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Bhubaneshwar, India

Panigrahi P.,Directorate of Water Management
Irrigation and Drainage | Year: 2014

Efficient irrigation and drainage are a prerequisite for sustainable citriculture. Citriculture in vertisols often faces the twin problem of waterlogging in the rainy season and water shortage during the post-rainy period, leading to suboptimal productivity and decline of citrus orchards in central India. With this in mind, the integrated impact of irrigation methods (drip and basin) and surface drainage (parallel trenches) was studied in citrus orchards of the region. Drip irrigation (DI) produced 23% higher fruit yield than basin irrigation (BI) under drainage. Drainage was an important consideration for both DI and BI. However, drainage was much more important for BI than DI to achieve higher fruit yield. Conjunctive use of DI and drainage (DID) reduced the soil and nutrient losses through runoff and produced 90% higher yield with better quality fruit, using 30% less irrigation water (171% improvement in irrigation water use efficiency) than BI without drainage. Citrus production with DID was also found to be economically superior to other treatments, generating more net return (INR 225 000 ha-1 yr-1)1 with higher benefit-cost ratio (5.2). Overall, the study demonstrates that adoption of DID could be a viable option for commercial citriculture on clay soil in water-scarce central India. © 2014 John Wiley & Sons, Ltd. Source

Kaledhonkar M.J.,Directorate of Water Management | Sharma D.R.,Indian Council of Agricultural Research | Tyagi N.K.,Agricultural Scientist Recruitment Board | Kumar A.,Directorate of Water Management | Van Der Zee S.E.A.T.M.,Wageningen University
Agricultural Water Management | Year: 2012

Prevalent irrigation water quality guidelines for use of sodic groundwater on sandy loam soils of Haryana for kharif (monsoon) fallow-rabi (winter) wheat crop rotation were investigated through modeling with UNSATCHEM. Three sandy loam soils that vary with respect to soil CEC (Cation Exchange Capacity) and Ks (Saturated Hydraulic Conductivity) were considered in the modeling. A procedure was developed to identify safe SAR value for sodic groundwater at a constant RSC for individual farm/soil considering soil CEC and proportions of sodic and fresh waters used for irrigation as variables. The criterion was that if the SAR of available sodic groundwater exceeded the safe SAR-value for irrigation water, a reduction in crop yield occurs. With this assumption, the procedure was tested with published data and the specific data collected from farmers' fields. If SAR of groundwater exceeds the safe SAR-value, rice-wheat rotation is assumed to be not sustainable in the long-term. The sustainability of rice-wheat crop rotation in sodic groundwater areas in the Assandh and Nissang blocks of the Karnal district of Haryana was assessed. The described procedure of identifying the safe SAR-values for individual farm/soil is more appropriate and flexible than already existing guidelines and could be easily used for efficient conjunctive water use planning of sodic and fresh water. © 2011 Elsevier B.V.. Source

Mohanty S.,Directorate of Water Management | Jha M.K.,Indian Institute of Technology Kharagpur | Kumar A.,Directorate of Water Management | Sudheer K.P.,Indian Institute of Technology Madras
Water Resources Management | Year: 2010

Forecasting of groundwater levels is very useful for planning integrated management of groundwater and surface water resources in a basin. In the present study, artificial neural network models have been developed for groundwater level forecasting in a river island of tropical humid region, eastern India. ANN modeling was carried out to predict groundwater levels 1 week ahead at 18 sites over the study area. The inputs to the ANN models consisted of weekly rainfall, pan evaporation, river stage, water level in the drain, pumping rate and groundwater level in the previous week, which led to 40 input nodes and 18 output nodes. Three different ANN training algorithms, viz., gradient descent with momentum and adaptive learning rate backpropagation (GDX) algorithm, Levenberg-Marquardt (LM) algorithm and Bayesian regularization (BR) algorithm were employed and their performance was evaluated. As the neural network became very large with 40 input nodes and 18 output nodes, the LM and BR algorithms took too much time to complete a single iteration. Consequently, the study area was divided into three clusters and the performance evaluation of the three ANN training algorithms was done separately for all the clusters. The performance of all the three ANN training algorithms in predicting groundwater levels over the study area was found to be almost equally good. However, the performance of the BR algorithm was found slightly superior to that of the GDX and LM algorithms. The ANN model trained with BR algorithm was further used for predicting groundwater levels 2, 3 and 4 weeks ahead in the tubewells of one cluster using the same inputs. It was found that though the accuracy of predicted groundwater levels generally decreases with an increase in the lead time, the predicted groundwater levels are reasonable for the larger lead times as well. © 2009 Springer Science+Business Media B.V. Source

Mohanty S.,Directorate of Water Management | Jha M.K.,Indian Institute of Technology Kharagpur | Kumar A.,Directorate of Water Management | Panda D.K.,Directorate of Water Management
Journal of Hydrology | Year: 2013

In view of worldwide concern for the sustainability of groundwater resources, basin-wide modeling of groundwater flow is essential for the efficient planning and management of groundwater resources in a groundwater basin. The objective of the present study is to evaluate the performance of finite difference-based numerical model MODFLOW and the artificial neural network (ANN) model developed in this study in simulating groundwater levels in an alluvial aquifer system. Calibration of the MODFLOW was done by using weekly groundwater level data of 2. years and 4. months (February 2004 to May 2006) and validation of the model was done using 1. year of groundwater level data (June 2006 to May 2007). Calibration of the model was performed by a combination of trial-and-error method and automated calibration code PEST with a mean RMSE (root mean squared error) value of 0.62. m and a mean NSE (Nash-Sutcliffe efficiency) value of 0.915. Groundwater levels at 18 observation wells were simulated for the validation period. Moreover, artificial neural network models were developed to predict groundwater levels in 18 observation wells in the basin one time step (i.e., week) ahead. The inputs to the ANN model consisted of weekly rainfall, evaporation, river stage, water level in the drain, pumping rate of the tubewells and groundwater levels in these wells at the previous time step. The time periods used in the MODFLOW were also considered for the training and testing of the developed ANN models. Out of the 174 data sets, 122 data sets were used for training and 52 data sets were used for testing. The simulated groundwater levels by MODFLOW and ANN model were compared with the observed groundwater levels. It was found that the ANN model provided better prediction of groundwater levels in the study area than the numerical model for short time-horizon predictions. © 2013 Elsevier B.V. Source

Mohanty S.,Directorate of Water Management | Jha M.K.,Indian Institute of Technology Kharagpur | Kumar A.,Directorate of Water Management | Jena S.K.,Directorate of Water Management
Water Resources Management | Year: 2012

The present study focuses on the in-depth hydrologic and hydrogeologic analyses of Kathajodi-Surua Inter-basin within the Mahanadi deltaic system of Orissa, eastern India to explore the possibility of enhanced and sustainable groundwater supply. The results of 6 years (2001-2006) streamflow analysis indicated that the river flow is highly seasonal and it reduces to almost no flow during summer seasons. Land use map of the study area for the monsoon (Kharif) and post-monsoon (Rabi) seasons was developed by remote sensing technique and runoff estimation was done by curve number method. The runoff estimated for the 20-year period (1990-2009) varied from a minimum of 10.2% of the total monsoon rainfall in 1995 to a maximum of 43.3% in 2003. The stratigraphy analysis indicated that a leaky confined aquifer comprising medium to coarse sand exists at depths of 15 to 50 m and has a thickness of 20 to 55 m. The analysis of pumping test data at 9 sites by Aquifer-Test software indicated that the aquifer hydraulic conductivity ranges from 11.3 to 96.8 m/day, suggesting significant aquifer heterogeneity. Overall groundwater flow is from north-west to south-east direction. There is a 5 to 6 m temporal variation and 3 to 4 m spatial variation of groundwater levels over the basin. The rainfall-groundwater dynamics and stream-aquifer interaction in the river basin were studied by correlation analysis of groundwater level with weekly rainfall and river stage. The correlation between the weekly rainfall and weekly groundwater level was found to vary from 'poor' to 'fair' (r00.333 to 0.659). In contrast, the weekly groundwater level was found to be strongly correlated with the weekly river stage (r00.686 to 0.891). The groundwater quality was found suitable for both irrigation and drinking purposes. It is recommended that a simulation-cum-optimization modeling following an integrated approach is essential for efficient utilization of groundwater resources in the study area. © Springer Science+Business Media B.V. 2012. Source

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