Assessing and modelling changes in rainfall erosivity at different climate scales

An understanding of the weather drivers of soil erosion necessitates an extended instrumental meteorological series and knowledge of the processes linking climate and hydrology. The nature of such linkages remains poorly understood for the Mediterranean region. This gap is addressed through a composite analysis of long‐term climatic controls on rain erosivity in the Calore River Basin (southern Italy) for the period 1869–2006. Based on a parsimonious interpretation of rainstorm processes, a model (comparable with the Revised Universal Soil Loss Equation) was adapted to generate erosivity values on different time‐aggregation scales (yearly and seasonal). The evolution of the generated series of cumulated and extreme erosivity events was assessed by two return period (T) quantiles via a 22‐year moving window analysis (low return period, T = 2 years; high return period, T = 50 years). Erosivity extremes are shown to be characterized by increasing yearly trends (at a 100‐year rate of ～150 MJ mm ha^–1 h^–1 for T = 2 years and ～800 MJ mm ha^–1 h^–1 for T = 50 years), especially during the spring and autumn seasons. Quantile patterns on the extremes are also shown to be decoupled from trends in the cumulated values. The Buishand test was applied to detect the presence of temporal change points, and a wavelet spectrum analysis used for time‐frequency localization of climate signals. A change‐point in the evolution of climate is revealed over the 1970s in the spring series, which correlates to a distinct rain erosivity increase. The results indicate that soil erosion risk tends to rise as a consequence of an escalation of the climate erosive hazard, predominantly between April and November (associated with cultivation and tillage practices). Copyright © 2009 John Wiley & Sons, Ltd.     

Estimating rainfall erosivity by aggregated drop size distributions

Rainfall erosivity is defined as the potential of the rain to cause erosion, and it can be represented by rainfall kinetic power. At first in this paper, the raindrop size distributions (DSD) measured by an optical disdrometer located at Palermo in the period June 2006–March 2014 and aggregated for intensity classes, are presented. Then an analysis of raindrop size characteristics is carried out, and the reliability of Ulbrich's distribution, using both the maximum likelihood and momentum estimate parameter methods, is tested. The raindrop size measurements are used to determine the experimental rainfall kinetic power values, which are compared with the ones calculated by a theoretically deduced relationship. This analysis demonstrates that the kinetic power is strictly related to the median volume diameter of DSD. Finally, the reliability of the simplest Marshall and Palmer exponential DSD for estimating the rainfall kinetic power is demonstrated. Copyright © 2015 John Wiley & Sons, Ltd.     

Exploring the effect of different time resolutions to calculate the rainfall erosivity factor R in Calabria,southern Italy

The rainfall erosivity factor R of the Universal Soil Loss Equation is a good indicator of the potential of a storm to erode soil, as it quantifies the raindrop impact effect on the soil based on storm intensity. The R‐factor is defined as the average annual value of rainfall erosion index, EI, calculated by cumulating the EI values obtained for individual storms for at least 22 years. By definition, calculation of EI is based on rainfall measurements at short time intervals over which the intensity is essentially constant, i.e. using so‐called breakpoint data. Because of the scarcity of breakpoint rainfall data, many authors have used different time resolutions (Δt = 5, 10, 15, 30, and 60 min) to deduce EI in different areas of the world. This procedure affects the real value of EI because it is strongly dependent on Δt. In this contribution, after a general overview of similar studies carried out in different countries, the relationship between EI and Δt is explored in Calabria, southern Italy. The use of 17 139 storm events collected from 65 rainfall stations allowed the calculation of EI for different time intervals ranging from 5 to 60 min. The overall results confirm that calculation of EI is dependent on time resolution and a conversion factor able to provide its value for the required Δt is necessary. Based on these results, a parametric equation that gives EI as a function of Δt is proposed, and a regional map of the scale parameter a that represents the conversion factor for converting fixed‐interval values of (EI₃₀)_Δt to values of (EI₃₀)₁₅ is provided in order to calculate R anywhere in the region using rainfall data of 60 min. Copyright © 2015 John Wiley & Sons, Ltd.     

Spatial distribution and temporal trends of rainfall and erosivity in the Eastern Africa region

Soil erosion by water is one of the main environmental concerns in the drought‐prone Eastern Africa region. Understanding factors such as rainfall and erosivity is therefore of utmost importance for soil erosion risk assessment and soil and water conservation planning. In this study, we evaluated the spatial distribution and temporal trends of rainfall and erosivity for the Eastern Africa region during the period 1981–2016. The precipitation concentration index, seasonality index, and modified Fournier index have been analysed using 5 × 5‐km resolution multisource rainfall product (Climate Hazards Group InfraRed Precipitation with Stations). The mean annual rainfall of the region was 810 mm ranging from less than 300 mm in the lowland areas to over 1,200 mm in the highlands being influenced by orography of the Eastern Africa region. The precipitation concentration index and seasonality index revealed a spatial pattern of rainfall seasonality dependent on latitude, with a more pronounced seasonality as we go far from the equator. The modified Fournier index showed high spatial variability with about 55% of the region subject to high to very high rainfall erosivity. The mean annual R‐factor in the study region was calculated at 3,246 ± 1,895 MJ mm ha^?1 h^?1 yr^?1, implying a potentially high water erosion risk in the region. Moreover, both increasing and decreasing trends of annual rainfall and erosivity were observed but spatial variability of these trends was high. This study offers useful information for better soil erosion prediction as well as can support policy development to achieve sustainable regional environmental planning and management of soil and water resources.     

Application of piezoelectric transducers in simulated rainfall erosivity assessment

Abstract

Rainfall simulators have often been used to mimic natural rainfall for studies of various land-surface and water interaction processes. The characteristics of the simulated rainfall are the main indicators used to judge the performance of the rainfall simulators. The aim of this study is to investigate the potential of piezoelectric transducers for measuring and evaluating a dripper-type simulated rainfall drop-size distribution (DSD) and kinetic energy (KE). The directly measured KE was significantly correlated with the estimated KE using the drop-size distribution and empirical rain drop fall velocity relationships. This result emphasizes the potential use of the piezoelectric sensor to directly measure and evaluate rainfall kinetic energy. Also, the relationship between rainfall intensity and KE showed good patterns of agreement between simulated rainfall and natural rainfall.

Citation Abd Elbasit, M. A. M., Yasuda, H. & Salmi, A. (2011) Application of piezoelectric transducers in simulated rainfall erosivity assessment. Hydrol. Sci. J. 56(1), 187–194.     

Comparing theoretically supported rainfall‐runoff erosivity factors at the Sparacia (South Italy) experimental site

Interpreting rainfall‐runoff erosivity by a process‐oriented scheme allows to conjugate the physical approach to soil loss estimate with the empirical one. Including the effect of runoff in the model permits to distinguish between detachment and transport in the soil erosion process. In this paper, at first, a general definition of the rainfall‐runoff erosivity factor REF_e including the power of both event runoff coefficient Q_R and event rainfall erosivity index EI₃₀ of the Universal Soil Loss Equation (USLE) is proposed. The REF_e factor is applicable to all USLE‐based models (USLE, Modified USLE [USLE‐M] and Modified USLE‐M [USLE‐MM]) and it allows to distinguish between purely empirical models (e.g., Modified USLE‐M [USLE‐MM]) and those supported by applying theoretical dimensional analysis and self‐similarity to Wischmeier and Smith scheme. This last model category includes USLE, USLE‐M, and a new model, named USLE‐M based (USLE‐MB), that uses a rainfall‐runoff erosivity factor in which a power of runoff coefficient multiplies EI₃₀. Using the database of Sparacia experimental site, the USLE‐MB is parameterized and a comparison with soil loss data is carried out. The developed analysis shows that USLE‐MB (characterized by a Nash–Sutcliffe Efficiency Index NSEI equal to 0.73 and a root mean square error RMSE = 11.7 Mg ha^?1) has very similar soil loss estimate performances as compared with the USLE‐M (NSEI = 0.72 and RMSE = 12.0 Mg ha^?1). However, the USLE‐MB yields a maximum discrepancy factor between predicted and measured soil loss values (176) that is much lower than that of USLE‐M (291). In conclusion, the USLE‐MB should be preferred in the context of theoretically supported USLE type models.     

Temporal and spatial variability of annual and seasonal rainfall over Ethiopia

Abstract

Characterization of the seasonal and inter-annual spatial and temporal variability of rainfall in a changing climate is vital to assess climate-induced changes and suggest adequate future water resources management strategies. Trends in annual, seasonal and maximum 30-day extreme rainfall over Ethiopia are investigated using 0.5° latitude?×?0.5° longitude gridded monthly precipitation data. The spatial coherence of annual rainfall among contiguous rainfall grid points is also assessed for possible spatial similarity across the country. The correlation between temporally coinciding North Atlantic Multidecadal Oscillation (AMO) index and annual rainfall variability is examined to understand the underlying coherence. In total 381 precipitation grid points covering the whole of Ethiopia with five decades (1951–2000) of precipitation data are analysed using the Mann-Kendall test and Moran spatial autocorrelation method. Summer (July–September) seasonal and annual rainfall data exhibit significant decreasing trends in northern, northwestern and western parts of the country, whereas a few grid points in eastern areas show increasing annual rainfall trends. Most other parts of the country exhibit statistically insignificant trends. Regions with high annual and seasonal rainfall distribution exhibit high temporal and spatial correlation indices. Finally, the country is sub-divided into four zones based on annual rainfall similarity. The association of the AMO index with annual rainfall is modestly good for northern and northeastern parts of the country; however, it is weak over the southern region.

Editor Z.W. Kundzewicz; Associate editor S. Uhlenbrook

Citation Wagesho, N., Goel, N.K., and Jain, M.K. 2013. Temporal and spatial variability of annual and seasonal rainfall over Ethiopia. Hydrological Sciences Journal, 58 (2), 354–373.     

Changes in rainfall and relative humidity in river basins in northwest and central India

Seasonal and annual trends of changes in rainfall, rainy days, heaviest rain and relative humidity have been studied over the last century for nine different river basins in northwest and central India. The majority of river basins have shown increasing trends both in annual rainfall and relative humidity. The magnitude of increased rainfall for considered river basins varied from 2–19% of mean per 100 years. The maximum increase in rainfall is observed in the Indus (lower) followed by the Tapi river basin. Seasonal analysis shows maximum increase in rainfall in the post‐monsoon season followed by the pre‐monsoon season. There were least variations in the monsoon rainfall during the last century and winter rainfall has shown a decreasing trend. Most of the river basins have experienced decreasing trends in annual rainy days with a maximum decrease in the Mahanadi basin. The heaviest rain of the year has increased from 9–27 mm per 100 years over different river basins with a maximum of 27 mm for the Brahamani and Subaranrekha river basins. A combination of increase in heaviest rainfall and reduction in the number of rainy days suggest the possibility of increasing severity of floods. Such information is useful in the planning, development and management of water resources in the study area. Further, the majority of river basins have also experienced an increasing trend in relative humidity both on seasonal and annual scales. An increase in annual mean relative humidity for six river basins has been found in the range of 1–18% of mean per 100 years, while a decrease for three river basins from ? 1 to ? 13% of mean per 100 years was observed, providing a net increase in the study area by 2·4% of mean per 100 years. It is understood that an increase in areal extent of vegetation cover as well as rainfall over the last century has increased the moisture in the atmosphere through enhanced evapotranspiration, which in turn has increased the relative humidity. Copyright © 2007 John Wiley & Sons, Ltd.     

The effects of climate change on historical and future extreme rainfall in Antalya,Turkey

Abstract

There is increasing concern that flood risk will be exacerbated in Antalya, Turkey as a result of global-warming-induced, more frequent and intensive, heavy rainfalls. In this paper, first, trends in extreme rainfall indices in the Antalya region were analysed using daily rainfall data. All stations in the study area showed statistically significant increasing trends for at least one extreme rainfall index. Extreme rainfall datasets for current (1970–1989) and future periods (2080–2099) were then constructed for frequency analysis using the peaks-over-threshold method. Frequency analysis of extreme rainfall data was performed using generalized Pareto distribution for current and future periods in order to estimate rainfall intensities for various return periods. Rainfall intensities for the future period were found to increase by up to 23% more than the current period. This study contributed to better understanding of climate change effects on extreme rainfalls in Antalya, Turkey.     

More rain,less soil: long‐term changes in rainfall intensity with climate change

This commentary discusses the role of long‐term climate change in driving increases in soil erosion. Assuming that land use and management remain effectively constant, we discuss changes in the ability of rainfall to cause erosion (erosivity), using long daily rainfall data sets from southeast England. An upward trend in mean rainfall per rain day is detected at the century‐plus timescale. Implications for soil erosion and sediment delivery are discussed and evidence from other regions reviewed. We conclude that rates of soil erosion may well increase in a warmer, wetter world. Copyright © 2015 John Wiley & Sons, Ltd.     

Spatial and temporal variations in rainfall characteristics in mountainous and lowland areas in Taiwan

Although changes in rainfall characteristics have been noted across the world, few studies have reported those in mountainous areas. This study was undertaken to clarify spatial and temporal variations in rainfall characteristics such as annual rainfall amount (Pr), mean daily rainfall intensity (η), and ratio of rain days (λ) in mountainous and lowland areas in Taiwan. To this aim, we examined spatial and year‐to‐year variations and marginal long‐term trends in Pr, η, and λ, based on rainfall data from 120 stations during the period 1978–2008. The period mean rainfall () at the lowland stations had strong relationships with the period mean daily rainfall intensity () and the period mean ratio of rain days () during those 31 years. Meanwhile, was only strongly related to at mountainous stations, indicating that influences on spatial variations in were different between lowland and mountainous stations. Year‐to‐year variations in Pr at each station were primarily determined from the variation in η at most stations for both lowland and mountainous stations. Long‐term trend analysis showed that Pr and η increased significantly at 10% and 31% of the total 120 stations, respectively, and λ decreased significantly at 6% of the total. The increases in Pr were mostly accompanied by increases in η. Although stations with significant η increases were slightly biased toward the western lowland area, increases or decreases in Pr and λ were not common. These results contribute to understanding the impacts of possible climate changes on terrestrial hydrological cycles. Copyright © 2012 John Wiley & Sons, Ltd.     

Modelling bivariate rainfall distribution and generating bivariate correlated rainfall data in neighbouring meteorological subdivisions using copula

The rainfall patterns of neighbouring meteorological subdivisions of India are similar because of similar climatological and geographical characteristics. Analysing the rainfall pattern separately for these meteorological subdivisions may not always capture the correlation and tail dependence. Furthermore, generating the multivariate rainfall data separately may not preserve the correlation. In this study, copula method is used to derive the bivariate distribution of monsoon rainfall in neighbouring meteorological subdivisions. Different Archimedean copulas are used for this purpose and the best copula is selected based on nonparametric test and tail dependence coefficient. The fitted copula is then applied to derive the bivariate distribution, joint return period and conditional distribution. Bivariate rainfall data is generated with the fitted copula and it is observed with the increase of sample size, the generated data is able to capture the correlation as well as tail dependence. The methodology is demonstrated with the case study of two neighbouring meteorological subdivisions of North‐East India: Assam and Meghalaya meteorological subdivision and Nagaland, Manipur, Mizoram and Tripura meteorological subdivision. Copyright © 2010 John Wiley & Sons, Ltd.     

Australian rainfall trends and their relation to the southern oscillation index

Rainfall is the key climate variable that governs the spatial and temporal availability of water. In this study we identified monthly rainfall trends and their relation to the southern oscillation index (SOI) at ten rainfall stations across Australia covering all state capital cities. The nonparametric Mann–Kendall (MK) test was used for identifying significant trends. The trend free pre‐whitening approach (TFPW) was used to remove the effects of serial correlation in the dataset. The trend beginning year was approximated using the cumulative summation (CUSUM) technique and the influence of the SOI was identified using graphical representations of the wavelet power spectrum (WPS). Decreasing trends of rainfall depth were observed at two stations, namely Perth airport for June and July rainfall starting in the 1970s and Sydney Observatory Hill for July rainfall starting in the 1930s. No significant trends were found in the Melbourne, Alice Springs and Townsville rainfall data. The remaining five stations showed increasing trends of monthly rainfall depth. The SOI was found to explain the increasing trends for the Adelaide (June) and Cairns (April) rainfall data and the decreasing trends for Sydney (July) rainfall. Other possible climatic factors affecting Australian rainfall are also discussed. Copyright © 2009 John Wiley & Sons, Ltd.     

The south to north progression of rainfall anomalies across India during the summer monsoon season

The low frequency spatio-temporal intraseasonal evolution of monsoon rainfall over India is studied by considering the pentad rainfall averages taken over 2.5° wide and 5.0° long blocks lying across the central longitudinal and latitudinal transacts. The time-latitude cross sections show south to north progressions of rainfall anomalies with a recurrence period of about 40 days. The progressions show considerable inter-annual and intra-seasonal variation in frequency, amplitude and rate of progression. The extended empirical orthogonal function analysis shows that the first two most important functions correspond to this northward progression of rain anomalies recurring after an interval of about 40 days. The rate of progression of anomalies is about 0.5° Lat./day. The time-longitude cross sections show the movement of rainfall anomalies towards both directions east and the west, with slight preference towards the east. The importance of these signals in rainfall forecasting is foreseen.     

Analysis of long-term rainfall trends in India

Abstract

The study of precipitation trends is critically important for a country like India whose food security and economy are dependent on the timely availability of water. In this work, monthly, seasonal and annual trends of rainfall have been studied using monthly data series of 135 years (1871–2005) for 30 sub-divisions (sub-regions) in India. Half of the sub-divisions showed an increasing trend in annual rainfall, but for only three (Haryana, Punjab and Coastal Karnataka), this trend was statistically significant. Similarly, only one sub-division (Chattisgarh) indicated a significant decreasing trend out of the 15 sub-divisions showing decreasing trend in annual rainfall. In India, the monsoon months of June to September account for more than 80% of the annual rainfall. During June and July, the number of sub-divisions showing increasing rainfall is almost equal to those showing decreasing rainfall. In August, the number of sub-divisions showing an increasing trend exceeds those showing a decreasing trend, whereas in September, the situation is the opposite. The majority of sub-divisions showed very little change in rainfall in non-monsoon months. The five main regions of India showed no significant trend in annual, seasonal and monthly rainfall in most of the months. For the whole of India, no significant trend was detected for annual, seasonal, or monthly rainfall. Annual and monsoon rainfall decreased, while pre-monsoon, post-monsoon and winter rainfall increased at the national scale. Rainfall in June, July and September decreased, whereas in August it increased, at the national scale.

Citation Kumar, V., Jain, S. K. & Singh, Y. (2010) Analysis of long-term rainfall trends in India. Hydrol. Sci. J. 55(4), 484–496.     

Spatial,inter and intra‐annual variability of the Upper Blue Nile Basin rainfall

In this study, monthly and annual Upper Blue Nile Basin rainfall data were analyzed to learn the rainfall statistics and its temporal and spatial distribution. Frequency analysis and spatial characterization of rainfall in the Upper Blue Nile Basin are presented. Frequency analysis was performed on monthly basin rainfall. Monthly basin average rainfall data were computed from a network of 32 gauges with varying lengths of records. Monthly rainfall probability distribution varies from month to month fitting Gamma‐2, Normal, Weibull and Log‐Normal distributions. The January, July, October and November basin rainfall fit the Gamma‐2 probability distribution. The February, June and December ones fit Weibull distribution. The March, April, May and August rainfall fit Normal distribution. The September rainfall fits Log‐Normal distribution. Upper Blue Nile Basin is relatively wet with a mean annual rainfall of 1423 mm (1960–2002) with a standard deviation of 125 mm. The annual rainfall has a Normal probability distribution. The 100‐year‐drought basin annual rainfall is 1132 mm and the 100‐year‐wet basin annual rainfall is 1745 mm. The dry season is from November through April. The wet season runs from June through September with 74% of the annual rainfall. October and May are transition months. Monthly and annual rainfalls for return periods 2‐, 5‐, 10‐, 25‐, 50‐ and 100‐year dry and wet patterns are presented. Spatial distribution of annual rainfall over the basin is mapped and shows high variation with the southern tip receiving as high as 2049 mm and the northeastern tip as low as 794 mm annual average rainfall. Copyright © 2009 John Wiley & Sons, Ltd.     

Spatial distribution of rainfall trends in Sicily (1921-2000)

The feared global climate change could have important effects on various environmental variables including rainfall in many countries around the world. Changes in precipitation regime directly affect water resources management, agriculture, hydrology and ecosystems. For this reason it is important to investigate the changes in the spatial and temporal rainfall pattern in order to improve water management strategies.In this study a non-parametric statistical method (Mann-Kendall rank correlation method) is employed in order to verify the existence of trend in annual, seasonal and monthly rainfall and the distribution of the rainfall during the year. This test is applied to about 250 rain gauge stations in Sicily (Italy) after a series of procedures finalized to the estimation of missing records and to the verification of data consistency.In order to understand the regional pattern of precipitation in Sicily, the detected trends are spatially interpolated using spatial analysis techniques in a GIS environment.The results show the existence of a generalized negative trend for the entire region.     

Wavelet analysis of rainfall variation in the Hebei Plain

Rainfall is an important climate factor, which has significant impacts on agricultural production and na-tional economic development[1]. Being part of the North China Plain, the Hebei Plain is an agricultural region. Under the continental monsoon climate, it is cold and dry in winter, hot and rainy in summer, and its variable rainfall is concentrated in summer. Droughts and floods occur frequently and impose sig-nificant impacts on agricultural production. Studies on the characteristics and …     

Urban hydrologic trend analysis based on rainfall and runoff data analysis and conceptual model calibration

Urban stormwater is a major cause of urban flooding and natural water pollution. It is therefore important to assess any hydrologic trends in urban catchments for stormwater management and planning. This study addresses urban hydrological trend analysis by examining trends in variables that characterize hydrological processes. The original and modified Mann‐Kendall methods are applied to trend detection in two French catchments, that is, Chassieu and La Lechere, based on approximately 1 decade of data from local monitoring programs. In both catchments, no trend is found in the major hydrological process driver (i.e., rainfall variables), whereas increasing trends are detected in runoff flow rates. As a consequence, the runoff coefficients tend to increase during the study period, probably due to growing imperviousness with the local urbanization process. In addition, conceptual urban rainfall‐runoff model parameters, which are identified via model calibration with an event based approach, are examined. Trend detection results indicate that there is no trend in the time of concentration in Chassieu, whereas a decreasing trend is present in La Lechere, which, however, needs to be validated with additional data. Sensitivity analysis indicates that the original Mann‐Kendall method is not sensitive to a few noisy values in the data series.