An integrated modeling approach for estimating monthly global rainfall erosivity

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: April 8, 2024

Abstract Modeling monthly rainfall erosivity is vital to the optimization of measures control soil erosion. Rain gauge data combined with satellite observations can aid in enhancing estimations. Here, we presented a framework which utilized Geographically Weighted Regression approach model global erosivity. The integrates long-term (2001–2020) mean annual estimates from IMERG (Global Precipitation Measurement (GPM) mission’s Integrated Multi-satellitE Retrievals for GPM) station GloREDa Rainfall Erosivity Database, n = 3,286 stations). merged was disaggregated into values based on fractions derived original data. Global distinctly seasonal; peaked at ~ 200 MJ mm ha −1 h month June–August over Northern Hemisphere and 700 December–February Southern Hemisphere, contributing 60% large areas each hemisphere. 4 times higher during most erosive months than least (December–February respectively). latitudinal distributions seasonal were highly heterogeneous, tropics showing greatest intra-annual variability particularly high within 10–30° latitude both hemispheres. maps be used improving spatiotemporal modeling erosion planning conservation measures.

Language: Английский

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Response mechanism of black soil structure to compound erosion forces in sloping farmland, Northeast China

Soil and Tillage Research, Journal Year: 2024, Volume and Issue: 240, P. 106103 - 106103

Published: April 3, 2024

Language: Английский

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An assessment of global land susceptibility to wind erosion based on deep-active learning modelling and interpretation techniques

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Aug. 15, 2024

Spatial accurate mapping of land susceptibility to wind erosion is necessary mitigate its destructive consequences. In this research, for the first time, we developed a novel methodology based on deep learning (DL) and active (AL) models, their combination (e.g., recurrent neural network (RNN), RNN-AL, gated units (GRU), GRU-AL) three interpretation techniques synergy matrix, SHapley Additive exPlanations (SHAP) decision plot, accumulated local effects (ALE) plot) map global erosion. respect, 13 variables were explored as controlling factors erosion, eight them speed, topsoil carbon content, clay elevation, gravel fragment, precipitation, sand content soil moisture) selected important via Harris Hawk Optimization (HHO) feature selection algorithm. The four models applied performance was assessed by measures consisting area under receiver operating characteristic (AUROC) curve, cumulative gain Kolmogorov Smirnov (KS) statistic plots. results revealed that GRU-AL model considered most accurate, revealing 38.5%, 12.6%, 10.3%, 12.5% 26.1% lands are grouped at very low, moderate, high classes hazard, respectively. Interpretation interpret contribution impact input model's output. Synergy plot exhibited with DEM moisture predictions. ALE showed precipitation had negative feedback prediction Based SHAP presented highest Results highlighted new regions latitudes (southern Greenland coast, hotspots in Alaska Siberia), which

Language: Английский

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An assessment of anticipated future changes in water erosion dynamics under climate and land use change scenarios in South Asia

Journal of Hydrology, Journal Year: 2024, Volume and Issue: 637, P. 131341 - 131341

Published: May 13, 2024

Language: Английский

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The global significance of post fire soil erosion

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: March 25, 2025

Wildfires affect land surface and post-fire geomorphological activity worldwide, increasing runoff soil erosion. Here, we present a global assessment of erosion, considering cumulative wildfire driven changes over the last two decades. Stemmed from largest database on wildfires occurrence fire severity in globe, this study estimates trends post erosion together with recovery those burned landscapes. Our results show that when multiple events, accounts for 8.1 ± 0.72 Pg annually, representing 19% budget, additional 5.1 0.56 annually comparison to pre-fire conditions. Moreover, attributed first year represents 31% total whereas remaining share can be previous occurrences. In what concerns spatial distribution, Africa is continent impacted most terms given its significantly larger area. The illustrate magnitude globally, therefore support management actions towards mitigation restoration affected areas, policies Land Degradation Neutrality.

Language: Английский

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Soil loss due to crop harvesting in highly mechanized agriculture: A case study of sugar beet harvest in northern Germany

Soil and Tillage Research, Journal Year: 2024, Volume and Issue: 242, P. 106144 - 106144

Published: May 15, 2024

Soil loss due to crop harvesting (SLCH) is a globally occurring and underestimated process that promotes soil degradation. Despite its negative effects on functionality fertility SLCH has received comparatively little scientific attention date. In Europe, sugar beets hold particular significance high production rates, while research in commercial mechanized farming of lacking. The aim this study measure for including nutrient SOC losses using typical state the art harvesters compare values estimated provided by beet factories. addition, we tried identify variables influence SLCH. Therefore, samples were collected 14 sampling sites over three-year period Northern Germany dependent different characteristics, properties weather conditions. results indicate 0.064 kg per harvested (SLCHspec) average, which corresponds 5.7 Mg ha-1 harvest-1 (SLCHcrop). These numbers are higher than former comparable studies but also about 83.3% Additionally, amounts considerably varied between years fields, within fields. most influential water content (SWC) clay content, observed impact differently relation SWC. Moreover, can lead significant losses, latter resulting direct costs farmers 18–34.4 € harvest-1. confirm importance considering degradation analyses estimations need models spatially assess from field global scales. This important explore conservation measures strategies reduce ongoing especially highly agriculture.

Language: Английский

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Utilizing geodetectors to identify conditioning factors for gully erosion risk in the black soil region of Northeast China

International Soil and Water Conservation Research, Journal Year: 2024, Volume and Issue: 12(4), P. 808 - 827

Published: July 31, 2024

In the black soil region of Northeast China, issue gully erosion persists as a significant threat, resulting in extensive damage to farmland, severe degradation soil, and decreased productivity. It is therefore utmost importance accurately identify areas that are susceptible effectively prevent control its negative impact. This study tried utilize geographical detectors (geodetectors) means factors contribute distribution gullies assess risk (GER) five catchments within region, with ranging from approximately 80 km2 200 km2. By employing geodetectors method, fourteen geo-environmental were analyzed, including topographic attributes (such aspect, catchment area, convergence index, elevation, plan curvature, profile slope length, slope, stream power wetness index), channel network distance, vegetation index (NDVI EVI), well land use/land cover (LULC). The modeling GER was conducted using random forest algorithm (RFA). Out examined factors, only subset, comprising less than or equal 50%, demonstrated (p < 0.05) influence on spatial gullies. These selected sufficient assessing GER, LULC (mean q-value=0.270) elevation q-value=0.113) identified two most important factors. Furthermore, RFA exhibited satisfactory performance across all catchments, achieving AUC values 0.712 0.933 = 0.863) predicting GER. Overall, classified into high, moderate, low, very low-risk levels, representing 9.67% 15.95%, 19.28% 26.08%, 24.59% 30.55%, 30.54% 39.08% total respectively. Importantly, positive linear relationship (r2 0.722, p observed between proportion cropland area occurrence high-level Although primary levels categorized low high-risk exceeded existing coverage (0.34% 3.69%). findings highlight substantial potential for underscore necessity intensified efforts prevention China.

Language: Английский

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Evaluation of the effect of the mixture of soil textural compounds on the strength of the soil crust: Coding and optimization

Results in Engineering, Journal Year: 2024, Volume and Issue: 22, P. 101988 - 101988

Published: March 15, 2024

Soil is one of the most important parts an ecosystem. If soil particles are conserved in a basin, it will be possible for ecosystem to survive. In this study, clay, silt and sand were selected as conservation compounds strength wind erosion tests performed assess crust these compounds. Moreover, due lack clear relationships between parameters, research aims identify correlations among them. These coded at specific intervals terms application rate then used inputs Design Expert software. After 48 h, penetrometer test was on layers. The results showed that based significant simulation laboratory data, best models 2FI mathematical model (strength test) quadratic (wind erosion). indicate values R2 Adj-R2 0.8994 0.9311 respectively, signal-to-noise ratio 21.254. interaction effect treatments clay studied increased penetration layer. Also, with increase content, first decreased, trend directly related characteristics clay. Further, accuracy = 0.9561. According optimization results, maximum resistance occurred 15 g each silt, sand. However, remained constant when content increased. This study suggests compound creates very different behavior formation can many projects local global scale.

Language: Английский

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Soil erosion modelling of degraded semi-arid highlands in Northern Ethiopia

Hydrological Sciences Journal, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 22, 2024

Soil erosion by water is one of the major threatening factors to agricultural production and food security. USPED (Unit Stream Power Erosion Deposition) model was applied analyse spatial distribution deposition rates in northern Ethiopia. The mean generated from area totals 12.4 t ha−1 yr−1 7.3 yr−1, respectively. About 57% lies under stable severity classes, while its 14% faces moderate very severe erosions. Slight slight accounted for ca. 10% total area. Less than 0.2% experienced deposition, whereas 7.1%, 6.8% 5.3% moderate, depositions, Topography land use have substantial implications erosion/deposition rates. has good predictive performance quantify soil accordingly can help identify hotspot areas.

Language: Английский

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Unveiling the Accuracy of New-Generation Satellite Rainfall Estimates across Bolivia’s Complex Terrain

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(12), P. 2211 - 2211

Published: June 18, 2024

This study evaluated the accuracy of two new generation satellite rainfall estimates (SREs): Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) and Integrated Multi-satellite Retrieval for GPM (IMERG) over Bolivia’s complex terrain. These SREs were compared against from rain gauge measurements on a point-to-pixel basis period 2002–2020. The evaluation was performed across three regions distinct topographical settings: Altiplano (Highland), Valles (Midland), Llanos (Lowland). IMERG exhibited better in detection than CHIRPS, highest skills observed Highland region. However, IMERG’s higher skill countered by its false alarm ratio. CHIRPS provided more accurate estimation amounts regions, exhibiting low random errors relative biases below 10%. tended to overestimate amounts, marked overestimation up 75% Bias decomposition revealed that high bias contributed rainfall. We showcase utility long-term investigate spatio-temporal patterns meteorological drought occurrence Bolivia. findings this offer valuable insights choosing appropriate informed decision-making, particularly topography lacking reliable data.

Language: Английский

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