technique is used as an effective alternative in hydrologic simulation studies. The present study aims at comparing the performance of the ANN technique with a widely used physically based hydrodynamic model in the MIKE 11 environment. The MIKE 11 hydrodynamic model was calibrated and validated for the monsoon periods (June-September) of the years 2006 and 2001, respectively. Feed forward neural network architecture with Levenberg-Marquardt (LM) back propagation training algorithm was used to train the neural network model using hourly water level data of the period June-September 2006. The trained ANN model was tested using data for the same period of the year 2001. Simulated water levels by the MIKE 11HD were compared with the corresponding water levels predicted by the ANN model. The results obtained from the ANN model were found to be much better than that of the MIKE 11HD results as indicated by the values of the goodness of fit indices used in the study. The Nash-Sutcliffe index (E) and root mean square error (RMSE) obtained in case of the ANN model were found to be 0.8419 and 0.8939m, respectively, during model testing, whereas in case of MIKE 11HD, the values of E and RMSE were found to be 0.7836 and 1.00m, respectively, during model validation. The difference between the observed and simulated peak water levels obtained from the ANN model was found to be much lower than that of MIKE 11HD. The study reveals that the use of Levenberg-Marquardt algorithm with eight hidden neurons in the hidden layer is sufficient to produce satisfactory results.

Effect of method and scheduling of irrigation on water and nitrogen use efficiencies of Okra (Abelmoschus esculentus)

Production of fresh vegetables usually calls for application of large amounts of irrigation water and fertiliser nitrogen (N). Combined application of high rates of water and N leads to excessive leaching of nitrate nitrogen, making most of it unavailable to the plants. Very few studies have been conducted to investigate the combined effect of irrigation method and scheduling on the yield, N use (based on N balance in the root zone) and N uptake (based on N content of plant material) of vegetable crops, especially Okra. A field experiment was conducted in a coarse textured lateritic soil (Haplustalf) of Kharagpur, India, planted to Okra to investigate the effect of method and scheduling of irrigation on yield attributes. Three methods of irrigation: sprinkler, furrow and basin and three irrigation treatments scheduled at 15, 30, 45 and 60% maximum allowable depletion (MAD) of available soil water were studied. The results of the study revealed that on sandy loam lateritic soil planted to Okra crop, furrow irrigation results in the maximum deep percolation (DP) loss while the minimum deep percolation occurs under sprinkler irrigation. Irrigation scheduled at 15% MAD resulted in higher deep percolation loss than irrigation timed at 60% MAD, particularly under surface irrigation methods. The DP loss under furrow and check basin irrigation scheduled at 15% MAD could be reduced to almost half by scheduling at 30% MAD. Maximum fresh fruit yield, nitrogen uptake and nitrogen uptake efficiency of Okra were obtained with sprinkler irrigation scheduled at 30% MAD, whereas the maximum nitrogen use efficiency (NUE) was obtained with furrow irrigation scheduled at 15% MAD. Irrigation schedules with 60% MAD resulted in the minimum fresh fruit yield, nitrogen use, nitrogen uptake as well as the least nitrogen use and uptake efficiencies irrespective of irrigation method. Thus, scheduling irrigation at 30% MAD under sprinkler method of irrigation was found to be the best for Okra crop in sandy loam soil.

Digital image processing for determining drop sizes from irrigation spray nozzles

Abstract All the existing methods for measuring drop sizes produced by a sprinkler nozzle are either cumbersome, expensive or time consuming. Moreover, none could quantitatively express the relationship between drop size distribution and sprinkler head parameters viz. operating pressure and nozzle size. In the present study digital image processing technique has been applied to determine the drop size distribution from an irrigation spray nozzle. Image processing is the technique of automating and integrating a wide range of processes used for the human vision perception. The present study revealed that image processing technique can be successfully implemented for drop size measurement accurately. Being a novel technique, the method has some limitations for adaptation. These limitations can be very well contained through further research.

Integrated Management of a Canal Command in a River Delta using Multi-Objective Techniques

Multi-criteria or multi-objective decision-making is becoming increasingly popular as a decision support tool for natural resource management.Stakeholders as well as the planners can be involved in the decision making process, using this approach. This article deals with the use of multi-criteria (multi-objective) technique in solving some complex problems related to water resource management. Five objectives were considered in the study. The benefit of combining these objective functions with the decisionsupport tool is that the management of land and water resourcescan be made more effectively. Based on this concept, a methodology was developed through this study, for the water managers and decision-makers, to obtain a compromising solutionin terms of area allocated under different crops and the magnitude of farming system variables in a canal command area. This study was under taken in the Mahanadi Delta of India. Multi-objective techniques such as Sequential Linear Fuzzy Programming and Goal Programming were used for their simplicity in computation and flexibility in application. Using Fuzzy programming technique, the objective function values under benefit maximization, production maximization, investmentminimization, labour maximization and labour minimizationwere found to be 44.26 M INR, 8795 tonnes, 42.00 M INR and548 150 man-days, respectively. These results were found tobe quite compromising in nature. Goal programming technique wasalso used to arrive at a consensus in allocation of the resources. It was used to decide the best out of the eight alternative priorities. Results indicated that only five alternative goals (Goal1, Goal2, Goal3, Goal6 and Goal8) had distinct allocations while the other three alternatives (Goal4,Goal5 and Goal7) had allocations similar to either of the abovefive alternatives irrespective of their priority levels. Croppingintensity was found to be the maximum (238%) for two of thegoals (Goal6 and Goal7). Though the results of the study were forthe specific site, the multi-criteria techniques used and therecommendations evolved are of objective nature and are applicable at any location for decision-making.

Runoff and Sediment Yield Modelling for a Treated Hilly Watershed in Eastern Himalaya Using the Water Erosion Prediction Project Model

The Water Erosion Prediction Project (WEPP) watershed model was calibrated and validated for a hilly watershed treated with graded bunding and water-harvesting tank in high rainfall condition of eastern Himalayan range in India. The performance of the model for the treated watershed was unacceptable with percent deviation of −45.81 and −38.35 respectively for runoff and sediment yield simulations when calibrated parameter values for the nearby untreated watershed were used. This was possibly due to differences in soil properties and average land slope. When soil parameters were calibrated for the treated watershed, the model performance improved remarkably. During calibration, the model simulated surface runoff and sediment yield with percent deviations equal to +6.24 and +9.02, and Nash–Sutcliffe simulation coefficients equal to 0.85 and 0.81, respectively. During validation period, the model simulated runoff and sediment yield with percent deviations equal to +8.56 and +9.36, and Nash–Sutcliffe simulation coefficients equal to 0.81 and 0.80, respectively. The model tended to slightly under-predict runoff and sediment yield of higher magnitudes. The model performance was quite sensitive to soil parameters namely, rill erodibility, interrill erodibility, hydraulic conductivity, critical shear stress and Manning’s roughness coefficient with varying levels. The WEPP model picked up the hydrology associated with bund and water-harvesting tank, and simulated runoff and sediment yield well with overall deviations within ±10% and Nash–Sutcliffe simulation coefficients >0.80. Simulation results indicate that in high slope and high rainfall conditions of eastern Himalayan region of India where vegetative measures are not adequate to restrict soil loss within the permissible limit, the WEPP model can be applied to formulate structure-based management strategies to control soil loss and to develop water resources.

Study of nitrate movement in a sandy loam soil

A study was conducted in sandy loam soil at Kharagpur, West Bengal (India) in 1996–1997 to assess the influence of different rates of nitrogen (N) fertilization on nitrate leaching. The nitrogen source was urea and there were four N fertilization treatments (70, 80, 100 and 120 kg N/ha), each having three replications arranged in a randomized complete block design (RCBD). The soil was irrigated to a field capacity at 50% available soil moisture depletion regime throughout the season and leaching losses were calculated. A sand tank was used to study the movement of pH, EC, calcium content and NO3-N in the leachate. pH, EC, calcium content was varied with respect to depth and time but due to the restriction of depth up to 105 cm, NO3-N concentration in the leachate remained constant up to 48 h of fertilizer application. A similar experiment was conducted in the field by collecting leachate up to a depth of 220 cm. Different doses of fertilizer application led to a build-up of NO3-N in the soil and vadose zone. Field results showed that the amount of NO3-N was positively correlated with soil depth up to 220 cm when fertilizer was applied in a single dose. This build-up acted as a reservoir, which could supply NO3-N to percolating water, which in turn carried NO3-N to the saturated zone. Statistical analysis was carried out with differential amounts of nitrogen and soil depth. Regression analysis was done to investigate the best fit of NO3-N movement with passage of time in different soil layers. The current study showed that at the shallow ground water table conditions (where groundwater table lies immediately below the root zone depth) with sandy loam topsoil, the application rate of commonly used nitrogenous fertilizer (urea) should not exceed 80 kg N/ha.

Runoff modelling of a small watershed using satellite data and GIS

This study was conducted for the Nagwan watershed of the Damodar Valley Corporation (DVC), Hazaribagh, Bihar, India. Geographic Information System (GIS) was used to extract the hydrological parameters of the watershed from the remote sensing and field data. The Digital Elevation Model (DEM) was prepared using contour map (Survey of India, 1:50000 scale) of the watershed. The EASI/PACE GIS software was used to extract the topographic features and to delineate watershed and overland flow-paths from the DEM. Land use classification were generated from data of Indian Remote Sensing Satellite (IRS-1B—LISS—II) to compute runoff Curve Number (CN). Data extracted from contour map, soil map and satellite imagery, viz. drainage basin area, basin shape, average slope of the watershed, main stream channel slope, land use, hydrological soil groups and CN were used for developing an empirical model for surface runoff prediction. It was found that the model can predict runoff reasonably well and is well suited for the Nagwan watershed. Design of conservation structures can be done and their effects on direct runoff can be evaluated using the model. In broader sense it could be concluded that model can be applied for estimating runoff and evaluating its effect on structures of the Nagwan watershed.

Effective crop evapotranspiration measurement using time-domain reflectometry technique in a sub-humid region

The primary objective of this study was to evaluate the performance of the time-domain reflectometry (TDR) technique for daily evapotranspiration estimation of peanut and maize crop in a sub-humid region. Four independent methods were used to estimate crop evapotranspiration (ETc), namely, soil water balance budgeting approach, energy balance approach—(Bowen ratio), empirical methods approach, and Pan evaporation method. The soil water balance budgeting approach utilized the soil moisture measurement by gravimetric and TDR method. The empirical evapotranspiration methods such as combination approach (FAO-56 Penman–Monteith and Penman), temperature-based approach (Hargreaves–Samani), and radiation-based approach (Priestley–Taylor, Turc, Abetw) were used to estimate the reference evapotranspiration (ET0). The daily ETc determined by the FAO-56 Penman-Monteith, Priestley-Taylor, Turc, Pan evaporation, and Bowen ratio were found to be at par with the ET values derived from the soil water balance budget; while the methods Abetw, Penman, and Hargreaves-Samani were not found to be ideal for the determination of ETc. The study illustrates the in situ applicability of the TDR method in order to make it possible for a user to choose the best way for the optimum water consumption for a given crop in a sub-humid region. The study suggests that the FAO-56 Penman–Monteith, Turc, and Priestley–Taylor can be used for the determination of crop ETc using TDR in comparison to soil water balance budget.