## 4 Results
### LULC Changes at the Catchment Scale  
The analysis at the catchment scale provides more thematic details since more land use classes were defined. Specifically, forests are subdivided in subclasses comprising natural forest types such as montane forest, closed woodland, open woodland and anthropogenic forest types such as teak plantations. LULC conversion north of the Kilombero river is largely determined by topography. The steep slopes of the Udzungwa mountain range are inappropriate for crop cultivation, though a few banana plantations can be found. Therefore, conversion mainly takes place for crop cultivation in the floodplain area reaching further towards the Kilombero river, and partly along the forest fringes. Natural grasslands north of the river almost completely disappeared in 2014 (Figure 4). South of the Kilombero river, topography has less impact on land use decisions and conversion reaches both further into the floodplain and also further away from the river towards the woodlands. Primary forests are increasingly converted in smaller patches to teak plantations. Teak plantations can also be found at the slopes of the Udzungwa mountains north of the Kilombero river but at a much smaller extent. Area proportions of each LULC class from the 1970s to 2014 are depicted in Table 6 and change detection statistics between 1994-2004 and 2004-2014, respectively, are shown in Table 7. The highest uncertainty is expected in the category \"changes within natural classes\" since these represent subtle transitions between classes that are spectrally (and often ecologically) similar. Changes listed in this category can be either attributed to natural processes or to classification errors. Classification errors are less likely in the conversion classes since those conversions are spectrally more intense than changes between similar classes and thus better detectable by means of remote sensing. Besides, the temporal dynamics, i.e., the combination of phenology and management, of natural classes and crops differ substantially since natural surfaces are usually not managed or at least they are managed in a different way. As the approach used in this study accounts for temporal dynamics, we assume the detection of conversions is realistic. However, classification errors are likely in parts of some protected regions classified as cropland, e.g., in the classification of 2014 of the Selous Game Reserve. Figure 4: LULC classifications for four time steps: **(a)** 1970s, **(b)** 1994, (c) 2004 and (d) 2014. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**LULC Class** & **1970s (km2)** & **1994 (km2)** & **2004 (km2)** & **2014 (km2)** \\ \hline Cropland & 1414.38 & 473.33 & 1293.50 & 5603.18 \\ Grassland & 9162.49 & 9489.96 & 13,139.04 & 6827.92 \\ Open Woodland & 16,771.86 & 17,660.93 & 14,222.44 & 17,394.11 \\ Closed Woodland & 8377.62 & 8662.76 & 7486.78 & 4609.35 \\ Montane Forest & 3138.89 & 2542.89 & 1901.42 & 4681.38 \\ Teak & n.a. & 35.72 & 70.30 & 154.32 \\ Swamp & 164.01 & 114.68 & 206.62 & 333.00 \\ Bare & 445.73 & 1094.82 & 1695.90 & 485.77 \\ Built-Up & n.a. & 9.23 & 40.62 & 78.43 \\ Water & 890.26 & 155.79 & 183.49 & 72.64 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Area proportions of each LULC class (catchment scale). Figure 5: Flow duration curves of the four land use setups from the 1970s up to 2014 for the whole catchment. Climate data (1958–1970) in all four scenarios is not modified to attribute all changes in exceedance probabilities to alterations in land use inputs.