IAPRS & SIS, Vol.34, Part 7, “Resource and Environmental Monitoring”, Hyderabad, India,2002 
There are other strategies, which fall in between these 
strategies. Evaluation of all these strategies will ultimately lead 
to the adoption of a strategy, which is optimal on the basis of 
economic, social and environmental indicators. 
2.7 The computational framework 
Behind the Shrimp-Crop DSS, the computational framework 
consists of a land use model, a salinity intrusion model and 
social, economic and environmental model. The output of the 
land use model is the spatial distribution of production regimes 
within the study area. The salinity intrusion model gives a 
spatial distribution of the salinity classes under different Gorai 
flow scenarios. The outputs from these models are used as 
inputs into a socio-economic and environmental model. This 
model uses a large database consisting of all relevant inputs and 
outputs of the shrimp and crop production systems and 
translates such outputs as “areas under land use and salinity" 
into “criteria” such as “net economic returns" and "aquatic 
biodiversity". The computational framework is described in 
more detail in Section 3. 
2.8 Analysis and evaluation 
The analysis step shows the impacts of alternatives in the form 
of graphics or score cards. The presentation may incorporate 
two steps. First, the user compares all impacts and effects in 
terms of the criteria as per the score card. The score card from 
the DSS lists the normalized values of the criteria for different 
cases such as those shown in Table 5. The analysis of each case 
is based on one strategy under a scenario. 
Table 2: 1999 landuse allocation ratio. 
Production regime Salinity Class 
<Sppt 5-10ppt 10-15ppt 15-20ppt »20ppt 
  
  
1 Bagda/Aman 3 24 34 39 30 
2 Bagdal/Bagda 0 0 8 18 0 
3 Aman 28 36 38 38 69 
4 Golda/Boro 15 6 6 0 0 
5 Aman/Boro 54 34 14 5 1 
Total 100 100 100 100 100 
  
Table 3: A strategy for maximizing paddy. 
Production regime Salinity Class 
  
  
  
  
<Sppt 5-1Oppt 10-ISppt 15-20ppt >20 ppt 
1 Bagda/Aman 0 0 0 0 0 
2 Bagda/Bagda 0 0 0 0 0 
3 Aman : 0 0 0 0 0 
4 Golda/Boro 0 0 0 0 0 
5 Aman/Boro 100 100 100 100 100 
Total 100 100 100 100 100 
  
Table 4: A strategy of balanced landuse. 
  
  
  
Production regime Salinity Class 
<5ppt 5-10ppt 10-15ppt 15-20ppt > 20 ppt 
| Bagda/Aman 3 24 42 57 30 
2 Bagda/Bagda 0 0 0 0 0 
3 Aman 28 36 38 38 69 
4 Golda/Boro 69 40 20 5 1 
5 Aman/Boro 0 0 0 0 0 
Total 100 100 100 100 100 
  
A comparative analysis of the strategies brings out such 
observations as the performance of most of the economic 
indicators, which are much lower in the maximize paddy 
strategy than the balanced landuse strategy. The maximize 
paddy strategy also brings down the foreign currency earning to 
a minimum. 
The analysis would also reveal that if all land is put under the 
Aman-Boro production regime, it would provide the best work 
opportunities for unskilled labour and access to common 
properties and small holdings. An optimal land use can be 
reached through the DSS following an interactive and iterative 
process of selection of land use policies and scenarios and 
comparative analysis of the score cards. 
Table 5: Values of the criteria for different strategies under 
one scenario. 
  
  
  
  
  
  
Environmental indicators Base case Strategy Strategy 
Max. Paddy Balanced LU 
Aquatic Biodiversity 38 1 37 
Mangrove Biodiversity 33 33 33 
Terrestrial Biodiversity 0 0 0 
Soil Condition 75 100 82 
Groundwater Supplies and Quality 71 0 70 
Social indicators 
Health — Risk of Waterborne Disease 86 100 86 
Health-Nutrition 46 98 41 
Education 37 16 $2 
Sanitation = Fresh Water Supplies 50 39 56 
Housing 36 100 26 
Access to common properties 65 100 51 
Access to Small Holdings for 64 100 62 
Production 
Work Opportunities for Women 31 0 47 
Job opportunities unskilled labour 38 100 20 
Economic indicators 
Net Economic Returns 31 17 45 
Regional Income 34 18 47 
Employment 34 46 49 
Foreign Currency Earned 19 0 43 
  
The comparative analysis may be followed by a ranking of the 
alternative strategies through multi criteria analysis (MCA) 
allowing the user to assign relative weights to each of the 
criteria to rank the strategies, based on the users political 
viewpoints and priorities. Such evaluation tools, however, have 
not been included in this DSS. 
3 THE COMPUTATIONAL FRAMEWORK 
3.1 General structure of the computational 
framework 
The general structure of the computational framework is shown 
in Figure 3. A major part of the computational framework is 
based on spatial models including a salinity intrusion model 
and a land use allocation model. Then a spreadsheet employing 
recursive equations generates and quantifies the environmental, 
economic and social trade-offs. 
According to the framework, land uses are allocated following 
a particular strategy. Such allocation will precipitate changes in 
a variety of environmental, economic and social indicators. For 
example, a shift to paddy cultivation from shrimp cultivation 
will improve soil conditions (environmental indicator), reduce 
regional income (economic indicator) and increase work 
opportunities for unskilled labor (social indicator). Salinity 
regimes in the study region alter the possible land allocation 
pattern. For example, with increasing flow from Gorai more 
area can be brought under paddy cultivation. 
3.2 Salinity intrusion model 
A hydrodynamic model simulates the flow velocity in the Gorai 
and associated river systems in the study area. The flow 
velocities from the hydrodynamic model and measured salinity 
at the downstream boundaries are used as inputs to an 
“advection and dispersion model" which simulates the surface 
water salinity throughout the river network. The simulated 
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