Soil erosion is one of the world’s three major environmental problems and is the primary cause of land degradation. Its origin is related to a series of natural factors including rainfall, topography, soil and vegetation properties, and inharmonious human activities that aggravate soil erosion. The rainfall is one of the main powers that lead to soil erosion. Rainfall erosivity is the tendency of rainfall to erode the soil, long time sequence rainfall erosivity is influenced by large scale circulation situation. Rainfall erosivity is highly dependent on rainfall, which is closely related to the ENSO (El Ni?o-Southern Oscillation) indices. Pearson’s correlation coefficient can be used to evaluate the validity of the relationship between the ENSO indices and annual rainfall erosivity. This article investigated the influence on rainfall erosivity in Shaoguan City of the El Ni?o SST (Sea Surface Temperatures) anomaly, the SOI (Southern Oscillation Index) and the MEI (Multivariate El Ni?o-Southern Oscillation Index) as representations of ENSO phenomena. These index were selected because of three teleconnection patterns that are known to be important for rainfall erosivity. Through selects month rainfall as calculate rainfall erosivity during 1951-2013 and analyze that ENSO events influence rainfall erosivity in Shaoguan City. The results are indicated as follows: 1) The rainfall erosivity show upward trend and evident seasonal variation and great variation between years. At the same time, the 5 a moving average curve of rainfall erosivity indicates that the general trend is an increase accompanied by fluctuations; 2) Correlation analyses were applied to rainfall erosivity and SST anomalies. The effects of the SST anomalies on rainfall erosivity are highly evident. The rainfall erosivity showed that increased at first and decreases afterwards with the increase of the SST anomalies, and low rainfall erosivity during cold events and slightly high rainfall erosivity during warm events. When other factors that affect soil erosion were fixed, soil erosion was slightly serious during El Ni?o, whereas it was light during La Ni?a; 3) The influence of the SOI on rainfall erosivity was shown by a significant correlation, the rainfall erosivity showed decreases with the increase of the SOI; 4) The MEI explains the effects of the ENSO on Shaoguan rainfall erosivity better than did the other indices assessed in this study. Empirical evidence has shown positive correlation between rainfall erosivity and MEI. Obviously, the MEI includes six variables rather than one variable (SOI and SST), providing a better indicator for representing the state of the ENSO. Through analysis of the effects of the ENSO events on rainfall erosivity in Shaoguan city, these findings can provide a theoretical basis for the comprehensive treatment and prevention of soil erosion, and it has significant importance for the monitoring, evaluation, prediction and treatment of soil erosion.
. ENSO对韶关市1951~2013年降雨侵蚀力影响研究[J]. 地理科学,
2016, 36(10): 1573-1580.
. Impact of ENSO on Rainfall Erosivity in Shaoguan City During 1951-2013[J]. SCIENTIA GEOGRAPHICA SINICA,
2016, 36(10): 1573-1580.
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Abstract Soil erosion is a complex phenomenon involving the detachment and transport of soil particles, storage and runoff of rainwater, and infiltration. The relative magnitude and importance of these processes depends on a host of factors, including climate, soil, topography, cropping and land management practices, control practices, the antecedent conditions, and the size of the area under consideration. In this study, the results of a series of experiments are reported, summarizing the soil loss and runoff response from a 0.6脳3.75 m area to different rainstorm regimes, slope steepnesses, subsurface soil water pressures, and surface roughnesses under controlled laboratory conditions using a flume and rainfall simulator as water applicators, and a laser microreliefmeter and tensiometric system as soil response measuring devices. The soil chosen was a highly erodible Grenada loess (fine silty, mixed, thermic, Glossic Fragiudalf). The results showed: (1) a sequence of rainstorms of decreasing intensity on an initially air-dry smooth surface caused more soil loss than a sequence of similar storms of increasing intensity; (2) the surface roughness-搒ediment concentration relationship was not monotonic in nature; (3) subsurface soil water pressure substantially affected sediment concentration in runoff but only marginally impacted runoff amounts; (4) initially smooth, uniform surfaces may yield less soil loss than initially rough surfaces; (5) interrill runoff occurred as spatially varying flow in which flow patterns determine the locations of rills.
AntonVrieling, Joost C B Hoedjes, Marijn van der Velde. Towards large-scale monitoring of soil erosion in Africa: Accounting for the dynamics of rainfall erosivity[J]. , 2014, 115(4):33-43.http://www.sciencedirect.com/science/article/pii/S0921818114000265
ABSTRACT Soil erosion by water occurs on sloped terrain when erosive rainfall and consequent surface runoff acts on soils that are not well-protected by vegetation or other soil protective measures. Both rainfall erosivity and vegetation cover are highly variable through space and time. Joint accounting for the variability of these factors is required to effectively map and monitor soil erosion. However, most studies merely use average annual erosivity values, partly due to data paucity. This study analyses the variability of rainfall erosivity across Africa through the use of 3-hourly TRMM Multi-satellite Precipitation Analysis (TMPA) precipitation data. We obtained average annual erosivity estimates from 15 years of TMPA data (1998-2012) using intensity-揺rosivity relationships. Our estimates showed a positive correlation (r = 0.84) with long-term annual erosivity values of 37 stations obtained from literature. Our TMPA-analysis confirmed and mapped the large interannual variability, with maximum annual erosivity often exceeding two to three times the mean value, especially in semi-arid areas. Seasonal variability of erosivity was investigated from TMPA-based average monthly erosivity estimates, which resulted in similar seasonal patterns as those reported in literature. We conclude that (1) spatial and temporal variability of erosivity is important and needs to be accounted for in combination with vegetation cover when monitoring soil erosion; and (2) 3-hourly TMPA data allow for a good first estimate of the variability of erosivity in Africa, which could be improved by upcoming techniques that provide more accurate rainfall information at higher spatial and temporal resolutions.
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NazzarenoDiodato, JasperKnight, GianniBellocchi.Reduced complexity model for assessing patterns of rainfall erosivity in Africa[J]. , 2013, 100(1):183-193.http://www.sciencedirect.com/science/article/pii/S0921818112002056
Multivariate geostatistical modeling can be used to generate spatial patterns of hydro-climate data over ungauged regions, but these models may be unsuitable when the hydro-climatological data available over large and remote areas are sparse and show different scales of resolution. In these cases, reduced complexity modeling can be better used in order to increase understanding of hydrological extremes at spatial scales and over time periods not covered by rainfall records. In this study we present and evaluate the African Rainfall Erosivity Subregional Empirical Downscaling (ARESED) model which has been developed based on hydro-climatological and geotopographic data from 46 stations across Africa with very varied climates and elevations. We spatially downscale the 85th percentile of monthly precipitation, based on several decades of data, from 50 km to 10 km grid squares in order to predict values of rainfall erosivity across Africa. This yields inputs comparable to values based on the standard Revised Universal Soil Loss Equation (RUSLE). The 46 African stations were chosen for model development because they are also sites for which there are RUSLE-based erosivity values. Once parameterized to capture mean rainfall erosivity over several decades, the ARESED model was run as a validation tool, comparing the output with actual erosivity data. On a continental scale and over decadal time scales, the ARESED model captures most of the important processes within the hydro-climatological system. Its reduced complexity structure also makes it suitable for application to regional management and environmental planning.
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A weeklong workshop in Brazil in August 2004 provided the opportunity for 28 scientists from southern South America to examine daily rainfall observations to determine changes in both total and extreme rainfall. Twelve annual indices of daily rainfall were calculated over the period 1960 to 2000, examining changes to both the entire distribution as well as the extremes. Maps of trends in the 12 rainfall indices showed large regions of coherent change, with many stations showing statistically significant changes in some of the indices. The pattern of trends for the extremes was generally the same as that for total annual rainfall, with a change to wetter conditions in Ecuador and northern Peru and the region of southern Brazil, Paraguay, Uruguay, and northern and central Argentina. A decrease was observed in southern Peru and southern Chile, with the latter showing significant decreases in many indices. A canonical correlation analysis between each of the indices and sea surface temperatures (SSTs) revealed two large-scale patterns that have contributed to the observed trends in the rainfall indices. A coupled pattern with ENSO-like SST loadings and rainfall loadings showing similarities with the pattern of the observed trend reveals that the change to a generally more negative Southern Oscillation index (SOI) has had an important effect on regional rainfall trends. A significant decrease in many of the rainfall indices at several stations in southern Chile and Argentina can be explained by a canonical pattern reflecting a weakening of the continental trough leading to a southward shift in storm tracks. This latter signal is a change that has been seen at similar latitudes in other parts of the Southern Hemisphere. A similar analysis was carried out for eastern Brazil using gridded indices calculated from 354 stations from the Global Historical Climatology Network (GHCN) database. The observed trend toward wetter conditions in the southwest and drier conditions in the northeast could again be explained by changes in ENSO.
ZhouLiantong, Tam ChiYung, Zhou Wen et al. Influence of South China Sea and the ENSO on winter rainfall over south China[J]. , 2010, 27(4):832-844.http://d.wanfangdata.com.cn/Periodical/dqkxjz-e201004010
The present study investigates the influence of South China Sea (SCS) SST and ENSO on winter (January-February-March; JFM) rainfall over South China and its dynamic processes by using station observations for the period 1951-2003, Met Office Hadley Center SST data for the period 1900-2008, and ERA-40 reanalysis data for the period 1958-2002. It is found that JFM rainfall over South China has a significant correlation with Niño-3 and SCS SST. Analyses show that in El Niño or positive SCS SST anomaly years, southwesterly anomalies at 700 hPa dominate over the South China Sea, which in turn transports more moisture into South China and favors increased rainfall. A partial regression analysis indicates that the independent ENSO influence on winter rainfall occurs mainly over South China, whereas SCS SST has a larger independent influence on winter rainfall in northern part of South China. The temperature over South China shows an obvious decrease at 300 hPa and an increase near the surface, with the former induced by Niño-3 and the latter SCS SST anomalies. This enhances the convective instability and weakens the potential vorticity (PV), which explains the strengthening of ascending motion and the increase of JFM rainfall over South China.
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Sen RS, RouaultM.Spatial patterns of seasonal scale trends in extreme hourly precipitation in South Africa[J]. , 2013, 39(5): 151-157.http://www.sciencedirect.com/science/article/pii/S014362281200166X
Hourly precipitation data from 1998 to 2007 spread across 102 stations in South Africa were analyzed for trends in extreme hourly precipitation events. The analyses were conducted at the seasonal scale for summer and winter for nine different variables. The results of our analysis showed predominantly positive trends during summer, with the strongest trends concentrated in the coastal areas in the southeast. The spatial variations in the trends were reversed during the winter season, with negative trends observed in the coastal areas and positive trends occurring in the interior. The summer patterns also overlap with areas experiencing overall increasing trends in annual extreme precipitation as well as a stronger diurnal cycle identified in recently published literature.
Stephenson TS, Vincent LA, Allen T et al. Changes in extreme temperature and precipitation in the Caribbean region, 1961-2010[J]. , 2014, 34(9): 2957-2971.http://onlinelibrary.wiley.com/doi/10.1002/joc.3889/pdf
A workshop was held at the University of the West Indies, Jamaica, in May 2012 to build capacity in climate data rescue and to enhance knowledge about climate change in the Caribbean region. Scientists brought their daily observational surface temperature and precipitation data from weather stations for an assessment of quality and homogeneity and for the calculation of climate indices helpful for studying climate change in their region. This study presents the trends in daily and extreme temperature and precipitation indices in the Caribbean region for records spanning the 1961–2010 and 1986–2010 intervals. Overall, the results show a warming of the surface air temperature at land stations. In general, the indices based on minimum temperature show stronger warming trends than indices calculated from maximum temperature. The frequency of warm days, warm nights and extreme high temperatures has increased while fewer cool days, cool nights and extreme low temperatures were found for both periods. Changes in precipitation indices are less consistent and the trends are generally weak. Small positive trends were found in annual total precipitation, daily intensity, maximum number of consecutive dry days and heavy rainfall events particularly during the period 1986–2010. Correlations between indices and the Atlantic multidecadal oscillation (AMO) index suggest that temperature variability and, to a lesser extent, precipitation extremes are related to the AMO signal of the North Atlantic surface sea temperatures: stronger associations are found in August and September for the temperature indices and in June and October for some of the precipitation indices.
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Derege TsegayeMeshesha, AtsushiTsunekawa, Mitsuru Tsubo et al. Evaluating spatial and temporal variations of rainfall erosivity, case of Central Rift Valley of Ethiopia[J]. , 2015, 119(3-4): 515-522.http://link.springer.com/article/10.1007/s00704-014-1130-2
Abstract Land degradation in many Ethiopian highlands occurs mainly due to high rainfall erosivity and poor soil conservation practices. Rainfall erosivity is an indicator of the precipitation energy and ability to cause soil erosion. In Central Rift Valley (CRV) of Ethiopia, where the climate is characterized as arid and semiarid, rainfall is the main driver of soil erosion that in turn causes a serious expansion in land degradation. In order to evaluate the spatial and temporal variability of rainfall erosivity and its impact on soil erosion, long-term rainfall data (1980-2010) was used, and the monthly Fournier index (FI) and the annual modified Fournier index (MFI) were applied. Student's t test analysis was performed particularly to examine statistical significances of differences in average monthly and annual erosivity values. The result indicated that, in a similar spatial pattern with elevation and rainfall amount, average annual erosivity is also found being higher in western highlands of the valley and gradually decreased towards the east. The long-term average annual erosivity (MFI) showed a general decreasing trend in recent 10 years (2000-2010) as compared to previous 20 years (1980-1999). In most of the stations, average erosivity of main rainy months (May, June, July, and August) showed a decreasing trend, whereby some of them (about 33.3 %) are statically significant at 90 and 95 % confidence intervals but with high variation in spatial pattern of changes. The overall result of the study showed that rainfall aggression (erosivity) in the region has a general decreasing trend in the recent decade as compared to previous decades, especially in the western highlands of the valley. Hence, it implies that anthropogenic factors such as land use change being coupled with topography (steep slope) have largely contributed to increased soil erosion rate in the region.
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Microerosion processes due to the impact of raindrops on the soil (rainsplash) represent an important mechanism of detachment and removal of soil parcels. The annual and interannual patterns of rainsplash erosion are controlled by the variability of rainfall, vegetation cover, and land-use practice. This paper presents a study of the interannual variability of rainfall erosivity (which is an indicator of the erosive power of rainfall) due to winter precipitation in the southwestern United States and its connection to the El Niño-Southern Oscillation (ENSO). A remarkable degree of dependence was found between the values of winter erosivity and the Southern Oscillation index (SOI) in the months proceeding and during each winter. In general, it was observed that the erosive power of rainfall is stronger during El Niño years and weaker during the La Niña phase in the U.S. southwest, as is the rainfall itself. It was also observed that the erosivity and SOI are nonlinearly related. This dependence of rainfall erosivity on the ENSO signal suggests a potential short-term predictability of the erosive phases and could be useful in the implementation of new strategies of soil conservation.
ChiaraVallebona, ElisaPellegrino, Paolo Frumento et al. Temporal trends in extreme rainfall intensity and erosivity in the Mediterranean region: a case study in southern Tuscany, Italy[J]. , 2015, 128(1): 139-151.http://link.springer.com/article/10.1007/s10584-014-1287-9
ABSTRACT Worldwide climate is likely to become more variable or extreme with increases in intense precipitation. In Mediterranean areas, climate change will increase the risks of droughts, flash floods and soil erosion. Despite rainfall intensity being a key factor in erosive processes, in these areas information on extreme rainfall intensity and the associated erosivity, based on high-temporal resolution data, is either non homogeneous or scarce. These parameters thus need to be assessed in order to highlight suitable adaptation strategies. In this paper, an hourly rainfall intensity (RI) data series is analyzed together with the corresponding 1-min rainfall intensity maximum (RIm) of 23 rainfall gauges located in Tuscany, Italy, in an area highly vulnerable to erosion. The aim is to look for temporal trends (1989-2010) in extreme rainfall intensity and erosivity. Fixed effect logistic regression shows statistically significant temporal increases in the number of RI and RIm exceedances over the 95th percentile threshold. Winter is shown to be the season with the strongest increasing trend in coastal and inland rainfall gauge groups, followed by spring for the coastal group and autumn for the inland group. Linear regressions show that in the inland group there is a temporal increase in rainfall erosivity and on a seasonal basis, the highest increase is observed in autumn. By contrast, for the coastal group this increasing trend is only detectable for spring and winter. Such an increase in rainfall erosivity and its potential continuation could have a strong adverse effect on Mediterranean land conservation.
The Chinese precipitation patterns in flood season associated with the El05ino/southern Oscillation(ENSO) are investigated, especially in the eastern China, using the rather long period rainfall data in this century. The results show that there are remarkable differences between the precipitation patterns in ENSO warm phase (El05ino year) and cold phase (La05ino year) flood seasons, as well as between the patterns in El05ino years and their next years. The most parts of China receive below normal rainfall in El05ino year flood seasons, but the coastal area of Southeast China receives above normal amounts. Comparatively, the most parts of China receives above normal rainfall in El05ino’s next year flood seasons, but the eastern part of the reaches among the Huanghe (Yellow) River, the Huaihe River and the Haihe River, and the05ortheast China receive less. During ENSO cold phase, the reaches of the Changjiang(Yangtze) River and the05orth China receive more amounts than normal rainfall in La05ino year flood seasons, and the other regions of China receive less. In La05ino next years, the coastal area of the Southeast China, the most part of the05ortheast China and the regions between the Huanghe River and the Huaihe River receive more precipitation during flood seasons, but the other parts receive below normal precipitation.
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Although there is an annual mean precipitation about 1 700 mm in Guangdong Province, it greatly varies with season and region. Flood season (April-September) includes above 80% rainfall of a year, and meanwhile the rainfall has a significant intra-seasonal variability. On the other hand, large evaporation due to high average air temperature also balances some part of the great precipitation in Guangdong. An index to reflect the drought is defined using rainfall and temperature observations of 86 surface stations in Guangdong. The index distinguishes the dry and wet season in Guangdong and reflects the fact that there is a dryer climate in the south than elsewhere of Guangdong in spring and a wetter climate in the north in fall, which indicates the index is reasonable. The trend analyses give an understanding of the linear humidity change. For the whole province of Guangdong, the climates from February to March, from July to August and December tend to be wetter than before, and dryer from October to November and few changes in months else. The results show that the autumn drought would be more severe in the future and the winter-spring drought would be lighter. The spatial distribution of the linear trends has a great difference and its interannual variability is affected by air-sea and air-land interactions.
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