155 research outputs found

    Cascade-based disaggregation of continuous rainfall time series: the influence of climate

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    International audienceRainfall data of high temporal resolution are required in a multitude of hydrological applications. In the present paper, a temporal rainfall disaggregation model is applied to convert daily time series into an hourly resolution. The model is based on the principles of random multiplicative cascade processes. Its parameters are dependent on (1) the volume and (2) the position in the rainfall sequence of the time interval with rainfall to be disaggregated. The aim is to compare parameters and performance of the model between two contrasting climates with different rainfall generating mechanisms, a semi-arid tropical (Brazil) and a temperate (United Kingdom) climate. In the range of time scales studied, the scale-invariant assumptions of the model are approximately equally well fulfilled for both climates. The model parameters differ distinctly between climates, reflecting the dominance of convective processes in the Brazilian rainfall and of advective processes associated with frontal passages in the British rainfall. In the British case, the parameters exhibit a slight seasonal variation consistent with the higher frequency of convection during summer. When applied for disaggregation, the model reproduces a range of hourly rainfall characteristics with a high accuracy in both climates. However, the overall model performance is somewhat better for the semi-arid tropical rainfall. In particular, extreme rainfall in the UK is overestimated whereas extreme rainfall in Brazil is well reproduced. Transferability of parameters in time is associated with larger uncertainty in the semi-arid climate due to its higher interannual variability and lower percentage of rainy intervals. For parameter transferability in space, no restrictions are found between the Brazilian stations whereas in the UK regional differences are more pronounced. The overall high accuracy of disaggregated data supports the potential usefulness of the model in hydrological applications. Keywords: Rainfall, temporal disaggregation, random cascade, scaling, semi-arid, temperate climate

    ENSO impact on simulated South American hydro-climatology

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    The variability of the simulated hydro-climatology of the WaterGAP Global Hydrology Model (WGHM) is analysed. Main object of this study is the ENSO-driven variability of the water storage of South America. The horizontal model resolution amounts to 0.5 degree and it is forced with monthly climate variables for 1961-1995 of the Tyndall Centre Climate Research Unit dataset (CRU TS 2.0) as a representation of the observed climate state. Secondly, the model is also forced by the model output of a global circulation model, the ECHAM4-T42 GCM. This model itself is driven by observed monthly means of the global Sea Surface Temperatures (SST) and the sea ice coverage for the period of 1903 to 1994 (GISST). Thus, the climate model and the hydrological model represent a realistic simulated realisation of the hydro-climatologic state of the last century. Since four simulations of the ECHAM4 model with the same forcing, but with different initial conditions are carried out, an analysis of variance (ANOVA) gives an impression of the impact of the varying SST on the hydro-climatology, because the variance can be separated into a SST-explained and a model internal variability (noise). Also regional multivariate analyses, like Empirical Orthogonal Functions (EOF) and Canonical Correlation Analysis (CCA) provide information of the complex time-space variability. In particular the Amazon region and the South of Brazil are significantly influenced by the ENSO-variability, but also the Pacific coastal areas of Ecuador and Peru are affected. Additionally, different ENSO-indices, based on SST anomalies (e.g. NINO3.4, NINO1+2), and its influence on the South American hydro-climatology are analysed. Especially, the Pacific coast regions of Ecuador, Peru and Chile show a very different behaviour dependant on those indices

    The importance of vegetation in understanding terrestrial water storage variations

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    Funding Information: The article processing charges for this openaccess publication were covered by the Max Planck Society. Publisher Copyright: © 2022 Tina Trautmann et al.So far, various studies have aimed at decomposing the integrated terrestrial water storage variations observed by satellite gravimetry (GRACE, GRACE-FO) with the help of large-scale hydrological models. While the results of the storage decomposition depend on model structure, little attention has been given to the impact of the way that vegetation is represented in these models. Although vegetation structure and activity represent the crucial link between water, carbon, and energy cycles, their representation in large-scale hydrological models remains a major source of uncertainty. At the same time, the increasing availability and quality of Earth-observation-based vegetation data provide valuable information with good prospects for improving model simulations and gaining better insights into the role of vegetation within the global water cycle. In this study, we use observation-based vegetation information such as vegetation indices and rooting depths for spatializing the parameters of a simple global hydrological model to define infiltration, root water uptake, and transpiration processes. The parameters are further constrained by considering observations of terrestrial water storage anomalies (TWS), soil moisture, evapotranspiration (ET) and gridded runoff (Q) estimates in a multi-criteria calibration approach. We assess the implications of including varying vegetation characteristics on the simulation results, with a particular focus on the partitioning between water storage components. To isolate the effect of vegetation, we compare a model experiment in which vegetation parameters vary in space and time to a baseline experiment in which all parameters are calibrated as static, globally uniform values. Both experiments show good overall performance, but explicitly including varying vegetation data leads to even better performance and more physically plausible parameter values. The largest improvements regarding TWS and ET are seen in supply-limited (semi-arid) regions and in the tropics, whereas Q simulations improve mainly in northern latitudes. While the total fluxes and storages are similar, accounting for vegetation substantially changes the contributions of different soil water storage components to the TWS variations. This suggests an important role of the representation of vegetation in hydrological models for interpreting TWS variations. Our simulations further indicate a major effect of deeper moisture storages and groundwater-soil moisture-vegetation interactions as a key to understanding TWS variations. We highlight the need for further observations to identify the adequate model structure rather than only model parameters for a reasonable representation and interpretation of vegetation-water interactions.publishersversionpublishe

    A change in perspective: downhole cosmic-ray neutron sensing for the estimation of soil moisture

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    Above-ground cosmic-ray neutron sensing (CRNS) allows for the non-invasive estimation of the field-scale soil moisture content in the upper decimetres of the soil. However, large parts of the deeper vadose zone remain outside of its observational window. Retrieving soil moisture information from these deeper layers requires extrapolation, modelling or other methods, all of which come with methodological challenges. Against this background, we investigate CRNS for downhole soil moisture measurements in deeper layers of the vadose zone. To render calibration with in situ soil moisture measurements unnecessary, we rescaled neutron intensities observed below the terrain surface with intensities measured above a waterbody. An experimental set-up with a CRNS sensor deployed at different depths of up to 10 m below the surface in a groundwater observation well combined with particle transport simulations revealed the response of downhole thermal neutron intensities to changes in the soil moisture content at the depth of the downhole neutron detector as well as in the layers above it. The simulation results suggest that the sensitive measurement radius of several decimetres, which depends on soil moisture and soil bulk density, exceeds that of a standard active neutron probe (which is only about 30 cm). We derived transfer functions to estimate downhole neutron signals from soil moisture information, and we describe approaches for using these transfer functions in an inverse way to derive soil moisture from the observed neutron signals. The in situ neutron and soil moisture observations confirm the applicability of these functions and prove the concept of passive downhole soil moisture estimation, even at larger depths, using cosmic-ray neutron sensing.</p

    Delayed subsidence of the Dead Sea shore due to hydro-meteorological changes

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    Many studies show the sensitivity of our environment to manmade changes, especially the anthropogenic impact on atmospheric and hydrological processes. The effect on Solid Earth processes such as subsidence is less straightforward. Subsidence is usually slow and relates to the interplay of complex hydro-mechanical processes, thus making relations to atmospheric changes difficult to observe. In the Dead Sea (DS) region, however, climatic forcing is strong and over-use of fresh water is massive. An observation period of 3 years was thus sufficient to link the high evaporation (97 cm/year) and the subsequent drop of the Dead Sea lake level (− 110 cm/year), with high subsidence rates of the Earth’s surface (− 15 cm/year). Applying innovative Global Navigation Satellite System (GNSS) techniques, we are able to resolve this subsidence of the “Solid Earth” even on a monthly basis and show that it behaves synchronous to atmospheric and hydrological changes with a time lag of two months. We show that the amplitude and fluctuation period of ground deformation is related to poro-elastic hydro-mechanical soil response to lake level changes. This provides, to our knowledge, a first direct link between shore subsidence, lake-level drop and evaporation

    The Electrophilicity of Surface Carbon Species in the Redox Reactions of CuO‐CeO<sub>2</sub> Catalysts

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    Electronic metal–support interactions (EMSI) describe the electron flow between metal sites and a metal oxide support. It is generally used to follow the mechanism of redox reactions. In this study of CuO‐CeO2 redox, an additional flow of electrons from metallic Cu to surface carbon species is observed via a combination of operando X‐ray absorption spectroscopy, synchrotron X‐ray powder diffraction, near ambient pressure near edge X‐ray absorption fine structure spectroscopy, and diffuse reflectance infrared Fourier transform spectroscopy. An electronic metal–support–carbon interaction (EMSCI) is proposed to explain the reaction pathway of CO oxidation. The EMSCI provides a complete picture of the mass and electron flow, which will help predict and improve the catalytic performance in the selective activation of CO2, carbonate, or carbonyl species in C1 chemistry

    Mass-change And Geosciences International Constellation (MAGIC) expected impact on science and applications

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    Summary The joint ESA/NASA Mass-change And Geosciences International Constellation (MAGIC) has the objective to extend time series from previous gravity missions, including an improvement of accuracy and spatio-temporal resolution. The long-term monitoring of Earth’s gravity field carries information on mass-change induced by water cycle, climate change, and mass transport processes between atmosphere, cryosphere, oceans and solid Earth. MAGIC will be composed of two satellite pairs flying in different orbit planes. The NASA/DLR–led first pair (P1) is expected to be in a near-polar orbit around 500 km of altitude; while the second ESA–led pair (P2) is expected to be in an inclined orbit of 65–70 degrees at approximately 400 km altitude. The ESA–led pair P2 Next Generation Gravity Mission (NGGM) shall be launched after P1 in a staggered manner to form the MAGIC constellation. The addition of an inclined pair shall lead to reduction of temporal aliasing effects and consequently of reliance on de-aliasing models and post-processing. The main novelty of the MAGIC constellation is the delivery of mass-change products at higher spatial resolution, temporal (i.e. sub–weekly) resolution, shorter latency, and higher accuracy than GRACE and GRACE-FO. This will pave the way to new science applications and operational services. In this article, an overview of various fields of science and service applications for hydrology, cryosphere, oceanography, solid Earth, climate change and geodesy is provided. These thematic fields and newly enabled applications and services were analysed in the frame of the initial ESA Science Support activities for MAGIC. The analyses of MAGIC scenarios for different application areas in the field of geosciences confirmed that the double-pair configuration will significantly enlarge the number of observable mass-change phenomena by resolving smaller spatial scales with an uncertainty that satisfies evolved user requirements expressed by international bodies such as IUGG. The required uncertainty levels of dedicated thematic fields met by MAGIC unfiltered Level-2 products will benefit hydrological applications by recovering more than 90% of the major river basins worldwide at 260 km spatial resolution, cryosphere applications by enabling mass change signal separation in the interior of Greenland from those in the coastal zones and by resolving small-scale mass variability in challenging regions such as the Antarctic Peninsula, oceanography applications by monitoring meridional overturning circulation changes on time scales of years and decades, climate applications by detecting amplitude and phase changes of Terrestrial Water Storage (TWS) after 30 years in 64% and 56% of the global land areas and solid Earth applications by lowering the Earthquake detection threshold from magnitude 8.8 to magnitude 7.4 with spatial resolution increased to 333 km.</jats:p
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