scholarly journals Reconstruction of Seasonal Net Erosion in a Mediterranean Landscape (Alento River Basin, Southern Italy) over the Past Five Decades

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2306 ◽  
Author(s):  
Nazzareno Diodato ◽  
Gianni Bellocchi
Keyword(s):  
Soil Erosion ◽  
River Basin ◽  
Rainfall Erosivity ◽  
Monthly Basis ◽  
Antecedent Soil Moisture ◽  
Rainfall Events ◽  
Sediment Yields ◽  
Convective Systems ◽  
Mesoscale Convective ◽  
Basic Scale

In the low Mediterranean basin, late spring and autumn rainfall events have the potential to increase discharge and transport substantial amounts of sediment soil (that is, the net soil erosion from a watershed). For the Alento River Basin (ARB), located in the low Tyrrhenian coast of Italy, we estimated changes of net erosion as dependent on the seasonality of antecedent soil moisture and its control on rainfall-runoff and erosivity. Based on rainfall and runoff erosivity sub-models, we developed a simplified model to evaluate basin-wide sediment yields on a monthly basis by upscaling point rainfall input. For the period 1951–2018, the reconstruction of a time series of monthly net erosion data indicated a decreasing trend of the sediment yield after 1991. Revegetation and land abandonment that occurred in the last decades can explain such a decrease of net erosion, which occurred even when rainfall erosivity increased. This response, obtained at the basic scale, does not exclude that rapidly developing mesoscale convective systems, typically responsible for the heaviest and most destructive rainfall events in the ARB, can affect small catchments, which are the most vulnerable systems to storm-driven flash floods and soil erosion hazards during soil tilling in spring and at beginning of autumn.

scholarly journals RUSLE Model Based Annual Soil Loss Quantification for Soil Erosion Protection in Fincha Catchment, Abay River Basin, Ethiopia.

2021 ◽  
Author(s):  
Habtamu Tamiru ◽  
Meseret Wagari
Keyword(s):  
Soil Erosion ◽  
River Basin ◽  
Soil Loss ◽  
Annual Rainfall ◽  
Rainfall Erosivity ◽  
Landsat 8 ◽  
Land Resources ◽  
Rusle Model ◽  
Factor C ◽  
Significant Factors

Abstract Background: The quantity of soil loss as a result of soil erosion is dramatically increasing in catchment where land resources management is very weak. The annual dramatic increment of the depletion of very important soil nutrients exposes the residents of this catchment to high expenses of money to use artificial fertilizers to increase the yield. This paper was conducted in Fincha Catchment where the soil is highly vulnerable to erosion, however, where such studies are not undertaken. This study uses Fincha catchment in Abay river basin as the study area to quantify the annual soil loss, where such studies are not undertaken, by implementing Revised Universal Soil Loss Equation (RUSLE) model developed in ArcGIS version 10.4. Results: Digital Elevation Model (12.5 x 12.5), LANDSAT 8 of Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS), Annual Rainfall of 10 stations (2010-2019) and soil maps of the catchment were used as input parameters to generate the significant factors. Rainfall erosivity factor (R), soil erodibility factor (K), cover and management factor (C), slope length and steepness factor (LS) and support practice factor (P) were used as soil loss quantification significant factors. It was found that the quantified average annual soil loss ranges from 0.0 to 76.5 t ha-1 yr-1 was obtained in the catchment. The area coverage of soil erosion severity with 55%, 35% and 10% as low to moderate, high and very high respectively were identified. Conclusion: Finally, it was concluded that having information about the spatial variability of soil loss severity map generated in the RUSLE model has a paramount role to alert land resources managers and all stakeholders in controlling the effects via the implementation of both structural and non-structural mitigations. The results of the RUSLE model can also be further considered along with the catchment for practical soil loss quantification that can help for protection practices.

scholarly journals Lightning and precipitation produced by severe weather systems over Belém, Brazil

2014 ◽  
Vol 29 (spe) ◽  
pp. 41-59 ◽  
Author(s):  
Wanda Maria do Nascimento Ribeiro ◽  
José Ricardo Santos Souza ◽  
Márcio Nirlando Gomes Lopes ◽  
Renata Kelen Cardoso Câmara ◽  
Edson José Paulino Rocha ◽  
...  
Keyword(s):  
Large Scale ◽  
Electric Activity ◽  
Weather Conditions ◽  
Rain Gauge ◽  
Mesoscale Convective Systems ◽  
Major Influence ◽  
Rainfall Events ◽  
Convective Systems ◽  
Mesoscale Convective ◽  
Cg Lightning

CG Lightning flashes events monitored by a LDN of the Amazon Protection System, which included 12 LPATS IV VAISALA sensors distributed over eastern Amazonia, were analyzed during four severe rainstorm occurrences in Belem-PA-Brazil, in the 2006-2007 period. These selected case studies referred to rainfall events, which produced more than 25 mm/hour, or more than 40 mm/ 2 hours of precipitation rate totals, registered by a tipping bucket automatic high-resolution rain gauge, located at 1º 47' 53" S and 48º 30' 16" W. Centered at this location, a 30 ,10 and 5 km radius circles were drawn by means of a geographic information system, and the data from lightning occurrences within this larger area, were set apart for analysis. During these severe storms the CG lightning events, occurred almost randomly over the surrounding defined circle, previously covered by mesoscale convective systems, for all cases studied. This work also showed that the interaction between large-scale and mesoscale weather conditions have a major influence on the intensity of the storms studied cases. In addition to the enhancement of the lightning and precipitation rates, the electric activity within the larger circles can precede the rainfall at central point of the areas

scholarly journals Estimating Rainfall Erosivity Factor Using Future Climate Projection in the Myjava Region (Slovakia)

2021 ◽  
Vol 24 (s1) ◽  
pp. 31-36
Author(s):  
Peter Valent ◽  
Roman Výleta
Keyword(s):  
Soil Erosion ◽  
Climate Models ◽  
Regional Climate ◽  
Multiple Linear Regression Model ◽  
Rain Gauge ◽  
Rainfall Erosivity ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
R Factor ◽  
Geostatistical Approach

Abstract Rainfall erosivity factor (R) of the USLE model is one of the most popular indicators of areas potentially susceptible to soil erosion. Its value is influenced by the number and intensity of extreme rainfall events. Since the regional climate models expect that the intensity of heavy rainfall events will increase in the future, the currently used R-factor values are expected to change as well. This study investigates possible changes in the values of R-factor due to climate change in the Myjava region in Slovakia that is severely affected by soil erosion. Two rain gauge stations with high-resolution 1-minute data were used to build a multiple linear regression model (r 2 = 0.98) between monthly EI 30 values and other monthly rainfall characteristics derived from low-resolution daily data. The model was used to estimate at-site R-values in 13 additional rain gauge stations homogeneously dispersed over the whole region for four periods (1981–2010, 2011–2040, 2041–2070, 2071–2100). The at-site estimates were used to create R-factor maps using a geostatistical approach. The results showed that the mean R-factor values in the region might change from 429 to as much as 520 MJ.mm.ha−1.h−1.yr−1 in the second half of the 21st century representing a 20.5% increase.

Soil Moisture Influence on the Incidence of Summer Mesoscale Convective Systems in the U.S. Great Plains

2021 ◽  
Author(s):  
Rachel Gaal ◽  
James L. Kinter
Keyword(s):  
Soil Moisture ◽  
Great Plains ◽  
Land Surface ◽  
Large Scale ◽  
Mesoscale Convective Systems ◽  
Antecedent Soil Moisture ◽  
Initiation Point ◽  
Convective Systems ◽  
Mesoscale Convective ◽  
The U.S

AbstractMesoscale convective systems (MCS) are known to develop under ideal conditions of temperature and humidity profiles and large-scale dynamic forcing. Recent work, however, has shown that summer MCS events can occur under weak synoptic forcing or even unfavorable large-scale environments. When baroclinic forcing is weak, convection may be triggered by anomalous conditions at the land surface. This work evaluates land surface conditions for summer MCS events forming in the U.S. Great Plains using an MCS database covering the contiguous United States east of the Rocky Mountains, in boreal summers 2004-2016. After isolating MCS cases where synoptic-scale influences are not the main driver of development (i.e. only non-squall line storms), antecedent soil moisture conditions are evaluated over two domain sizes (1.25° and 5° squares) centered on the mean position of the storm initiation. A negative correlation between soil moisture and MCS initiation is identified for the smaller domain, indicating that MCS events tend to be initiated over patches of anomalously dry soils of ~100-km scale, but not significantly so. For the larger domain, soil moisture heterogeneity, with anomalously dry soils (anomalously wet soils) located northeast (southwest) of the initiation point, is associated with MCS initiation. This finding is similar to previous results in the Sahel and Europe that suggest that induced meso-β circulations from surface heterogeneity can drive convection initiation.

scholarly journals Regional Characteristics of Extreme Rainfall Extracted from TRMM PR Measurements

2014 ◽  
Vol 27 (21) ◽  
pp. 8151-8169 ◽  
Author(s):  
Atsushi Hamada ◽  
Yuki Murayama ◽  
Yukari N. Takayabu
Keyword(s):  
Regional Differences ◽  
Tropical Rainfall Measuring Mission ◽  
Extreme Rainfall ◽  
Horizontal Resolution ◽  
Mesoscale Convective Systems ◽  
Extreme Rainfall Events ◽  
Near Surface ◽  
Rainfall Events ◽  
Convective Systems ◽  
Mesoscale Convective

Abstract Characteristics and global distribution of regional extreme rainfall are presented using 12 yr of the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) measurements. By considering each rainfall event as a set of contiguous PR rainy pixels, characteristic values for each event are obtained. Regional extreme rainfall events are defined as those in which maximum near-surface rainfall rates are higher than the corresponding 99.9th percentile on a 2.5° × 2.5° horizontal-resolution grid. The geographical distribution of extreme rainfall rates shows clear regional differences. The size and volumetric rainfall of extreme events also show clear regional differences. Extreme rainfall rates show good correlations with the corresponding rain-top heights and event sizes over oceans but marginal or no correlation over land. The time of maximum occurrence of extreme rainfall events tends to be during 0000–1200 LT over oceans, whereas it has a distinct afternoon peak over land. There are also clear seasonal differences in which the occurrence over land is largely coincident with insolation. Regional extreme rainfall is classified by extreme rainfall rate (intensity) and the corresponding event size (extensity). Regions of “intense and extensive” extreme rainfall are found mainly over oceans near coastal areas and are likely associated with tropical cyclones and convective systems associated with the establishment of monsoons. Regions of “intense but less extensive” extreme rainfall are distributed widely over land and maritime continents, probably related to afternoon showers and mesoscale convective systems. Regions of “extensive but less intense” extreme rainfall are found almost exclusively over oceans, likely associated with well-organized mesoscale convective systems and extratropical cyclones.

scholarly journals Atmospheric Rivers and Rainfall during NASA’s Iowa Flood Studies (IFloodS) Campaign*

2015 ◽  
Vol 17 (1) ◽  
pp. 257-271 ◽  
Author(s):  
Munir A. Nayak ◽  
Gabriele Villarini ◽  
A. Allen Bradley
Keyword(s):  
Stage Iv ◽  
Major Axis ◽  
Extratropical Cyclones ◽  
Rainfall Events ◽  
Atmospheric Rivers ◽  
Convective Systems ◽  
Central United States ◽  
Mesoscale Convective ◽  
The Tropics ◽  
Heavy Rainfall Events

Abstract Atmospheric rivers (ARs) play a major role in causing extreme precipitation and flooding over the central United States (e.g., Midwest floods of 1993 and 2008). The goal of this study is to characterize rainfall associated with ARs over this region during the Iowa Flood Studies (IFloodS) campaign that took place in April–June 2013. Total precipitation during IFloodS was among the five largest accumulations recorded since the mid-twentieth century over most of this region, with three of the heavy rainfall events associated with ARs. As a preliminary step, the authors evaluate how well different remote sensing–based precipitation products captured the rainfall associated with the ARs and find that stage IV is the product that shows the closest agreement to the reference data. Two of the three ARs during IFloodS occurred within extratropical cyclones, with the moist ascent associated with the presence of cold fronts. In the third AR, mesoscale convective systems resulted in intense rainfall at many locations. In all the three cases, the continued supply of warm water vapor from the tropics and subtropics helped sustain the convective systems. Most of the rainfall during these ARs was concentrated within ~100 km of the AR major axis, and this is the region where the rainfall amounts were highly positively correlated with the vapor transport intensity. Rainfall associated with ARs tends to be larger as these events mature over time. Although no major diurnal variation is detected in the AR occurrences, rainfall amounts during nocturnal ARs were higher than for ARs that occurred during the daytime.

The Relationship of Debris Flow Hazards and Rainfall Erosivity in the Bailong River Basin of Southern Gansu Province, China

2014 ◽  
Vol 1073-1076 ◽  
pp. 1614-1619
Author(s):  
Peng Zhang ◽  
He Ping Shu ◽  
Jin Zhu Ma ◽  
Gang Wang ◽  
Li Ming Tian
Keyword(s):  
Soil Erosion ◽  
River Basin ◽  
Debris Flows ◽  
Temporal Distribution ◽  
Gansu Province ◽  
Annual Precipitation ◽  
Annual Rainfall ◽  
Rainfall Erosivity ◽  
Erosive Rainfall ◽  
Bailong River Basin

Rainfall is one of the main factors that drive soil erosion, leading to environmental problems such as increased frequency and severity of debris flows, and ecosystem damage. Rainfall erosivity represents the potential of rainfall to cause soil erosion, and is determined by a combination of rainfall intensity. The spatial and temporal distribution of rainfall erosivity was analyzed to get its relationship with the debris flows in the Bailong River Basin in China's Gansu Province. The mean annual amount of erosive rainfall accounts for 36.0-47.1% of annual precipitation. The annual mean rainfall erosivity amounts to 798.8 MJ mm ha-1 h-1 yr-1 in the Bailong River Basin. A positive correlation between annual precipitation and annual rainfall erosivity was demonstrated at all 18 rainfall stations. However, further research is required to reveal the key factors that explain soil erosion and debris flows.

scholarly journals Early warm-season mesoscale convective systems dominate soil moisture–precipitation feedback for summer rainfall in central United States

2021 ◽  
Vol 118 (43) ◽  
pp. e2105260118
Author(s):  
Huancui Hu ◽  
L. Ruby Leung ◽  
Zhe Feng
Keyword(s):  
United States ◽  
Soil Moisture ◽  
Land Surface ◽  
Warm Season ◽  
Summer Rainfall ◽  
Mesoscale Convective Systems ◽  
Rainfall Events ◽  
Convective Systems ◽  
Central United States ◽  
Mesoscale Convective

Land–atmosphere interactions play an important role in summer rainfall in the central United States, where mesoscale convective systems (MCSs) contribute to 30 to 70% of warm-season precipitation. Previous studies of soil moisture–precipitation feedbacks focused on the total precipitation, confounding the distinct roles of rainfall from different convective storm types. Here, we investigate the soil moisture–precipitation feedbacks associated with MCS and non-MCS rainfall and their surface hydrological footprints using a unique combination of these rainfall events in observations and land surface simulations with numerical tracers to quantify soil moisture sourced from MCS and non-MCS rainfall. We find that early warm-season (April to June) MCS rainfall, which is characterized by higher intensity and larger area per storm, produces coherent mesoscale spatial heterogeneity in soil moisture that is important for initiating summer (July) afternoon rainfall dominated by non-MCS events. On the other hand, soil moisture sourced from both early warm-season MCS and non-MCS rainfall contributes to lower-level atmospheric moistening favorable for upscale growth of MCSs at night. However, soil moisture sourced from MCS rainfall contributes to July MCS rainfall with a longer lead time because with higher intensity, MCS rainfall percolates into deeper soil that has a longer memory. Therefore, early warm-season MCS rainfall dominates soil moisture–precipitation feedback. This motivates future studies to examine the contribution of early warm-season MCS rainfall and associated soil moisture anomalies to predictability of summer rainfall in the major agricultural region of the central United States and other continental regions frequented by MCSs.

scholarly journals Estimation of the Changes in the Rainfall Erosivity in Hungary

2016 ◽  
Vol 9 (3-4) ◽  
pp. 43-48 ◽  
Author(s):  
Gábor Mezősi ◽  
Teodóra Bata
Keyword(s):  
Soil Erosion ◽  
Rainfall Intensity ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Rainfall Erosivity ◽  
Precipitation Data ◽  
Rainfall Events ◽  
Long Run ◽  
Erosion Effect

Abstract According to the forecasts of numerous regional models (eg. REMO, ALADIN, PREGIS), the number of predicted rainfall events decreases, but they are not accompanied by considerably less precipitation. It represents an increase in rainfall intensity. It is logical to ask (if the limitations of the models make it possible) to what extent rainfall intensity is likely to change and where these changes are likely to occur in the long run. Rain intensity is considered to be one of the key causes of soil erosion. If we know which areas are affected by more intense rain erosion, we can identify the areas that are likely to be affected by stronger soil erosion, and we can also choose effective measures to reduce erosion. This information is necessary to achieve the neutral erosion effect as targeted by the EU. We collected the precipitation data of four stations every 30 minute between 2000 and 2013, and we calculated the estimated level of intensity characterizing the Carpathian Basin. Based on these data, we calculated the correlation of the measured data of intensity with the values of the MFI index (the correlation was 0.75). According to a combination of regional climate models, precipitation data could be estimated until 2100, and by calculating the statistical relationship between the previous correlation and this data sequence, we could estimate the spatial and temporal changes of rainfall intensity.

scholarly journals El-Niño southern oscillation and rainfall erosivity in the headwater region of the Grande River Basin, Southeast Brazil

2011 ◽  
Vol 8 (6) ◽  
pp. 10707-10738 ◽  
Author(s):  
C. R. Mello ◽  
L. D. Norton ◽  
N. Curi ◽  
S. N. M. Yanagi ◽  
A. M. Silva
Keyword(s):  
River Basin ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Minas Gerais ◽  
Rainfall Pattern ◽  
Rainfall Erosivity ◽  
Rainfall Events ◽  
Rainfall Depth ◽  
Erosive Rainfall

Abstract. Relationships between regional climate and oceanic and atmospheric anomalies are important tools in order to promote the development of models for predicting rainfall erosivity, especially in regions with substantial intra-annual variability in the rainfall regime. In this context, this work aimed to analyze the rainfall erosivity in headwaters of Grande River Basin, Southern Minas Gerais State, Brazil. This study considered the two most representative environments, the Mantiqueira Range (MR) and Plateau of Southern Minas Gerais (PSM). These areas are affected by the El Nino Southern Oscillation (ENSO) indicators Sea Surface Temperature (SST) for Niño 3.4 Region and Multivariate ENSO Index (MEI). Rainfall erosivity was calculated for individual rainfall events from January 2006 to December 2010. The analyses were conducted using the monthly data of ENSO indicators and the following rainfall variables: rainfall erosivity (EI30), rainfall depth (P), erosive rainfall depth (E), number of rainfall events (NRE), number of erosive rainfall events (NEE), frequency of occurrence of an early rainfall pattern (EP), occurrence of late rainfall pattern (LP) and occurrence of intermediate rainfall patter (IP). Pearson's coefficient of correlation was used to evaluate the relationships between the rainfall variables and SST and MEI. The coefficients of correlation were significant for SST in the PSM sub-region. Correlations between the rainfall variables and negative oscillations of SST were also significant, especially in the MR sub-region, however, the Person's coefficients were lesser than those obtained for the SST positive oscillations. The correlations between the rainfall variables and MEI were also significant but lesser than the SST correlations. These results demonstrate that SST positive oscillations play a more important role in rainfall erosivity, meaning they were more influenced by El-Niño episodes. Also, these results have shown that the ENSO variables have potential to be useful for rainfall erosivity forecasting in this region.

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