Hydroclimatic Processes Research Articles

The Energy Side of Budyko: Surface‐Energy Partitioning From Hydrological Observations

AbstractLand‐surface partitioning of net radiation into sensible and latent heat fluxes is critical for hydroclimatic processes but remains highly uncertain due to limited observations. We show that a suitable extension of the Budyko's curve, a well‐known framework in hydrology for water balance estimation, can be utilized effectively to partition the surface energy fluxes by expressing the long‐term evaporative fraction (EF) as a function of the dryness index only. The combination of this energy partitioning method with hydrological observations allows us to estimate the surface energy components at watershed and continental scales. Using this new framework, we show that North American Regional Reanalysis data overestimate surface evaporation, likely influencing the modeling of atmospheric convection. The obtained hydrologic constrains on energy partitioning can be used to provide more accurate estimations of surface energy fluxes for hydroclimatic predictions.

Isotopic records of climate seasonality in equid teeth

We investigate how oxygen isotopes in equid teeth can be used as a record of seasonality. First, we use in situ laser ablation and conventional microsampling techniques to understand time-averaging of environmental signals in intra-tooth isotope profiles in modern feral horse teeth (n = 5) from Mongolia, where there is a large seasonal gradient in the oxygen isotopic composition of precipitation. We demonstrate that laser ablation can be used to sample inner, middle, and outer enamel layers in large mammalian herbivore teeth. The inner enamel layer records less attenuated isotopic signals than other layers, as predicted by the mineralization patterns, but intra-tooth signal amplitude is similar for laser and conventional sampling methods. Second, we use modern zebra teeth (n = 21) collected in eastern Africa to evaluate how intra-tooth oxygen isotope variation relates to rainfall patterns in the tropics. We show that the intra-tooth isotopic range increases with intra-annual precipitation isotopic range, which in turn relates to aridity in the equatorial bimodal rainfall region but is influenced by other hydroclimate processes in the region as a whole. Finally, we address isotopic seasonality during the Early Pleistocene in eastern Africa using oxygen isotopes in fossil equid teeth from southwestern Kenya (n = 11) and northern Tanzania (n = 5). We find variable isotopic seasonality in the past, similar to present-day eastern Africa, consistent with the notion that hominins and other mammals were able to accommodate environmental variability on intra-annual scales in addition to well-documented orbital cycles.

Sediment distribution pattern of the South Caspian Sea: possible hydroclimatic implications

The south Caspian subbasin extends from the foot of the Alborz Mountains to the deepest part of Caspian Sea. The lithological background and tectonic setting of the study area primarily control the deposition of thick sedimentary sequences of the basin, while hydroclimatic processes exert secondary impacts on the sediment distribution pattern. To evaluate past hydroclimatic changes, short sediment cores were retrieved from the continental shelf and upper slope of the south Caspian Sea and were treated for basic sedimentological properties and mineralogy. The results show that the sediments are composed of terrigenous, biogenic, and chemical components. The chemical component has a significant signature in the internal structure of the sediment, which reflects degradation of organic material due to a succession of aerobic and anaerobic conditions. Aerobic conditions reflect the extreme climatic conditions that lead to formation of well-oxygenated deep water in lowstands and extremely cold winters, when dense oxygenated water is allowed to touch the bottom sediments. The sediment distribution pattern demonstrates three distinctive areas in the southern continental margin with different organic matter and carbonate content. Fluvial inputs and wave hydrodynamics control the sediment properties and their distribution pattern in the upper shelf, while in deeper parts, the dynamics of water stratification and its temporal and long-term variations, relating to climate and water level changes, determine sediment composition. Overall, the sedimentary distribution pattern is a result of their sources in the catchment basin and the hydroclimate of the Caspian Sea.

Extremely high flow within the Alpine catchments in the Rila Mountain

The study of high flow characteristics within the Alpine catchments represents one of the most challenging tasks for the modern hydrological science, because of high vulnerability response of these areas to the global and regional climate changes, including to the proven positive air temperature trends. The current picture of the hydro-climatic processes in the Rila Mountain – the highest mount within the Balkan Peninsula, is not exception. Study area covers eight Alpine catchment areas, located above 1600 m sea level in the Rila Mountain. The aim of this research is to perform a spatio-temporal analysis of the extremely high streamflow characteristics within the researched drainage basins. Study period includes six years in the beginning of the XXІ century: there are very dry (2001), very wet (2005) and four normal water years. The analysis is based of Threshold level method (TLM) with fixed constant threshold value: 5th percentile of all discharge daily data for the given term. Results obtained show the number of extremely high streamflow events ranges from 6 to 26 – for the catchments of the Stara River at Kostenets and the Blagoevgradska Bistritsa River at Bistritsa, respectively. The maximal duration of these events varies from 15 (for the Mesta River at Yakoruda) do 39 days (the Stara River at Kostenets), but the oneweek extremely high flow periods are most typical here (a frecquency to 88% of all cases). The temporal analysis shows a concentration of studied hydrological events during the spring season (in the months of April, May and June), when occurs also a high streamflow phase, due to the snow melting and rainfalls. An exception of this statement is the wettest year in Bulgaria from the beginning of this century – 2005. Then because of heavy prolonged rainfalls during the months of July, August and September, were detected sharp peaks of the hydrographs. Present work establishes some spatial differences of extremely high flow characteristics (time of occurring, duration, frequency) in study area due to the slopes exposition peculiarities. Results obtained supplement previous scientific works and give new information about the risk hydrological processes within the mountainous catchment areas in Bulgaria.

The Influence of Competing Hydroclimate Processes on Stable Isotope Ratios in Tropical Rainfall

AbstractIn tropical paleoclimate studies, paleo‐precipitation is often reconstructed from proxies via the “amount effect,” that is, the empirical inverse relationship between local precipitation amount (P) and the oxygen isotopic composition of precipitation (δ18OP). However, recent research has illustrated numerous microphysical and dynamical controls on δ18OP that do not necessarily covary with P, complicating the reconstruction of circulation features like the Intertropical Convergence Zone. Here we introduce a new conceptual and statistical model for δ18OP that better captures the physical foundations for δ18OP as a tracer of hydrological balance. We find that bulk precipitation microphysics and cloud type exert comparable influences on δ18OP. Moisture transport plays an important secondary role in regions of deep atmospheric convection such as the Intertropical Convergence Zone and Indo‐Pacific Warm Pool. Our findings help reconcile conflicting interpretations of Intertropical Convergence Zone excursions, and provide a firm physical grounding for more nuanced, accurate interpretations of past hydroclimate using water isotope proxies.

Holocene fluvial history of Romanian Carpathian rivers

The Holocene fluvial history of rivers draining the Romanian Carpathians has been assessed using a database resulting from the authors’ own field research at more than 50 sites comprising natural exposures (riverbanks), anthropogenic exposures (gravel pits) and manual boreholes carried out in floodplains, as well as on the analysis of over 30 published sources. Thus, 196 dated fluvial units were obtained, of which, subsequent to filtering, 142 units were retained for application of Cumulative Probability Functions (CPFs). To this database we added 274 radiocarbon-dated lacustrine sedimentary units originating in small lakes and bogs linked to the fluvial network of the study area. The resulting data bases were classified, processed and analysed under the methodological framework of meta-analysis in order to reconstruct the phases of geomorphic activity of rivers during major flood events and periods of low hydroclimatic intensity throughout the Holocene, and to understand the river response in terms of dominant fluvial processes. Based on the analysis of probability frequency, 17 major flooding episodes were identified, of which 12 (mostly from the last 4500 years) coincide with wet phases determined for lacustrine sedimentary units from the study area. At regional scale, of the 17 centennial intervals with flood events recorded in fluvial archives from Romania in the last 10 ka, 15 intervals are synchronous with at least one area from Central or Eastern Europe, leading to the conclusion that the climatic factor manifested dominantly in SE Europe, as well. At local scale, the orographic barrier of the Carpathians interfering with the dominant circulation of western air masses has modified the magnitude and timing of flood events, resulting in increased rates of hydroclimatic and geomorphic processes in western rivers compared to rivers east of the Carpathian range. Other controls which have local influence on the evolution of hydroclimatic processes (i.e. vegetation changes and human impact) determined an increase in the susceptibility of areas located between 700 and 1000 m asl throughout Romania and contributed to the acceleration of fluvial systems dynamics post ca. 4500 cal BP.

Identifying Water Storage Variation in Krishna Basin, India from in situ and Satellite based Hydrological Data

Terrestrial water storage (TWS), a sum total of water stored on or beneath the earth’s surface, transits in response to hydroclimatic processes such as precipitation, evapo-transpiration, runoff etc. and serves an indicator of hydrological condition of a region. We analyse spatio-temporal variance of water storage in Krishna Basin, India, derived from in-situ groundwater data and Gravity Recovery and Climate Experiment (GRACE) satellite data in order to determine physical causes of variations, and compare the variance with climatic factors such as Cumulative Rainfall Departure (CRD) and drought index i.e. Standardized Precipitation Index (SPI). GRACE satellite based TWS is found to reflect insitu groundwater changes and also shows a relationship with drought patterns as indicated by a good correlation with SPI. The largest part of TWS represents seasonal flux, and at an interannual scale, TWS depicts spatio-temporal variability in response to drought index viz. SPI. We infer that the groundwater storage derived from GRACE time-variable gravity solutions can be utilised to complement in-situ observations at basin scale and it reflects climatic forcing quite well.

Hydroclimatic control on suspended sediment dynamics of a regulated Alpine catchment: a conceptual approach

Abstract. We analyse the control of hydroclimatic factors on suspended sediment concentration (SSC) in Alpine catchments by differentiating among the potential contributions of erosion and suspended sediment transport driven by erosive rainfall, defined as liquid precipitation over snow-free surfaces, ice melt from glacierized areas, and snowmelt on hillslopes. We account for the potential impact of hydropower by intercepting sediment fluxes originated in areas diverted to hydropower reservoirs, and by considering the contribution of hydropower releases to SSC. We obtain the hydroclimatic variables from daily gridded datasets of precipitation and temperature, implementing a degree-day model to simulate spatially distributed snow accumulation and snow–ice melt. We estimate hydropower releases by a conceptual approach with a unique virtual reservoir regulated on the basis of a target-volume function, representing normal reservoir operating conditions throughout a hydrological year. An Iterative Input Selection algorithm is used to identify the variables with the highest predictive power for SSC, their explained variance, and characteristic time lags. On this basis, we develop a hydroclimatic multivariate rating curve (HMRC) which accounts for the contributions of the most relevant hydroclimatic input variables mentioned above. We calibrate the HMRC with a gradient-based nonlinear optimization method and we compare its performance with a traditional discharge-based rating curve. We apply the approach in the upper Rhône Basin, a large Swiss Alpine catchment heavily regulated by hydropower. Our results show that the three hydroclimatic processes – erosive rainfall, ice melt, and snowmelt – are significant predictors of mean daily SSC, while hydropower release does not have a significant explanatory power for SSC. The characteristic time lags of the hydroclimatic variables correspond to the typical flow concentration times of the basin. Despite not including discharge, the HMRC performs better than the traditional rating curve in reproducing SSC seasonality, especially during validation at the daily scale. While erosive rainfall determines the daily variability of SSC and extremes, ice melt generates the highest SSC per unit of runoff and represents the largest contribution to total suspended sediment yield. Finally, we show that the HMRC is capable of simulating climate-driven changes in fine sediment dynamics in Alpine catchments. In fact, HMRC can reproduce the changes in SSC in the past 40 years in the Rhône Basin connected to air temperature rise, even though the simulated changes are more gradual than those observed. The approach presented in this paper, based on the analysis of the hydroclimatic control of suspended sediment concentration, allows the exploration of climate-driven changes in fine sediment dynamics in Alpine catchments. The approach can be applied to any Alpine catchment with a pluvio-glacio-nival hydrological regime and adequate hydroclimatic datasets.

Unified theory for stochastic modelling of hydroclimatic processes: Preserving marginal distributions, correlation structures, and intermittency

Abstract Hydroclimatic processes come in all “shapes and sizes”. They are characterized by different spatiotemporal correlation structures and probability distributions that can be continuous, mixed-type, discrete or even binary. Simulating such processes by reproducing precisely their marginal distribution and linear correlation structure, including features like intermittency, can greatly improve hydrological analysis and design. Traditionally, modelling schemes are case specific and typically attempt to preserve few statistical moments providing inadequate and potentially risky distribution approximations. Here, a single framework is proposed that unifies, extends, and improves a general-purpose modelling strategy, based on the assumption that any process can emerge by transforming a specific “parent” Gaussian process. A novel mathematical representation of this scheme, introducing parametric correlation transformation functions, enables straightforward estimation of the parent-Gaussian process yielding the target process after the marginal back transformation, while it provides a general description that supersedes previous specific parameterizations, offering a simple, fast and efficient simulation procedure for every stationary process at any spatiotemporal scale. This framework, also applicable for cyclostationary and multivariate modelling, is augmented with flexible parametric correlation structures that parsimoniously describe observed correlations. Real-world simulations of various hydroclimatic processes with different correlation structures and marginals, such as precipitation, river discharge, wind speed, humidity, extreme events per year, etc., as well as a multivariate example, highlight the flexibility, advantages, and complete generality of the method.

Wavelet regression: An approach for undertaking multi-time scale analyses of hydro-climate relationships

Previous studies showed that hydro-climate processes are stochastic and complex systems, and it is difficult to discover the hidden patterns in the and non-stationary data and thoroughly understand the hydro-climate relationships. For the purpose to show multi-time scale responses of a hydrological variable to climate change, we developed an integrated approach by combining wavelet analysis and regression method, which is called wavelet regression (WR). The customization and the advantage of this approach over the existing methods are presented below:•The patterns in the data series of a hydrological variable and its related climatic factors are revealed by the wavelet analysis at different time scales.•The hydro-climate relationship of each pattern is revealed by the regression method based on the results of wavelet analysis.•The advantage of this approach over the existing methods is that the approach provides a routing to discover the hidden patterns in the stochastic and non-stationary data and quantitatively describe the hydro-climate relationships at different time scales.

Validation of IMERG precipitation in Africa.

Our understanding of hydroclimatic processes in Africa has been hindered by the lack of in-situ precipitation measurements. Satellite-based observations, in particular, the TRMM Multi-Satellite Precipitation Analysis (TMPA) have been pivotal to filling this void. The recently-released Integrated Multi-satellitE Retrievals for GPM (IMERG) project aims to continue the legacy of its predecessor, TMPA, and provide higher resolution data. Here, we validate IMERG-V04A precipitation data using in-situ observations from the Trans-African Hydro-Meteorological Observatory (TAHMO) project. Various evaluation measures are examined over a select number of stations in West and East Africa. In addition, continent-wide comparisons are made between IMERG and TMPA. The results show that the performance of the satellite-based products varies by season, region and the evaluation statistics. Precipitation diurnal cycle is relatively better captured by IMERG than TMPA. Both products exhibit a better agreement with gauge data in East Africa and humid West Africa than in the Southern Sahel. However, a clear advantage for IMERG is not apparent in detecting the annual cycle. Although all gridded products used here reasonably capture the annual cycle, some differences are evident during the short rains in East Africa. Direct comparison between IMERG and TMPA over the entire continent reveals that the similarity between the two products is also regionally heterogeneous. Except for Zimbabwe and Madagascar, where both satellite-based observations present a good agreement, the two products generally have their largest differences over mountainous regions. IMERG seems to have achieved a reduction in the positive bias evident in TMPA over Lake Victoria.

Providing a non-deterministic representation of spatial variability of precipitation in the Everest region

Abstract. This paper provides a new representation of the effect of altitude on precipitation that represents spatial and temporal variability in precipitation in the Everest region. Exclusive observation data are used to infer a piecewise linear function for the relation between altitude and precipitation and significant seasonal variations are highlighted. An original ensemble approach is applied to provide non-deterministic water budgets for middle and high-mountain catchments. Physical processes at the soil–atmosphere interface are represented through the Interactions Soil–Biosphere–Atmosphere (ISBA) surface scheme. Uncertainties associated with the model parametrization are limited by the integration of in situ measurements of soils and vegetation properties. Uncertainties associated with the representation of the orographic effect are shown to account for up to 16 % of annual total precipitation. Annual evapotranspiration is shown to represent 26 % ± 1 % of annual total precipitation for the mid-altitude catchment and 34% ± 3 % for the high-altitude catchment. Snowfall contribution is shown to be neglectable for the mid-altitude catchment, and it represents up to 44 % ± 8 % of total precipitation for the high-altitude catchment. These simulations on the local scale enhance current knowledge of the spatial variability in hydroclimatic processes in high- and mid-altitude mountain environments.

Characterization of phytoplankton assemblages in a tropical coastal environment using Kohonen self‐organizing map

AbstractThis study was aimed at understanding the main abiotic environmental factors controlling the distribution patterns of abundance and composition of phytoplankton (size less than 10 μm) assemblages in the coastal waters of south‐eastern Côte d'Ivoire. Data were collected during two cruises, in January (low‐water period) and October (high‐water period) of 2014. A total of 67 species were identified and assigned to Bacillariophyceae (49%), Cyanophyceae (21%), Chlorophyceae (13%), Euglenophyceae (10%), Dinophyceae (4%) and Chrysophyceae (3%). Three biotic zones (I, IIA and IIB) were distinguishable on a Kohonen self‐organizing map after an unsupervised learning process. The diatom genera Eunotia sp., Navicula sp. and Actinoptychus senarius are significantly associated with I, IIA and IIB biotic zones, respectively. A clear seasonal cum salinity trend was apparent in phytoplankton distribution patterns. Turbidity and nitrate levels were the main abiotic factors controlling phytoplankton distribution in I, the upland tidal regions of the lagoon. In regions along the lagoon–sea continuum, phosphate and turbidity exert the most control during the low‐water season (IIA), while total dissolved solids control phytoplankton distribution during the high‐water season (IIB). These are climate‐sensitive parameters whose concentrations depend on prevailing hydroclimatic processes. Therefore, seasonality can have important consequences on phytoplankton community and inadvertently the productivity of these systems.

Influence of reanalysis datasets on dynamically downscaling the recent past

Multiple reanalysis datasets currently exist that can provide boundary conditions for dynamic downscaling and simulating local hydro-climatic processes at finer spatial and temporal resolutions. Previous work has suggested that there are two reanalyses alternatives that provide the best lateral boundary conditions for downscaling over southern Africa. This study dynamically downscales these reanalyses (ERA-I and MERRA) over southern Africa to a high resolution (10 km) grid using the WRF model. Simulations cover the period 1981–2010. Multiple observation datasets were used for both surface temperature and precipitation to account for observational uncertainty when assessing results. Generally, temperature is simulated quite well, except over the Namibian coastal plain where the simulations show anomalous warm temperature related to the failure to propagate the influence of the cold Benguela current inland. Precipitation tends to be overestimated in high altitude areas, and most of southern Mozambique. This could be attributed to challenges in handling complex topography and capturing large-scale circulation patterns. While MERRA driven WRF exhibits slightly less bias in temperature especially for La Nina years, ERA-I driven simulations are on average superior in terms of RMSE. When considering multiple variables and metrics, ERA-I is found to produce the best simulation of the climate over the domain. The influence of the regional model appears to be large enough to overcome the small difference in relative errors present in the lateral boundary conditions derived from these two reanalyses.

Estimation of snowfall limit for the Kashmir Valley, Indian Himalayas, with TRMM PR Bright Band information

Knowing the height of the snowfall limit during precipitation events is crucial for better understanding a number of hydro-climatic processes, for instance glacier-climate interactions or runoff from high mountain catchments. However, knowledge on heights of the phase change during precipitation events is limited by the small number of meteorological measurements available at high altitudes, such as the Himalayas. The bright band (BB) of satellite based radar data may be a promising proxy for the snow/rain transition during particular stratiform precipitation events over high mountain regions. The BB is a horizontal layer of stronger radar reflectivity caused by the melting of hydrometeors at the level where solid precipitation turns into rain. Here, we present BB heights detected by the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) 2A23 algorithm over a mountainous area. To assess the performance of BB heights, we have compared a 17-year data set of BB estimations of the TRMM PR with radiosonde observations and meteorological station data from Srinagar, Kashmir Valley, India. During March to November, the BB lies mostly about 200 to 800m below the freezing level (FL) recorded by radiosondes. The correlation between BB and FL heights extrapolated from a ground-based station is smaller and depends on the timing of the air temperature measurement – an important finding for applying extrapolation techniques in data sparse regions. Further on, we found a strong seasonal and monthly variability of the BB height, e.g. extending in summer months from about 2700m to almost 6000m asl. Comparison with near surface rain intensity from the TRMM PR product 2A25 indicates that – during intense monsoonal summer precipitation events – the BB height is concentrated between about 3500 and 4000m asl. We can conclude that TRMM PR BB data deliver valuable complementary information for regional or seasonal variability in snow/rain transition in data sparse regions and, further on, BB data from surrounding lowlands could be used to validate extrapolation approaches to assess snowfall limit for mainly stratiform precipitation events where stations at high elevations are missing.

Yosemite Hydroclimate Network: Distributed stream and atmospheric data for the Tuolumne River watershed and surroundings

AbstractRegions of complex topography and remote wilderness terrain have spatially varying patterns of temperature and streamflow, but due to inherent difficulties of access, are often very poorly sampled. Here we present a data set of distributed stream stage, streamflow, stream temperature, barometric pressure, and air temperature from the Tuolumne River Watershed in Yosemite National Park, Sierra Nevada, California, USA, for water years 2002–2015, as well as a quality‐controlled hourly meteorological forcing time series for use in hydrologic modeling. We also provide snow data and daily inflow to the Hetch Hetchy Reservoir for 1970–2015. This paper describes data collected using low‐visibility and low‐impact installations for wilderness locations and can be used alone or as a critical supplement to ancillary data sets collected by cooperating agencies, referenced herein. This data set provides a unique opportunity to understand spatial patterns and scaling of hydroclimatic processes in complex terrain and can be used to evaluate downscaling techniques or distributed modeling. The paper also provides an example methodology and lessons learned in conducting hydroclimatic monitoring in remote wilderness.

Advances in projection of climate change impacts using supervised nonlinear dimensionality reduction techniques

One of the main challenges in climate change studies is accurate projection of the global warming impacts on the probabilistic behaviour of hydro-climate processes. Due to the complexity of climate-associated processes, identification of predictor variables from high dimensional atmospheric variables is considered a key factor for improvement of climate change projections in statistical downscaling approaches. For this purpose, the present paper adopts a new approach of supervised dimensionality reduction, which is called “Supervised Principal Component Analysis (Supervised PCA)” to regression-based statistical downscaling. This method is a generalization of PCA, extracting a sequence of principal components of atmospheric variables, which have maximal dependence on the response hydro-climate variable. To capture the nonlinear variability between hydro-climatic response variables and projectors, a kernelized version of Supervised PCA is also applied for nonlinear dimensionality reduction. The effectiveness of the Supervised PCA methods in comparison with some state-of-the-art algorithms for dimensionality reduction is evaluated in relation to the statistical downscaling process of precipitation in a specific site using two soft computing nonlinear machine learning methods, Support Vector Regression and Relevance Vector Machine. The results demonstrate a significant improvement over Supervised PCA methods in terms of performance accuracy.

Understanding Persistence to Avoid Underestimation of Collective Flood Risk

The assessment of collective risk for flood risk management requires a better understanding of the space-time characteristics of flood magnitude and occurrence. In particular, classic formulation of collective risk implies hypotheses concerning the independence of intensity and number of events over fixed time windows that are unlikely to be tenable in real-world hydroclimatic processes exhibiting persistence. In this study, we investigate the links between the serial correlation properties of 473 daily stream flow time series across the major river basins in Europe, and the characteristics of over-threshold events which are used as proxies for the estimation of collective risk. The aim is to understand if some key features of the daily stream flow data can be used to infer properties of extreme events making a more efficient and effective use of the available data. Using benchmark theoretical processes such as Hurst-Kolmogorov (HK), generalized HK (gHK), autoregressive fractionally integrated moving average (ARFIMA) models, and Fourier surrogate data preserving second order linear moments, our findings confirm and expand some results previously reported in the literature, namely: (1) the interplay between short range dependence (SRD) and long range dependence (LRD) can explain the majority of the serial dependence structure of deseasonalized data, but losing information on nonlinear dynamics; (2) the standardized return intervals between over-threshold values exhibit a sub-exponential Weibull-like distribution, implying a higher frequency of return intervals longer than expected under independence, and expected return intervals depending on the previous return intervals; this results in a tendency to observe short (long) inter-arrival times after short (long) inter-arrival times; (3) as the average intensity and the number of events over one-year time windows are not independent, years with larger events are also the more active in terms of number of events; and (4) persistence influences the distribution of the collective risk producing a spike of probability at zero, which describes the probability of years with no events, and a heavier upper tail, suggesting a probability of more extreme annual losses higher than expected under independence. These results provide new insights into the clustering of stream flow extremes, paving the way for more reliable simulation procedures of flood event sets to be used in flood risk management strategies.

Sedimentary environment, lithostratigraphy and dating of sediment sequences from Arctic lakes Revvatnet and Svartvatnet in Hornsund, Svalbard

Abstract The sedimentary environment, sediment characteristics and age-depth models of sediment sequences from Arctic lakes Revvatnet and Svartvatnet, located near the Polish Polar Station in Hornsund, southern Svalbard (77°N), were studied with a view to establishing a basis for paleolimnological climate and environmental reconstructions. The results indicate that catchment-to-lake hydroclimatic processes probably affect the transportation, distribution and accumulation of sediments in different parts of lakes Revvatnet and Svartvatnet. Locations with continuous and essentially stable sedimentary environments were found in both lakes between water depths of 9 and 26 m. We used several different dating techniques, including 137Cs, 210Pb, AMS 14C, and paleomagnetic dating, to provide accurate and secured sediment chronologies. Arecovered sequence from the northern basin of Revvatnet spans more than one thousand years long with laminated stratigraphy in the upper part of the sediment. Based on AMS 14C dates, it is possible to suppose that Revvatnet basin was not occupied by a valley glacier during the Little Ice Age. The dates were supported by 137Cs chronologies, but not confirmed with other independent dating methods that extent beyond the last 50 years. A sedimentary sequence from the northern basin of Svartvatnet provides a potential archive for the study of climate and environmental change for the last ca. 5000 years. Based on the stratigraphy and a Bayesian age-depth model of AMS14C and paleosecular variation (PSV) dates, the recovered sediment sections represent a continuous and stable sedimentation for the latter half of the Holocene.

Sharp change of lake levels during the two extreme droughts and its hydroclimatic processes in Lake Dongting, China

Sharp change of lake levels during the two extreme droughts and its hydroclimatic processes in Lake Dongting, China