**4.4 Flood risk analysis**

Conducting analyses of flood risks and contributors to increased flood risk are necessary to have substance in communications. That said, management of risk is unwanted, but necessary. No single organization, within the U.S. or international,

### **Figure 3.**

*Projected return period (in years) of 20-year return values of annual maximum 24-hour precipitation rates (after IPCC, SREX [12]).*

can control all aspects of population and property at risk from flooding or contributing to flooding. However, sharing risk is not desired by those who depend on or expect some other organization to provide their protection. The greater value of risk-based analyses lies in the better articulation of roles and responsibilities affiliated with flood risk reduction and response.

### **4.5 Measurement**

For developing flood control measures and flood management, spatial and temporal data from different disciplines are needed. More particularly, hydrometeorologic data, hydrometric data, watershed physiographic data, and land use and land cover data are needed to get started. Measurement technologies-remote sensing, satellite and drones- can be employed at a large scale. The remote sensing technology can provide information on rainfall fields, including storm movement, spatial variability, temporal variability, and rainfall field coverage. Also, measurements techniques are available that help describe the spatial variability of hydraulic roughness. The collected data should be subject to quality analysis/control, should be archived, and be retrievable. Then, the data needs processing and should be made accessible.

### **4.6 Integrated hydrologic modeling**

Hydrologic modeling should be integrated with remote sensing, geographical information system (GIS), data base management system, hydraulics, land use/land cover, hydrometeorology, geomorphology, uncertainty and risk analysis. In distributed hydrologic modeling, it is important to quantify the effect of the spatial variability of watershed characteristics on runoff dynamics and hydrograph, and formation of shocks. Impacting the runoff or flood hydrograph is also the spatial variability of infiltration, hydraulic conductivity, steady infiltration, and mean infiltration. The spatial and temporal variability is directly dependent on scaling. Spatial scaling entails spatial heterogeneity in watershed characteristics, spatial variability in hydrologic processes, as well as physical spatial size involving representative elementary area, hydrologic response units, and computational grid size. On the other hand, temporal scaling involves time interval of observations, computational grid size, and temporal variability of processes. These issues play a vital role in flood model response.

An important issue in integrated modeling is calibration which involves parameter estimation algorithm, an objective function, an optimization algorithm, a termination criterion, calibration data, handling data errors, determination of data needs-quantity and information-richness, and representation of uncertainty of the calibrated model. Artificial neural networks can also be employed for modeling or model calibration.

In modern era, new tools are emerging or the existing tools are being made more accurate and versatile. These tools may include mechanistic models, data mining models, uncertainty analysis, entropy theory, risk analysis, multivariate stochastic analysis (copula theory), intelligent systems (ANN, Fuzzy logic, etc.), optimization algorithms, decision support systems, and GIS software.

With increasing demand on hydrologic models, new challenges are emerging. For flood modeling, such challenges are the need for more data at finer spatial resolutions, regional scale models, quantification of model uncertainty, long-term forecasting (ahead of time), determination of probable maximum precipitation and probable maximum flood, integration with climate models as well as with ecosystems models, and coupling with decision making models (social, political, economic, environmental, etc.).

### **4.7 Watershed management**

Floods should be managed at the watershed scale and watershed management therefore becomes critically important. It involves land use management, drainage, soil conservation, forest management. There is growing need in the U.S. to provide increasing, and reliable, volumes of water for municipal, industrial, and agricultural needs. Reliable is a key criterion, especially during variable climatic conditions. Finding means to store flood waters in aquifers or move flood waters to areas experiencing water shortages are engineering and socio-political challenges where the U.S. will see increasing interest and pressure to address.

### **4.8 Education**

In many cases people are unaware of the flood risk they expose themselves and families to, while in other cases people are intentionally ignorant so others can assume responsibility for their flood risk. Education is an essential long-term measure, but for education to make a difference it needs to be part of the K-12 education system. Education limited to project specific Town Halls and briefings to elected leaders is not achieving any significant change in societal behaviors.

### **4.9 Skilled professionals**

While there is opportunity to improve hydrology and hydraulics and structural analysis tools and models, the tools available are mostly sufficient for the need.

### *Challenges in Flood Management DOI: http://dx.doi.org/10.5772/intechopen.99973*

What is lacking is experience and competence to use these tools appropriately on the most complicated projects. Identifying the right individuals and teams for unique tasks and convening multi-disciplinary teams with these special skills is a continuing issue and provides the rationale for the engineering, environmental, and social science professional fields to manage themselves and identify credentials recognizing those with advanced education and experience.
