# Flash Floods Hazard to the Settlement Network versus Land Use Planning (Lublin Upland, East Poland)
## 1 Introduction  
Hydrological phenomena associated with rapid runoff after rainfall of more than average intensity are among the natural hazards that are still poorly recognized. This is primarily due to their local nature. The heavy rainfall that causes them can occur almost anywhere [1; 2]. This makes it difficult to forecast and therefore warn of the danger. At the same time, due to their negative social and economic effects, these incidents are receiving more and more attention. This is particularly true of flash floods [3; 4; 5; 6; 7]. These floods are characterized by a short duration and high flow rates [8; 9]. The spatial distribution of flash floods is determined primarily by climatic conditions and terrain. They occur primarily in mountainous and upland areas [4; 10; 11]. In the latter case, surface runoff forms quickly due to higher gradients and agricultural land use [12; 13; 14]. Rapid episodic runoff can form outside river valley areas [15; 14; 16]. A concentration of runoff in the bottom of dry valleys of various ranks may appear. Intense hydrologicaland geomorphological processes can then pose a threat to the network of settlements and infrastructure located in the bottoms of such landforms. In agricultural areas, rapid surface runoff after heavy downpours causes intense erosion, which can lead to the destruction of crops or the road network [14; 17]. Accumulated material covers fields, roads, and farms [15; 16]. In Poland, runoff in the bottoms of dry valleys does not pose a direct threat to human health and life but can cause significant property damage. Intense episodic runoff can occur at any location: the only precondition is the occurrence of rainfall of a certain intensity and amount. The identification of threatened areas is more complicated than in the case of floods occurring in river bottoms. This is because flash floods often occur in areas not covered by a network of standard meteorological and hydrological measurements. Therefore, our knowledge of the frequency, intensity, and spatial distribution of such phenomena is limited. Heavy rainfall in temperate climates usually covers a small area of tens of square kilometers [18; 19]. Such incidents are usually studied post factum on the basis of geomorphological effects [14; 20; 21; 22]. In the upland part of Poland, heavy rainfalls of 20-30 mm\(\cdot\)h\({}^{-1}\) occur every year [16; 18], with those exceeding 50 mm\(\cdot\)h\({}^{-1}\) once every 10 years [17]. On the other hand, the probability of rainfall of \(>\)100 mm is 1% in the upland areas of Poland [23]. Due to the inability to predict the locations of flash floods, the only way to delineate threatened areas is to analyze the susceptibility of catchments to intense surface runoff and flash flood phenomena. Susceptible catchments are identified on the basis of analysis of various criteria in a GIS environment [24; 25; 26; 27; 28; 29; 30]. The most common methods for assessing vulnerability to flash floods are the analytical hierarchy process (AHP), weight of evidence (WoE) and frequency ratio (FR), and artificial neural networks (ANN). When assessing catchment susceptibility, the most commonly used indicators include slope, elevation, curvature, stream density, lithology, distance from stream, land use, the TWI (topographic wetness index), and the SPI (stream power index) [31; 32; 33; 34; 35]. The resultant models make it possible to pinpoint areas prone to flash floods. However, it is necessary to have an extensive database of these phenomena to develop and validate the models. It should be also noted that analyses of this type have been performed primarily for urbanized areas [36; 37; 38]. The identification of susceptible catchments is very important from the point of view of land use planning [8; 39] because it allows planners to limit the negative effects of flash floods [40; 41; 42]. At the same time, the results of many climate change models indicate an increase in the frequency of extreme precipitation events [43].