Detailed Analysis of Spatial–Temporal Variability of Rainfall Erosivity and Erosivity Density in the Central and Southern Pannonian Basin

Estimation of rainfall erosivity (RE) and erosivity density (ED) is essential for understanding the complex relationships between hydrological and soil erosion processes. The main objective of this study is to assess the spatial–temporal trends and variability of the RE and ED in the central and southern Pannonian Basin by using station observations and gridded datasets. To assess RE and ED, precipitation data for 14 meteorological stations, 225 grid points. and an erosion model consisting of daily, monthly, seasonal, and annual rainfall for the period of 1961–2014 were used. Annual RE and ED based on station data match spatially variable patterns of precipitation, with higher values in the southwest (2100 MJ·mm·ha−1·h−1) and southeast (1650 MJ·mm·ha−1·h−1) of the study area, but minimal values in the northern part (700 MJ·mm·ha−1·h−1). On the other hand, gridded datasets display more detailed RE and ED spatial–temporal variability, with the values ranging from 250 to 2800 MJ·mm·ha−1·h−1. The identified trends are showing increasing values of RE (ranging between 0.20 and 21.17 MJ·mm·ha−1·h−1) and ED (ranging between 0.01 and 0.03 MJ·ha−1·h−1) at the annual level. This tendency is also observed for autumn RE (from 5.55 to 0.37 MJ·mm·ha−1·h−1) and ED (from 0.05 to 0.01 MJ·ha−1·h−1), as for spring RE (from 1.00 to 0.01 MJ·mm·ha−1·h−1) and ED (from 0.04 to 0.01 MJ·ha−1·h−1), due to the influence of the large-scale processes of climate variability, with North Atlantic Oscillation (NAO) being the most prominent. These increases may cause a transition to a higher erosive class in the future, thus raising concerns about this type of hydro-meteorological hazard in this part of the Pannonian Basin. The present analysis identifies seasons and places of greatest erosion risk, which is the starting point for implementing suitable mitigation measures at local to regional scales.

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Spatial and Temporal Variability in Rainfall Erosivity Under Alpine Climate: A Slovenian Case Study Using Optical Disdrometer Data

Frontiers in Environmental Science ◽

10.3389/fenvs.2021.735492 ◽

2021 ◽

Vol 9 ◽

Author(s):

Nejc Bezak ◽

Sašo Petan ◽

Matjaž Mikoš

Keyword(s):

Temporal Variability ◽

Large Scale ◽

Annual Rainfall ◽

Mean Annual Precipitation ◽

Rainfall Erosivity ◽

Spatial And Temporal Variability ◽

Strongly Correlated ◽

Erosion Rates ◽

Precipitation Events

Rainfall erosivity is one of the most important parameters that influence soil erosion rates. It is characterized by a large spatial and temporal variability. For example, in Slovenia, which covers around 20,000 km2, the annual rainfall erosivity ranges from less than 1,000 MJ mm ha−1 h−1 to more than 10,000 MJ mm ha−1 h−1. Drop size distribution (DSD) data are needed to investigate rainfall erosivity characteristics. More than 2 years of DSD measurements using optical disdrometers located at six stations in Slovenia were used to investigate the spatial and temporal variability in rainfall erosivity in Slovenia. Experimental results have indicated that elevation is a poor predictor of rainfall erosivity and that erosivity is more strongly correlated to the mean annual precipitation. Approximately 90% of the total kinetic energy (KE) was accounted for in about 35% of 1 min disdrometer data. The highest 1 min intensities (I) and consequently also KE values were measured in summer followed by autumn and spring. The local KE-I equation yielded an acceptable fit to the measured data in case of all six stations. The relatively large percentage of 1 min rainfall intensities above 5 mm/h can at least partially explain some very high annual rainfall erosivity values (i.e., near or above 10,000 MJ mm ha−1 h−1). Convective and large-scale precipitation events also result in various rainfall erosivity characteristics. The station microlocation and wind impacts in case of some stations yielded relatively large differences between the data measured using the optical disdrometer and the pluviograph. Preliminary conclusions have been gathered, but further measurements are needed to get even better insight into spatial and temporal variability in rainfall erosivity under Alpine climate in Slovenia.

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Assessing Soil Loss by Water Erosion in a Typical Mediterranean Ecosystem of Northern Greece under Current and Future Rainfall Erosivity

Water ◽

10.3390/w13152002 ◽

2021 ◽

Vol 13 (15) ◽

pp. 2002

Author(s):

Stefanos Stefanidis ◽

Vasileios Alexandridis ◽

Chrysoula Chatzichristaki ◽

Panagiotis Stefanidis

Keyword(s):

Open Source ◽

Soil Loss ◽

Renewable Resource ◽

Mitigation Strategies ◽

Mitigation Measures ◽

Mediterranean Ecosystem ◽

Rainfall Erosivity ◽

Negative Consequences ◽

Northern Greece ◽

Erosion Risk

Soil is a non-renewable resource essential for life existence. During the last decades it has been threatened by accelerating erosion with negative consequences for the environment and the economy. The aim of the current study was to assess soil loss changes in a typical Mediterranean ecosystem of Northern Greece, under climate change. To this end, freely available geospatial data was collected and processed using open-source software package. The widespread RUSLE empirical erosion model was applied to estimate soil loss. Current and future rainfall erosivity were derived from a national scale study considering average weather conditions and RCMs outputs for the medium Representative Concentration Pathway scenario (RCP4.5). Results showed that average rainfall erosivity (R-Factor) was 508.85 MJ mm ha h−1 y−1 while the K-factor ranged from 0.0008 to 0.05 t ha h ha−1 MJ−1 mm−1 and LS-factor reached 60.51. Respectively, C-factor ranged from 0.01 to 0.91 and P-factor ranged from 0.42 to 1. The estimated potential soil loss rates will remain stable for the near future period (2021–2050), while an increase of approximately 9% is expected by the end of the 21th century (2071–2100). The results suggest that appropriate erosion mitigation strategies should be applied to reduce erosion risk. Subsequently, appropriate mitigation measures per Land Use/Land Cover (LULC) categories are proposed. It is worth noting that the proposed methodology has a high degree of transferability as it is based on open-source data.

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Comparison of the Spatial Wind Erosion Patterns of Erosion Risk Mapping and Quantitative Modeling in Eastern Austria

Land ◽

10.3390/land10090974 ◽

2021 ◽

Vol 10 (9) ◽

pp. 974

Author(s):

Simon Scheper ◽

Thomas Weninger ◽

Barbara Kitzler ◽

Lenka Lackóová ◽

Wim Cornelis ◽

...

Keyword(s):

Soil Loss ◽

Wind Erosion ◽

Large Scale ◽

Pannonian Basin ◽

Target Area ◽

Erosion Risk ◽

Additional Information ◽

Weather Factor ◽

Not At Risk ◽

Erosion Equation

Various large-scale risk maps show that the eastern part of Austria, in particular the Pannonian Basin, is one of the regions in Europe most vulnerable to wind erosion. However, comprehensive assessments of the severity and the extent of wind erosion risk are still lacking for this region. This study aimed to prove the results of large-scale maps by developing high-resolution maps of wind erosion risk for the target area. For this, we applied a qualitative soil erosion assessment (DIN 19706) with lower data requirements and a more data-demanding revised wind erosion equation (RWEQ) within a GIS application to evaluate the process of assessing wind erosion risk. Both models defined similar risk areas, although the assignment of severity classes differed. Most agricultural fields in the study area were classified as not at risk to wind erosion (DIN 19706), whereas the mean annual soil loss rate modeled by RWEQ was 3.7 t ha−1 yr−1. August was the month with the highest modeled soil loss (average of 0.49 t ha−1 month−1), due to a low percentage of vegetation cover and a relatively high weather factor combining wind speed and soil moisture effects. Based on the results, DIN 19706 is suitable for a general classification of wind erosion-prone areas, while RWEQ can derive additional information such as seasonal distribution and soil loss rates besides the spatial extents of wind erosion.

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A Comparison of Spatial Interpolation Models for Mapping Rainfall Erosivity on China Mainland

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.518-523.4489 ◽

2012 ◽

Vol 518-523 ◽

pp. 4489-4495

Author(s):

Liang Ma ◽

Chang Qing Zuo

Keyword(s):

Water Conservation ◽

Spatial Interpolation ◽

Large Scale ◽

Annual Rainfall ◽

Rainfall Erosivity ◽

Daily Precipitation Data ◽

Distance Weighting ◽

China Mainland ◽

Precipitation Changes ◽

Inverse Distance

Rainfall erosivity is an essential factor to reveal the response of water erosion to precipitation changes, and its spatial variation reveals erosion regional difference and water conservation regionalization. In this research, average annual rainfall erosivity in 1951 -2008 on China mainland is calculated through daily precipitation data from 711 meteorological stations. Precisions of 29 spatial interpolation models are quantitative compared including inverse distance weighting (IDW), radial basis function (RBF), kriging, cokriging (CK) and thin plate smoothing spline (TPS). Three variables cubic TPS is confirmed the optimum spatial interpolation model to rainfall erosivity on a large scale.

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Rainfall Erosivity in Soil Erosion Processes

Water ◽

10.3390/w12030722 ◽

2020 ◽

Vol 12 (3) ◽

pp. 722

Author(s):

Gianni Bellocchi ◽

Nazzareno Diodato

Keyword(s):

Soil Erosion ◽

Construction Projects ◽

Water Resource Management ◽

Large Scale ◽

Rainfall Erosivity ◽

Special Issue ◽

Environmental Consequences ◽

Erosion Processes ◽

Natural Rainfall ◽

Raindrop Energy

Regional studies on the erosive power of rainfall patterns are still limited and the actual impacts that may follow on erosional and sedimentation processes are poorly understood. Given the several interrelated challenges of environmental management, it is also not always unclear what is relevant for the development of adaptive and integrated approaches facilitating sustainable water resource management. This editorial introduces the Special Issue entitled “Rainfall Erosivity in Soil Erosion Processes”, which offers options to fill some of these gaps. Three studies performed in China and Central Asia (by Duulatov et al., Water 2019, 11, 897, Xu et al., 2019, 11, 2429, Gu et al. 2020, 12, 200) show that the erosion potential of rainfall is increasing in this region, driving social, economic, and environmental consequences. In the same region (the Weibei Plateau in China), Fu et al. (Water 2019, 11, 1514) assessed the effect of raindrop energy on the splash distance and particle size distribution of aggregate splash erosion. In the Mediterranean, updated estimates of current and future rainfall erosivity for Greece are provided by Vantas et al. (Water 2020, 12, 687), while Diodato and Bellocchi (Water 2019, 11, 2306) reconstructed and investigated seasonal net erosion in an Italian catchment using parsimonious modelling. Then, this Special Issue includes two technologically oriented articles by Ricks at al. The first (Water 2019, 11, 2386) evaluated a large-scale rainfall simulator design to simulate rainfall with characteristics similar to natural rainfall. The data provided contribute to the information that may be useful for the government’s decision making when considering landscape changes caused by variations in the intensity of a rainfall event. The second article (Water 2020, 12, 515) illustrated a laboratory-scale test of mulching methods to protect against the discharge of sediment-laden stormwater from active construction sites (e.g., highway construction projects).

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Less rain and rainy days - lessons from 45 years of rainfall data (1971 to 2015) in the Kathmandu Valley, Nepal

10.21203/rs.3.rs-167685/v1 ◽

2021 ◽

Author(s):

Rajaram Prajapati ◽

Rocky Talchabhadel ◽

Priya Silwal ◽

Surabhi Upadhyay ◽

Brandon Ertis ◽

...

Keyword(s):

Temporal Variability ◽

Temporal Trends ◽

Daily Rainfall ◽

Rainfall Data ◽

Annual Rainfall ◽

Kathmandu Valley ◽

Light Rain ◽

Mk Test ◽

Spatio Temporal ◽

Rainy Days

Abstract Understanding spatio-temporal variability in rainfall patterns is crucial for evaluating water balances needed for water resources planning and management. This paper investigates spatio-temporal variability in rainfall and assesses the frequency of daily rainfall observations from seven stations in the Kathmandu Valley, Nepal, from 1971–2015. Daily rainfall totals were classified into five classes, namely, A (light rain, daily rainfall < 10 mm in a day), B (between 10–50 mm), C (between 50–100 mm), D (between 100–150 mm) and E (> 150 mm). The relationship between daily rainfall and rainfall frequency of various rainfall rate classes were analysed. Kriging method was used for interpolation in interpreting seasonal and annual rainfall data and spatial maps were generated using QGIS. The Mann-Kendall (MK) test was performed to determine the temporal trends and Theil-Sen’s (TS) slope estimator was used in quantifying the magnitude of trends. Mountain stations showed a decreasing trend in rainfall for all seasons, ranging from − 8.4 mm/year at Sankhu to -21.8 mm/year at Thankot, whereas, a mixed pattern was found on the Valley floor. Mean annual rainfall in the Valley was 1610 mm. Both annual rainfall and the number of rainy days decreased in the Kathmandu Valley over the study period. The study indicated a significant reduction in rainfall after 2000. Since springs and shallow groundwater are the primary sources of water supply for residents in the Kathmandu Valley, it is apparent that decreasing rainfall will have (and is already having) an adverse impact on domestic, industrial, and agricultural water supplies, and the livelihoods of people.

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Post-fire Soil Erosion Risk in Portugal– Prediction, Validation and Uncertainties of a Nation-wide MMF Application

10.21203/rs.3.rs-776845/v1 ◽

2021 ◽

Author(s):

J. Parente ◽

A. Girona-García ◽

A.R. Lopes ◽

J.J. Keizer ◽

D.C.S. Vieira

Keyword(s):

Soil Erosion ◽

Climate Extremes ◽

Mitigation Measures ◽

Erosion Risk ◽

Soil Erosion Risk ◽

Erosion Processes ◽

Mainland Portugal ◽

Independent Field ◽

Emergency Stabilization ◽

Semi Empirical

Abstract Wildfires are a recurrent and increasing threat in mainland Portugal, where over 4,5 million hectares of forests and scrublands have burned over the last 38 years. These fire-affected landscapes have suffered an intensification of soil erosion processes, which can negatively affect soil carbon storage, reduce fertility, forest productivity, and become a source of pollutants. The main objective of the present study is to produce a post-fire soil erosion risk map for the forest and scrubland areas in Mainland Portugal and assess its reliability. To this end, the semi-empirical Morgan–Morgan–Finney erosion model was used to assess the potential post-fire soil erosion according to distinct scenarios (burn severity and climate), and the accuracy of the predictions was verified by an uncertainty analysis and validated against independent field datasets. The proposed approach successfully allowed mapping post-fire soil erosion in Portugal and identified the areas with higher post-fire erosion risk for past and future climate extremes. The outcomes of this study comprise a set of tools to help forest managers in their decision-making for post-fire emergency stabilization, ensuring the adequate selection and implementation of mitigation measures to minimize the economic and environmental losses caused by fire-enhanced soil erosion.

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Post-fire soil erosion risk map in Portugal: prediction and validation

10.5194/egusphere-egu21-7936 ◽

2021 ◽

Author(s):

Joana Parente ◽

Ana Lopes ◽

Antonio Girona-García ◽

Marta Basso ◽

Diana Vieira

Keyword(s):

Soil Erosion ◽

Science And Technology ◽

Mitigation Measures ◽

Research Centre ◽

Joint Research ◽

Erosion Risk ◽

Soil Erosion Risk ◽

Erosion Processes ◽

Mainland Portugal ◽

Forest Managers

Wildfires are a recurrent and increasing threat in Mainland Portugal, where over 4,500 thousand hectares of forests and shrublands have burned in the last 38 years. Landscapes affected by those wildfires have suffered an increase of soil erosion processes, which can negatively affect soil carbon storage, reduce fertility, forest productivity, and become a source of pollutants. Taking these in mind, the main objective of this study is to offer a ground base of post-fire soil erosion risk determination for Mainland Portugal, which will provide a set of tools to help forest managers in the post-fire decision-making, and therefore adequately implement mitigation measures to prevent such impacts.Post-fire soil erosion was assessed by the applying the semi-empirical soil erosion model Revised Morgan&#8211;Morgan&#8211;Finney(Morgan, 2001), to the entire Portuguese forest and shrubland areas according to distinct scenarios (burn severity, climate). This study benefits from the use of several reliable official datasets of soil characteristics, as also from several model calibrations and validation with field data collected in the last 10 years for the 1st and 2nd post-fire years. The obtained soil erosion map identifies areas with higher post-fire erosion risk in the past and for future climate extremes. Findings of this study will be a valuable tool for forest managers to minimize the economic and environmental losses of vegetation fires in Portugal.AcknowledgementsThis work was supported and conducted in the framework of the FEMME project (PCIF/MPG/0019/2017) funded by FCT - Portuguese Foundation for Science and Technology. The study was also supported by: i) National Funds by FCT - Portuguese Foundation for Science and Technology, under the project UIDB/04033/2020; and, ii) National Funds by FCT - Portuguese Foundation for Science and Technology, under the project UID/AMB/50017/2019. Data were provided by the European Forest Fire Information System &#8211; EFFIS (http://effis.jrc.ec.europa.eu) of the European Commission Joint Research Centre.

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Assessing the sources of uncertainty associated with the calculation of rainfall kinetic energy and erosivity – application to the Upper Llobregat Basin, NE Spain

Hydrology and Earth System Sciences ◽

10.5194/hess-15-679-2011 ◽

2011 ◽

Vol 15 (3) ◽

pp. 679-688 ◽

Cited By ~ 17

Author(s):

G. Catari ◽

J. Latron ◽

F. Gallart

Keyword(s):

Kinetic Energy ◽

Temporal Variability ◽

Rainfall Intensity ◽

Spatial Scales ◽

Annual Rainfall ◽

Rainfall Erosivity ◽

Sources Of Uncertainty ◽

Eastern Pyrenees ◽

Erosion Modelling

Abstract. The diverse sources of uncertainty associated with the calculation of rainfall kinetic energy and rainfall erosivity, calculated from precipitation data, were investigated at a range of temporal and spatial scales in a mountainous river basin (504 km2) in the south-eastern Pyrenees. The sources of uncertainty analysed included both methodological and local sources of uncertainty and were (i) tipping-bucket rainfall gauge instrumental errors, (ii) the efficiency of the customary equation used to derive rainfall kinetic energy from intensity, (iii) the efficiency of the regressions obtained between daily precipitation and rainfall erosivity, (iv) the temporal variability of annual rainfall erosivity values, and the spatial variability of (v) annual rainfall erosivity values and (vi) long-term erosivity values. The differentiation between systematic (accuracy) and random (precision) errors was taken into account in diverse steps of the analysis. The results showed that the uncertainty associated with the calculation of rainfall kinetic energy from rainfall intensity at the event and station scales was as high as 30%, because of insufficient information on rainfall drop size distribution. This methodological limitation must be taken into account for experimental or modelling purposes when rainfall kinetic energy is derived solely from rainfall intensity data. For longer temporal scales, the relevance of this source of uncertainty remained high if low variability in the types of rain was supposed. Temporal variability of precipitation at wider spatial scales was the main source of uncertainty when rainfall erosivity was calculated on an annual basis, whereas the uncertainty associated with long-term erosivity was rather low and less important than the uncertainty associated with other model factors such as those in the RUSLE, when operationally used for long-term soil erosion modelling.

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Seasonal Dynamics of Rainfall Erosivity in Switzerland

10.5194/hess-2016-208 ◽

2016 ◽

Author(s):

Simon Schmidt ◽

Christine Alewell ◽

Panos Panagos ◽

Katrin Meusburger

Keyword(s):

Kriging Interpolation ◽

Annual Rainfall ◽

Rainfall Erosivity ◽

Monthly Precipitation ◽

Erosion Risk ◽

Explanatory Variables ◽

R Factor ◽

Monthly Pattern ◽

June July ◽

Leave One Out

Abstract. One major controlling factor of water erosion is rainfall erosivity, which is quantified by the kinetic energy of a rainfall event and its maximum 30-min intensity. Rainfall erosivity is often expressed as R-factor in soil erosion risk models like the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). As rainfall erosivity is closely correlated with dynamic rainfall amount and intensity, the rainfall erosivity of Switzerland can be expected to have a characteristic regional and seasonal dynamic throughout the year. This intra-annual variability was mapped by a monthly modelling approach to assess simultaneously spatial and monthly pattern of rainfall erosivity. So far only national seasonal means and regional annual means exist for Switzerland. We used a network of 87 precipitation gauging stations with a 10-minute temporal resolution to calculate long-term monthly mean R-factors. Stepwise regression and Leave-one-out cross-validation (LOOCV) were used to select spatial covariates which explain the spatial and temporal pattern of the R-factor for each month across Switzerland. The monthly R-factor is mapped by its specific regression equation and the ordinary kriging interpolation of its residuals (Regression-Kriging). As covariates, a variety of precipitation indicator data has been included like snow depths, a combination product of hourly precipitation measurements and radar observations (CombiPrecip), daily alpine precipitation (EURO4M-APGD) and monthly precipitation sums (RhiresM). Topographic parameters (elevation, slope) were also significant explanatory variables for single months. The comparison of the 12 monthly rainfall erosivity maps showed a distinct seasonality with highest rainfall erosivity in summer (June, July, and August) influenced by intense rainfall events. Winter months have lowest rainfall erosivity. A proportion of 62 % of the total annual rainfall erosivity is identified within four months only (June to September). Highest erosion risk can be expected for July where not only rainfall erosivity but also erosivity density is high. Additionally to the intra-annual temporal regime, a spatial variability of this seasonality was detectable between different regions of Switzerland. The assessment of the dynamic behavior of the R-factor is valuable for the identification of susceptible seasons and regions.

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