Impact of climate change on the stream flow of the lower Brahmaputra: Trends in high and low flows based on discharge-weighted ensemble modelling

Climate change is likely to have significant effects on the hydrology. The Ganges-Brahmaputra river basin is one of the most vulnerable areas in the world as it is subject to the combined effects of glacier melt, extreme monsoon rainfall and sea level rise. To what extent climate change will impact river flow in the Brahmaputra basin is yet unclear, as climate model studies show ambiguous results. In this study we investigate the effect of climate change on both low and high flows of the lower Brahmaputra. We apply a novel method of discharge-weighted ensemble modeling using model outputs from a global hydrological models forced with 12 different global climate models (GCMs). Our analysis shows that only a limited number of GCMs are required to reconstruct observed discharge. Based on the GCM outputs and long-term records of observed flow at Bahadurabad station, our method results in a multi-model weighted ensemble of transient stream flow for the period 1961-2100. Using the constructed transients, we subsequently project future trends in low and high river flow. The analysis shows that extreme low flow conditions are likely to occur less frequent in the future. However a very strong increase in peak flows is projected, which may, in combination with projected sea level change, have devastating effects for Bangladesh. The methods presented in this study are more widely applicable, in that existing multi-model streamflow simulations from global hydrological models can be weighted against observed streamflow data to assess at first order the effects of climate change for specific river basins. © Author(s) 2011

Международно-правовое регулирование труда трудящихся мигрантов на универсальном уровне

Раскрываются особенности правовых актов МОТ, которые отличают данные акты от документов других специализированных учреждений ООН и международных договоров в области прав человека, принятых Генеральной Ассамблеей ООН.Analyse, it is necessary to open in brief at first features of legal acts of ILO, which distinguish the given acts from documents of other specialised institutions of the United Nations and the international contracts in human rights sphere accepted by the United Nations General Assembl

Global patterns of change in discharge regimes for 2100

This study makes a thorough global assessment of the effects of climate change on hydrological regimes and their accompanying uncertainties. Meteorological data from twelve GCMs (SRES scenarios A1B and control experiment 20C3M) are used to drive the global hydrological model PCR-GLOBWB. This reveals in which regions of the world changes in hydrology can be detected that have a high likelihood and are consistent amongst the ensemble of GCMs. New compared to existing studies is: (1) the comparison of spatial patterns of regime changes and (2) the quantification of notable consistent changes calculated relative to the GCM specific natural variability. The resulting consistency maps indicate in which regions the likelihood of hydrological change is large. <br><br> Projections of different GCMs diverge widely. This underscores the need of using a multi-model ensemble. Despite discrepancies amongst models, consistent results are revealed: by 2100 the GCMs project consistent decreases in discharge for southern Europe, southern Australia, parts of Africa and southwestern South-America. Discharge decreases strongly for most African rivers, the Murray and the Danube while discharge of monsoon influenced rivers slightly increases. In the Arctic regions river discharge increases and a phase-shift towards earlier peaks is observed. Results are comparable to previous global studies, with a few exceptions. Globally we calculated an ensemble mean discharge increase of more than ten percent. This increase contradicts previously estimated decreases, which is amongst others caused by the use of smaller GCM ensembles and different reference periods

Selecting the optimal method to calculate daily global reference potential evaporation from CFSR reanalysis data for application in a hydrological model study

Potential evaporation (PET) is one of the main inputs of hydrological models. Yet, there is limited consensus on which PET equation is most applicable in hydrological climate impact assessments. In this study six different methods to derive global scale reference PET daily time series from Climate Forecast System Reanalysis (CFSR) data are compared: Penman-Monteith, Priestley-Taylor and original and re-calibrated versions of the Hargreaves and Blaney-Criddle method. The calculated PET time series are (1) evaluated against global monthly Penman-Monteith PET time series calculated from CRU data and (2) tested on their usability for modeling of global discharge cycles. <br><br> A major finding is that for part of the investigated basins the selection of a PET method may have only a minor influence on the resulting river flow. Within the hydrological model used in this study the bias related to the PET method tends to decrease while going from PET, AET and runoff to discharge calculations. However, the performance of individual PET methods appears to be spatially variable, which stresses the necessity to select the most accurate and spatially stable PET method. The lowest root mean squared differences and the least significant deviations (95% significance level) between monthly CFSR derived PET time series and CRU derived PET were obtained for a cell-specific re-calibrated Blaney-Criddle equation. However, results show that this re-calibrated form is likely to be unstable under changing climate conditions and less reliable for the calculation of daily time series. Although often recommended, the Penman-Monteith equation applied to the CFSR data did not outperform the other methods in a evaluation against PET derived with the Penman-Monteith equation from CRU data. In arid regions (e.g. Sahara, central Australia, US deserts), the equation resulted in relatively low PET values and, consequently, led to relatively high discharge values for dry basins (e.g. Orange, Murray and Zambezi). Furthermore, the Penman-Monteith equation has a high data demand and the equation is sensitive to input data inaccuracy. Therefore, we recommend the re-calibrated form of the Hargreaves equation which globally gave reference PET values comparable to CRU derived values for multiple climate conditions. <br><br> The resulting gridded daily PET time series provide a new reference dataset that can be used for future hydrological impact assessments in further research, or more specifically, for the statistical downscaling of daily PET derived from raw GCM data. The dataset can be downloaded from <a href ="http://opendap.deltares.nl/thredds/dodsC/opendap/deltares/FEWS-IPCC"target="_blank">http://opendap.deltares.nl/thredds/dodsC/opendap/deltares/FEWS-IPCC</a>

Significant uncertainty in global scale hydrological modeling from precipitation data errors

In the past decades significant progress has been made in the fitting of hydrologic models to data. Most of this work has focused on simple, CPU-efficient, lumped hydrologic models using discharge, water table depth, soil moisture, or tracer data from relatively small river basins. In this paper, we focus on large-scale hydrologic modeling and analyze the effect of parameter and rainfall data uncertainty on simulated discharge dynamics with the global hydrologic model PCR-GLOBWB. We use three rainfall data products; the CFSR reanalysis, the ERA-Interim reanalysis, and a combined ERA-40 reanalysis and CRU dataset. Parameter uncertainty is derived from Latin Hypercube Sampling (LHS) using monthly discharge data from five of the largest river systems in the world. Our results demonstrate that the default parameterization of PCR-GLOBWB, derived from global datasets, can be improved by calibrating the model against monthly discharge observations. Yet, it is difficult to find a single parameterization of PCR-GLOBWB that works well for all of the five river basins considered herein and shows consistent performance during both the calibration and evaluation period. Still there may be possibilities for regionalization based on catchment similarities. Our simulations illustrate that parameter uncertainty constitutes only a minor part of predictive uncertainty. Thus, the apparent dichotomy between simulations of global-scale hydrologic behavior and actual data cannot be resolved by simply increasing the model complexity of PCR-GLOBWB and resolving sub-grid processes. Instead, it would be more productive to improve the characterization of global rainfall amounts at spatial resolutions of 0.5° and smaller

Significant uncertainty in global scale hydrological modeling from precipitation data errors

In the past decades significant progress has been made in the fitting of hydrologic models to data. Most of this work has focused on simple, CPU-efficient, lumped hydrologic models using discharge, water table depth, soil moisture, or tracer data from relatively small river basins. In this paper, we focus on large-scale hydrologic modeling and analyze the effect of parameter and rainfall data uncertainty on simulated discharge dynamics with the global hydrologic model PCR-GLOBWB. We use three rainfall data products; the CFSR reanalysis, the ERA-Interim reanalysis, and a combined ERA-40 reanalysis and CRU dataset. Parameter uncertainty is derived from Latin Hypercube Sampling (LHS) using monthly discharge data from five of the largest river systems in the world. Our results demonstrate that the default parameterization of PCR-GLOBWB, derived from global datasets, can be improved by calibrating the model against monthly discharge observations. Yet, it is difficult to find a single parameterization of PCR-GLOBWB that works well for all of the five river basins considered herein and shows consistent performance during both the calibration and evaluation period. Still there may be possibilities for regionalization based on catchment similarities. Our simulations illustrate that parameter uncertainty constitutes only a minor part of predictive uncertainty. Thus, the apparent dichotomy between simulations of global-scale hydrologic behavior and actual data cannot be resolved by simply increasing the model complexity of PCR-GLOBWB and resolving sub-grid processes. Instead, it would be more productive to improve the characterization of global rainfall amounts at spatial resolutions of 0.5° and smaller

A global water resources ensemble of hydrological models: the eartH2Observe Tier-1 dataset

The dataset presented here consists of an ensemble of 10 global hydrological and land surface models for the period 1979–2012 using a reanalysis-based meteorological forcing dataset (0.5° resolution). The current dataset serves as a state of the art in current global hydrological modelling and as a benchmark for further improvements in the coming years. A signal-to-noise ratio analysis revealed low inter-model agreement over (i) snow-dominated regions and (ii) tropical rainforest and monsoon areas. The large uncertainty of precipitation in the tropics is not reflected in the ensemble runoff. Verification of the results against benchmark datasets for evapotranspiration, snow cover, snow water equivalent, soil moisture anomaly and total water storage anomaly using the tools from The International Land Model Benchmarking Project (ILAMB) showed overall useful model performance, while the ensemble mean generally outperformed the single model estimates. The results also show that there is currently no single best model for all variables and that model performance is spatially variable. In our unconstrained model runs the ensemble mean of total runoff into the ocean was 46 268 km3 yr−1 (334 kg m−2 yr−1), while the ensemble mean of total evaporation was 537 kg m−2 yr−1. All data are made available openly through a Water Cycle Integrator portal (WCI, wci.earth2observe.eu), and via a direct http and ftp download. The portal follows the protocols of the open geospatial consortium such as OPeNDAP, WCS and WMS. The DOI for the data is https://doi.org/10.1016/10.5281/zenodo.167070

Over- and Misuse of Antibiotics and the Clinical Consequence in Necrotizing Pancreatitis:An Observational Multicenter Study

OBJECTIVE: The use and impact of antibiotics and the impact of causative pathogens on clinical outcomes in a large real-world cohort covering the entire clinical spectrum of necrotizing pancreatitis remain unknown. SUMMARY BACKGROUND DATA: International guidelines recommend broad-spectrum antibiotics in patients with suspected infected necrotizing pancreatitis. This recommendation is not based on high-level evidence and clinical effects are unknown. METHODS: This study is a post-hoc analysis of a nationwide prospective cohort of 401 patients with necrotizing pancreatitis in 15 Dutch centers (2010-2019). Across the patient population from time of admission to 6 months post admission, multivariable regression analyses were used to analyze (1) microbiological cultures and (2) the antibiotic use. RESULTS: Antibiotics were started in 321/401 patients (80%) administered at a median of 5 days (P25-P75: 1-13) after admission. Median duration of antibiotics was 27 days (P25-P75: 15-48). In 221/321 patients (69%) infection was not proven by cultures at time of initiation of antibiotics. Empirical antibiotics for infected necrosis provided insufficient coverage in 64/128 patients (50%) with a pancreatic culture. Prolonged antibiotic therapy was associated with Enterococcus infection (OR1.08 [95%CI 1.03-1.16], P=0.01). Enterococcus infection was associated with new/persistent organ failure (OR3.08 [95%CI 1.35-7.29], P<0.01) and mortality (OR5.78 [95% CI 1.46-38.73], P=0.03). Yeast were found in 30/147 cultures (20%). DISCUSSION: In this nationwide study of patients with necrotizing pancreatitis, the vast majority received antibiotics, typically administered early in the disease course and without a proven infection. Empirical antibiotics were inappropriate based on pancreatic cultures in half the patients. Future clinical research and practice must consider antibiotic selective pressure due to prolonged therapy, coverage of Enterococcus and yeast. Improved guidelines on antimicrobial diagnostics and therapy could reduce inappropriate antibiotic use and improve clinical outcomes

The geography of future water challenges: Bending the trend

Industrial EcologyEnvironmental Biolog