A new global landslide dam database (RAGLAD) and analysis utilizing auxiliary global fluvial datasets

To address the current data and understanding knowledge gap in landslide dam inventories related to geomorphological parameters, a new global-scale landslide dam dataset named River Augmented Global Landslide Dams (RAGLAD) was created. RAGLAD is a collection of landslide dam records from multiple data sources published in various languages and many of these records we have been able to precisely geolocate. In total, 779 landslide dam records were compiled from 34 countries/regions. The spatial distribution, time trend, triggers, and geomorphological characteristic of the landslides and catchments where landslide dams formed are summarized. The relationships between geomorphological characteristics for landslides that form river dams are discussed and compared with those of landslides more generally. Additionally, a potential threshold for landslide dam formation is proposed, based on the relationship of landslide volume to river width. Our findings from our analysis of the value of the use of additional fluvial datasets to augment the database parameters indicate that they can be applied as a reliable supplemental data source, when the landslide dam records were accurately and precisely geolocated, although location precision in smaller river catchment areas can result in some uncertainty at this scale. This newly collected and supplemented dataset will allow the analysis and development of new relationships between landslides located near rivers and their actual propensity to block those particular rivers based on their geomorphology.

Reconstructing High-Precision Coral Reef Geomorphology from Active Remote Sensing Datasets: A Robust Spatial Variability Modified Ordinary Kriging Method

Active remote sensing technology represented by multi-beam and lidar provides an important approach for the effective acquisition of underwater coral reef geomorphological information. A spatially continuous surface model of coral reef geomorphology reconstructed from active remote sensing datasets can provide important geomorphological parameters for the research of coral reef geomorphological and ecological changes. However, the surface modeling methods commonly used in previous studies, such as ordinary kriging (OK) and natural neighborhood (NN), often represent a “smoothing effect”, which causes the strong spatial variability of coral reefs to be imprecisely reflected by the reconstructed surfaces, thus affecting the accurate calculation of subsequent geomorphological parameters. In this study, a spatial variability modified OK (OK-SVM) method is proposed to reduce the impact of the “smoothing effect” on the high-precision reconstruction of the complex geomorphology of coral reefs. The OK-SVM adopts a collaborative strategy of global parameter transformation, local residual correction, and extremum correction to modify the spatial variability of the reconstructed model, while maintaining high local accuracy. The experimental results show that the OK-SVM has strong robustness to spatial variability modification. This method was applied to the geomorphological reconstruction of the northern area of a coral atoll in the Nansha Islands, South China Sea, and the performance was compared with that of OK and NN. The results show that OK-SVM has higher numerical accuracy and attribute accuracy in detailed morphological fidelity, and is more adaptable in the geomorphological reconstruction of coral reefs with strong spatial variability. This method is relatively reliable for achieving high-precision reconstruction of complex geomorphology of coral reefs from active remote sensing datasets, and has potential to be extended to other geomorphological reconstruction applications.

Bending of the concentration discharge relationship can inform about in-stream nitrate removal

Nitrate (NO3-) excess in rivers harms aquatic ecosystems and can induce detrimental algae growths in coastal areas. Riverine NO3- uptake is a crucial element of the catchment-scale nitrogen balance and can be measured at small spatiotemporal scales, while at the scale of entire river networks, uptake measurements are rarely available. Concurrent, low-frequency NO3- concentration and streamflow (Q) observations at a basin outlet, however, are commonly monitored and can be analyzed in terms of concentration discharge (C–Q) relationships. Previous studies suggest that steeper positive log (C)–log (Q) slopes under low flow conditions (than under high flows) are linked to biological NO3- uptake, creating a bent rather than linear log (C)–log (Q) relationship. Here we explore if network-scale NO3- uptake creates bent log (C)–log (Q) relationships and when in turn uptake can be quantified from observed low-frequency C–Q data. To this end we apply a parsimonious mass-balance-based river network uptake model in 13 mesoscale German catchments (21–1450 km2) and explore the linkages between log (C)–log (Q) bending and different model parameter combinations. The modeling results show that uptake and transport in the river network can create bent log (C)–log (Q) relationships at the basin outlet from log–log linear C–Q relationships describing the NO3- land-to-stream transfer. We find that within the chosen parameter range the bending is mainly shaped by geomorphological parameters that control the channel reactive surface area rather than by the biological uptake velocity itself. Further we show that in this exploratory modeling environment, bending is positively correlated to percentage of NO3- load removed in the network (Lr.perc) but that network-wide flow velocities should be taken into account when interpreting log (C)–log (Q) bending. Classification trees, finally, can successfully predict classes of low (∼4 %), intermediate (∼32 %) and high (∼68 %) Lr.perc using information on water velocity and log (C)–log (Q) bending. These results can help to identify stream networks that efficiently attenuate NO3- loads based on low-frequency NO3- and Q observations and generally show the importance of the channel geomorphology on the emerging log (C)–log (Q) bending at network scales.

Quantitative Analysis of a River Basin - A GIS-based Approach

The river basin plays a fundamental role in planning the management of natural resources. The hydrological behavior of the basin depends on the geomorphological parameters of the hydrographic basin. In the present study, a morphometric analysis was performed to determine the linear, areal and relief parameters of the Panzara River, the main tributary of the Tapi River, using the Geographic Information System tool. The river basin is of seventh order, showing a dendritic pattern of drainage that indicates the homogeneity in the texture of the basin. The drainage density in the area is 2.56 and the mean bifurcation ratio 5.065 indicates the less impact of structural deformations on the basin. The stream frequency of the basin is 3.20 showing low relief and high permeability. The present study reveals that the applications of GIS techniques are reliable, take less time and are competent to manage large databases for management of river basins.

Inventário de movimentos de massa na bacia hidrográfica do rio Mascarada/RS

Mass movements inventories play a key role to the understanding of watershed dynamics. The alteration of this dynamics occurs in the moment of failure and after it due the erosion when precipitation hits the uncovered soil at the mass movement scars. Thus, this paper has characterized these mass movements, which are classified as landslides, occurred in Mascarada´s river basin through different geomorphological parameters, as slope and curvature, and comparing shape parameters against different methodologies to determine the evaluation area. The proposed shape parameters Percentage of affected area (PAA), Drainage density of scars (Ddc) and Density of scars (Dcic) were evaluated against total area of Mascarada´s river basin, against two sub-basins and against a proposed “Area of influence”. 407 scars were mapped with an area of 2,2 km², a mean slope of 36,1° and all scars are in convergent areas. The evaluation of shape forms showed that “area of influence” improved the understanding of this mass movements magnitude. Thus, the elaboration of mass movement inventories with reliable methodologies can provide important information for the natural disaster management.

How landscape and climate affect the spatial variability of the Italian rainfall extremes? Some initial clues based on I2-RED

<p>The intensity and the spatial distribution of precipitation depths are known to be highly dependent on relief and geomorphological parameters. Complex environments like mountainous regions are prone to intense and frequent precipitation events, especially if located near the coastline. Although the link between the mean annual rainfall and geomorphological parameters has received substantial attention, few literature studies investigate the relationship between the sub-daily maximum annual rainfall depth and geographical or morphological landscape features.<br>In this study, the mean of the rainfall extremes in Italy, recently revised in the so-called I<sup>2</sup>-RED dataset, are investigated in their spatial variability in comparison with some landscape and also some broad climatic characteristics. The database includes all sub-daily rainfall extremes recorded in Italy from 1916 until 2019 and this analysis considers their mean values (from 1 to 24 hours) in stations with at least 10 years of records, involving more than 3700 stations.<br>The geo-morpho-climatic factors considered range from latitude, longitude and minimum distance from the coastline on the geographic side, to elevation, slope, openness and obstruction morphological indices, and also include an often-neglected robust climatological information, as the local mean annual rainfall.<br>Obtained results highlight that the relationship between the annual maximum rainfall depths and the hydro-geomorphological parameters is not univocal over the entire Italian territory and over different time intervals. Considering the whole of Italy, the highest correlation is reached between the mean values of the 24-hours records and the mean annual precipitation (correlation coefficient greater than 0.75). This predominance remains also in sub-areas of the Italian territory (i.e., the Alpine region, the Apennines or the coastal areas) but correlation decreases as the time interval decreases, except for the Alpine region (0.73 for the 1-hour maximum). The other geomorphological parameters seem to act in conjunction, making it difficult to evaluate, with a simple linear regression analysis, their impact. As an example, the absolute value of the correlation coefficient between the elevation and the 1-hour extremes is greater than 0.35 for the Italian and the Alpine regions, while for the 24-hours interval it is greater than 0.35 over the coastal areas.<br>To further investigate the spatial variability of the relationship between rainfall and elevation, a spatial linear regression analysis has been undertaken. Local linear relationships have been fitted in circles centered on any of the 0.5-km size pixels in Italy, with 1 to 30 km radius and at least 5 stations included. Results indicate the need of more comprehensive terrain analysis to better understand the causes of local increasing or decreasing relations, poorly described in the available literature.</p>

Assessing the ecological value of dynamic mountain geomorphosites

<p>Over the last 15 years, the methodological proposals for assessing the heritage value of geomorphosites have been numerous and varied (Brilha, 2018). While some of the main criteria for assessing the geoscientific value, i.e. the interest for Earth sciences (rarity, representativeness, integrity), are mentioned in most methods, the criteria for assessing additional values (Reynard, 2005, 2009:  aesthetic, ecological and cultural values) are much more heterogeneous (Mucivuna et al., 2019). There is particularly little discussion in the literature about the assessment of the ecological value of geomorphosites. Many case studies suggest to give a high score when “valuable” or “interesting” fauna and/or flora are observed, without explaining the link with a specific geomorphological landform or process. A few authors, such as Bollati et al. (2015), proposed to assess the “ecologic support role”, i.e. the impacts of geomorphological processes and landforms on vegetal and animal diversity or their contribution to ecosystem services. Despite these suggestions, there is still no detailed methodological proposal to assess the ecological value of geomorphosites based on clearly defined criteria.</p><p>The bi-directional relationship between geomorphology and biological elements of nature has been the subject of many publications and led to the development of the biogeomorphology, defined as the study of interactions between geomorphological processes and structures and living organisms, like plants, animals and microorganisms (e.g. Knox, 1972; Butler, 1995; Gorbushina, 2007). Compared to other categories of geosites, the activity of processes responsible for their formation and evolution is often a core characteristic of geomorphosites (Reynard, 2009; Pelfini and Bollati, 2014; Coratza and Hobléa, 2018) and this dynamic can have a strong influence on vegetation. This is especially the case in mountain environment, where dynamic geomorphological parameters can have various effects on vegetation distribution and community composition (Giaccone et al., 2019).</p><p>The aim of this communication is to clarify and objectivize the assessment of the ecological value of dynamic mountain geomorphosites. A complete evaluation of the ecological value should take into account the impacts of geomorphological processes and landforms on vegetation and fauna diversity. Here we propose to look further into the question of the influence of dynamic mountain geomorphosites on vegetation diversity. We suggest the definition of three criteria – disturbances, microhabitats, types of substrates – that should be used for a more accurate and objective assessment of the ecological value of this category of geomorphosites, with a particular focus on the links between geomorphology and vegetal biodiversity. We finally apply these criteria for the assessment of the ecological value of four mountain geomorphosites situated in the Vallon de Nant (Swiss Alps): a rock glacier, a moraine complex from the Younger Dryas, a side and frontal moraine from the Little Ice Age and a zone of scree slopes and avalanche deposits.</p>

Bending of the concentration discharge relationship can inform about in-stream nitrate removal

Nitrate (NO3−) excess in rivers harms aquatic ecosystems and can induce detrimental algae growths in coastal areas. Riverine NO3− uptake is a crucial element of the catchment scale nitrogen balance and can be measured at small spatiotemporal scales while at the scale of entire river networks, uptake measurements are rarely available. Concurrent, low frequency NO3− concentration and stream flow (Q) observations at a basin outlet, however, are commonly monitored and can be analyzed in terms of concentration discharge (C-Q) relationships. Previous studies suggest that more positive log(C)-log(Q) slopes under low flow conditions (than under high flows) are linked to biological NO3− uptake, creating a bent rather than linear log(C)-log(Q) relationship. Here we explore if network scale NO3− uptake creates bent log(C)-log(Q) relationships and when in turn uptake can be quantified from observed low frequency C-Q data. To this end we apply a parsimonious mass balance based river network uptake model in 13 mesoscale German catchments (21–1450 km2) and explore the linkages between log(C)-log(Q) bending and different model-parameter combinations. The modelling results show that uptake and transport in the river network can create bent log(C)-log(Q) relationships at the basin outlet from log-log linear C-Q relationships describing the NO3− land to stream transfer. We find that the bending is mainly shaped by geomorphological parameters that control the channel reactive surface area rather than by the biological uptake velocity itself. Further we show that in this exploratory modelling environment, bending is positively correlated to percentage NO3− load removed in the network (Lr.perc) but that network wide flow velocities should be taken into account when interpreting log(C)-log(Q) bending. Classification trees, finally, can successfully predict classes of low (~ 4 %), intermediate (~ 32 %) and high (~ 68 %) Lr.perc using information on water velocity and log(C)-log(Q) bending. These results can help to identify stream networks that efficiently attenuate NO3− loads based on low frequency NO3− and Q observations and generally show the importance of the channel geomorphology on the emerging log(C)-log(Q) bending at network scales.