Framework for Assessing the Impact of Salinity on Productivity Amy Cheung University of New South...

Framework for Assessing the Impact of Salinity on Productivity

Amy CheungUniversity of New South WalesWorkshop: “Policy Choices for Salinity Mitigation: Bridging the Disciplinary Divides”1-2 February 2007

1. Introduction

Salinity: mobilisation of salt in soil due to rising watertables from increased leakages into groundwater system

No fundamental difference in the hydrologic process: whether this rise was caused by reduction in deep-rooted native vegetation, or by natural means

1. Introduction

Salinity becomes problematic: damage to built and natural assets (roads, buildings, agricultural production, biodiversity, rivers and water supplies)

Threatens sustainability of productive agriculture areas and natural resources

Estimates of total cost and impact of salinity varies partly due complexity of the salinity problem, thus reliability of estimates

1. Introduction

No single solution can be applied to vastly different conditions across Australia: regional variations in hydrogeology, soil characteristics, climate

Effects of salinity:- not felt most severely in immediate vicinity of

the activity which generates the degradation- spread throughout the catchment area of a

given stream, termed “externalities” or off-site effects

1. Introduction

Aim: build a framework for assessing impact of salinity on farm productivity

That is, the effect this externality (salt) has on farm productivity

Large literature devoted to farm productivity – but production inputs are treated as either discretionary or non-discretionary

Salinity is an interesting case: located in between the two cases

2. Formulating the problem

Salinity: a bundled input with clean catchment water.

Salt + clean catchment water = saline water, z

Impact of applying this z to production on three farms, located from upstream to downstream

Effect of z on productivity – expect reduction in productivity as quality of water decreases

2. Formulating the problem

E.g. Same volume of z on two identical farms, situated upstream and downstream respectively, will not produce the same amount of output.

Quality of water deteriorates over time (unless with engineering intervention).

The movement of z units of water can be formulated into a network.

Begin with figure 1:

2. Formulating the problem

Figure 1

3

1

2

Upstream

Downstream

z

z

12z

23z

13z

2. Formulating the problem

Shows how much saline water z moves from each farm

Farm 1 passes saline water to farm 2, and farm 2 passes saline water to farm 3

Farm 1 can pass saline water to farm 3

2. Formulating the problem

z varies in quality as it moves from farm to farm

To show quality change, denoting: s = the quality of saline water (the amount of

“salt” in the water) v = the quantity of saline water (the volume of

water moved), z=f(v, s) Figure 2 illustrates the change in the quantity

and quality of saline water in the catchment.

2. Formulating the problem

Figure 2

3

1

2

Upstream

Downstream

z

z

12 12,v s

23 23,v s

13 13,v s

2. Formulating the problem

Accommodate this “saline water” z variable into formulation

(i) Consider including z as discretionary inputs:

Then z can be treated as other inputs (x) to produce output (y), that farmer can control over the amount of z into production.

2. Formulating the problem

True that farmer i has discretion over the quantity of water applied onto farm

But may not be possible to reduce the amount of salt in the water

(ii) Perhaps may be better to treat z as a non-discretionary variable since:

Farmer can’t alter the quality of the water

2. Formulating the problem

Ambiguous direction: z bundles “productive” water and “counter-productive” salt

Further complication arises: a multi-period case where the quality of z deteriorates over time (water quality not uniform)

Consideration of a network model:

3. Salinity as a network problem Formulate the three farms over time as a

network. Begin with attaching a cost c with each

movement of z c = combine cost of transporting water and

the cost of the change in quality in the water (e.g. cost on the farmer) as it moves from one farm to the next.

3. Salinity as a network problem Assume: c of moving increasing saline water

increases from one farm to the next Assuming in any one period, Figure 3 illustrates the different cost across

the three farms.

1 3 1 2 23c c c

Figure 3

3. Salinity as a network problem In the next period, accumulation of salt in the

water affects the farms. E.g. Assume the same amount of water

passes through the system over three periods, illustrated in figure 4:

3 t-1

1 t-1

2t-1

z

3t

1t

2t

3t+1

1t+1

2t+1

z

c3c2

c1

c4

c8

c7

c9

c5

c11

c12

c13

c6

c10

c14

c15

Figure 4

3. Salinity as a network problem Each node (e.g. 1t ) represents a farm in a

certain period cn is the cost of farm (due to salinity)

3. Salinity as a network problem Addition of time interdependence allows the

model to potentially assess the effectiveness of different policy options over time.

E.g. test policy via experiments, simulations Inclusion of uncertainty, such as the weather,

water reliability, extent of salt mobilisation in a given catchment

3. Salinity as a network problem ci=f(vi,xi, si ,i, ,)

yi=g(ci)

vi , xi discretionary variable

si ,i, = non-discretionary variable

4. Data requirement

To test this framework, the following data may be required:Value of farm produce:

Prices, quantitiesFarm inputs:

Land, Labour, CapitalWater input:

v = records of water usage s = the quality (EC levels)

4. Data requirement

Type of industry/crops across a catchment Salt tolerance of these crops:

At which point will saline water begin to reduce, stun, and terminates growth?

e.g. Change plant at times where c for a farm reaches some level to adapt to water quality changes

5. Summary

Salinity: a bundled input with clean catchment water.

Consideration of a network model: Assume: c of moving increasing saline water

increases from one farm to the next Addition of time interdependence allows the

model to potentially assess the effectiveness of different policy options over time.