Badland landscape response to individual geomorphic events

Abstract

Landscapes form by the erosion and deposition of sediment, driven by tectonic and climatic forcing. The principal geomorphic processes of badland - landsliding, debris flow and runoff erosion - are similar to those in full scale mountain topography, but operate faster. Here, we show that in the badlands of SW Taiwan, individual rainfall events cause quantifiable landscape change, distinct for the type of rainfall. Typhoon rain reduced hillslope gradients, while lower-intensity precipitation either steepened or flattened the landscape, depending on its initial topography. The steep topography observed in our first survey is inconsistent with the effects of any of the rainfall events. We suggest that it is due to the 2016 Mw 6.4 Meinong earthquake. The observed pattern in the badlands was mirrored in the response of the Taiwan mountain topography to typhoon Morakot in 2009, confirming that badlands offer special opportunities to quantify natural landscape dynamics on observational time scales.

Fig. 1. Location and geological background in front of Taiwan orogenic belt.

a Color-shaded relief map driven from 20 m spatial resolution digital elevation model data (downloaded from https://data.gov.tw/dataset/35430) showing the distribution of major active faults (downloaded from https://www.moeacgs.gov.tw) and intensity of 2016 Meinong earthquakes (red number). Intensity and focal mechanism solution was acquired from the Central Weather Bureau (https://www.cwb.gov.tw/eng/) with a focal mechanism of 295°, 30°, and 37° in a strike, dip, and rake. The black dashed lines denote vertical PGA contours (https://scweb.cwb.gov.tw/special/20160206pga.asp). GTK (yellow square) is a meteorological station providing hourly precipitation data. b Shaded relief map of the drone survey area with 30 cm spatial resolution digital surface model data is conducted by this study. The boundaries of target (red block) mapping by this study. c Drone image of a typical badland catchment (red dashed block) is conducted by this study. d Daily and cumulative precipitation from hourly measurements, red triangles mean UAV survey data.

Fig. 2. Distribution of mean spatiotemporal erosion for the survey periods.

a Oct. 22, 2016–Jun. 30, 2017 (monsoon). b Jul. 01, 2017–Aug. 04, 2017 (typhoons). c Aug. 05, 2017–Dec. 02, 2017 (winter precipitation). d Dec. 03, 2017–May 25, 2018 (winter precipitation). The color indicates the mean of height change, warm and cold colors represent positive and negative values, respectively (see Methods).

Fig. 3. Gradient change as function of hillslope gradient (a–d) and drainage area (e–h) for the four survey periods.

Gray dots and error bars denote median and standard deviation of gradient change on each bin, respectively. Horizontal red dashed lines denote no gradient change and vertical red dashed lines denote the inflection of gradient change from steepening to flattening. a, e Oct. 22, 2016–Jun. 30, 2017 (monsoon). b, f Jul. 01, 2017–Aug. 04, 2017 (typhoons). c, g Aug. 05, 2017–Dec. 02, 2017 (winter precipitation). d, h Dec. 03, 2017–May 25, 2018 (winter precipitation).

Fig. 4. Distribution of hillslope gradients.

a Compiled observed (yellow) and simulated (cyan) distribution of hillslope gradients. The upper limit of the box means 75% of percentile, the lower limit of the box means 25% of percentile. Significant differences (p < 0.01) between the initially observed data and simulations using the Kolmogorov–Smirnov test are indicated by *. b Gray bars denote the fraction of steep gradients (> 55^o) at small drainage areas (<0.5 m²). The blue bar denotes rainfall intensity.