Operational Options of Water Resource to Improve Food Productivity by

Conjunctive Use of Surface andGroundwater in Dry Zone

Dr (Eng.) S.S.SivakumarDeputy Director of Irrigation

Mullaitivu

Seminar on “Operational options of water resource to improve food productivity by conjunctive use of surface water and groundwater in dry zone” on 26th February 2009 in the Northern provincial council conference hall Trincomalee Sri Lanka

 

“Growth of a Nation Depends on Effective Economic and Equitable

Use of Water Resource”

2

3

Problem in Water Resource

• Economically feasible surface water storage sites are limited

• Unplanned utilization of water resource by various stake holders

• Difficulty in analytical solution for groundwater storage, due to non-homogeneous and anisotropic nature of groundwater resource

4

Objective

To improve the groundwater system in a restricted areausing modeling technique to spell out

An economic policy in operating the minor and medium Irrigation schemes

A new technique of peripheral treatment by clay or geotextile or a subsurface dam

To economize the cost of water for irrigation and in turn improve the productivity

5

Methodology

1. Study area selection

* Selection of observation wells.

* Polygonal network formulation.

* Polygonal parameter calculation.

2. Data collection

* Seasonal/Monthly field data

* Data from documents and publication3. Model * Formulation

* Calibration* Validation* Prediction

4. Analyzing predicted system response for various

* Operational policy of minor medium irrigation scheme

* Boundary treatment

5. Economic analysis

6

Selection of Study Area

• Vavuniya District.• 71.5 squire miles (185 sq.km)• 41 Observation wells• 6 Medium Irrigation schemes• 40 Minor Irrigation schemes• 3 Agrarian service centers• 31 Grama Nilathary divisions

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Polygonal Network of the Study Area

The study are is divided into 41 Thissin polygons based on the 41observation wells

Maximum polygonal area 8440 m2 (node 26)

Minimum polygonal area 1294 m2 (node 35)

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Aquifer Characteristic

– Unconfined– 10 to 15 m. thick– Gravelly or decomposed material– Bottom layer of this aquifer is a rarely fractured

crystalline rock having vertical transmissibility less than one sq. meter per day.

– Darcy's law (Linear resistance to laminar flow) and Dupuit's assumption (vertical flow can be neglected) are applicable

– Two-dimensional flow system

11

Hydraulic Assumptions

The aquifer is treated as a two-dimensional flow system

Only one aquifer system is modelled with one storage coefficient in vertical direction

The aquifer is bounded at the bottom by an impermeable layer(aqutard)

The upper boundary of the aquifer is an impermeable layer (confined aquifer) or a slightly permeable layer (semi confined aquifer) or the free water table (unconfined aquifer)

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Hydraulic Assumptions ctd.

Darcy’s law (Linear resistance to laminar flow) and Dupuit’s assumption (vertical flow can be neglected) are applicable for the aquifer under study.

The processes of the infiltration and percolation of rain and surface water and of capillary rise and evapotranspiration, taking place in the unsaturated zone(vadozone) of the aquifer (above the water table) need not be simulated.

“This means the net recharge to the aquifer is calculated manually and prescribed to the model”

13

Operational Assumptions

Same groundwater elevation within a polygonal area.

The area where the minor & medium irrigation schemes are governing the water table, then one meter below FSL of the tank can be taken as the water table elevation

The rain fall of Vavuniya can be used for entire area under study as all the polygons are around Vavuniya rainfall station and within 15 km radius.

The irrigation efficiency 70 %

14

Operational Assumptions ctd.

Conveyance efficiency of the canal 80% As the irrigation canals within this study area are very

small and for simplicity recharge from canal and irrigation field can be combined for calculation

All the 6 medium and 40 minor irrigation schemes within the study area have their maximum head of water less than 3m. Hence the percolation of water is calculated either as 0.005m/day/planearea or 0.5% of the volume stored monthly

For keeping 10% of the full capacity of the minor medium irrigation scheme, 12% of the cultivation to be forgone.

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Economic Assumptions

Benefit cost ratio based on present value should exceed unity

Percaptia domestic water consumption - 160 litres/day Water requirement for OFC

Maha 1.5 to 2.0 ac.ft./ac.Yala 2.0 to 2.5 ac.ft./ac.

Net return from one acre of paddy cultivation - Rs. 3875/= One meter raise in water table will save 1.4 unit of

electricity for the pumping of 10 m3 of water One mile of peripheral treatment will cost Rs. 5.32million

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Data collection

Field data Seasonal water levels collected from September 1997 to

May 2004 Monthly water levels collected from April 2001 to May 2003

Data from yearly publication Rain fall Population Paddy/OFC Cultivation Water stored in Irrigation schemes Pumping from production wells

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Processing Data

• Connecting water levels to MSL• Converting data obtained from publications in to polygonal

seasonal data such as• Capacity of water store in Irrigation schemes• Water issued for cultivation from Irrigation schemes• Rain fall volume• Pumping from domestic wells• Pumping from agro. wells• Pumping from production wells

Note:-Discharging period 1st June to 31st Sept.- 122 days Recharging period 1st Oct. to 31st May -

224 days.

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Modeling Technique

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

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Modeling Technique

Actual SystemResponse

Model predictedSystem Response

MathematicalModel

Modeled InputNon - Modeled

Input

Real PhysicalSystem

Solution Strategy(Optimization)

Schematic representation of the process of system modeling and optimization.

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Model Formulation

Observation well

Typical polygon for node B

hi - piezometric head of node ihB - peizometric head at node BYiB = (JiB/LiB) - conductance factorTiB - transmissibility at mid point between node B and iJiB - length of perpendicular bisector associated with node B and i.LiB - distance between nodes i and BAB - polygonal area of node BSB - storage coefficient of node BQB - volumetric flow rate per unit area at node B.M - No of observation wells surrounding node Bt - time step between j and j+1

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Model Formulation ctd.Integrated finite difference form of water balance for

a typical polygon can be written as

1111

1

)()(

jBBB

jB

jBt

SiBiB

jB

ji

M

i

QAAhhTYhh B

11 jBB

jB QAAQowVerticalfl

iBiBjB

ji

M

i

jB TYhhQQflowSubsurface )( 11

1

1

)(. 11 jB

jB

BBj hht

SABSTORorageChangeinst

11111 jdB

jirB

jifB

jisB

jBB QdQcQbQaQAowVerticalfl BBBB

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Model Formulation ctd.

Subsurface flow + Vertical flow = Change in storage

1111

1

1 )()(

jBBB

jB

jBt

SiBiB

jB

ji

M

i

jB QAAhhTYhhRES B

T h e f i r s t s t e p o f t h e m o d e l r u n n i n g i s t o f i n d t h e f o l l o w i n g

1 . Q Q Bj + 1 / T i B

2 S T O R E . B j + 1 / S B

W h e r e

1 jBQQflowSubsurface

1. jBSTORorageChangeinst

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Model Formulation in Spreadsheet

Data entrySeasonal Identification on one cell (D7)Nodal connectivity

A 41 x 41 square symmetric matrix B11 to AP 51Seasonal water level

Water level in MSL B61 to K101Conductance factor (J/L)

Manually calculated and fed into a 41x 41 symmetric

matrix ( B 211 to AP 251)

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Model Formulation in Spreadsheet ctd.

Water level matrix for the seasons 41 x 41 matrix ( B111 to PP151) will give water levels

of the seasons Head difference matrix

Will give the head difference for the particular connection

Denoted by row number and column number (B141 to AP201)

Intermediate calculations

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Model Formulation in Spreadsheet ctd.

Matrix of lateral flow divided by Transmissibility

41 x 41 square matrix B261 to AP301

Change in storage divided by Storage coefficient

Only a column 311 to B351

Final calculation

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Calibration of Model Using Optimization

Where, M - No of observation wells surrounding node B N - No of seasons calibration is to be done

Calibration is done from October 1997 to September 2001 (eight seasons) Subject to 0.001 < SB <0.01 15 < TiB <25 0.075 <a <0.15 0.05 <b <0.1 0.05 <c <0.1 0.9 <d <1.1

2

1111

11

)()(

j

BBBjB

jBt

SiBiB

jB

ji

M

i

N

i

QAAhhTYhhMin B

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Boundary sub surface flow component will be replaced by another unknown parameter "q"times the difference in head of water. In the boundary node minimisation model, this "q" also will come as an additional constraint.

Constrain for the boundary nodes ofstudy area

The range of this will be given by analysing the topography of the area surrounding the boundary and the seasonal water level contour.

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Four types of boundaries 1.Zero flow 2,3 2.Head controlled 4,5,6 3.Flow controlled 1 4.Free surface 7

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123variables for polygonal recharge coefficients Rainfall Tank storage Irrigation

41 variables for withdrawal 100 variables for transmissibility 41 variables for specific yield 17 additional variables for boundary lateral flow

Constrains for the Entire Study Area

Found by error minimisation using “MATCAD 2000”.

.

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Prediction Process

M - No of observation wells surrounding node B hi - piezometric 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

BBiBiBjB

ji

M

i

jBB

jB

jB AStTYhhQAhh /.)(. 11

1

11

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Prediction Model in Spreadsheet

For prediction the water balance equation has been re arranged to have hBj+1 in

LHS with RHS as function of hBj+1 . as below.

Gauss-Seidal iteration method, hBj+1 could be found utilizing the function of GOALSEEK on spreadsheet.

As hBj+1 is connected to M surrounding nodes, while finding the hBj+1 the already found hBj+1 will slightly vary

After completing first iteration process for all the forty one nodes, the same process to be repeated five to six times to get accurate results.

BBiBiBjB

ji

M

i

jBB

jB

jB AStTYhhQAhh /.)(. 11

1

11

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Prediction Model in Spreadsheet ctd.

Main matrixes formulated in spreadsheet

Time step Δt Nodal connectivity matrix Water level matrix for the selected time step Head different matrix Conductance factor matrix Transmissible matrix Calculation of trial hBj+1 Error in water level

The function of GOALSEEK in spreadsheet with a small micro has been used in this prediction to do all the iteration on few key strokes to predict the water level with zero error.

Even though the model is formulated season wise prediction is possible monthly or even weekly by changing few cells formula and adding few more cell formula.

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Model Validation

To test the validity of the model, using the calibrated parameters and using 8th season (Sept. 2001) water level as initial water level and for the rest of the inputs the 9th season (May 2002) water level was predicted using the prediction model

Where ever the predicted values were not matching with the

observed value the stress parameters were systematically slightly adjusted to get good response

The same way, using 9th season (May 2002) water level as initial

water level and for the rest of the inputs the 10th season (Sept. 2002) water level was predicted using the prediction model

The same way the water levels of May 2003, Sept. 2003 May 2004

and Sept. 2004 were predicted and compared with observed water levels.

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Results of Validation

Boonstra and Ridder suggested a refinement by introducing a relax coefficient for all nodes.

Comparing the predicted results with the data used for calibration an error of –0.8% to +2.1% is observed. For a groundwater simulation model in integrated finite difference method an error of this magnitude is allowable depending on the scope of the project

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Refining Results

While calibrating the actual model all hydro geological stress parameters TiB , SB and Recharge coefficients obtained from optimisation have to be systematically slightly adjusted to get less error in water levels

111 Re*Re)(Pr)( jBB

jB

jB slaxedictedhModifiedh

1111Re jB

jB

jB

jB orageChangeinstowLatteralflQs

tSATYlax

BBiBiBB /.

1Re

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Peripheral Treatment Area Boundary

37

Behavior of Aquifer with Decrease in Transmissibility

The T values between seventeen very extreme peripheral nodes (18, 30, 41, 29, 28, 40, 39, 38, 37, 36, 24, 35, 22, 34, 33, 32, 31) and fourteen interior adjoining nodes (8, 17, 16, 15, 27, 26, 25, 13, 23, 12, 11, 21, 20, 19) were reduced in steps of 2 – 3 m2 /day and the water levels were predicted.

T values were reduced in five steps It was found from the predicted water levels, there was not

much significant variation in water level change after 40 – 55 % reduction in T.

Even below this range also few nodes gained on the expense of others in the close vicinity

The maximum gain or lose occurred for the reduction of T by 39.8 % on average (i.e. step 4).

This effect occurred only in recharge season (Oct. – May).

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Behavior of Aquifer with Decrease in Transmissibility ctd.

Effect on Outer Boundary Nodes

Nodes 18, 41, 29, 35, 34, 33, 32 and 31 lost their water level by 1.25 – 2.0 ft. in recharge season (Oct – May). The nodes 28, 39, 36 and 24 gained their water level by 1.0 – 2.25 ft. in recharge season Oct – May, whereas nodes 30, 40, 38, 37 and 22 showed only very negligible variation.

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Behavior of Aquifer with Decrease in Transmissibility ctd.

Effect on Nodes within Treated Boundary

The gainers of this boundary treatment are mostly the nodes within the boundary. The nodes 8, 19, 17, 16, 27, 26, 25, 23, 11, 21, 20 and 2 gained their water level by 1.5 – 2.75 ft. in season Oct – May, whereas nodes 13 and 14 lost their water level by 0.75 – 1.25 ft. in recharge season (Oct – May) and other nodes did not show any significant impact due to this boundary treatment

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Behavior of Aquifer with Various Operational Policies of Irrigation Schemes

The behavior of water table of this catchment was analyzed by keeping 10, 20, 30, 40 and 50 % of the full capacity of the irrigation scheme during season June – Sept.

The water table in almost all (except node 37 and 38) nodes, mainly

during discharging season (June – Sept.) considerably gained.

During step 2 and step 3 the gain of water table was between 2.5 and 3.75 ft., scattered among study area during season June – Sept. and 1.75 to 3 ft., during season Oct – May.

But this trend was changed in step 4 and step 5. In step 4 and step 5 the nodes 6, 7, 9, 17, 20, 21, 13, 25, 27, 39, 31and 19 showed only little incremental change of 0.25 to 0.75ft. in water level.

This positive progressive change observed during discharging season (June – Sept) with change of operational policy of irrigation schemes within catchment under study.

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Behavior of Aquifer with Various Operational Policies of Irrigation Schemes

with Boundary Treatment

During this analysis every steps first option was carried out for all five steps of second option. By this method altogether twenty five trials were carried out. Even though this was very tiresome and very cumbersome exercise very interesting shift was observed in the research finding.

The result of option one was shifted positively almost one step further. The step 4 of option one and two resulted an average gain of water table during discharging season (June – Sept) by 3.0 to 4.75 ft excluding nodes 37 and 38.

This is almost a gain of water level of 60% to 70% of water

table loss in between two seasons in 95 % of the catchment under study.

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Summary of Operational Research The above operational research summarizing the following out puts as policy alternatives as integrated conjunctive operation and management of minor / medium irrigation schemes in any restricted catchment.

Peripheral boundary treatment up to the reduction of permeability by 35% to 45% is giving water table raise of nodes closer to treated boundary by 1.5 ft. to 2.75 ft. during recharging season (Oct – May).

Changing the operational policy of minor / medium irrigation schemes by forgoing cultivation by 25% to 35% is giving water table gain in almost all nodes except nodes 37 and 38 by 1.75 ft to 3.0 ft during discharging season (June – Sept).

Combining peripheral reduction in permeability by 35% to 45% and forgoing cultivation of minor / medium irrigation scheme by 45% to 55% result an average gain of water table during discharging season (June – Sept) by 3.0 to 4.75 ft excluding node37 and 38.

This is almost a water level gain of 60% to 70% of water table loss in between two seasons in 95 % of the catchment under study.

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OptionsSteps of each

option

Discharging

periodRecharging period

Nodes on which raise in

water level occurred

Operational policy

change

Forgoing 24% -

36% cultivation

0.762

to

1.143

0.533

to

0.914

Scattered except 37 and 38

Forgoing 48% -

60% cultivation

0.838

to

1.371

0.610

to

1.067

Scattered except 37 and 38

Boundary

treatment

Reduction of

permeability by

40%

-0.381 to

-0.610.

18, 41, 29,35,34,33,32 and

31

0.305 to 0.68628, 39,36 and 24

-0.229 to

-0.45713 and 14

0.457 to 0.838 8,19,17,16,27,26,25,23,11,21,

20 and 2

Combination of

policy change and

creation of artificial

boundary

Step 4 of both the

season0.914 to 1.448

95 % of the nodes within the

catchment

Summary of maximum water level change in m for various options

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Economic Performance Indices

There are mainly the following four methods or indices that are considered conceptually correct for comparing alternatives.

The present worth method The rate of return method The benefit-cost ratio method The annual cost method.

45

Summary of Economic Analysis of the Operational Research Detail cost benefit analysis for all the three findings

of the operational research reveled

The boundary treatment led almost 90% of the trial, the benefit cost ratio became less than one. Only if the year of implementation exceeded 20 years and interest rate 10% it showed positive results and that too was for the last two trials

The alternate policy on changing the operational policy of minor / medium irrigation schemes by forgoing cultivation by 24% and 36% gave the benefit cost ratio became greater than unity occurred almost 80% of the observation wells and the gain in water level was around 45% to 65% of the loss in water table between two consecutive seasons.

The combination of the above two alternatives did not yield much economic results due to high cost of boundary treatment. Even though for the last two steps it showed positive results those were also for the implementation period of 20 years and interest rate of 10% and permeability reduction by 47% to 50%.

46

OptionSteps for each

seasonBenefit cost ratio

Operational policy

change

Discharging season Recharging season

2 14.52 1.59

3 14.63 1.46

4 12.43 1.33

5 10.27 1.13

Boundary treatment

Year of

implementation20 25

Interest rate 7.5% 10% 7.5% 10%

3 0.73 0.97 1.15 1.66

4 0.88 1.17 1.39 2.01

5 0.83 1.10 1.30 1.88

Combination of

policy change and

creation of artificial

boundary

Year of

implementation20 25 20 25

Interest rate 7.5% 10% 7.5% 10% 7.5% 10% 7.5% 10%

3 0.97 1.13 1.28 1.78 0.82 1.09 1.17 1.75

4 1.09 1.19 1.49 2.23 1.01 1.13 1.44 2.18

5 1.04 1.13 1.42 2.22 0.97 1.15 1.37 2.02

Summary of benefit/cost ratio greater than unity option and steps

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Summery of the Research Finding

The best economically feasible option for implementation in any restricted area

“The change in operational policy of minor / medium irrigation schemes by forgoing one third of the cultivation under minor / medium irrigation schemes or keeping one fourth of the storage of minor / medium irrigation schemes at any time will recover on an average of 45% to 65% of the loss of water table in any consecutive seasons in almost 80% to 90% of the area under consideration”

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Implementation of the Research Finding

No time bound No area specific Additional financial resource not require to implement

But proper knowledge based awareness is required to implement this policy in field among the stake holders.

Even now the practice of alternate track cultivation in different years depending on availability of water in the irrigation shames are practiced

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Conclusion

“This research finding shows that 25% of the storage of minor / medium irrigation scheme can be kept at any time balance by forgoing one third of the cultivation under the minor / medium irrigation scheme for recharging the groundwater and make the water table to gain on an average of 45% to 65% of the loss of water table in any consecutive seasons in almost 80% to 90% of the area under consideration for the economic utilization for domestic as well as agriculture use”

Recommendation

“Construction of new or reconstruction of abandoned minor /medium irrigation scheme with 25% of storage exclusively for recharging groundwater and changing the operational policy to keep 25% of the present storage of existing minor /medium irrigation scheme to recharging groundwater will reduce considerably the average cost of irrigation water due to less energy cost and this in turn will increase the extent of cultivation per unit of irrigation water and led to increase in productivity”

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51

Area of Future Study

“Further study on policy alternative towards conjunctive use water management policy of major irrigation schemes will be very useful in macro development of water resource in developing country like Sri Lanka”

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Advantages of Conjunctive use of Surface and Groundwater

Greater water conservation Operation of both surface and groundwater reservoirs provides for large water storage

Smaller surface storage Groundwater storage can provide for water requirements during a series of dry years

Smaller surface distribution system Greater utilisation of groundwater from widely distributed wells

Smaller drainage systemPumping from wells aids in controlling the water table

Reduced canal liningSeepage from canals is an asset because it provides artificial recharge to groundwater

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Advantages of Conjunctive use of Surface and Groundwater ctd.

Smaller evapotranspiration lossesGreater underground water storage with lowered groundwater level is reduces losses.

Greater control over outflowSurface waste and subsurface outflow are reduced by conjunctive use, thereby providing greater water conservation.

Less danger from failureThe smaller the dam reservoir storage, the smaller the damage or risk.

Reduction in weed seed distributionWith a smaller surface distribution system there is less opportunity for spread of noxious weed seeds.

Better timing of water distributionAn irrigator prefers to have water available when he wants it, as from a pump, than to take water on schedule from surface conduits.

Thank U

“Growth of a Nation Depends on Effective Economic and Equitable

Use of Water Resource”

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