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Climate change (CC) is expected affecting weather forcing regulating the triggering, reactivation, and severity of slope failures and soil erosion. In this view, the influence of CC can be different according to the area, the time horizon of interest and to the specific trends of weather variables. Similarly, land use/cover change can play a pivotal role in exacerbating or reducing such hazards.
Thus, the overall impacts depend on the region, spatial scale, time frame and socio-economic context addressed. However, even the simple identification of the weather patterns regulating the occurrence of such phenomena represents a not trivial issue, also assuming steady conditions, due to the crucial role played by geomorphological details. To support hazards’ monitoring, predictions and projections, last-generation and updated datasets with high spatio-temporal resolution and quality - like those from the Copernicus Services’ Portals - are useful to feed models, big-data analytics and indicators’ frameworks enabling timely, robust and efficient decision making.
The Session aims at presenting studies concerning ongoing to future landslide dynamics and soil erosion hazards across different geographical contexts and scales (from slope to regional, to global scale) including analyses of historical records and related climate variables, or modeling approaches driven by future climate exploiting downscaled output of climate projections. Studies assessing variations in severity, frequency and/or timing of events and consequent risks are valuable. Finally, tested or designed adaptation strategies can be discussed.

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Co-organized by CL2/SSS2
Convener: Guido Rianna | Co-conveners: Stefano Luigi GarianoECSECS, Fausto Guzzetti, Alfredo RederECSECS, Monia Santini
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| Thu, 07 May, 10:45–12:30 (CEST)

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Chat time: Thursday, 7 May 2020, 10:45–12:30

D1898 |
EGU2020-9327
| Highlight
Marcel Hürlimann, Vicente Medina, Zizheng Guo, Carol Puig-Polo, Antonio Lloret, and Jean Vaunat

Future environmental changes will strongly affect the occurrence of rainfall-induced landslides in mountainous regions. In our ongoing study, we focus on the effects of climate changes as well as land use and land cover (LULC) changes on shallow slope failures in the Pyrenees. For this reason, a physically-based susceptibility model was developed, which calculates the landslide susceptibility at regional scale. The model merges two different approaches for the calculation of pore fluid pressure and also includes the option of defining the values of input parameters stochastically.

The model was validated using landslide inventories from two different study areas located in the Central and Eastern Pyrenees. One is the inventory of historic shallow slides and debris flows in Andorra country. The other one is the inventory of the catastrophic landslide episode in Val d’Aran area in June 2013, which includes 393 landslide initiation points. The susceptibility modelling of these two validation cases produced acceptable results and showed that our physically-based model is producing consistent stability conditions.

In the next step, the future LULC and climate changes until the end of the 21th century were simulated for Val d’Aran study area. The LULC changes were determined with the IDRISI TerrSet software suite, while the climate changes were obtained from the ensemble of regional climate models using RCP 4.5 and 8.5 scenarios. The results of the susceptibility modelling showed that the impacts of future LULC changes increase the overall stability because of the larger area of forest and shrubs (and consequently higher cohesion due to root strength). In contrast, the impact of future climate changes, which was principally incorporated by higher rainfall intensity, reduced the overall slope stability. However, when we compared the impacts of both future changes, the results showed that the influence of the vegetation expansion is more important than the effect of higher rainfall intensity. Therefore, the overall stability conditions in the study area seem to slightly improve in the future.

As always in such studies, there are many uncertainties in the input data and additional simulations are necessary to confirm the observed trends. Nonetheless, the outcomes provide helpful information for researchers and practitioners that deal with the impacts of future changes on landslide susceptibility in mountainous regions.

How to cite: Hürlimann, M., Medina, V., Guo, Z., Puig-Polo, C., Lloret, A., and Vaunat, J.: Impacts of future land cover and climate changes on landslide susceptibility. Results obtained from regional-scale modelling in the Pyrenees., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9327, https://doi.org/10.5194/egusphere-egu2020-9327, 2020

D1899 |
EGU2020-3358
Irene Corno, Corrado Camera, Greta Bajni, Stefania Stevenazzi, and Tiziana Apuani

The Mont Cervin and Mont Emilius Mountain Communities (Aosta Valley, North-West Italy) are particularly predisposed to shallow landslide phenomena due to their morphological and geological characteristics. In addition, short intense rainfalls, which are considered one of the main landslides triggering factors, are expected to increase over the Alpine region due to climate changes. This study was carried out to provide a potentially dynamic landslide susceptibility map, adaptable to these changes, for the two Communities (total area 670 km2). To achieve this goal, the susceptibility analysis was set up on a statistical basis, using the Logistic Regression method. The objectives of this study were:

  1. to verify the completeness of the database of dated shallow landslides, and define an optimal training set with the addition of non-landslide points;
  2. to find a potentially dynamic variable, statistically and physically significant, which summarizes the landslide-climate relationships;
  3. to derive a parsimonious model for the definition of landslide susceptibility that includes this variable.

For the period 1990-2018, 293 dated records of shallow landslides were extracted from the Landslide Regional Database. For non-landslide points, two sampling algorithms (Random and Stratified Sampling) and different sample sizes (from a minimum of one to a maximum of three times the number of landslide points) were evaluated. For the same period, the precipitation and temperature data were obtained from the time series available in Regional archives. The relationships between the triggering of landslides and the characteristics of the preceding precipitation (e.g., amount and intensity for durations ranging from 0.5 hours to 30 days) were studied using graphs and correlation indices, to determine the climatic variable to be used in the statistical analysis. Other geological-environmental data (e.g. elevation, land use, lithology) were downloaded from the Regional geoportal and then processed in a GIS environment to obtain traditional predictive variables. Logistic Regression analysis was implemented in SPSS. The models were evaluated through the confusion matrix, optimized keeping only the statistically significant variables, and validated through a 70% (training) - 30% (test) subdivision of the input data and the calculation of the Area Under the Curve (AUC values). The climatic variable was expressed in terms of the average annual number of exceedances of a rainfall intensity-duration landslide-triggering threshold, validated for the study area. The optimal sample of non-landslide points was obtained through Random Sampling and is equal to 1.15 times the number of landslide points. Statistically significant predictors were altitude, land use, slope and exceedances of the threshold. Applying the optimized model (discriminating probability 0.5), the true positives reached the 89.6% and 88.9% on training and test points, respectively. The resulting AUC values ​​for the training and test curves are 83.1% and 82.1%, respectively. Both indicators show that the model is robust and has good predictive power. The susceptibility map obtained from the developed model was reclassified through the geometrical interval method and 93% of the landslides fell into the high and very high susceptibility classes.

How to cite: Corno, I., Camera, C., Bajni, G., Stevenazzi, S., and Apuani, T.: Towards a dynamic landslide susceptibility assessment: evaluation of a novel climate-related variable, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3358, https://doi.org/10.5194/egusphere-egu2020-3358, 2020

D1900 |
EGU2020-20083
| Highlight
Renzo Rosso, Maria Cristina Rulli, Mattia Galizzi, Davide Danilo Chiarelli, and Daniele Bocchiola

Mass wasting is a major landform shaping process in mountainous and steep terrains, and Italy is among the most affected countries in Europe. Lombardia region has 130.450 landslides mapped, covering an area of 3.300 km2 (i.e. 7.2% of the regional area). The 41% of landslides in Lombardia are rapid mass movements involving shallow soils, occurring mainly in the Alps and Fore-Alps. Many shallow landslides (SLs) result from infrequent meteorological events, inducing unstable conditions, or accelerate movements on otherwise stable slopes. In mountainous areas such as the Alps of Lombardia region, snowmelt concurs with rainfall intensity, and duration in setting the hydrologic conditions favorable to the occurrence of SLs. However, snowmelt contribution to SLs triggering is little investigated hitherto.  In regions experiencing seasonal snowmelt in spring and summer, melting water thereby could decrease the intensity and duration of rainfall needed for SL initiation, or even lead to LSs in dry weather conditions.  

Under the umbrella of the project MHYCONOS, a project founded by Fondazione CARIPLO, we developed a robust, and parameter wise parsimonious model, that mimics the triggering mechanism of shallow landslides by accounting for the combined effect of precipitation duration and intensity in, and snowmelt at thaw. The model is applied to the case study of Tartano basin, paradigmatic of SLs in the Alps of Lombardia, where in July 1987 a SL event produced 30 fatalities.

Our results show that about 37% of the Tartano Basin slopes display unstable condition, and more than 50% therein is influenced by soil moisture variation. Using a traditional (i.e. rainfall based) approach, occurrence of shallow landslides is predicted only during rainy periods, mainly October and November. In contrast, when including snow melt, the model mimics failures potentially also during April and May, when melting rate is the highest, and may increase triggering potential of rainfall. Currently, our efforts are aimed to conduct interviews and construct temporally based datasets, where occurrences of snow melt driven failures can be evidenced.

Risk perception by population may change, and public authority may be prepared to implement emergency plans in order to prevent injuries, causalities and damages to infrastructures also during spring time, when shallow landslides may occur in response to fast snow melt, even during clear sky days, in lack of precipitation.

 

How to cite: Rosso, R., Rulli, M. C., Galizzi, M., Chiarelli, D. D., and Bocchiola, D.: Snowmelt influence in shallow landslides, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20083, https://doi.org/10.5194/egusphere-egu2020-20083, 2020

D1901 |
EGU2020-21500
Evelina Volpe, Diana Salciarini, and Elisabetta Cattoni

Landslide risk mitigation that takes into account the safeguarding of environmental landscape involves several technical difficulties. However, at present, it is fundamental to identify sustainable technical and economic solutions in order to preserve the Italian areas characterized by an undoubted landscape and environmental heritage.

In most cases, landscape is deeply and destructively hit both when a landslide occurs, both when countermeasures for its mitigation are taken. Indeed, traditional technical solutions to increase slope safety are often costly and very impacting on natural environment and landscape. A possible alternative for improving slope stability is based on the use of non-invasive naturalistic engineering techniques [1]. Such solutions have a low impact on landscape and natural environment, conserving landscape identity and characteristics. Unfortunately, nowadays the use of these solutions is limited, since they suffer of a lack of rational approaches that quantify their stabilizing action. To overcome such constraint, we carried out a numerical study to evaluate the efficiency of remedial works based on naturalistic engineering to improve slope stability, considering a wide range of ideal slopes and different combinations of pre- and post- conditions (geometry, materials, types of soil protection solutions, etc.). As shown by the results of the stability analyses, in all the cases considered, the adopted naturalistic engineering techniques are able to increase the level of safety of the slopes with a very limited impact on the natural environment and landscape, due to the use of natural materials for the construction.

In this work we present a summary of the main techniques adopted in the field of naturalistic engineering. After introducing the methods generally used in evaluating the slope stability, the role played by vegetation in the mitigation of hydrogeological instability will be presented, with particular reference to the mechanical effect exerted by the plant roots which typically increases the soil shear strength. Then, the numerical study carried out to quantify the stabilizing effects deriving from the presence of vegetation will be shown, together with the main results obtained. Finally design indications for the application of non-invasive reinforcement techniques are presented.

 

Acknowledgements: The activities by the second Author have been carried out thanks to the PRIN2015 project "Innovative Monitoring and Design Strategies for Sustainable Landslide Risck Mitigation".

How to cite: Volpe, E., Salciarini, D., and Cattoni, E.: Technical solutions for landslide risk mitigation with law impact on landscape, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21500, https://doi.org/10.5194/egusphere-egu2020-21500, 2020

D1902 |
EGU2020-4546
Keh-Jian Shou

Due to active tectonic activity, the rock formations are young and highly fractured in Taiwan area. The dynamic changing of river morphology makes the highly weathered formations or colluviums prone to landslide and debris flow. For the past decade, the effect of climate change is significant and creates more and more extreme weather events. The change of rainfall behavior significantly changes the landslide behavior, which makes the large-scale landslides, like the Shiaolin landslide, possible. Therefore, it is necessary to develop the new technologies for landslide investigation, monitoring, analysis, early warning, etc.

Since the landslide hazards in Taiwan area are mainly induced by heavy rainfall, due to climate change and the subsequent extreme weather events, the probability of landslides is also increased. Focusing on the upstreams of the watersheds in Central Taiwan, this project studied the behavior and hazard of shallow and deep-seated landslides. Different types of susceptibility models in different catchment scales were tested, in which the control factors were analyzed and discussed. This study also employs rainfall frequency analysis together with the atmospheric general circulation model (AGCM) downscaling estimation to predict the extreme rainfalls in the future. Such that the future hazard of the shallow and deep-seated landslide in the study area can be predicted. The results of predictive analysis can be applied for risk prevention and management in the study area.

How to cite: Shou, K.-J.: On the Landslide Hazard with the Impact of Climate Change in Central Taiwan, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4546, https://doi.org/10.5194/egusphere-egu2020-4546, 2020

D1903 |
EGU2020-22030
Bruno Delvaux, Clairia Kankurize, and Gervais Rufyikiri

In Burundi, landslides are frequent on the western slope of the Congo-Nile ridge. Unfortunately, they are poorly studied and understood despite their deadly consequences. Previous reports have suggested that slope steepness, lithology and clay soils expose this slope to landslides, while heavy and intense rainfall is a trigger. However, the role of soil in the vulnerability of this specific slope to landslides is unknown. Here we investigate on soil characteristics involved in land sliding in this area.

We selected and sampled black and red soils in two Muhunguzi landslides. We determined the soil plasticity from Atterberg limits as well as the particle size distribution. In addition, we measured the soil weathering stage, and further identified the clay minerals from measuring the cation exchange capacity of the clay fraction and analyzing clay samples with X-ray diffraction (XRD).

Both the black and red soils are moderately weathered since TRB values in the B horizons range between 330 and 425 cmol(+) kg-1. The soils are loamy clayey to clayey (% clay: 33-55%), and contain high charge clay minerals. They do not differ in their Atterberg limits, which classify the soils as medium plasticity soils in the Casagrande plasticity diagram. Our data further show that both soils have a medium swelling potential. XRD show that the clay fraction consists of kaolinite and smectite and/or vermiculite. The latter 2:1 clay minerals are expandable and swelling clays, respectively. They give these two soils their plasticity and swelling properties. These two properties play an important role in the mechanical behavior of water-saturated soils. Indeed, swelling reduces soil cohesion while the plasticity index and the liquidity limit vary inversely with the internal angle of friction of the soil; cohesion and internal angle of friction being the fundamental parameters of the soil shear resistance. In addition, the soil mantle covers a hard schistose rock whose declivity is parallel to the soil surface slope. Thus, after intense rainfall during the wet season, the water-saturated soil reaches a level of liquidity sufficient to favor a landslide, all the more easily if the slope of the hard rock is inclined in the direction of the gravity flow.gru

How to cite: Delvaux, B., Kankurize, C., and Rufyikiri, G.: Swelling clayey soils promote slope instability in the Muhunguzi watershed, western Burundi, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22030, https://doi.org/10.5194/egusphere-egu2020-22030, 2020

D1904 |
EGU2020-5703
Clairia Kankurize, Gervais Rufyikiri, and Bruno Delvaux

Located in the East African Rift Valley, western Burundi is often threatened by landslides during the rainy season. Damage can be seen both in the mountains, the sites of the landslides, and in the plain where sediments are deposited: environmental degradation, loss upstream and downstream of cultivated land, destruction of infrastructures, loss of life, waterborne diseases, floods of streams laden with sludge and stones torn off during landslides... The magnitude of these shifts justifies the need for studies to understand the factors that cause this part of Burundi to be vulnerable to landslides.

Here we highlight the relationship between the environmental context and the process of landslides in this region. To analyze the impact of geomorphological, geological, soil and climatic conditions as well as anthropogenic factors, we carried out an inventory of landslides in the Muhunguzi watershed, a survey of the local population and an analysis of rainfall over the period 1935-2014.

Of 7 Muhunguzi sub-watersheds with a total area of 21.2 km2, 43 landslides were identified, 29 of which were on a single sub-watershed. Most landslides were shallow. Geomorphology was characterized by steep escarpments interspersed with valleys. The landslides were located on the lower slopes and most affected the rivers. The lithology was dominated by shale inclined parallel to the slope. Landslides were located on rocky, black or red soils, identified as Nitisols. The majority of landslides occurred on cultivated fields. Daily precipitations ranging between 75mm and 100mm with a return period of 5.3 years are strongly correlated to shallow landslides in the studied area. Such intense daily rain thus appears here as a major trigger to these landslides. In addition, relief, geological and soil conditions are predisposing factors while population density and the resulting land pressure worsen land instability.

We conclude that further studies are needed to understand the impact of soil processes and human activity in order to identify adequate management practices preventing landslides in Muhunguzi area.

How to cite: Kankurize, C., Rufyikiri, G., and Delvaux, B.: Daily rainfall above 75mm is a major trigger to landslides in the Muhunguzi, western Burundi, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5703, https://doi.org/10.5194/egusphere-egu2020-5703, 2020

D1905 |
EGU2020-2237
Prediction of landslide susceptibility using Hybrid Support Vector Regression (SVR) with metaheuristic algorithms
(withdrawn)
Lee Saro and Mahdi Panahi
D1906 |
EGU2020-22249
| Highlight
Gianvito Scaringi

Global warming will alter the frequency and patterns of landslides, increasing the risk to populations, infrastructures, and ecosystems in many regions of the world. Scientists draw this prediction mainly from expected changes in precipitation, ice covers, sea level, and land uses. The direct role of soil temperature is usually neglected, even though changes in patterns of temperature – propagating from the surface to depths of several metres – can alter the strength, permeability, water retention capacity, and other properties of various soils. This has been demonstrated, for instance, for active clays subjected to heating while addressing specific engineering problems, such as the long-term storage of radioactive waste in deep geological repositories.

In an ongoing project, we attempt to apply an advanced thermo-hydro-mechanical soil model – based on the theory of hypoplasticity and accounting for various coupled behaviours – to perform slope stability analyses in clayey soils. By this model, we can reproduce complex hydro-mechanical responses caused by changes of temperature, including effects on water pressures, water retention, and swelling or shrinkage. We plan to carry out short- and long-term parametric analyses under climate scenarios, to compare the direct role of temperature with that of other types of forcing (such as changes in precipitation). This way, we expect to quantify how local warming or cooling and altered patterns of temperature can control some types of landslides, and consequently affect current landslide hazard and risk assessments. Ultimately, we plan to conceptualise an upscaled model, so as to work towards physically-based regional assessments through a thermo-hydro-mechanical coupled approach.

How to cite: Scaringi, G.: Climate change and landslides: introducing a thermo-hydro-mechanical approach, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22249, https://doi.org/10.5194/egusphere-egu2020-22249, 2020

D1907 |
EGU2020-11816
Gaurav Savant, Ian Floyd, and Ronald Heath

Gravity driven flows such as debris, pyroclastic, avalanche, landslides etc. pose a great threat to life and property. In recent years rainfall combined with prior fire events have resulted in the generation of debris flows in the United States and elsewhere, landslides and mud flows are common occurrences in several regions of  the world where monsoon rains cause soils to saturate, slump and then flow. In some regions these flows take the form of sand, boulders or other cohesionless material generated flows, and avalanches. These flows exhibit non-Newtonian flow characteristics, and provide a challenging engineering problem. These problems arise in the prediction of these flows as well as devising engineering solutions to alleviate danger these pose to the public. Since the advent of numerical modelling, engineers and scientists have used shallow-water equation based mathematical equations to simulate Newtonian flows. In the recent past researchers have attempted to use modifications to the stress terms in the shallow-water equations to account for non-Newtonian behaviour. However these modifications, in general, rely on just one or two of the non-Newtonian formulations to mathematically represent and then numerically simulate non-Newtonian flows. The non-Newtonian behaviour of flows is dynamic, and can change non-Newtonian states depending upon a variety of properties. These properties are inherent to the flows and depend upon the formative process, composition, as well as grain sizes of the debris. Therefore, the requirement is that of a mathematical and numerical description that accounts for these changing states. The Engineer Research and Development Centre (ERDC) of the U.S. Army Corps of Engineers (USACE) has developed a library of debris processes, DebrisLib. This, model agnostic, debris processes library can be linked to any shallow-water based hydrodynamic driver to enable the simulation of debris flows, and the changing non-Newtonian state of the debris flow. This presentation will demonstrate the mathematical development, and incorporation of DebrisLib into the USACE finite element and adaptive meshing software Adaptive Hydraulics (AdH). The implementation will be demonstrated using application to flume tests, avalanches as well as landslides.

How to cite: Savant, G., Floyd, I., and Heath, R.: Numerical Modeling of Non-Newtonian Flows within a Newtonian Equation Framework, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11816, https://doi.org/10.5194/egusphere-egu2020-11816, 2020

D1908 |
EGU2020-22194
Nawa Raj Pradhan, Steven Brown, and Ian Floyd

Data acquisition and an efficient processing method for hydrological model initialization, such as soil moisture, and parameter value identification are critical for a physics based distributed watershed modelling of flood and flood related disasters such as sediment and debris flow. Site measurements can provide relatively accurate estimates of soil moisture, but such techniques are limited due to the need for a variety of measurement accessories, which are difficult to obtain to cover a large area sufficiently. Available satellite-based digital soil moisture data is at 9 kilometers to 50 kilometers in resolution which completely filters the soil moisture details at the hill slope scale. Moreover, available satellite-based digital soil moisture data represents only a few centimeters of the top soil column that informs nothing about the effective root-zone wetness. A recently developed soil moisture estimation method called SERVES (Soil moisture Estimation of Root zone through Vegetation index-based Evapotranspiration fraction and Soil properties) overcomes this limitation of satellite-based soil moisture data by estimating distributed root zone soil moisture at 30 meter resolution. In this study, a distributed watershed hydrological model of a sub-catchment of Reynolds Creek Experimental Watershed was developed with GSSHA (Gridded Surface Sub-surface Hydrological Analysis) Model. SERVES soil moisture estimated at 30 meter resolution was deployed in the watershed hydrological parameter value calibration and identification process. The 30 meter resolution SERVES soil moisture data was resampled to 4500 meter and 9000 meter resolutions and was separately employed in the calibrated hydrological model to determine the effect soil moisture resolution  has on the simulated outputs and the model parameters. It was found that the simulated discharge significantly decreased as the initial soil moisture resolution was coarsened. To compensate for this underestimated simulated discharge, the soil hydraulic conductivity value decreased logarithmically with respect to the decreased resolutions. This study will reduce parameter value identification uncertainty especially in flood and soil erosion modelling at multi scale watershed in a changing climate.

How to cite: Pradhan, N. R., Brown, S., and Floyd, I.: Soil Moisture Initialization Input Scale Effect on Parameter Value Identification of a Physically Based Distributed Hydrologic Modelling, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22194, https://doi.org/10.5194/egusphere-egu2020-22194, 2020

D1909 |
EGU2020-1853
Rocky Talchabhadel, Hajime Nakagawa, Kenji Kawaike, Kazuki Yamanoi, Anil Aryal, Binod Bhatta, and Saroj Karki

This study uses Soil Water Assessment Tool (SWAT) for watershed modeling in West Rapti River Basin (WRRB) of Nepal for assessing future scenarios of soil erosion till the end of 2100. Firstly, the river discharge was calibrated for the period (2003–2009) and validated for the period (2010-2013). We used three discharge stations (namely Mari at upstream, Bagasoti at mid-stream and Jalkundi at downstream). Secondly, sediment discharge was calibrated and validated at two sediment monitoring stations (namely Mari at upstream and Jalkundi at downstream). A Sequential Uncertainty Fitting (SUFI-2) technique was employed for the fine-tuning of sensitive hydrological parameters. The model achieved a good performance in both the calibration and validation periods. R2, NSE, PBIAS, and RSR were taken as performance indicators.  Finally, the developed model was then used to assess future scenarios of sediment yield in the WRRB. This study used five regional climate models (RCMs) for precipitation and temperature, and their ensemble under two representative concentration pathways (RCPs 4.5 and 8.5). This study analyses future scenarios for three time-frames namely, near future (NF: 2025-2049), mid future (MF: 2050-2074), and far future (FF: 2075-2099) with respect to the baseline (2003-2013). We found a significant increase in temperature in the future with annual average temperature anticipated to change from +0.76 oC to +5.8 oC and a moderate increase in precipitation with annual precipitation projected to change from -1.9% to 19.3% under different scenarios. In general, the MME shows slightly increasing precipitation (higher under RCP 4.5 than RCP 8.5), significantly increasing temperature (higher under RCP 8.5 than RCP 4.5) and moderately increasing sediment discharge. Our findings are useful for water resources and sediment management in WRRB under changing climate.

How to cite: Talchabhadel, R., Nakagawa, H., Kawaike, K., Yamanoi, K., Aryal, A., Bhatta, B., and Karki, S.: SWAT modeling for assessing future scenarios of soil erosion in West Rapti River Basin of Nepal, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1853, https://doi.org/10.5194/egusphere-egu2020-1853, 2019

D1910 |
EGU2020-11356
Guido Rianna, Monia Santini, Marco Mancini, Roberta Padulano, and Sergio Noce

Soil erosion by water greatly affects Italy impacted by 24% of total soil loss of Europe, 33% of agricultural lands exposed, and costs, e.g. for crop production, up to about 600Meuro. Furthermore, expected increases in severity and magnitude of extreme precipitation events could exacerbate such an issue.

In this regard, rainfall information at very fine spatial and temporal resolution represents a key point; unfortunately, weather stations are not spread uniformly across regions and they uncommonly provide free data at sub-daily scale. Moreover, the reliable projections of how rainfall will change in the coming decades are hard to store and manage for non-experts.

In trying to overcome such a gap, Copernicus Climate Change Service (C3S) provides several tools. The C3S is part of the Copernicus Earth Observation Programme and is implemented by the European Centre for Medium-Range Weather Forecasts (ECMWF) on behalf of the European Commission. In particular, Climate Data Store (CDS) hosts rainfall time series for the historical period and most recent decades from observational (E-OBS) and reanalysis (ERA5, ERA5-Land, UERRA) datasets, at (sub) daily time step and with horizontal resolution ranging from 31 km to 5.5 km. For the future, the simulations’ ensemble within EURO-CORDEX (resolution ~12 km, daily time step) are available for robust evaluations, i.e. to consider the uncertainty due to alternative greenhouse gas concentration scenarios and model chain used.

In this context, in the last months, C3S funded the Demo Case SOIL EROSION implemented by the CMCC Foundation and aimed at assessing ongoing and future soil loss by water erosion over Italy. The Demo Case is expected to develop further specific datasets and a web-application by exploiting products and tools also provided by Climate Data Store (CDS) infrastructure.

To assess soil losses, the largely adopted Revised Universal Soil Loss Equation (RUSLE) is selected. Such an empirical equation combines rainfall erosivity (R-factor), evaluated in this case by exploiting datasets in CDS, to soil susceptibility to erosion due to soil intrinsic properties but also to land cover, land management, and topography. Gridded datasets related to R-factor and soil losses will be then made available within the CDS catalog. Moreover, the web application will permit visualizing and retrieving trends and results for specific areas (e.g. NUTS) in the way of maps and graphs. In addition to the "Basic" mode, the Application is expected to support "what-if" analysis ("Advanced" mode) permitting to understand how variations in land use (C-factor) or management practice (P-factor) can influence soil losses at large scale under current and future conditions.

How to cite: Rianna, G., Santini, M., Mancini, M., Padulano, R., and Noce, S.: Exploiting Copernicus Climate Change Service (C3S) to assess ongoing and future soil erosion over Italy, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11356, https://doi.org/10.5194/egusphere-egu2020-11356, 2020