# Post-Flood Risk Management and Resilience Building Practices: A Case Study
## 6 Results and Discussions
### Survey Results
#### 6.2.5 Comparison of Resilience Indices  
Based on the collected data resilience, indices were calculated of the households across the four severely affected communities of LN, BAK, KHS, and SW (Figure 17). Four components of resilience i.e., social, physical, economic, and institutional resilience were calculated. Social resilience depicted the ability of the community to deal with the flood risk and was based on different social variables such as education, past flood experience, and the social network of the community. The economic resilience looked at the livelihood sources within the community. While institutional resilience considered the support provided by the government and NGOs, recovery, rehabilitation, and restoring livelihood. Physical or infrastructure resilience was based on variables such as the raised platform of houses and flood protection bund around the community. From the findings, it was revealed that the BAK, KHS, and SW were less vulnerable to floods, as higher infrastructure and social resilience were observed for these communities. Also, these communities were economically resilient as compared to LN. LN was found to be socially resilient, having a high index of 0.5. Figure 16: Practice of raised plinth level in flood-prone communities of LN, district Layyah. Figure 17: Comparison of resilience indices among the districts. 2.6 Satisfaction Level of Communities towards Government and Organization Role Comparison of Satisfaction Level against Emergency Relief in 2010 Flood between Government and NGOs  
The emergency services and response plans are the variables for the institutional Dimension of community resilience, as stated by [43; 45]. Table 2 below represents the findings of a comparison of satisfaction level between government and NGOs against emergency relief received by the affected community of 2010 flood in four localities of district Layyah using Yeh's Index of Satisfaction [47]. The results show that respondents had a very low satisfaction level in SW (\(-1.56\)) and KHS (\(-1.76\)) for the government. This indicates that these two areas did not get any emergency relief from the government. In SW and KHS, flood victims were overlooked due to the negligence of local government and local representatives of areas. As SW is in Tehsil Karor and KHS is adjacent to it, so both union councils could not get emergency relief as the focus of government and NGOs were Tehsil Layyah being the main city in tehsil Layyah. Although in LN and BAK, the values of the index were 1.54 and 1.62, which showed that the satisfaction level was very high due to political biases. In these two localities, the community that experienced the 2010 flood reported vast destruction. LN is the nearest union council from the city of Layyah. While in BAK, political persons had a strong connection with district disaster management authority (DDMA) Layyah. On the other side, the satisfaction level for NGOs in BAK, KHS, and SW was very low as the value of the index is below 0.2 in these three localities, which indicated that organizations did not play any part in relief works such as evacuation, rescue, and first aid. While in LN, the affected community responded positively against NGOs role in emergency relief activities during and after the 2010 flood event [48]. Comparison of Satisfaction Level against Response after 2010 Flood between Government and NGOs  
Table 3 below depicts the comparison of results for the satisfaction level of response plans between government and NGOs in four localities of district Layyah. The findings show that values of the index were negative in LN (\(-1.72\)), KHS (\(-0.28\)), and SW (\(-1.32\)), indicating a very low satisfaction level of respondents for the government. Lack of political support and coordination between local government, NGOs, and international donors were the major reasons for low satisfaction within the community. The satisfaction level for the government was very high, with the value of the index being positive (1.78) in BAK.