PESERA-DESMICE: Land management evaluation model

Table of Contents

1. Authors
2. Summary
3. Acronyms
4. Introduction
5. Coarse-scale model description
   1. The PESERA model: summary
   2. Alternative approaches to assessing soil erosion
   3. Process representation in PESERA
   4. Extensions of PESERA
   5. Adapting PESERA
   6. Assessment at catchment scales
6. Cost-effectiveness modelling
   1. Step 1
   2. Step 2
   3. Step 3
   4. Step 4
   5. Step 5
   6. Step 6
   7. Step 7
   8. Step 8
   9. Step 9
   10. Step 10
   11. Step 11
   12. Step 12
7. Agent-Based modelling in Spain
   1. Phase 1
   2. Phase 2
   3. Phase 3
   4. Phase 4
   5. Phase 5
   6. Phase 6
8. Input-Output modelling in Spain
   1. Model construction
   2. Scenario analyses
9. References

Step 3

Step 3: Investment cost calculation of the technology

The WOCAT QT in most cases presents a cost estimate of the technology. However, this estimate is made for its most common application area or is an informed estimate of average costs across several local application areas. In reality, construction costs will differ based on environmental factors (e.g. slope) and socio-economic factors (e.g. distance to market). The same holds for maintenance costs. In this phase, investment and maintenance costs will be made spatially explicit by considering both types of factors. For each type of input the location of source areas (markets) needs to be identified and transportation costs defined. The following points present the pathway to arrive at spatially-explicit investment and maintenance costs:

• Data preparation: the data contained in the WOCAT database will be stored in a modified database to allow better querying. This also involves the inclusion of rules of how inputs would vary with environmental conditions. Data on source areas (markets), costs of inputs in those source areas, transport methods and associated costs, and infrastructure will need to be prepared. Further details about this will be sent to study site coordinators in due course. Quantities and unit costs will be assessed separately;
• Variation of input requirements with varying environmental conditions: a cost breakdown for the standard situation is provided in the database (WOCAT QT data). Through a query, a single line of total quantity per input category per technology will be extracted. This is the quantity for a standard situation. By using technology-specific rules, the standard quantities per input category will be linked to the environmental conditions in each grid cell;
• Calculation of the cost of inputs at the destination area: network analysis will be used to specify the price of inputs in nodes of an infrastructure (road) network, assuming the cheapest transport path. From there, the costs of transport to individual grid cells will be added;
• Labour: this is a special case as it entails multiple return journeys. This does not only affect the labour (opportunity) cost, but also the total amount of labour needed. Hence, for the case of labour, distance-related travel time will be considered to reduce the effective 'on-site' person day from 1 with a proportionate fraction. If this effective person day is e.g. 0.8, a total 'on-site' labour input of 40 will then require 50 person days (possible transport costs for 50 return journeys would still need to be added when the journey is not made on foot);
• Multiplying spatially-explicit inputs with their respective spatially-explicit costs gives the total investment or annual maintenance cost.

While the above presents a general methodology, some deviations may be necessary. For example, some inputs may be assumed to be present everywhere (e.g. earth) without the need to consider transport costs. Some, like wood or stones, could be linked to input map layers to consider patchy availability across a landscape. The source area for labour may be hard to define, as where farmers live and where their fields are is very likely unknown. One solution to this could be to assume an average estimated distance from farm to field. Alternatively, in cases where population lives in village centres (and those are digitized as a GIS layer), the distance from farm to field can be assumed to be that of the closest distance village centre - grid cell.

The above refers to investment cost calculation for new technologies. Where SLM technologies are already existing and their extent is mapped (WB1), treated areas can either be considered as areas where no investment is needed (taking only maintenance costs into account), or as areas where upgrading is necessary to reach the design standards of newly constructed technologies (where upgrading can be a variable percentage of the standard construction costs; maintenance costs are fully accounted for).

Data sources:

1. WOCAT QT - further cost breakdown may need to be requested from study sites
2. Estimates of the variation of implementation costs for each technology with the most important environmental factors need to be requested from the study sites and complemented by literature research (an important source may be construction manuals from extension services if it concerns technologies that are already being implemented)
3. Additional input data required for distance-related costs are:
4. Source point/area vector data needed for all input types (or assumed to be available everywhere)
5. Price data for all input types (prices in source area)
6. Infrastructure data needed and their accessibility for different transport categories
7. Table of cost, time (labour), and capacity per transport type and distance unit
8. Maps of existing SLM technologies (WB1) and data of their current quality/maintenance status or age

Intermediate product: Raster layers showing the spatially explicit investment and maintenance costs of implementing a technology (for an example see Figure 3.4).

Figure 3.4: A schematic example of calculating spatially-explicit investment costs of a technology