Essay: Model simulation

Hessel et al. (2003) states that LISEM could be useful for simulating different scenarios for the same area. He also states that due to the necessity to recalibrate the model for each specific event, the model is not very useful to predict future discharge. The LISEM model is an event-based model, which means that only the effects of short-term events will be shown and simulated for different SWC scenarios.
Therefore, the study done by Baartman et al. (2013) to see whether the event-based or the landscape development model could do predictions as the other model is an interesting questions. SWC strategies usually focus on short-term objectives and long-term impact, so the combination of both models (maybe even in one model) could be a step towards better predictions of soil erosion in different SWC strategy scenarios. Nonetheless, combining both an event and a landscape evolution model increases the simulation uncertainty and the complexity of the model (Baartman, Temme, Veldkamp, Jetten, & Schoorl, 2013).
Nonetheless, even when the model simulations are calibrated and estimated accurately for the short-term effect, there is little prove this will be helpful for policy makers. Both Hessel et al. (2003) and Masters (2009) state that the LISEM model can be useful to simulate different scenarios and can be a helpful tool for choosing SWC measures, but no specific examples are given. Only Hengsdijk et al. (2005) give a specific comparison between SWC measures, but these results are questioned (Nyssen, et al., 2006). Of course, an illustrated scenario provided by GIS with LISEM will simulate erosion and deposition after a heavy rainfall and might lead to intrinsic motivation by locals to decrease soil losses. But, when taking the results from Hengsdijk et al. (2005), the limited effects from different SWC measures on reducing soil erosion would not stimulate local participants and policy makers to invest in a SWC strategy or the measures would be ill-targeted, so in the end benefits would not justify the costs (Nyssen, et al., 2006). Both in when presenting ideas with model scenarios simulation as well as in real-life.
And even when certain measures seem to be more effective and sustainable then other, it would not mean these measures would actually be (or possible to be) implemented. Socio-economic factors like policies, social acceptability, financial efficiency, resource availability (in money, in materials or social capital), market prices or measures taking valuable land and environmental factors like nutrient availability, water quality or native plant availability and growth. The final assessment of the choice for implementing certain measures should therefore still be done with a Multi Criteria Analysis (MCA) and/or a Cost-Benefit Analysis (CBA). A study from (Teshome Firew, de Graaff, & Stroosnijder, 2014) states that ‘the MCA is a useful tool that also takes into account non-monetary and less quantifiable effects of SWC practices’. For example, on areas with steep slopes farmers preferred to invest in measures more focused on ecological aspects, while on area with less steeper slopes farmers preferred to invest in measures focused on economic gain (Teshome Firew, de Graaff, & Stroosnijder, 2014).

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