Statistical analysis and modelling of surface runoff from arable fields in central Europe

Abstract

Abstract. Surface runoff generation on arable fields is an important driver of flooding, on-site and off-site damages by erosion, and of nutrient and agrochemical transport. In general, three different processes generate surface runoff (Hortonian runoff, saturation excess runoff, and return of subsurface flow). Despite the developments in our understanding of these processes it remains difficult to predict which processes govern runoff generation during the course of an event or throughout the year, when soil and vegetation on arable land are passing many states. We analysed the results from 317 rainfall simulations on 209 soils from different landscapes with a resolution of 14 286 runoff measurements to determine temporal and spatial differences in variables governing surface runoff, and to derive and test a statistical model of surface runoff generation independent from an a priori selection of modelled process types. Measured runoff was related to 20 time-invariant soil properties, three variable soil properties, four rain properties, three land use properties and many derived variables describing interactions and curvilinear behaviour. In an iterative multiple regression procedure, six of these properties/variables best described initial abstraction and the hydrograph. To estimate initial abstraction, the percentages of stone cover above 10 % and of sand content in the bulk soil were needed, while the hydrograph could be predicted best from rain depth exceeding initial abstraction, rainfall intensity, soil organic carbon content, and time since last tillage. Combining the multiple regressions to estimate initial abstraction and surface runoff allowed modelling of event-specific hydrographs without an a priori assumption of the underlying process. The statistical model described the measured data well and performed equally well during validation. In both cases, the model explained 71 and 58 % of variability in accumulated runoff volume and instantaneous runoff rate (RSME: 5.2 mm and 0.23 mm min −1 , respectively), while RMSE of runoff volume predicted by the curve number model was 50 % higher (7.7 mm). Stone cover, if it exceeded 10 %, was most important for the initial abstraction, while time since tillage was most important for the hydrograph. Time since tillage is not taken into account either in typical lumped hydrological models (e.g. SCS curve number approach) or in more mechanistic models using Horton, Green and Ampt, or Philip type approaches to address infiltration although tillage affects many physical and biological soil properties that subsequently and gradually change again. This finding should foster a discussion regarding our ability to predict surface runoff from arable land, which seemed to be dominated by agricultural operations that introduce man-made seasonality in soil hydraulic properties.

Surface water floods in Switzerland: what insurance claim records tell us about the caused damages in space and time

“…As there are no such data concerning SWFs (Steinbrich et al, 2016), we must exploit other data sources in order to quantify the relevance of this flood type in space and time. Possible data sources include, but are not limited to, insurance claim records (e.g., Spekkers et al, 2013;Zhou et al, 2013;Moncoulon et al, 2014;Bernet et al, 2016;Grahn and Nyberg, 2017), disaster databases (e.g., Gall et al, 2009;Kron et al, 2012), press reports (e.g., Hilker et al, 2009) and interviews with or reports from affected people (e.g., Thieken et al, 2007;Evrard et al, 2007;Gaitan et al, 2016). All data sources are probably subjected to a varying degree of a socalled "threshold bias", which refers to the bias introduced due to varying damage inclusion criteria (Gall et al, 2009).…”

“…SWFs are characterized by overland flow and ponding, which can be defined as follows. As precipitation reaches the land surface, different runoff generation mechanisms determine whether water starts to pond and whether overland flow is generated (e.g., Fiener et al, 2013). The water may then take several routes towards the stream channels (Ward and Robinson, 2000), as depicted in Fig.…”

“…The Swiss canton of Schaffhausen was affected severely in 2013 (e.g., Scherrer et al, 2013). On the same day in 2014, the Dutch capital Amsterdam (e.g., Gaitan et al, 2016;Spekkers et al, 2017) and Münster, Germany, experienced substantial flooding (Spekkers et al, 2017). These events in Europe share a common thread, which stems from their origin as inland floods, triggered by heavy precipitation, but are mostly unrelated to watercourses.…”

Surface water floods in Switzerland: what insurance claim records tell us about the damage in space and time

“…As precipitation reaches the land surface, different runoff generation mechanisms determine whether water starts to pond and whether overland flow is generated (e.g., Fiener et al, 2013). The water may then take several routes towards the stream channels (Ward and Robinson, 2000), as depicted in Fig.…”

Perennial to Ephemeral Transformation of a Lesser Himalayan Watershed

“…They can be broadly classified into Hortonian (infiltration excess) mechanism, subsurface return flow or Hewlitt (saturation excess) mechanisms 47,48 . These could operate alone or in combination.…”