Browsing by Person "Lippe, Melvin"

Now showing 1 - 1 of 1

Simulating the impact of land use change on ecosystem functions in data-limited watersheds of Mountainous Mainland Southeast Asia
(2015) Lippe, Melvin; Cadisch, Georg
The presented PhD thesis deals with the development of new modelling approaches and application procedures to simulate the impact of land use change (LUC) on soil fertility, carbon sequestration and mitigation of soil erosion and sediment deposition under data-limited conditions, using three mountainous watersheds in Northern Thailand, Northern and North-western Vietnam as case study areas. The first study investigated if qualitative datasets derived during participatory processes can be used to parameterize the spatially-explicit, soil fertility-driven FALLOW (Forest, Agroforest, Low-value Landscape Or Wasteland?) model. Participatory evaluations with different stakeholder groups were conducted in a case study village of Northwest Vietnam to generate model input datasets. A local colour-based soil quality classification system was successfully integrated into the FALLOW soil module to test scenarios how current or improved crop management would impact the evolution of upland soil fertility levels. The scenario analysis suggested a masking effect of ongoing soil fertility decline by using fertilizers and hybrid crop varieties, indicating a resource overuse that becomes increasingly irreversible without external interventions. Simulations further suggested that the success rate of improved cropping management methods becomes less effective with increasing soil degradation levels and cannot fully restore initial soil fertility. The second case study examined the effects of LUC on the provisioning of long-term carbon sinks illustrated for a case study watershed in Northern Thailand. Based on land use history data, participatory appraisals and expert interviews, a scenario analysis was conducted with the Dyna-CLUE (Dynamic and Conversion of Land use Effects) model to simulate different LUC trajectories in 2009 to 2029. The scenario analysis demonstrated a strong influence of external factors such as cash crop demands and nature conservation strategies on the spatial evolution of land use patterns at watershed-scale. Coupling scenario-specific LUC maps with a carbon accounting procedure further revealed that depending on employed time-averaged input datasets, up to 1.7 Gg above-ground carbon (AGC) could be built-up by increasing reforestation or orchard areas until 2029. In contrast, a loss of 0.4 Gg in AGC stocks would occur, if current LUC trends would be continued until 2029. Coupled model computations further revealed that the uncertainty of estimated AGC stocks is larger than the expected LUC scenario effects as a function of employed AGC input dataset. The third case study examined the impact of land use change on soil erosion and sediment deposition patterns in a small watershed of mountainous Northern Vietnam using a newly developed dynamic and spatially-explicit erosion and sediment deposition model (ERODEP), which was further coupled with the LUCIA (Land Use Change Impact Assessment) model building on its hydrological and vegetation growth routines. Employing available field datasets for a period of four years, ERODEP-LUCIA simulated reasonably well soil erosion and sediment deposition patterns following the annual variations in land use and rainfall regimes. Output validation (i.e. Modelling Efficiency=EF) revealed satisfying to good simulation results, i.e. plot-scale soil loss under upland swiddening (EF: 0.60-0.86) and sediment delivery rates in monitored streamflow (EF: 0.44-0.93). Cumulative sediment deposition patterns in lowland paddy fields were simulated fairly well (EF: 0.66), but showed limitations in adequately predicting silt fractions along a spatial gradient in a lowland monitoring site. In conclusion, data-limited conditions are a common feature of many tropical environments such as Northern Thailand and Northern/North-western Vietnam. Environmental modellers, decision makers and stakeholders have to be aware of the trade-offs between model complexity, input demands, and output reliability. It is not necessarily the challenge of data-limitations, but rather the decision from the very beginning if the aim is to develop a new model tool or to use existing model structures to support environmental decision making. Future modelling-based investigations in data-limited areas should combine scientifically-based approaches with participatory procedures, because scientific assessment can support environmental policy making, but stakeholders’ decision will finally determine the provisioning of ecosystem functions in the long run. A generic assessment framework is proposed as synthesis of this study to employ dynamic and spatially-explicit models to examine the impact of LUC on ecosystem functions. The application of such a generic framework is especially useful in data-limited environments such as Mountainous Mainland Southeast Asia, as it not only provides guidance during the modelling process, but also supports the prioritisation of input data demands and reduces fieldwork needs to a minimum.