# Characterization of the 2014 Indus River Flood Using Hydraulic Simulations and Satellite Images
## 3 Results  
### Changes in LULC after the Flood and Assessment of Accuracy  
Figure 3 illustrates the LULC types before the flood, during the flood, and after it. 'Deposited material' was not a LULC category for the image taken during the flood but only for the image after it. The change detection technique reveals significant changes for all LULC types. Before the flood, the watershed, covering a surface area of approximately 581.8 km2, consisted of 63.8% crop/agricultural land, 11.3% built-up area, 21.1% barren land, 0.9% sand, and 1.1% deposited material (Figure 4). The 'Water/Wetlands' category covered only 1.1% of the watershed area, but, as expected, this increased dramatically to 38% during the flood, therefore affecting other LULC types. Specifically, the 'built-up' LULC type decreased from 11.34 to 9.35%, the 'crop/agricultural land' category, which covers the largest surface area of the catchment, decreased from 63.8 to 55.9%, and the 'barren land' LULC type decreased from 21.1 to 17.2% because of the flood; hence explaining the extensive damage that the 2014 flood caused to crops and the built environment. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Scheme** & **Land Use** & **Manning’s “nr”** \\ \hline
1 & Water & 0.015 \\
2 & Soil & 0.32 \\
3 & Vegetation & 0.045 \\
4 & Healthy Vegetation & 0.19 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: The estimated Manning’s \(n\) value for different land use categories. Different measures were used to assess the accuracy of the supervised and MLC classification to categorize the watershed into the six LULC types. The highest overall accuracy (OA) value, i.e., 96%, was obtained from the pre-flood image (July 22), while the post-flood image (September 24) had the lowest OA of 90%. The highest UA of the 'built-up' area class was attained for the pre-flood image, with a value of 98.98%, while the lowest was 80.11% for 'water/wetland' class for the image taken during the flood (August 8). The OA and K for Muzzaffargarh District as a whole are 0.96 and 0.94 (corrected samples, 576), 0.93 and 0.91 (corrected samples, 545), 0.90 and 0.85 (corrected samples, 560) for the pre-flood, during the flood, and post-flood image, respectively (Table 3). Overall, the results reveal a high level of accuracy of the LULC categorization technique. For the pre-flood image, the highest UA, i.e., 98.98%, is attained for the 'built-up area' class, while the highest PA, also at 98.98%, is seen for the 'crop/agricultural land' LULC type. After the flood, the water category returned nearly to its original pre-flood level, decreasing from 38% to 1.87%. However, the percentage of the watershed covered by the 'built-up' LULC category did not return to its original value, but to only 9.35%. This is likely because after the flood water receded, materials were deposited, hence this category showed a significant increase from 1.10% to 15.04% in the post-flood image (Figure 4). An increase from 45.22% to 55.92% was also seen in the 'crop/agricultural land' category, while the 'barren land' LULC type, for its part, remained unchanged. The category defined as'sand' increased marginally from 0.14 to 0.60%, as seen in Figure 3 (right image).