Optimizing Digital Elevation Model Resolution Inputs and Number of Stream Gauges in Geographic Information System Predictions of Flood Inundation: A Case Study along the Illinois River, USA ANAS RABIE 1,2 ERIC PETERSON 3 JOHN KOSTELNICK 1 REX ROWLEY 1 Illinois State University, Department of Geography-Geology, Campus Box 4400, Normal, IL 61790-4400 Key Terms: Hydrology, Geographic Information System (GIS), Spatial Analysis, Flood Hazards, River Manage- ment ABSTRACT Spatial analysis using Geographic Information Sys- tems (GISs) is evaluated for its ability to predict the po- tential hazard of a flood event in the Illinois River region in the state of Illinois. The data employed in the analy- sis are available to the public from trusted organizations such as the Illinois State Geological Survey and the U.S. Geological Survey. Since available GIS data may be lim- ited for flood risk modeling in some parts of the world, the purposes of this study are to examine the use of spa- tial analysis in a GIS to determine flood inundation risk and to produce an accurate flood inundation vulnerabil- ity map employing the least amount of data. This study concentrates on areas that have stream gauge data with definable flood stage(s) and utilizes the inverse distance weighted interpolation method on different digital ele- vation models (DEMs) with different spatial resolutions (1 m, 10 m, and 30 m) to determine the extent of flood- ing over the study area. Resulting maps created for the Illinois River region yielded about 80 percent agreement with the effects of an actual flood event on the Illinois River near Peoria, IL, on April 23, 2013. A four-gauge distribution scenario using a 10-m DEM produced the most accurate results, but all scenarios generated rea- sonable flood simulation. Thus, we speculate that it is possible to create a flood prediction map with a reason- able amount of accuracy using only two initial input data layers: stream gauges and a DEM. 1 Emails: arabie@kau.edu.sa; jckoste@ilstu.edu; rjrowley@ilstu.edu 2 Present address: Indiana University, Department of Earth and Atmospheric Sciences, 1001 East 10th Street, Bloomington, IN 47405-1405. 3 Corresponding author email: ewpeter@ilstu.edu. INTRODUCTION Rainfall and runoff gauges are not readily available for every river system, which affects the availability and credibility of hydrological data. Vigorous urban- ization of areas coupled with temporal and spatial vari- ation in hydrological characteristics makes the quanti- tative assessment of runoff characteristics in most areas unattainable (El-Hames and Richards, 1998). Disas- ters due to natural hazards are subject to many types of uncertainty, which complicates how these disas- ters are predicted and represented on maps and geo- visualizations (Kostelnick et al., 2013). For example, natural variability of streamflow and uncertainty of even “best available” elevation data create ambiguity in defining the floodplain boundary for flood hazard maps. The term “flood risk” indicates the perceived or ac- tual exposure to loss from a river flooding event dur- ing a natural disaster. The level of risk depends on the natural disaster’s overall impact on human lives and/or the economy (Safaripour et al., 2012). In or- der to identify that risk, however, accurate maps show- ing potential inundation (hazard) are required. Sim- ple maps depicting floodwater distribution allowing real-time and rapid simulations, which can be consid- ered “an effective real-time flood modeling and pre- diction system” (Al-Sabhan et al., 2003), could give decision makers an understanding of the threatened areas. For thorough flood modeling to be successful, many models require detailed information, including dis- charge, precipitation, ambient soil water content, land use, evaporation intensity, watershed infiltration, and the geology and geomorphology of the area. Each of the factors affects the others significantly, and their complex relationship affects the stream runoff. To create an accurate hydrological model, a good grasp of the interaction between such factors is manda- Environmental & Engineering Geoscience, Vol. XXIII,No. 4, November 2017, pp. 345–357 345