scholarly journals Mapping rainfall erosivity at a regional scale: a comparison of interpolation methods in the Ebro Basin (NE Spain)

2009 ◽  
Vol 13 (10) ◽  
pp. 1907-1920 ◽  
Author(s):  
M. Angulo-Martínez ◽  
M. López-Vicente ◽  
S. M. Vicente-Serrano ◽  
S. Beguería
Keyword(s):  
Soil Erosion ◽  
Prediction Models ◽  
Regional Scale ◽  
Geostatistical Simulation ◽  
High Temporal Resolution ◽  
Rainfall Erosivity ◽  
Ebro Basin ◽  
Spatial Coverage ◽  
Interpolation Techniques ◽  
Ne Spain

Abstract. Rainfall erosivity is a major causal factor of soil erosion, and it is included in many prediction models. Maps of rainfall erosivity indices are required for assessing soil erosion at the regional scale. In this study a comparison is made between several techniques for mapping the rainfall erosivity indices: i) the RUSLE R factor and ii) the average EI30 index of the erosive events over the Ebro basin (NE Spain). A spatially dense precipitation data base with a high temporal resolution (15 min) was used. Global, local and geostatistical interpolation techniques were employed to produce maps of the rainfall erosivity indices, as well as mixed methods. To determine the reliability of the maps several goodness-of-fit and error statistics were computed, using a cross-validation scheme, as well as the uncertainty of the predictions, modeled by Gaussian geostatistical simulation. All methods were able to capture the general spatial pattern of both erosivity indices. The semivariogram analysis revealed that spatial autocorrelation only affected at distances of ~15 km around the observatories. Therefore, local interpolation techniques tended to be better overall considering the validation statistics. All models showed high uncertainty, caused by the high variability of rainfall erosivity indices both in time and space, what stresses the importance of having long data series with a dense spatial coverage.

scholarly journals Mapping rainfall erosivity at a regional scale: a comparison of interpolation methods in the Ebro Basin (NE Spain)

2009 ◽  
Vol 6 (1) ◽  
pp. 417-453 ◽  
Author(s):  
M. Angulo-Martínez ◽  
M. López-Vicente ◽  
S. M. Vicente-Serrano ◽  
S. Beguería
Keyword(s):  
Soil Erosion ◽  
Goodness Of Fit ◽  
Prediction Models ◽  
Regional Scale ◽  
Data Series ◽  
High Temporal Resolution ◽  
Rainfall Erosivity ◽  
Ebro Basin ◽  
Spatial Coverage ◽  
Ne Spain

Abstract. Rainfall erosivity is a major causal factor of soil erosion, and it is included in many prediction models. Maps of rainfall erosivity indices are required for assessing soil erosion at the regional scale. In this study a comparison is made between several techniques for mapping the rainfall erosivity indices: i) the RUSLE R factor and ii) the average EI30 index of the erosive events over the Ebro basin (NE Spain). A spatially dense precipitation data base with a high temporal resolution (15 min) has been used. Global, local and geostatistical interpolation techniques were employed to produce maps of the rainfall erosivity indices, as well as mixed methods (regression plus local interpolation). To determine the reliability of the maps several goodness-of-fit and error statistics were computed, using a cross-validation scheme. All methods represented correctly the spatial patterns of both erosivity indices, but the mixed approaches tended to be better overall considering the validation statistics. Additionally, they allowed identifying statistically significant relationships between rainfall erosivity and other geographical variables, as elevation and distance to the water bodies. All models had a relatively high uncertainty, caused by the high variability of rainfall erosivity indices both in time and space, what stresses the importance of using the longest data series available with a good spatial coverage.

scholarly journals Classification of Landslide Activity on a Regional Scale Using Persistent Scatterer Interferometry at the Moselle Valley (Germany)

2018 ◽  
Vol 10 (12) ◽  
pp. 1880 ◽  
Author(s):  
Andre Kalia
Keyword(s):  
A Priori ◽  
Regional Scale ◽  
Economic Loss ◽  
Data Availability ◽  
High Temporal Resolution ◽  
Persistent Scatterer Interferometry ◽  
Landslide Activity ◽  
Persistent Scatterer ◽  
Spatial Coverage ◽  
Sar Data

Landslides are a major natural hazard which can cause significant damage, economic loss, and loss of life. Between the years of 2004 and 2016, 55,997 fatalities caused by landslides were reported worldwide. Up-to-date, reliable, and comprehensive landslide inventories are mandatory for optimized disaster risk reduction (DRR). Various stakeholders recognize the potential of Earth observation techniques for an optimized DRR, and one example of this is the Sendai Framework for DRR, 2015–2030. Some of the major benefits of spaceborne interferometric Synthetic Aperture Radar (SAR) techniques, compared to terrestrial techniques, are the large spatial coverage, high temporal resolution, and cost effectiveness. Nevertheless, SAR data availability is a precondition for its operational use. From this perspective, Copernicus Sentinel-1 is a game changer, ensuring SAR data availability for almost the entire world, at least until 2030. This paper focuses on a Sentinel-1-based Persistent Scatterer Interferometry (PSI) post-processing workflow to classify landslide activity on a regional scale, to update existing landslide inventories a priori. Before classification, a Line-of-Sight (LOS) velocity conversion to slope velocity and a cluster analysis was performed. Afterwards, the classification was achieved by applying a fixed velocity threshold. The results are verified through the Global Positioning System (GPS) survey and a landslide hazard indication map.

scholarly journals Estimating the Impact of Land Cover Change on Soil Erosion Using Remote Sensing and GIS Data by USLE Model and Scenario Design

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Anmin Fu ◽  
Yulin Cai ◽  
Tao Sun ◽  
Feng Li
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Land Cover ◽  
Land Cover Change ◽  
Regional Scale ◽  
Rainfall Erosivity ◽  
Rainfall Runoff ◽  
Scenario Design ◽  
Gis Data ◽  
The Impact

Great efforts have been made to curb soil erosion and restore the natural environment to Inner Mongolia in China. The purpose of this study is to evaluate the impact of returning farmland to the forest on soil erosion on a regional scale. Considering that rainfall erosivity also has an important impact on soil erosion, the effect of land use and land cover change (LUCC) on soil erosion was evaluated through scenario construction. Firstly, the universal soil loss equation (USLE) model was used to evaluate the actual soil erosion (2001 and 2010). Secondly, two scenarios (scenario 1 and scenario 2) were constructed by assuming that the land cover and rainfall-runoff erosivity are fixed, respectively, and soil erosion under different scenarios was estimated. Finally, the effect of LUCC on soil erosion was evaluated by comparing the soil erosion under actual situations with the hypothetical scenarios. The results show that both land use/cover change and rainfall-runoff erosivity change have significant effects on soil erosion. The land use and land cover change initiated by the ecological restoration projects have obviously reduced the soil erosion in this area. The results also reveal that the method proposed in this paper is helpful to clarify the influencing factors of soil erosion.

scholarly journals Assessment of Intra-Annual and Inter-Annual Variabilities of Soil Erosion in Crete Island (Greece) by Incorporating the Dynamic “Nature” of R and C-Factors in RUSLE Modeling

2020 ◽  
Vol 12 (15) ◽  
pp. 2439 ◽  
Author(s):  
Christos Polykretis ◽  
Dimitrios D. Alexakis ◽  
Manolis G. Grillakis ◽  
Stelios Manoudakis
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Temporal Resolution ◽  
Soil Loss ◽  
High Temporal Resolution ◽  
Rainfall Erosivity ◽  
Management Interventions ◽  
Crete Island ◽  
The Impact ◽  
Loss Rates

Under the continuously changing conditions of the environment, the exploration of spatial variability of soil erosion at a sub-annual temporal resolution, as well as the identification of high-soil loss time periods and areas, are crucial for implementing mitigation and land management interventions. The main objective of this study was to estimate the monthly and seasonal soil loss rates by water-induced soil erosion in Greek island of Crete for two recent hydrologically contrasting years, 2016 (dry) and 2019 (wet), as a result of Revised Universal Soil Loss Equation (RUSLE) modeling. The impact of temporal variability of the two dynamic RUSLE factors, namely rainfall erosivity (R) and cover management (C), was explored by using rainfall and remotely sensed vegetation data time-series of high temporal resolution. Soil, topographical, and land use/cover data were exploited to represent the other three static RUSLE factors, namely soil erodibility (K), slope length and steepness (LS) and support practice (P). The estimated rates were mapped presenting the spatio-temporal distribution of soil loss for the study area on a both intra-annual and inter-annual basis. The identification of high-loss months/seasons and areas in the island was achieved by these maps. Autumn (about 35 t ha−1) with October (about 61 t ha−1) in 2016, and winter (about 96 t ha−1) with February (146 t ha−1) in 2019 presented the highest mean soil loss rates on a seasonal and monthly, respectively, basis. Summer (0.22–0.25 t ha−1), with its including months, showed the lowest rates in both examined years. The intense monthly fluctuations of R-factor were found to be more influential on water-induced soil erosion than the more stabilized tendency of C-factor. In both years, olive groves in terms of agricultural land use and Chania prefecture in terms of administrative division, were detected as the most prone spatial units to erosion.

Spatial and seasonal patterns of rainfall erosivity in the Lake Kivu region: Insights from a meteorological observatory network

2021 ◽  
pp. 030913332110017
Author(s):  
R.M. Bagalwa ◽  
C. Chartin ◽  
S. Baumgartner ◽  
S. Mercier ◽  
M. Syauswa ◽  
...  
Keyword(s):  
Temporal Resolution ◽  
Prediction Models ◽  
Temporal Dynamics ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
High Temporal Resolution ◽  
Rainfall Erosivity ◽  
Lake Kivu ◽  
Meteorological Observatory ◽  
Resolution Data

In the Lake Kivu region, water erosion is the main driver for soil degradation, but observational data to quantify the extent and to assess the spatial-temporal dynamics of the controlling factors are hardly available. In particular, high spatial and temporal resolution rainfall data are essential as precipitation is the driving force of soil erosion. In this study, we evaluated to what extent high temporal resolution data from the TAHMO network (with poor spatial and long-term coverage) can be combined with low temporal resolution data (with a high spatial density covering long periods of time) to improve rainfall erosivity assessments. To this end, 5 minute rainfall data from TAHMO stations in the Lake Kivu region, representing ca. 37 observation-years, were analyzed. The analysis of the TAHMO data showed that rainfall erosivity was mainly controlled by rainfall amount and elevation and that this relation was different for the dry and wet season. By combining high and low temporal resolution databases and a set of spatial covariates, an environmental regression approach (GAM) was used to assess the spatiotemporal patterns of rainfall erosivity for the whole region. A validation procedure showed relatively good predictions for most months (R2 between 0.50 and 0.80), while the model was less performant for the wettest (April) and two driest months (July and August) (R2 between 0.24 and 0.38). The predicted annual erosivity was highly variable with a range between 2000 and 9000 MJ mm ha−1 h−1 yr−1 and showed a pronounced east–west gradient which is strongly influenced by local topography. This study showed that the combination of high and low temporal resolution rainfall data and spatial prediction models can be used to improve the assessments of monthly and annual rainfall erosivity patterns that are grounded in locally calibrated and validated data.

scholarly journals The solar eclipse: a natural meteorological experiment

2016 ◽  
Vol 374 (2077) ◽  
pp. 20150225 ◽  
Author(s):  
R. Giles Harrison ◽  
Edward Hanna
Keyword(s):  
Solar Radiation ◽  
Solar Eclipse ◽  
Prediction Models ◽  
Numerical Models ◽  
Weather Prediction ◽  
Regional Scale ◽  
Electrical Energy ◽  
Atmospheric Effects ◽  
Modern Approach ◽  
Spatial Coverage

A solar eclipse provides a well-characterized reduction in solar radiation, of calculable amount and duration. This captivating natural astronomical phenomenon is ideally suited to science outreach activities, but the predictability of the change in solar radiation also provides unusual conditions for assessing the atmospheric response to a known stimulus. Modern automatic observing networks used for weather forecasting and atmospheric research have dense spatial coverage, so the quantitative meteorological responses to an eclipse can now be evaluated with excellent space and time resolution. Numerical models representing the atmosphere at high spatial resolution can also be used to predict eclipse-related changes and interpret the observations. Combining the models with measurements yields the elements of a controlled atmospheric experiment on a regional scale (10–1000 km), which is almost impossible to achieve by other means. This modern approach to ‘eclipse meteorology’ as identified here can ultimately improve weather prediction models and be used to plan for transient reductions in renewable electricity generation. During the 20 March 2015 eclipse, UK electrical energy demand increased by about 3 GWh (11 TJ) or about 4%, alongside reductions in the wind and photovoltaic electrical energy generation of 1.5 GWh (5.5 TJ). This article is part of the themed issue ‘Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse’.

A meta-analysis on the effectiveness of post-fire soil erosion mitigation treatments

2021 ◽  
Author(s):  
Antonio Girona-García ◽  
Diana Vieira ◽  
Joana Silva ◽  
Cristina Fernández ◽  
Peter Robichaud ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Effect Size ◽  
Meta Analysis ◽  
Regional Scale ◽  
Ground Cover ◽  
Rainfall Erosivity ◽  
Application Rates ◽  
Different Types ◽  
Erosion Mitigation ◽  
Overall Effectiveness

<p>Wildfires are considered to be one of the main causes of soil erosion and land degradation processes in fire-prone areas [1], which are expected to increase in the future because of fire patterns shifting worldwide as a consequence of changes in climate and land use [2]. To maintain the sustainability of ecosystems and protect the values at risk downstream from the fire-affected areas, it is vital to mitigate the increased hydrological and erosive response after fires. Despite soil erosion mitigation treatments have been widely applied after wildfires, their effectiveness has only been assessed in local and regional-scale studies, so the obtained conclusions might be heavily influenced by site-specific conditions.</p><p>To overcome this constraint, a meta-analysis was applied on the scientific literature on post-fire soil erosion mitigation treatments indexed in Scopus. The search resulted in 34 publications from which 53 and 222 pairs of treated/untreated observations on post-fire runoff and erosion, respectively, were obtained. The overall effectiveness of mitigation treatments, expressed as effect size, was determined for the runoff and erosion observations, and further analyzed for four different types of treatments (mulching, barriers, seeding, and chemical). The erosion observations concerning mulches were analyzed for differences in effect size between 3 different types of materials (straw, wood, and hydromulch) as well as between different application rates of straw and wood. The erosion observations were also analyzed for the overall effect size of post-fire year, burn severity, rainfall amount and erosivity, and ground cover.</p><p>The results showed that all four types of treatments significantly reduced post-fire soil erosion, but that only the mulch and barrier treatments significantly reduced post-fire runoff. From the 3 different mulch treatments, the straw and wood were significantly more efficient in mitigating erosion than the hydromulch. The different straw and wood mulch application rates also influenced their effectiveness. Straw mulch was less effective at rates below than above 200 g m<sup>-2</sup>, while mulching with wood at high rates (1300 to 1750 g m<sup>-2</sup>) produced more variable outcomes. Results also suggested that the overall effectiveness of the treatments was greatest shortly after fire, in severely burned sites, providing or promoting the development of ground cover over 70%, and with increasing rainfall erosivity.</p><p>It can be concluded that, in overall terms, the application of the studied post-fire erosion mitigation treatments represented a better choice than doing nothing, especially in sites where erosion is high. However, works on this topic are underrepresented outside of the USA, Spain and Portugal. Most of the studies were conducted at hillslope scale and tested mulching and/or barriers, while larger scales and other treatments were neglected. Further efforts are needed in testing, from field and modelling experiments, combinations of existing and/or emerging erosion mitigation treatments to ensure that the most suitable measures are applied after fires.</p><p>[1] Shakesby (2011). Earth-Sci. Revs. 105:71-100. DOI: 10.1016/j.earscirev.2011.01.001</p><p>[2] Andela et al. (2017). Science 356: 1356-1362. DOI: 10.1126/science.aal4108</p>

scholarly journals Modelling floods in the Ammer catchment: limitations and challenges with a coupled meteo-hydrological model approach

2003 ◽  
Vol 7 (6) ◽  
pp. 833-847 ◽  
Author(s):  
R. Ludwig ◽  
S. Taschner ◽  
W. Mauser
Keyword(s):  
Hydrological Model ◽  
Prediction Models ◽  
Meteorological Data ◽  
Weather Prediction ◽  
Input Parameter ◽  
Rain Gauge ◽  
Complex Nature ◽  
High Temporal Resolution ◽  
Flood Modelling ◽  
Spatial Coverage

Abstract. Numerous applications of hydrological models have shown their capability to simulate hydrological processes with a reasonable degree of certainty. For flood modelling, the quality of precipitation data — the key input parameter — is very important but often remains questionable. This paper presents a critical review of experience in the EU-funded RAPHAEL project. Different meteorological data sources were evaluated to assess their applicability for flood modelling and forecasting in the Bavarian pre-alpine catchment of the Ammer river (709 km2), for which the hydrological aspects of runoff production are described as well as the complex nature of floods. Apart from conventional rain gauge data, forecasts from several Numerical Weather Prediction Models (NWP) as well as rain radar data are examined, scaled and applied within the framework of a GIS-structured and physically based hydrological model. Multi-scenario results are compared and analysed. The synergetic approach leads to promising results under certain meteorological conditions but emphasises various drawbacks. At present, NWPs are the only source of rainfall forecasts (up to 96 hours) with large spatial coverage and high temporal resolution. On the other hand, the coarse spatial resolution of NWP grids cannot yet address, adequately, the heterogeneous structures of orographic rainfields in complex convective situations; hence, a major downscaling problem for mountain catchment applications is introduced. As shown for two selected Ammer flood events, a high variability in prediction accuracy has still to be accepted at present. Sensitivity analysis of both meteo-data input and hydrological model performance in terms of process description are discussed and positive conclusions have been drawn for future applications of an advanced meteo-hydro model synergy. Keywords: RAPHAEL, modelling, forecasting, model coupling, PROMET-D, TOPMODEL

scholarly journals Modelling soil erosion at European scale: towards harmonization and reproducibility

2015 ◽  
Vol 15 (2) ◽  
pp. 225-245 ◽  
Author(s):  
C. Bosco ◽  
D. de Rigo ◽  
O. Dewitte ◽  
J. Poesen ◽  
P. Panagos
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Regional Scale ◽  
Computational Modelling ◽  
Mitigation Strategies ◽  
Soil Parameters ◽  
Rainfall Erosivity ◽  
Nutrient Contents ◽  
Continental Scale ◽  
Country Level

Abstract. Soil erosion by water is one of the most widespread forms of soil degradation. The loss of soil as a result of erosion can lead to decline in organic matter and nutrient contents, breakdown of soil structure and reduction of the water-holding capacity. Measuring soil loss across the whole landscape is impractical and thus research is needed to improve methods of estimating soil erosion with computational modelling, upon which integrated assessment and mitigation strategies may be based. Despite the efforts, the prediction value of existing models is still limited, especially at regional and continental scale, because a systematic knowledge of local climatological and soil parameters is often unavailable. A new approach for modelling soil erosion at regional scale is here proposed. It is based on the joint use of low-data-demanding models and innovative techniques for better estimating model inputs. The proposed modelling architecture has at its basis the semantic array programming paradigm and a strong effort towards computational reproducibility. An extended version of the Revised Universal Soil Loss Equation (RUSLE) has been implemented merging different empirical rainfall-erosivity equations within a climatic ensemble model and adding a new factor for a better consideration of soil stoniness within the model. Pan-European soil erosion rates by water have been estimated through the use of publicly available data sets and locally reliable empirical relationships. The accuracy of the results is corroborated by a visual plausibility check (63% of a random sample of grid cells are accurate, 83% at least moderately accurate, bootstrap p ≤ 0.05). A comparison with country-level statistics of pre-existing European soil erosion maps is also provided.

Sign in / Sign up

Export Citation Format

Share Document