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Conjunctive Use of Surface and Ground Water for the Economic Food Productivity

Conjunctive Use of Surface and Ground Water for the Economic Food Productivity Dr. (Eng.) S.S.Sivakumar Senior Lecturer, Faculty of Engineering University of Jaffna. flj;jg;gLk; Mtpahfp ePH EVAPOTRANSPRATION. ePH tPo;gbT / kio. Precipitation. ePH Njf;fq;fs ; Reservoirs. MtpahFk; ePh;.

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Conjunctive Use of Surface and Ground Water for the Economic Food Productivity

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  1. Conjunctive Use of Surface and Ground Water for the Economic Food Productivity Dr. (Eng.) S.S.Sivakumar Senior Lecturer, Faculty of Engineering University of Jaffna

  2. flj;jg;gLk; Mtpahfp ePH EVAPOTRANSPRATION ePH tPo;gbT/kio Precipitation ePHNjf;fq;fs; Reservoirs MtpahFk; ePh; Rivers cl;GFk; ePH INFILTRATION ,wq;F ePH PERCOLATION fly; sea gf;ftbg;G ePH SEEPAGE cg;GePH Salt water epyj;jbapy; cs;s ePH GROUND WATER FLOW ePhpay; tl;lk; Hydraulic Cycle

  3. Water resource in globe; 1.36 x 108Million Hector meter 97.2% 2.8% Fresh water Salt water 2.2% 0.6% Surface water Ground water 0.08% 0.09% 2.05% 0.03% 0.57% River Others Glacis Extractable Non-Extractable Human usage ????

  4. Economic Food Productivity • Proper utilization of climate condition • Cultivation pattern • Water availability • Quantum of water • Cost of water • Timing of water availability • Marketability

  5. Conjunctive use of water • What you mean by conjunctive use? • What is the importance of water in economic food production • How to inter connect all the water resources? • Whether a model representation possible? • Model formulation • Model calibration • Model validation • Prediction of system response for various decision

  6. Conceptually the modeling technique used for system representation can be very simply explained as below. Select or formulate a suitable model Assume the parameters approximately Adopt some error function to quantify the difference between measured and predicted responses Minimize the error function Determine the parameters accurately Predict system response Modeling Technique

  7. Actual System Response Model predicted System Response Real Physical System Mathematical Model Non - Modeled Input Modeled Input Solution Strategy (Optimization) Schematic representation of the process of system modeling and optimization.

  8. Model Formulation

  9. Model Formulation Subsurface flow = Change in storage - Vertical flow

  10. Model Calibration

  11. Model Calibration While doing the 2nd node minimisation, if it is connected to the 1st node the corresponding TiB found from previous minimisation to be used and that particular constrain be removed from the 2nd optimisation model

  12. M - No of observation wells surrounding node B hi - peizometric head of node i hB - peizometric head at node B YiB = (JiB/LiB) - conductance factor TiB - transmissibility at mid point between node B and i JiB - length of perpendicular bisector associated with node B and i. LiB - distance between nodes i and B AB - polygonal area of node B SB - storage coefficient of node B QB - volumetric flow rate per unit area at node B. j -time Prediction Process For prediction the water balance equation is to be re arranged to have hBj+1 in LHS with RHS as function of hBj+1 . By Gauss-Seidal iteration method hBj+1to be found.

  13. Possible policies for economic food production • Raising the water table for economic pumping • Keeping certain percentage of water in irrigation schemes for recharge • Increasing temporary detention during off season raining • Blocking /reducing sub surface flow to sea • Practicing proper water management • Micro irrigation system

  14. Thank you sssiva100@yahoo.com

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