## 4 Results
### Result of Land-Use/Land-Cover Changes  
The Markov matrix (Table 2) was used in order to identify the direction and area of each land-use/land-cover transition. According to the matrix, the most dynamic classes were: agriculture areas, transitional woodlands, forests, and pastures. Agriculture areas faced an overall extension, especially by means of pasture conversion, but certain losses also occured as a consequence of the abandonment of several agricultural areas. The general balance revealed an increase of 1164.4 ha of agriculture zones during the studied period. The evolution of the transitional woodlands followed the inverse track of the forested areas, where forest areas decreased almost 5574.9 ha, which was 14.8% of the total forest area in 1989 (37,660 ha). According to the Markov matrix, the surface of built-up areas decreased approximately 3600 ha. This fact was due to the depopulation process that occurred after the political changes in 1989. Numerous types of transitions occurred, including conversions to agriculture zones, transitional woodlands, built-up areas, and pastures. The most important transition was from forests to pastures (4088.73 ha), mostly due to deforestation. \begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Year.**} & **Overall** & **Kappa** & \multirow{2}{*}{**Class**} & \multicolumn{6}{c}{**Ground Truth Samples (Pixels)**} & \multirow{2}{*}{**T.C.**} & **User** \\ \cline{3-3} \cline{5-12}  & & & **B.A.** & & **A.Z.** & & **F.T.** & **P.** & **F.** & **T.W.** & **W.B.** & **Pixels** & **Acc. (\%)** \\ \hline \multirow{14}{*}{1989} & \multirow{14}{*}{93.7} & \multirow{14}{*}{0.92} & B.A. & 347 & 0 & 2 & 0 & 2 & 0 & 7 & 358 & 96.9 \\  & & & A.Z. & 3 & 179 & 1 & 3 & 3 & 4 & 3 & 196 & 91.3 \\  & & & F.T. & 0 & 0 & 125 & 0 & 0 & 0 & 4 & 129 & 96.9 \\  & & & P. & 1 & 4 & 1 & 271 & 18 & 7 & 6 & 308 & 88.0 \\  & & & F. & 0 & 3 & 6 & 5 & 783 & 10 & 1 & 808 & 96.9 \\  & & & T.W. & 0 & 0 & 0 & 0 & 29 & 252 & 0 & 281 & 89.7 \\  & & & W.B. & 7 & 0 & 3 & 0 & 2 & 4 & 114 & 130 & 87.7 \\  & & & T.G.T. & & & & & & & & & \\  & & & Pixels & 358 & 186 & 138 & 279 & 837 & 277 & 135 & 2210 & \\  & & & Prod. & 96.9 & 96.2 & 90.6 & 97.1 & 93.5 & 91.0 & 84.4 & & \\  & & & Acc. (\%) & & & & & & & & & \\ \hline \multirow{14}{*}{2019} & \multirow{14}{*}{95.23} & B.A. & 419 & 0 & 0 & 0 & 1 & 0 & 6 & 426 & 98.4 \\  & & & A.Z. & 2 & 245 & 7 & 0 & 0 & 0 & 0 & 254 & 96.5 \\  & & & F.T. & 0 & 2 & 56 & 0 & 0 & 0 & 0 & 58 & 96.6 \\  & & & P. & 10 & 0 & 0 & 173 & 9 & 0 & 6 & 198 & 87.4 \\  & & & F. & 0 & 5 & 1 & 7 & 706 & 25 & 8 & 752 & 93.9 \\  & & & T.W. & 2 & 0 & 0 & 7 & 0 & 229 & 0 & 238 & 96.2 \\  & & & W.B. & 2 & 0 & 0 & 0 & 0 & 0 & 172 & 174 & 98.9 \\  & & & T.G.T. & & & & & & & & & \\  & & & Pixels & 435 & 252 & 64 & 187 & 716 & 254 & 192 & 2100 & \\  & & & Prod. & 96.3 & 97.2 & 87.5 & 92.5 & 98.6 & 90.2 & 90.2 & & \\  & & & Acc. (\%) & & & & & & & & & \\ \hline \hline \end{tabular} B.A.—built-up areas; A.Z.—agriculture zones; F.T.—fruit trees; P.—pastures; F.—forests; T.W.—transitional wood-land; W.B.—water bodies; T.G.T. Pixels—total ground truth pixels; T.C. Pixels—total classified pixels; Prod. Acc.—producer accuracy.  
\end{table} 
Table 1: Confusion matrix for classification accuracy assessment. These transitions highlight major and complex land-use/land-cover changes that affected the Zabala catchment between 1989 and 2019 involving all land-use/land-cover classes, a situation that strengthens our hypothesis that significant changes in runoff and flash flood potential occurred too. In order to quantize the land-use/land-cover changes at the appropriate analysis scale, TRDSDLUI was calculated at the grid-cell level (1 km\({}^{2}\)) (Figure 10a). The spatial distribution of this indicator highlights the differences concerning the intensity of land-use/land-cover changes within the study area.