scholarly journals Rainfall erosivity–intensity relationships for normal rainfall events and a tropical cyclone on the US southeast coast

2016 ◽  
Vol 534 ◽  
pp. 440-450 ◽  
Author(s):  
Kazuki Nanko ◽  
Susanne M. Moskalski ◽  
Raymond Torres
Keyword(s):  
Tropical Cyclone ◽  
Rainfall Erosivity ◽  
Rainfall Events ◽  
Southeast Coast ◽  
The Us ◽  
Normal Rainfall

scholarly journals Tropical cyclone contribution to extreme rainfall over southwest Pacific Island nations

2021 ◽  
Author(s):  
Anil Deo ◽  
Savin S. Chand ◽  
Hamish Ramsay ◽  
Neil J. Holbrook ◽  
Simon McGree ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
El Niño ◽  
El Nino ◽  
Extreme Rainfall ◽  
Pacific Island ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Southwest Pacific ◽  
Inactive Phase ◽  
Pacific Island Nations

AbstractSouthwest Pacific nations are among some of the worst impacted and most vulnerable globally in terms of tropical cyclone (TC)-induced flooding and accompanying risks. This study objectively quantifies the fractional contribution of TCs to extreme rainfall (hereafter, TC contributions) in the context of climate variability and change. We show that TC contributions to extreme rainfall are substantially enhanced during active phases of the Madden–Julian Oscillation and by El Niño conditions (particularly over the eastern southwest Pacific region); this enhancement is primarily attributed to increased TC activity during these event periods. There are also indications of increasing intensities of TC-induced extreme rainfall events over the past few decades. A key part of this work involves development of sophisticated Bayesian regression models for individual island nations in order to better understand the synergistic relationships between TC-induced extreme rainfall and combinations of various climatic drivers that modulate the relationship. Such models are found to be very useful for not only assessing probabilities of TC- and non-TC induced extreme rainfall events but also evaluating probabilities of extreme rainfall for cases with different underlying climatic conditions. For example, TC-induced extreme rainfall probability over Samoa can vary from ~ 95 to ~ 75% during a La Niña period, if it coincides with an active or inactive phase of the MJO, and can be reduced to ~ 30% during a combination of El Niño period and inactive phase of the MJO. Several other such cases have been assessed for different island nations, providing information that have potentially important implications for planning and preparing for TC risks in vulnerable Pacific Island nations.

Estimating storm erosion with a rainfall simulator

1997 ◽  
Vol 77 (4) ◽  
pp. 669-676 ◽  
Author(s):  
S. C. Nolan ◽  
L. J. P. van Vliet ◽  
T. W. Goddard ◽  
T. K. Flesch
Keyword(s):  
Soil Loss ◽  
Conventional Tillage ◽  
Reduced Tillage ◽  
Natural Soil ◽  
Rainfall Erosivity ◽  
Slope Length ◽  
Rainfall Simulator ◽  
Rainfall Events ◽  
Plot Size ◽  
Natural Rainfall

Interpreting soil loss from rainfall simulators is complicated by the uncertain relationship between simulated and natural rainstorms. Our objective was to develop and test a method for estimating soil loss from natural rainfall using a portable rainfall simulator (1 m2 plot size). Soil loss from 12 rainstorms was measured on 144-m2 plots with barley residue in conventional tillage (CT), reduced tillage (RT) and zero tillage (ZT) conditions. A corresponding "simulated" soil loss was calculated by matching the simulator erosivity to each storm's erosivity. High (140 mm h−1) and low (60 mm h−1) simulation intensities were examined. The best agreement between simulated and natural soil loss occurred using the low intensity, after making three adjustments. The first was to compensate for the 38% lower kinetic energy of the simulator compared with natural rain. The second was for the smaller slope length of the simulator plot. The third was to begin calculating simulator erosivity only after runoff began. After these adjustments, the simulated soil loss over all storms was 99% of the natural soil loss for CT, 112% for RT and 95% for ZT. Our results show that rainfall simulators can successfully estimate soil loss from natural rainfall events. Key words: Natural rainfall events, simulated rainfall, erosivity, tillage

scholarly journals Southeastern U.S. Rainfall Prediction in the North American Multi-Model Ensemble

2014 ◽  
Vol 15 (2) ◽  
pp. 529-550 ◽  
Author(s):  
Johnna M. Infanti ◽  
Ben P. Kirtman
Keyword(s):  
North American ◽  
Seasonal Prediction ◽  
Lead Times ◽  
Model Ensemble ◽  
Rainfall Events ◽  
Rainfall Prediction ◽  
The North ◽  
Predictive Skill ◽  
Normal Rainfall

Abstract The present study investigates the predictive skill of the North American Multi-Model Ensemble (NMME) system for intraseasonal-to-interannual (ISI) prediction with focus on southeastern U.S. precipitation. The southeastern United States is of particular interest because of the typically short-lived nature of above- and below-normal extended rainfall events allowing for focus on seasonal prediction, as well as the tendency for more predictability in the winter months. Included in this study is analysis of the forecast quality of the NMME system when predicting above- and below-normal rainfall and individual rainfall events, with particular emphasis on results from the 2007 dry period. Both deterministic and probabilistic measures of skill are utilized in order to gain a more complete understanding of how accurately the system predicts precipitation at both short and long lead times and to investigate the multimodel aspect of the system as compared to using an individual predictive model. The NMME system consistently shows low systematic error and relatively high skill in predicting precipitation, particularly in winter months as compared to individual model results.

scholarly journals Variability of Summer Precipitation Events Associated with Tropical Cyclones over Mid-Lower Reaches of Yangtze River Basin: Role of the El Niño–Southern Oscillation

Atmosphere ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 256 ◽  
Author(s):  
Fuqiang Cao ◽  
Tao Gao ◽  
Li Dan ◽  
Lian Xie ◽  
Xiang Gong
Keyword(s):  
River Basin ◽  
El Niño ◽  
Yangtze River ◽  
El Nino ◽  
Southern Oscillation ◽  
Yangtze River Basin ◽  
El Nino Southern Oscillation ◽  
Rainfall Events ◽  
Normal Rainfall ◽  
Precipitation Events

Based on tropical cyclone (TC) track data and gridded observational rainfall data of CN05.1 during the period of 1961 to 2014, we examine the contribution of TCs on three metrics of summertime rainfall regimes and identify the connection between TC-induced precipitation events and El Niño–Southern Oscillation (ENSO) in middle–lower reaches of Yangtze River Basin (MLYRB). At the regional scale, TCs are responsible for approximately 14.4%, 12.5%, and 6.9% of rainfall events for normal, 75th, and 95th percentile precipitation cases, respectively. There is no evidence of significant long-term trends of the three type events linked with TCs, while their interdecadal variability is remarkable. Fractionally, larger proportions of TC-induced events occur along southeast coastal regions of MLYRB for normal rainfall events, and they are recorded over southwest and central-east MLYRB for 95th percentile cases. Moreover, a larger contribution of 95th percentile precipitation events to summer total rainfall is found than that for 75th percentile cases, suggesting that TCs may exert stronger impacts on the upper tail of summertime precipitation distribution across MLYRB. The TC-induced normal rainfall events tend to occur more frequency over central-west MLYRB during negative phase of ENSO in summer. However, the higher likelihood of TC-induced rainfall for three defined metrics are found over the majority of areas over MLYRB during negative ENSO phase in spring. In preceding winter, La Niña episode plays a crucial role in controlling the frequency of both normal and 75th percentile precipitation events.

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 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.

Zimbabwe economic pressures will linger

2019 ◽  
Keyword(s):  
Tropical Cyclone ◽  
Foreign Currency ◽  
Tax Revenue ◽  
Interbank Market ◽  
Content Type ◽  
Local Currency ◽  
The Us ◽  
Us Dollar ◽  
Price Distortions ◽  
Energy Regulatory

Significance Since its introduction in February, the local real-time gross settlement (RTGS) dollar, a de facto new local currency, has lost over 60% of its value relative to the US dollar on both the formal interbank market and the parallel market. Meanwhile, drought and the damage wrought by Tropical Cyclone Idai have placed further pressure on scarce foreign currency resources, prompting increased public protests. Impacts Forex and fuel turmoil will harm the pivotal mining sector, particularly gold, prompting rising job losses and scaling back of operations. Increased tax collection obscures the emergence of an increasingly self-defeating tax revenue system. The Zimbabwe Energy Regulatory Authority's continued control of pricing could see price distortions persisting and renewed fuel shortages.

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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