TanDEM-X12m Sayısal Yükselti Verisine Dayalı Toprak Erozyonu Tespiti (Rusle)

Soil is one of the most important natural resources in the world. Determination of soil degradation has been widely attempted all over the world in the last 50 years. This study provides a perspective of comparing the digital elevation model (DEM) in terms of the Revised Universal Soil Loss Equation (RUSLE) model, which calculates soil loss in Mountain Karadağ - Akçay Basin. RUSLE comprises the topographic (LS), climatic (R), vegetation (C), soil (K), and support practice (P) parameters. To evaluate soil loss in the Akçay Basin, TanDEM-X12m. DEM was used and compared with ALOS12.5m and SRTM30m. DEM. Distribution of soil loss has a positive correlation with slope degree (R2 = 0.62) and rainfall and runoff factor (R). As the elevation increases in the short range (15 km) from south to north in Akçay Basin, the rainfall and runoff increase together with elevation. The tributaries of the trunk river (Akçay) were characterized by a narrow and incised V-shaped valley, and this gave rise to increase in the LS factor in the short range. This phenomenon shows that the LS factor is one of the most important factors with regard to triggering factors. According to the TanDEM-X12m-based DEM, the mean annual soil loss is 28 ton ha−1 ya−1 from the basin. Keywords: Soil Loss, Rusle, TanDEM-X12m DE

Regional distribution and characteristics of major badland landscapes in Turkey

Badlands are extremely rugged, outstanding landscapes that can be seen in all ice-free climate regions over erosion-susceptible unconsolidated materials, and they have drawn attention with their spectacular and iconic forms. Unlike nearly all badlands researches conducted at the experimental site and watershed scale, so far, the broader-scale evaluation has been neglected in the analysis of badland distribution, characteristics, and dynamics. Our study provides an integrative new insight into badland landscapes by investigating the distribution, characteristics and controlling factors of Turkish badlands on a broad, regional scale. We inventoried Turkish badlands using aerial imagery and studied their distribution using K-means clustering, an unsupervised machine learning algorithm, based on a set of major conditional geo-environmental factors that control the regional distribution and characteristics of badlands, including tectonics, lithology, topography, climate, and vegetation. Here, we identified, a total of 4494 km2 of badland areas which are non-uniformly distributed across Turkey, substantially clustered in the Central Anatolian Plateau (CAP). According to our regional analyses, we have determined a total of five badland regions comprising three major types classified as Semi-arid, Mediterranean, and Montane (humid), together with two transitional types in-between the Semi-arid and Montane badland regions. Our results indicate that temperature seasonality (0.83), mean annual precipitation (0.83), and precipitation seasonality (0.76) are predominantly assigned to the badlands clusters. The clastic rocks are revealed as the most crucial and inevitable factor for the development of Turkish badlands, which are represented in a wide geologic time-scale (Cretaceous to Quaternary) and diverse lithological units (i.e., lacustrine, volcaniclastics, and terrestrial). Neogene and Paleogene terrestrial clastics (77 %) constitute the majority of the lithologic settings of these badland landscapes. The active and complex tectonic history of Turkey has portrayed the fundamental frame of the identified badland regions, by providing a susceptible environment (i.e., development of sedimentary basins) and promoting badland development through successive base-level changes. Furthermore, tectonically-modulated (i.e., formation of orogenic belts, and uplifting of CAP) climate dynamics outline the distribution pattern and differentiation of the regional characteristics of badlands in Turkey. Overall, our regional-scale approach to badland mapping and regional synthesis may decipher not only the tectonic and climatic conditions of the identified badlands regions, but it may also contribute to the implementation of future effective strategies for the detection and mapping of erosion susceptible and high sediment flux areas in very broad spatial contexts of similar unexplored territories.The authors are thankful to editor Arnaud Temme and three anonymous reviewers for their useful and constructive comments. This study is supported by the 2232 International Fellowship for Outstanding Researchers Program of the Scientific and Technological Research Council of Turkey (TUBITAK) through grant 118C329. The financial support received from TUBITAK does not indicate that the content of the publication is approved in a scientific sense by TUBITAK. MMH is a Serra Hunter fellow funded by the Generalitat the Catalunya (UB-LE-9055). The authors thank to Orkan Ozcan, Ali Mohammadi, Serdar Yeşilyurt, Cihan Yıldız, Onur Altınay, and Tunahan Aykut for their support during the fieldworks.Peer reviewe