# Characterization of the 2014 Indus River Flood Using Hydraulic Simulations and Satellite Images
## 4 Discussion  
Pakistan is a country highly vulnerable to floods [45; 46]. For instance, in the past decade, other disasters were overshadowed by floods due to the heavy death toll and the significant disruption to the economy that they caused [34; 47]. In 2014, heavy monsoon rains resulted in a high discharge of the Indus River, which exceeded the channel capacity, causing a major flood in Muzzaffargarh District of the Punjab province. This paper showed that a supervised classification of Landsat images was able to identify the LULC types of the study region with a high degree of accuracy. Even though Landsat images are available at a relatively high spatial resolution, they are typically available every 15 days over the study area [34], a time interval that is not frequent enough for flood monitoring and that is also often not suitable for damage assessment, especially given that cloud coverage sometimes restricts the use of optical images [48; 49]. This was different for path 151 of the Landsat, which provided cloud-free images over the study area at the time of the 2014 flood, allowing for the current study to be performed. Previous research has shown the potential of optical satellite imagery to monitor inundated farmland and built-up areas [2]. This study has further expanded this evidence to other LULC types. Moreover, the potential of using Landsat images for damage assessment, even many days following a flood, is demonstrated in this paper, a result in agreement with other studies [26; 37]. This paper also shows that sediment build-up can also be detected with good accuracy over crop/agricultural fields and built-up areas [48]. When assessing the reliability of the flood monitoring reports, the precision of the satellite data and the methods used to process and analyze them must also be considered. This analysis performed in this paper has provided an accuracy of more 85% for the LULC categorization. This analysis identified'sand' with an accurate accuracy, however, wet sand has often been mistaken with water and vegetation/agricultural land in some instances. This is also observed in some situations where blurred pixels, crop/agricultural land, and built-up areas are also misclassified in transition areas. For flood mapping and damage assessment, high-resolution SAR data are suggested [50]. This is because radar satellite imagery can penetrate clouds, thereby they can be used under any weather conditions [50], and they are considered more accurate to assess disruption to crop/agricultural land and built-up areas [6; 48]. However, freely available SAR images could not be obtained during the timing of the 2014 flood. Finally, in built-up areas where floodwaters flow over buildings, roads, and other elements, the modest 30 m spatial resolution of the Landsat images can lead to misclassification. Another objective of this study was to evaluate the suitability of the HEC-RAS model to simulate the water surface profiles and determine the spatial extent of floods of different return periods. It was found that the HEC-RAS model was able to replicate the magnitude of the 2014 flood. The floodplain map showed that the flood levels were about four times higher for a flood with a 50-year return period than those under typical flow conditions. During the field surveys, it was noticed that the marginal barriers are necessary to restore, because the villagers cut them down in many places and build passages for their tractors and cattle. The deterioration of the foundations of barriers has contributed to the extent of the 2014 flood. The interference by citizens is another related concern with the protection of the floodplain in the basin. In recent years, the population and anthropogenic activities have increased in the floodplains. The floodplain must be reinstated or maintained to its natural undeveloped state to ensure citizens and infrastructure safety. Protection from damage and restoring the floodplain will significantly mitigate the risk of flooding.