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Rainfall erosivity and its derivative, erosivity density (ED, i.e., the erosivity per unit of rain), is a main driver of considerable environmental damages and economic losses worldwide. This study is the first to investigate the interannual variability, and return periods, of both rainfall erosivity and ED over the Mediterranean for the period 1680–2019. By capturing the relationship between seasonal rainfall, its variability, and recorded hydrological extremes in documentary data consistent with a sample (1981–2015) of detailed Revised Universal Soil Loss Erosion-based data, we show a noticeable decreasing trend of rainfall erosivity since about 1838. However, the 30-year return period of ED values indicates a positive long-term trend, in tandem with the resurgence of very wet days (> 95th percentile) and the erosive activity of rains during the past two decades. A possible fingerprint of recent warming is the occurrence of prolonged wet spells in apparently more erratic and unexpected ways. [ABSTRACT FROM AUTHOR]

A gridded 0.25° reconstruction of rainfall kinetic energy (RKE) over the UK, on the basis of pluviometric observations and reanalysis back to 1765, shows that autumn RKE doubled in 1991-2013 (∼2 MJ m) compared to 1948-1990 (∼1 MJ m). A shift eastward is underway, which includes southern and northern portions of the country. Analyzing the long-running England and Wales precipitation series, we conclude that it is likely that increased precipitation amounts associated with more frequent convective storms created conditions for higher energy events. [ABSTRACT FROM AUTHOR]

Periods characterized by heavy rain and storms can trigger Multiple Damaging Hydrological Events (MDHE), in turn developing flooding, erosion, downpours and other phenomena affecting human habitats and ecosystems. However, approaches and applications to model MDHE and weather warning under specific environmental conditions are still poor. Based on the interpretation of the rainstorm-MDHE relationship, it was reconsidered and extended to a model-based rainstorms hazard index (RHI) developed in a previous paper, where rainstorm-pulsing force and resistance state are combined. In this way, landscape response was achieved by individual formative rainfall events, while the specific sequence of events that can affect landscape was only assessed in a qualitative way. A retrospective evaluation of rainstorm hazard modelling, control runs, are also given for different precipitation durations (from 1 to 240 h), to be compared with MDHE at two test-sites of Southern Italy (Benevento, Campania region; Scilla, Calabria region). For these sites, the complete series of historical MDHE which occurred during a 10 year period (1997-2008) was gathered and used to validate the results of the rainfall model. The tool is relatively simple and potentially attractive to rapidly prediction of adverse consequences of rainstorms. Perspectives for real-time applications in emergency planning are ultimately given for an agenda in future research. Copyright © 2011 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Abstract: This paper presents and assesses the Decadal Rainfall Erosive Multiscale Model (DREMM), in which extreme precipitation data (95th percentile) are used to estimate decadal-scale rainfall–runoff erosivity values compatible with the Universal Soil Loss Equation and its revision — (R)USLE. The test area was a large region including central Europe and Mediterranean countries, in which 111 decades from 88 weather stations (ranging from about 3 to 1680m above sea level) with rain and (R)USLE rainfall–runoff erosivity data were available. The construction of the model is simplified to a location-explicit term and to the understanding that the most erosive rainfalls are those recorded during the summertime and the beginning of autumn (May–October). These precipitation events are suitable for use in spatial and temporal climate variability studies on decadal time-scales. Once parameterized to capture decadal rainfall–runoff erosivity variability over central Europe and the Mediterranean, the DREMM was run to produce spatial patterns of rainfall–runoff erosivity in Germany and Bulgaria, compared to maps from the (R)USLE approach for 1961–1990. Implications for rainfall–runoff erosivity modelling were discussed concluding that a limited number of parameters may be sufficient to represent decadal rainfall–runoff erosivity for the central European and Mediterranean region. A transferable approach is recommended by employing the DREMM to assess the spatial impact of rainfall extremes. Its use to characterize the long-term dynamics of rainfall–runoff erosivity may also be of value in climate investigation. [Copyright &y& Elsevier]

Summary: This paper presents and assesses the model MedREM, in which annual-based climate and rainstorm data are used to estimate the long-term (R)Universal Soil Loss Equations and its Revisions (USLE) annual rainfall erosivity over a large region. Two known models of rainfall erosivity (named after the first author of the original paper, Torri and Yang) were also assessed and compared with the MedREM. Yang and Torri models are both based on the annual precipitation models. MedREM also takes annual maximum daily precipitation data into account, and incorporates a longitude-dependent coefficient. The test area was a large region centered on the Mediterranean basin, in which 66 weather stations were available – 43 Italian and 23 out-of-Italy sites (12 countries, about 30–50° latitude North, and 10–50° longitude East) – with multi-year data of (R)USLE annual erosivity. The three models were calibrated against (R)USLE rainfall erosivity data from 55 stations and evaluated over a validation dataset from 11 Italian stations. On the validation dataset, the MedREM estimates generally compared well with the (R)USLE data according to Nush–Sutcliffe coefficient (0.87 against 0.76 and 0.73 with Torri and Yang model, respectively). Implications for erosivity modelling were discussed in the context of climatic features concluding that accurate estimations of site-specific annual erosivity for the Mediterranean region require process-based model with spatially-explicit parameterization. [Copyright &y& Elsevier]

Severity of drought in California (U.S.) varies from year-to-year and is highly influenced by precipitation in winter months, causing billion-dollar events in single drought years. Improved understanding of the variability of drought on decadal and longer timescales is essential to support regional water resources planning and management. This paper presents a soft-computing approach to forecast the Palmer Drought Severity Index (PDSI) in California. A time-series of yearly data covering more than two centuries (1801–2014) was used for the design of ensemble projections to understand and quantify the uncertainty associated with interannual-to-interdecadal predictability. With a predictable structure elaborated by exponential smoothing, the projections indicate for the horizon 2015–2054 a weak increase of drought, followed by almost the same pace as in previous decades, presenting remarkable wavelike variations with durations of more than one year. Results were compared with a linear transfer function model approach where Pacific Decadal Oscillation and El Niño Southern Oscillation indices were both used as input time series. The forecasted pattern shows that variations attributed to such internal climate modes may not provide more reliable predictions than the one provided by purely internal variability of drought persistence cycles, as present in the PDSI time series. [ABSTRACT FROM AUTHOR]

Highly dynamic hydro-geomorphic processes are known to drive exports of carbon (C) from river basins, but are not yet fully understood. Within this study, we simulated total organic carbon (TOC) exports at the outlet of Lake Simojärvi in the Gulf of Bothnia (Finland) with a parsimonious hydrological model. With thorough consideration of the dependence of erosion and sediment transport processes on seasonal precipitation rates, a satisfactory agreement was obtained between modelling and experimental observations (1962–2005). This provided confidence in the capability of the parsimonious model to represent temporal and spatial export dynamics. In the period 1860–2014, TOC export at the outlet of Lake Simojärvi was estimated to be highest on average (~5.5 Mg km−2·year−1) over 1974–2014 while the lowest TOC export (~2.5 Mg km−2·year−1) was estimated in 1860–1918 (with high levels of interannual-to-multidecadal variation). Regional simulations indicate that TOC increased in recent decades (on average, 4–5 Mg km−2·year−1 in 1974–2014 against ~3 Mg km−2·year−1 in 1940–1973) in northern Scandinavia and Finland. Warming-induced variability of TOC (which depends on precipitation patterns) may have altered the rates of C exchanges in aquatic ecosystems over recent years. TOC exports may continue to increase in boreal catchments with increasing temperatures as represented by future projections. [ABSTRACT FROM AUTHOR]

The boreal forest of the northern hemisphere represents one of the world's largest ecozones and contains nearly one third of the world's intact forests and terrestrially stored carbon. Long-term variations in temperature and precipitation have been implied in altering carbon cycling in forest soils, including increased fluxes to receiving waters. In this study, we use a simple hydrologic model and a 40-year dataset (1971–2010) of dissolved organic carbon ( DOC ) from two pristine boreal lakes (ELA, Canada) to examine the interactions between precipitation and landscape-scale controls of DOC production and export from forest catchments to surface waters. Our results indicate that a simplified hydrologically-based conceptual model can enable the long-term temporal patterns of DOC fluxes to be captured within boreal landscapes. Reconstructed DOC exports from forested catchments in the period 1901–2012 follow largely a sinusoidal pattern, with a period of about 37 years and are tightly linked to multi-decadal patterns of precipitation. By combining our model with long-term precipitation estimates, we found no evidence of increasing DOC transport or in-lake concentrations through the 20th century. [ABSTRACT FROM AUTHOR]

Summary: The objective of this work is to provide a tool for modelling and temporal reconstruction of the sediment load in a proglacial valley in Norway. For this purpose, we have developed the SEdiment Load CLImatological Model (SELCLIM) to predict climate-induced sediment load based on seasonal precipitation and temperature inputs. The model is tested using observational data for the period 1968–2000. The main development of the Nigardsbreen Valley system is likely the combined effects of pulsed erosion over multiple nivoglacial cycles of expansion and retreat at interdecadal scale, pulsed flushes and runoff-erosivity erosion. The model used discharge and surrogate predictors to model annual sediment load. The study attempted at relating historical and instrumental glacier front movement, thermal spring–summer conditions, snow and glacier ice ablation, and summer rainfall with total summer sediment accumulation to assess interannual to centennial-scale variability of sediment load during the Little Ice Age glacier expansion and following retreat at Nigardbreen. [Copyright &y& Elsevier]

Abstract: 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 50km to 10km 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. [Copyright &y& Elsevier]