Contrasting dynamic fluvial-aeolian interaction landscapes in China
1, Ping Yan2, Xiaomei Li3, Wei Wu2
1Xiamen University, Xiamen, China, 2Beijing Normal University, Beijing, China, 3Qufu Normal University, Rizhao, China
Although the interaction between fluvial and aeolian system have been noticed in many studies, very few of them have focused on the dynamic interaction process and the implication on geomorphology. Liu and Coulthard (2015) have classified six fluvial-aeolian interaction types after a global inventory. However, these are based on static satellite images which could not (obviously) allow the generation of information relating the specific physical processes occurring within each of the systems being mapped.
As such, in the current study, preliminarily investigations into the geomorphologic characteristics as well as dynamics of four distinctive fluvial-aeolian interaction landscapes in China in undertaken. The study sites are located separately in the downstream region of the Tuolahai River (36°37'21.66"N 94°32'37.43"E), the downstream region of the Heihe River (or Ruoshui/Ejin River) (39°55'40.54"N 99°22'32.72"E), the downstream region of Lang Creek (Langqu) (35°34'46.91"N 101°01'01.23"E) and the upstream region of the Yarlung Tsangpo River (Maquan River or Horse Spring) (29°54'29.18"N 83°34'01.23" E). According to the fluvial-aeolian interaction type classification categorized in Liu and Coulthard (2015)'s research, these four sites represent four distinct landscapes dominated by corresponding interaction types: namely Fluvial dominant (F), Mostly Fluvial (MF) dominant, Balanced (B) and Mostly Aeolian (MA) dominant interaction, respectively. At each location, environment data were collected including the local wind regime, hydrological dynamics, landform information (cross sections, DEM and satellite images) as well as sediment characteristics.
By contrasting the fluvial/aeolian regime at each location, and mapping the resulted landscape characteristics, this study provides in situ field monitoring data to test the theory of fluvial-aeolian interaction classification in Liu and Coulthard's (2015) work. The results have the potential to inform our understanding of the ways in which humans in dynamic fluvial-aeolian environments are at risk through both internal systems and natural landscape evolution processes. Given the changing patterns of flooding occurring globally it is apparent that a more nuanced understanding of these environments is fundamental to future risk management strategies in many areas.