ESTIMATION OF PLASTIC FINE ALTERED RIVER BED PERMEABILITY USING ARTIFICIAL NEURAL NETWORKS

The permeability of the soil is one of the most important properties of an unlined earthen canal or river bed. Using fine plastic particles has experimentally proven to reduce soil permeability, but the experimental study of the effect of a variety of types of plastic fines and their percentages in riverbed soil is tedious work to do. Estimation of permeability of riverbed soil by altering it with plastic fines using Artificial Neural Networks (ANNs) may reduce this effort. Particle size distributions (PSDs) have a significant influence on the permeability of bed soils. Being able to predict the permeability of bed soil by knowing the PSDs may provide an easy approach to know the loss of water by percolation. This study has investigated the quantitative relationships between permeability and PSD indices using ANNs. The aim was to build a mathematical model capable of predicting the permeability of bed soil by PSD indices of choice. A model was built using ANNs including PSD indices as input and permeability as output. The model stated that the coefficients of curvature and uniformity (Cc) and (Cu) and effective particle size (D50) may be used to predict the bed permeability. The computational model was able to predict the effect of variation of PSD indices on bed permeability, thus allowing increasing the efficiency of the river bed, to ensure maximum downstream water supply, lesser seepage and percolation and better productivity. The test result has confirmed the efficiency of the developed ANN tool in predicting the bed permeability for different PSD combinations.

Climate smart agricultural technologies in rice-wheat water stressed regions of Punjab, India- A review

Intensively cultivated rice-wheat cropping sequence of Punjab, India responsible for many sustainability issues viz. declining underground water, declining soil health, arising micro-nutrient deficiencies etc. Around 1.3 M ha-m additional withdrawal of water from the ground is being taken place annually in Punjab and mainly it is used for the rice crop which is not a traditional crop of the region. Puddling, seepage and percolation losses are the main sources of water loss from the rice based cropping systems in the Indo-Gangetic plains (IGPs) and many Resource Conservation Technologies (RCTs) have been recommended for water saving. The real water saving techniques are those which hinder the water from going into those sinks from where it cannot be reused (Evaporation, E) and diverted greater fraction of water of ET toward transpiration (T) which is desired as greater transpiration, greater the inflow of water and nutrients andwhich ultimately increase the grain yield with the lesser consumption of irrigation water as interval in between two irrigation increases, which further increase the water productivity. Among different RCTs, short duration crop varieties and delaying transplanting time are the real water saving techniques for the regions where water table is already declining down, however other RCTs may be suitable for the regions facing water logging problems as these cut down the drainage losses and these energy saving rather than water saving techniques.

On-Farm Balancing Reservoir Design on the Basis of Canal W ater A vailability and Gr ound W ater Quality

Balancing reserv oir is an intermediate w ater storage tank betw een the w atercourse and the farm. Ev en in high rainfall areas, agriculture is not sustainable in the absence of w ater storage structures. Inflow components i.e. w ater av ailability of canal w ater , groundw ater and rainfall occurrence ov er the balancing reserv oir . The outflow components mainly w ater requirements for crops and ev aporation from surface area of w ater balancing reserv oir , balance the w ater storage capacity that mitigates the w ater demand of the crops and on the basis of balancing components deciding the design of w ater balancing reserv oir . A comparativ e analysis rev eals that the part of this capacity results from a v ery significant dev elopment of balancing reserv oir (particularly in the smaller range of sizes) in the time interv al, probably as a response to rapidly declining canal supplies. The rainfall trend analysis shows that the rainfall occurrence at probability at 50% chance is 370.8 mm which occurs once at tw o y ears of recurrence interv al that shows the occurrence of surface as w ell as subsurface w ater to the study areas. A fundamental implication is that field 'losses' such as seepage and percolation do not necessary to represent losses at a larger scale.