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Distributed hydrological models rely on hydrography data such as flow direction, river length, slope and width. For large-scale applications, many of these models still rely on a few flow direction datasets, which are often manually derived. We propose the Iterative Hydrography Upscaling (IHU) method to upscale high-resolution flow direction data to the typically coarser resolutions of distributed hydrological models. The IHU aims to preserve the upstream–downstream relationship of river structure, including basin boundaries, river meanders and confluences, in the D8 format, which is commonly used to describe river networks in models. Additionally, it derives representative sub-grid river length and slope parameters, which are required for resolution-independent model results. We derived the multi-resolution MERIT Hydro IHU dataset at resolutions of 30 arcsec (∼ 1 km), 5 arcmin (∼ 10 km) and 15 arcmin (∼ 30 km) by applying IHU to the recently published 3 arcsec MERIT Hydro data. Results indicate improved accuracy of IHU at all resolutions studied compared to other often-applied upscaling methods. Furthermore, we show that MERIT Hydro IHU minimizes the errors made in the timing and magnitude of simulated peak discharge throughout the Rhine basin compared to simulations at the native data resolutions. As the method is open source and fully automated, it can be applied to other high-resolution hydrography datasets to increase the accuracy and enhance the uptake of new datasets in distributed hydrological models in the future.

The presence of significant biases in real-time radar quantitative precipitation estimations (QPEs) limits its use in hydrometeorological forecasting systems. Here, we introduce CARROTS (Climatology-based Adjustments for Radar Rainfall in an OperaTional Setting), a set of fixed bias reduction factors, which vary per grid cell and day of the year. The factors are based on a historical set of 10 years of 5 min radar and reference rainfall data for the Netherlands. CARROTS is both operationally available and independent of real-time rain gauge availability and can thereby provide an alternative to current QPE adjustment practice. In addition, it can be used as benchmark for QPE algorithm development. We tested this method on the resulting rainfall estimates and discharge simulations for 12 Dutch catchments and polders. We validated the results against the operational mean field bias (MFB)-adjusted rainfall estimates and a reference dataset. This reference consists of the radar QPE, that combines an hourly MFB adjustment and a daily spatial adjustment using observations from 32 automatic and 319 manual rain gauges. Only the automatic gauges of this network are available in real time for the MFB adjustment. The resulting climatological correction factors show clear spatial and temporal patterns. Factors are higher away from the radars and higher from December through March than in other seasons, which is likely a result of sampling above the melting layer during the winter months. The MFB-adjusted QPE outperforms the CARROTS-corrected QPE when the country-average rainfall estimates are compared to the reference. However, annual rainfall sums from CARROTS are comparable to the reference and outperform the MFB-adjusted rainfall estimates for catchments away from the radars, where the MFB-adjusted QPE generally underestimates the rainfall amounts. This difference is absent for catchments closer to the radars. QPE underestimations are amplified when used in the hydrological model simulations. Discharge simulations using the QPE from CARROTS outperform those with the MFB-adjusted product for all but one basin. Moreover, the proposed factor derivation method is robust. It is hardly sensitive to leaving individual years out of the historical set and to the moving window length, given window sizes of more than a week.

Medium-term hydrologic forecast uncertainty is strongly dependent on the forecast quality of meteorological variables. Of these variables, the influence of precipitation has been studied most widely, while temperature, radiative forcing and their derived product potential evapotranspiration (PET) have received little attention from the perspective of hydrological forecasting. This study aims to fill this gap by assessing the usability of potential evaporation forecasts for 10-day-ahead streamflow forecasting in the Rhine basin, Europe. In addition, the forecasts of the meteorological variables are compared with observations. Streamflow reforecasts were performed with the daily wflow_hbv model used in previous studies of the Rhine using the ECMWF 20-year meteorological reforecast dataset. Meteorological forecasts were compared with observed rainfall, temperature, global radiation and potential evaporation for 148 subbasins. Secondly, the effect of using PET climatology versus using observation-based estimates of PET was assessed for hydrological state and for streamflow forecast skill. We find that (1) there is considerable skill in the ECMWF reforecasts to predict PET for all seasons, and (2) using dynamical PET forcing based on observed temperature and satellite global radiation estimates results in lower evaporation and wetter initial states, but (3) the effect on forecasted 10-day streamflow is limited. Implications of this finding are that it is reasonable to use meteorological forecasts to forecast potential evaporation and use this is in medium-range streamflow forecasts. However, it can be concluded that an approach using PET climatology is also sufficient, most probably not only for the application shown here, but also for most models similar to the HBV concept and for moderate climate zones. As a by-product, this research resulted in gridded datasets for temperature, radiation and potential evaporation based on the Makkink equation for the Rhine basin. The datasets have a spatial resolution of 1.2×1.2 km and an hourly time step for the period from July 1996 through 2015. This dataset complements an earlier precipitation dataset for the same area, period and resolution.

Intercatchment groundwater flows (IGFs), defined as groundwater flows across topographic divides, can occur as regional groundwater flows that bypass headwater streams and only drain into the channel further downstream or directly to the sea. However, groundwater flows can also be diverted to adjacent river basins due to geological features (e.g., faults, dipping beds and highly permeable conduits). Even though intercatchment groundwater flows can be a significant part of the water balance, they are often not considered in hydrological studies. Yet, assuming this process to be negligible may introduce misrepresentation of the natural system in hydrological models, for example in regions with complex geological features. The presence of limestone formations in France and Belgium potentially further exacerbates the importance of intercatchment groundwater flows, and thus brings into question the validity of neglecting intercatchment groundwater flows in the Meuse basin. To isolate and quantify the potential relevance of net intercatchment groundwater flows in this study, we propose a three-step approach that relies on the comparison and analysis of (1) observed water balance data within the Budyko framework, (2) results from a suite of different conceptual hydrological models and (3) remote-sensing-based estimates of actual evaporation. The data of 58 catchments in the Meuse basin provide evidence of the likely presence of significant net intercatchment groundwater flows occurring mainly in small headwater catchments underlain by fractured aquifers. The data suggest that the relative importance of net intercatchment groundwater flows is reduced at the scale of the Meuse basin, as regional groundwater flows are mostly expected to be self-contained in large basins. The analysis further suggests that net intercatchment groundwater flow processes vary over the year and that at the scale of the headwaters, net intercatchment groundwater flows can make up a relatively large proportion of the water balance (on average 10 % of mean annual precipitation) and should be accounted for to prevent overestimating actual evaporation rates.

Hydrological modelling in the Canadian sub-Arctic is hindered by sparse meteorological and snowpack data. The snow water equivalent (SWE) of the winter snowpack is a key predictor and driver of spring flow, but the use of SWE data in hydrological applications is limited due to high uncertainty. Global re-analysis datasets that provide gridded meteorological and SWE data may be well suited to improve hydrological assessment and snowpack simulation. To investigate representation of hydrological processes and SWE for application in hydropower operations, global re-analysis datasets covering 1979–2014 from the European Union FP7 eartH2Observe project are applied to global and local conceptual hydrological models. The recently developed Multi-Source Weighted-Ensemble Precipitation (MSWEP) and the WATCH Forcing Data applied to ERA-Interim data (WFDEI) are used to simulate snowpack accumulation, spring snowmelt volume and annual streamflow. The GlobSnow-2 SWE product funded by the European Space Agency with daily coverage from 1979 to 2014 is evaluated against in situ SWE measurement over the local watershed. Results demonstrate the successful application of global datasets for streamflow prediction, snowpack accumulation and snowmelt timing in a snowmelt-driven sub-Arctic watershed. The study was unable to demonstrate statistically significant correlations (p < 0.05) among the measured snowpack, global hydrological model and GlobSnow-2 SWE compared to snowmelt runoff volume or peak discharge. The GlobSnow-2 product is found to under-predict late-season snowpacks over the study area and shows a premature decline of SWE prior to the true onset of the snowmelt. Of the datasets tested, the MSWEP precipitation results in annual SWE estimates that are better predictors of snowmelt volume and peak discharge than the WFDEI or GlobSnow-2. This study demonstrates the operational and scientific utility of the global re-analysis datasets in the sub-Arctic, although knowledge gaps remain in global satellite-based datasets for snowpack representation, for example the relationship between passive-microwave-measured SWE to snowmelt runoff volume.

A portion of globally generated surface and groundwater resources evaporates from wetlands, waterbodies and irrigated areas. This secondary evaporation of blue water directly affects the remaining water resources available for ecosystems and human use. At the global scale, a lack of detailed water balance studies and direct observations limits our understanding of the magnitude and spatial and temporal distribution of secondary evaporation. Here, we propose a methodology to assimilate satellite-derived information into the landscape hydrological model W3 at an unprecedented 0.05°, or ca. 5 km resolution globally. The assimilated data are all derived from MODIS observations, including surface water extent, surface albedo, vegetation cover, leaf area index, canopy conductance and land surface temperature (LST). The information from these products is imparted on the model in a simple but efficient manner, through a combination of direct insertion of the surface water extent, an evaporation flux adjustment based on LST and parameter nudging for the other observations. The resulting water balance estimates were evaluated against river basin discharge records and the water balance of closed basins and demonstrably improved water balance estimates compared to ignoring secondary evaporation (e.g., bias improved from +38 to +2 mm yr−1). The evaporation estimates derived from assimilation were combined with global mapping of irrigation crops to derive a minimum estimate of irrigation water requirements (I0), representative of optimal irrigation efficiency. Our I0 estimates were lower than published country-level estimates of irrigation water use produced by alternative estimation methods, for reasons that are discussed. We estimate that 16 % of globally generated water resources evaporate before reaching the oceans, enhancing total terrestrial evaporation by 6.1×1012 m3 yr−1 or 8.8 %. Of this volume, 5 % is evaporated from irrigation areas, 58 % from terrestrial waterbodies and 37 % from other surfaces. Model-data assimilation at even higher spatial resolutions can achieve a further reduction in uncertainty but will require more accurate and detailed mapping of surface water dynamics and areas equipped for irrigation.

In this study we assess the skill of seasonal streamflow forecasts with the global hydrological forecasting system Flood Early Warning System (FEWS)-World, which has been set up within the European Commission 7th Framework Programme Project Global Water Scarcity Information Service (GLOWASIS). FEWS-World incorporates the distributed global hydrological model PCR-GLOBWB (PCRaster Global Water Balance). We produce ensemble forecasts of monthly discharges for 20 large rivers of the world, with lead times of up to 6 months, forcing the system with bias-corrected seasonal meteorological forecast ensembles from the European Centre for Medium-range Weather Forecasts (ECMWF) and with probabilistic meteorological ensembles obtained following the ESP procedure. Here, the ESP ensembles, which contain no actual information on weather, serve as a benchmark to assess the additional skill that may be obtained using ECMWF seasonal forecasts. We use the Brier skill score (BSS) to quantify the skill of the system in forecasting high and low flows, defined as discharges higher than the 75th and lower than the 25th percentiles for a given month, respectively. We determine the theoretical skill by comparing the results against model simulations and the actual skill in comparison to discharge observations. We calculate the ratios of actual-to-theoretical skill in order to quantify the percentage of the potential skill that is achieved. The results suggest that the performance of ECMWF S3 forecasts is close to that of the ESP forecasts. While better meteorological forecasts could potentially lead to an improvement in hydrological forecasts, this cannot be achieved yet using the ECMWF S3 dataset.

Abstract Although Essential Climate Variables (ECVs) have been widely adopted as important metrics for guiding scientific and policy decisions, the Earth Observation (EO) and Land Surface and Hydrologic Model (LSM/HM) communities have yet to treat terrestrial ECVs in an integrated manner. To develop consistent terrestrial ECVs at regional and continental scales, greater collaboration between EO and LSM/HM communities is needed. An essential first step is assessing the LSM/HM simulation uncertainty. To that end, we introduce a new hydrological reference dataset that comprises a range of 19 existing LSM/HM simulations that represent the current state-of-the-art of our LSM/HMs. Simulations are provided on a daily time step, covering Europe, notably the Rhine and Po river basins, alongside the Tugela river basin in Africa, and are uniformly formatted to allow comparisons across simulations. Furthermore, simulations are comprehensively validated with discharge, evapotranspiration, soil moisture and total water storage anomaly observations. Our dataset provides valuable information to support policy development and serves as a benchmark for generating consistent terrestrial ECVs through the integration of EO products.

Abstract The neurohormone oxytocin (OT) has been proposed as a treatment for alcohol and nicotine use disorders. The aim of the present study was to examine whether intravenous (IV) OT decreases alcohol oral self-administration and consumption in nonhuman primates under a 6-h alcohol access procedure as well as alcohol and nicotine (IV) self-administration under 6-h concurrent access conditions. The subjects were five male baboons (Papio anubis) that self-administered oral alcohol (4% w/v) during 6-h sessions under a fixed ratio 3 (FR3) schedule per drink. Baseline levels of alcohol self-administration were established and then OT treatment was initiated. A single dose of OT (20, 40, 80, 120 IU, IV) or its vehicle (saline) was administered before and again in the middle of the 6-h drinking session for 5 consecutive days (total oxytocin dose of 40, 80, 160, 240 IU/day). After each 5-day treatment, baseline levels of alcohol self-administration were reestablished before the next 5-day OT treatment. In addition, the effect of OT on concurrent alcohol and IV nicotine self-administration was explored in 3 of the baboons where alcohol and nicotine were concurrently available during the 6-hr session each under an FR3 schedule for each drug. Establishment of baseline self-administration and 5-day OT treatments were completed as in the alcohol only study. There was a significant overall reduction in alcohol consumption with OT compared to placebo. On post-hoc analysis, after correcting for multiple comparisons, the 40 and 80 IU doses of OT significantly reduced alcohol consumption compared with vehicle, and consumption did not vary significantly within each 5-day treatment period. OT, qualitatively, also reduced the coadministration of both alcohol and nicotine in each baboon for at least one of the OT doses administered. These results underscore the therapeutic potential of oxytocin as a treatment of alcohol use disorder and possibly, co-use of nicotine.

The e-Science environment developed in the framework of the EU-funded DRIHM project was used to demonstrate its ability to provide relevant, meaningful hydrometeorological forecasts. This was illustrated for the tragic case of 4 November 2011, when Genoa, Italy, was flooded as the result of heavy, convective precipitation that inundated the Bisagno catchment. The Meteorological Model Bridge (MMB), an innovative software component developed within the DRIHM project for the interoperability of meteorological and hydrological models, is a key component of the DRIHM e-Science environment. The MMB allowed three different rainfall-discharge models (DRiFt, RIBS and HBV) to be driven by four mesoscale limited-area atmospheric models (WRF-NMM, WRF-ARW, Meso-NH and AROME) and a downscaling algorithm (RainFARM) in a seamless fashion. In addition to this multi-model configuration, some of the models were run in probabilistic mode, thus giving a comprehensive account of modelling errors and a very large amount of likely hydrometeorological scenarios (> 1500). The multi-model approach proved to be necessary because, whilst various aspects of the event were successfully simulated by different models, none of the models reproduced all of these aspects correctly. It was shown that the resulting set of simulations helped identify key atmospheric processes responsible for the large rainfall accumulations over the Bisagno basin. The DRIHM e-Science environment facilitated an evaluation of the sensitivity to atmospheric and hydrological modelling errors. This showed that both had a significant impact on predicted discharges, the former being larger than the latter. Finally, the usefulness of the set of hydrometeorological simulations was assessed from a flash flood early-warning perspective.

The wflow_sbm hydrological model, recently released by Deltares, as part of the Wflow.jl (v0.7.3) modelling framework, is being used to better understand and potentially address multiple operational and water resource planning challenges from a catchment scale to national scale to continental and global scale. Wflow.jl is a free and open-source distributed hydrological modelling framework written in the Julia programming language. The development of wflow_sbm, the model structure, equations and functionalities are described in detail, including example applications of wflow_sbm. The wflow_sbm model aims to strike a balance between low-resolution, low-complexity and high-resolution, high-complexity hydrological models. Most wflow_sbm parameters are based on physical characteristics or processes, and at the same time wflow_sbm has a runtime performance well suited for large-scale high-resolution model applications. Wflow_sbm models can be set a priori for any catchment with the Python tool HydroMT-Wflow based on globally available datasets and through the use of point-scale (pedo)transfer functions and suitable upscaling rules and generally result in a satisfactory (0.4 ≥ Kling–Gupta efficiency (KGE) < 0.7) to good (KGE ≥ 0.7) performance for discharge a priori (without further tuning). Wflow_sbm includes relevant hydrological processes such as glacier and snow processes, evapotranspiration processes, unsaturated zone dynamics, (shallow) groundwater, and surface flow routing including lakes and reservoirs. Further planned developments include improvements on the computational efficiency and flexibility of the routing scheme, implementation of a water demand and allocation module for water resource modelling, the addition of a deep groundwater concept, and computational efficiency improvements through for example distributed computing and graphics processing unit (GPU) acceleration.

No abstract available.

A 2.5-year-old female entire Pomeranian dog was presented for acute paraparesis progressing within 2 days to paraplegia. General physical examination was unremarkable. Neurological examination showed paraplegia without nociception, a mass reflex upon testing perineal reflexes and withdrawal reflexes in the pelvic limbs and patellar hyperreflexia. Cutaneous trunci reflexes were absent caudal to the level of the 6th thoracic vertebra. Spinal hyperesthesia was present. Neuroanatomical localization was consistent with a T3-L3 myelopathy. Hematological and biochemical blood tests [including C-reactive protein (CRP)] were within reference ranges. MRI of the spinal cord from the level of the 1st thoracic vertebra to the sacrum revealed a patchy, ill-defined, moderate to marked T2W hyperintense, contrast enhancing intramedullary lesion extending from T1 to L4. Medical treatment based on a working diagnosis of meningomyelitis of unknown cause was initiated with corticosteroids and methadone based on pain scores. Prognosis was grave and after 3 days without return of nociception, the dog was euthanized according to the owners’ wishes. Post-mortem histopathological examination of the brain and spinal cord yielded a morphological diagnosis of severe, segmental, bilateral and fairly symmetrical, necrotizing lymphohistiocytic leukomyelitis, with a non-suppurative angiocentric leptomeningitis. Some minor, focal, lymphocytic perivascular cuffing was found in the medulla oblongata as well, but otherwise there were no signs of brain involvement. No infectious causes were identified with ancillary tests. This case report underlines the importance of including meningomyelitis in the differential diagnosis list of dogs presented for acute progressive neurological signs referable to a myelopathy.

ABSTRACT: In broiler chickens, fractures of wings and legs are recorded at poultry slaughterhouses based on the time of occurrence. Prekilling (PRE) fractures occur before the death of animal, so the chicken was still able to experience pain and distress associated with the injury (an animal welfare issue). Postkilling (POST) fractures occur when the chickens are deceased and fully bled-out and consequently unable to feel pain (not an animal welfare issue). Current practice dictates that fractures are recognized visually and recorded by the animal welfare officers as mandated by European Union and/or national regulations. However, new potential monitoring solutions are desired since human inspection suffers from some significant limitations including subjectivism and fatigue. One possible solution in detecting injuries is X-ray computed tomography (CT) scanning and in this study we aim to evaluate the potential of CT scanning and visual inspection in detecting limb fractures and their causes. Eighty-three chicken wings and 60 chicken legs (n = 143) were collected from a single slaughterhouse and classified by an animal welfare officer as PRE, POST or healthy (HEAL). Samples were photographed and CT scanned at a veterinary hospital. The interpretation of CT scans along with photographs took place in 3 rounds (1. CT scans only, 2. CT scans + photographs, 3. photographs only) and was performed independently by 3 veterinarians. The consistency of the interpretation in 3 rounds was compared with the animal welfare officer's classification. Furthermore, selected samples were also analyzed by histopathological examination due to questionability of their classification (PRE/POST). In questionable samples, presence of hemorrhages was confirmed, thus they fit better as PRE. The highest consistency between raters was obtained in the 2nd round, indicating that interpretation accuracy was the highest when CT scans were combined with photographs. These results indicate that CT scanning in combination with visual inspection can be used in detecting limbs fracture and potentially applied as a tool to monitor animal welfare in poultry slaughterhouses in the future.

The potential role of the transient receptor potential Vanilloid 1 (TRPV1) non-selective cation channel in gastric carcinogenesis remains unclear. The main objective of this study was to evaluate TRPV1 expression in gastric cancer (GC) and precursor lesions compared with controls. Patient inclusion was based on a retrospective review of pathology records. Patients were subdivided into five groups: Helicobacter pylori (H. pylori)-associated gastritis with gastric intestinal metaplasia (GIM) (n = 12), chronic atrophic gastritis (CAG) with GIM (n = 13), H. pylori-associated gastritis without GIM (n = 19), GC (n = 6) and controls (n = 5). TRPV1 expression was determined with immunohistochemistry and was significantly higher in patients with H. pylori-associated gastritis compared with controls (p = 0.002). TRPV1 expression was even higher in the presence of GIM compared with patients without GIM and controls (p < 0.001). There was a complete loss of TRPV1 expression in patients with GC. TRPV1 expression seems to contribute to gastric-mucosal inflammation and precursors of GC, which significantly increases in cancer precursor lesions but is completely lost in GC. These findings suggest TRPV1 expression to be a potential marker for precancerous conditions and a target for individualized treatment. Longitudinal studies are necessary to further address the role of TRPV1 in gastric carcinogenesis.

Creating sustainable revenue streams to support community engagement is critical to building engaged colleges and universities. Drawing on social cognition theories within the organizational science literature, this article explores how community engagement professionals (CEPs) can promote sensemaking and organizational learning in ways that promote engagement as a pathway to institutional sustainability. Specifically, this article explores ways in which engagement can be positioned to differentiate institutions from their competitors, attract enrollment, and bolster public and private support for an institution. Toward these ends, this article makes connections among campus engagement identity, retention and completion, enrollment management, state relations, grant-writing strategy, advancement/alumni relations, and marketing and communications. Practical tools are provided to help CEPs lead strategic conversations about engagement as a means to promote institutional health and vitality.