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The experimental conditions in a gravimetric analysis should be optimized to maximize the particle size and purity of the obtained precipitate. Ideally, the concentration of the precipitating reagent should be low with effective stirring to maintain low relative supersaturation for the growth of large crystals. In homogeneous precipitation, the precipitant is slowly generated by a chemical reaction in the solution to avoid local reagent excesses. For example, urea decomposes gradually to...
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Laboratory and Field Protocol for Estimating Sheet Erosion Rates from Dendrogeomorphology
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Rainfall erosivity in Europe.

Panos Panagos1, Cristiano Ballabio1, Pasquale Borrelli1

  • 1European Commission, Joint Research Centre, Institute for Environment and Sustainability, Via E. Fermi 2749, I-21027 Ispra, VA, Italy.

The Science of the Total Environment
|January 27, 2015
PubMed
Summary
This summary is machine-generated.

This study maps European rainfall erosivity using high-resolution data, revealing highest soil erosion risk in Mediterranean and alpine areas. Findings inform soil erosion and flood risk management across the EU.

Keywords:
Erosivity densityModellingPrecipitationR-factorRUSLERainfall intensityRainstormSoil erosion

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Area of Science:

  • Environmental Science
  • Hydrology
  • Soil Science

Background:

  • Soil erosion is primarily driven by rainfall erosivity, quantified by the R-factor in the USLE/RUSLE models.
  • Continental-scale erosion modeling is hampered by low-resolution rainfall data (daily/monthly averages).
  • Accurate R-factor assessment requires high temporal resolution precipitation data (5-60 min).

Purpose of the Study:

  • To assess and map rainfall erosivity across Europe using the RUSLE R-factor.
  • To create a high-resolution (1 km) European rainfall erosivity map.
  • To identify regions with high soil erosion and flood risk based on erosivity density.

Main Methods:

  • Collected precipitation data from 1541 stations across EU Member States and Switzerland (5-60 min resolution).
  • Normalized R-factor values to 30-min resolution using linear regression.
  • Interpolated R-factor station data using Gaussian Process Regression (GPR) with climatic, elevation, and spatial covariates.

Main Results:

  • Calculated a mean R-factor of 722 MJ mm ha⁻¹ h⁻¹ yr⁻¹ for the EU and Switzerland.
  • Identified highest R-factor values (>1000 MJ mm ha⁻¹ h⁻¹ yr⁻¹) in Mediterranean and alpine regions.
  • Observed highest erosivity density in Mediterranean regions, indicating elevated erosion and flood risk.

Conclusions:

  • High-resolution rainfall data significantly improves R-factor assessment for soil erosion modeling.
  • The generated European rainfall erosivity map provides crucial data for environmental management.
  • Mediterranean regions face a disproportionately high risk of soil erosion and associated floods.