Flood risk mitigation in developing countries: deriving accurate topographic data for remote areas under severe time and economic constraints

Abstract

Isla Hispaniola, the island shared by Haiti and the Dominican Republic, has repeatedly witnessed catastrophic disasters that caused dramatic economic losses and killed thousands of people over the last decades. One striking example is the disastrous flood event that hit the transnational basin of River Soliette on 24 May 2004. The event resulted from a severe tropical storm and killed over 1000 Haitian and 400 Dominican people. In the context of an International Cooperation Initiative, the University of Bologna led several activities in the fields of flood risk assessment, management and mitigation, and sustainable development planning for the Soliette river basin. This paper presents new techniques for a timely assessment of flood risk in data-scarce and remote areas in developing countries showing in particular: (1) Global Navigation Satellite System (GNSS)-based topographic survey of the Soliette riverbed, carried out under urgent temporal, logistical and technical constraints, and (2) some possible utilisations of the collected topographic data for the identification of structural and non-structural flood risk mitigation measures. The analysis enabled us to set and test a GNSS-based technique for fast, reliable and detailed topographic surveys in remote regions, which represents a valid option for similar areas with limited accessibility in emerging and developing countries.

Establishing flood damage functions for agricultural crops using estimated inundation depth and flood disaster statistics in data-scarce regions

“…National and local authorities in sufficiently gauged regions often prepare their own standard methodology for assessing flood risks including damage functions, as in the UK (Penning-Rowsell and Chatterton, 1977), Netherlands (Messner et al, 2007), EU (Meyer et al, 2009), and Japan (Kazama et al, 2009). However, the framework for flood risk assessment in developing countries with typically insufficient hydrometeorological measurements causing relatively low data availability is mostly under development, although many studies have been already conducted (Ganji et al, 2012;Chau et al, 2015;Domeneghetti et al, 2015).…”

The Use of GIS and Hydrodynamic Model for Performance Evaluation of Flood Control Structure

“…In relation to the phenomenon and possible flood impact, an early analysis is needed in the form of flood routing [11] to optimize flood disaster management activities at an advanced stage. Basically, disaster management includes three main issues: mitigation includes monitoring, prevention, and preparedness, evacuation includes rescue and emergency relief and rehabilitation services including reconstruction and restoration of the situation to normal on physical and nonphysical facilities [12][13]. This analysis is indispensable to provide preliminary information related to flood mitigation and control in the flood disaster management framework.…”

Assessment of stream flood susceptibility: a cross‐analysis between model results and flood losses

“…Kourgialas and Karatzas, 2011), although other statistical methods such as machine learning are also commonly used (Tehrany et al, 2014(Tehrany et al, , 2015. In certain geographical contexts where resources are scarce (inexistence of input data to run hydrologic and hydraulic flood models, insufficient time to conduct field studies of fluvial geomorphology, or other financial or technical constraints) the availability of tools that provide hazard assessments less dependent on such requirements is a valuable asset (AOS, 1991;Hagen et al, 2010;Nobre et al, 2011;Yan et al, 2014aYan et al, , 2014b. A comprehensive application of this approach along with data provided by geomorphological analysis, flow levels, topographic bases, and historical hydrological records was developed for the Arno river basin (Morelli et al, 2014).…”

“…Further to the consideration of such predisposing factors, historical flood data is a useful resource in understanding the spatio-temporal patterns of natural disasters (Yi et al, 2012), and its application in the improvement and validation of flood hazard assessments is a common approach (Barnolas and Llasat, 2007;Prinos, 2008;de Moel et al, 2009). Historical data are also used to calibrate models for the assessment of flood hazard at a nation-wide scale (Hagen et al, 2010). The use of this type of data is not always possibleparticularly in data-poor contextsbut whenever available it provides a more accurate assessment of flood frequency and extent (Benito and Hudson, 2010).…”