Description and evaluation of a surface runoff susceptibility mapping method

Abstract

Please cite this article as: Lagadec, L-R., Patrice, P., Braud, I., Chazelle, B., Moulin, L., Dehotin, J., Hauchard, E., Breil, P., Description and evaluation of a surface runoff susceptibility mapping method, Journal of Hydrology (2016), doi: http://dx. AbstractSurface runoff is the hydrological process at the origin of phenomena such as soil erosion, floods out of rivers, mudflows, debris flows and can generate major damage. This paper presents a method to create maps of surface runoff susceptibility. The method, called IRIP (Indicator of Intense Pluvial Runoff, French acronym), uses a combination of landscape factors to create three maps representing the susceptibility (1) to generate, (2) to transfer, and (3) to accumulate surface runoff. The method input data are the topography, the land use and the soil type. The method aims to be simple to implement and robust for any type of study area, with no requirement for calibration or specific input format. In a second part, the paper focuses on the evaluation of the surface runoff susceptibility maps. The method is applied in the Lézarde catchment (210 km², northern France) and the susceptibility maps are evaluated by comparison with two risk regulatory zonings of surface runoff and soil erosion, and two databases of surface runoff impacts on roads and railways.Comparison tests are performed using a standard verification method for dichotomous forecasting along with five verification indicators: accuracy, bias, success ratio, probability of detection, and false alarm ratio. The evaluation shows that the susceptibility map of surface runoff accumulation is able to identify the concentrated surface runoff flows and that the susceptibility map of transfer is able to identify areas that are susceptible to soil erosion. Concerning the ability of the IRIP method to detect sections of the transportation network susceptible to be impacted by surface runoff, the evaluation tests show promising probabilities of detection (73 to 90%) but also high false alarm ratios (77 to 92%). However, a qualitative analysis of the local configuration of the infrastructure shows that taking into account the transportation network vulnerability can explain numerous false alarms. This paper shows that the IRIP method can be a valuable tool to facilitate field analysis and perform surface runoff zonings and opens interesting prospects for the use of the IRIP method in a context of risk management.3

Mapping geospatial processes affecting the environmental fate of agricultural pesticides in Africa

“…This product collated land use data between 2001 and 2012 and categorized the data into 17 different land use classes. Based on background information [65,67], we categorized the MODIS land cover type data product into five classes and gave a weight to each class to indicate how infiltrative or impervious surfaces under a certain land use class are (Table 3). Table 3.…”

“…The weights that were allocated to the different land use classes in order to estimate the process affecting surface runoff. Data on surface runoff generation, slope, break of slope, catchment capacity and artificial linear axes were required to model surface runoff transfer [65]. Data on slope were obtained from the SRTM-DEM.…”

“…Geospatial variation of the processes associated with surface runoff generation (A), transportation (B) and accumulation (C) assessed by the Intense Pluvial Runoff (IRIP) method(65).…”

Use of post-event surveys of impacts on railways for the evaluation of the IRIP method for surface runoff mapping

“…Several methods allow the mapping of surface runoff, such as STREAM [6], SCALES [7], RuiCells [8], EXZECO [9] or Erruisoll [10]. In this paper, we focus on the IRIP method [11]- [14] -Indicator of Intense Pluvial Runoff (French Acronym) -. It is a geomatics method which produces maps of the spatial susceptibility of a territory to generate, to transfer and to accumulate surface runoff.…”

“…Large scale comparison has been made with the Gaspar French database of natural disaster claims [13] showing promising correlation. Statistical comparisons has been made with surface runoff impact locations on the transportation network, such as roads and railways [12], [14], [28] showing good correlation between the high susceptibility levels of the transfer and accumulation maps and the occurrence of surface runoff impacts. These works are part of the IRIP method evaluation process and show encouraging results but further works must be performed to evaluate the ability of the method for specific tasks.…”