Observational and predictive uncertainties for multiple variables in a spatially distributed hydrological model

In this study, uncertainty in model input data (precipitation) and parameters is propagated through a physically based, spatially distributed hydrological model based on the MIKE SHE code. Precipitation uncertainty is accounted for using an ensemble of daily rainfall fields that incorporate four different sources of uncertainty, whereas parameter uncertainty is considered using Latin hypercube sampling. Model predictive uncertainty is assessed for multiple simulated hydrological variables (discharge, groundwater head, evapotranspiration, and soil moisture). Utilizing an extensive set of observational data, effective observational uncertainties for each hydrological variable are assessed. Considering not only model predictive uncertainty but also effective observational uncertainty leads to a notable increase in the number of instances, for which model simulation and observations are in good agreement (e.g., 47% vs. 91% for discharge and 0% vs. 98% for soil moisture). Effective observational uncertainty is in several cases larger than model predictive uncertainty. We conclude that the use of precipitation uncertainty with a realistic spatio‐temporal correlation structure, analyses of multiple variables with different spatial support, and the consideration of observational uncertainty are crucial for adequately evaluating the performance of physically based, spatially distributed hydrological models.     

Trend analysis for rainfall in Delhi and Mumbai, India

Urbanisation has burdened cities with many problems associated with growth and the physical environment. Some of the urban locations in India are becoming increasingly vulnerable to natural hazards related to precipitation and flooding. Thus it becomes increasingly important to study the characteristics of these events and their physical explanation. This work studies rainfall trends in Delhi and Mumbai, the two biggest Metropolitan cities of Republic of India, during the period from 1951 to 2004. Precipitation data was studied on basis of months, seasons and years, and the total period divided in the two different time periods of 1951–1980 and 1981–2004 for detailed analysis. Long-term trends in rainfall were determined by Man-Kendall rank statistics and linear regression. Further this study seeks for an explanation for precipitation trends during monsoon period by different global climate phenomena. Principal component analysis and Singular value decomposition were used to find relation between southwest monsoon precipitation and global climatic phenomena using climatic indices. Most of the rainfall at both the stations was found out to be taking place in Southwest monsoon season. The analysis revealed great degree of variability in precipitation at both stations. There is insignificant decrease in long term southwest monsoon rainfall over Delhi and slight significant decreasing trends for long term southwest monsoon rainfall in Mumbai. Decrease in average maximum rainfall in a day was also indicated by statistical analysis for both stations. Southwest monsoon precipitation in Delhi was found directly related to Scandinavian Pattern and East Atlantic/West Russia and inversely related to Pacific Decadal Oscillation, whereas precipitation in Mumbai was found inversely related to Indian ocean dipole, El Ni?o- Southern Oscillation and East Atlantic Pattern.     

Efficiency of mixing by a turbulent jet in a stably stratified fluid

Mixing in a two-layer stably stratified fluid by a turbulent jet was studied by a laboratory experiment. A non-swirling jet was discharged vertically downwards in a confined fluid system consisting initially of a top layer of fresh water and a bottom layer of salt water. In total, 16 experimental cases were considered, where the diameter and exit velocity of the jet were varied together with the density difference between the top and bottom layer. Vertical density profiles were determined from conductivity measurements. A three-layer density structure developed in all cases with an intermediate layer that grew in size with time elapsed as fresh and salt water were mixed. The mixing efficiency, defined as the percentage of the supplied kinetic jet energy that is used for increasing the potential energy of the fluid system, was related to a densimetric Froude number based on the intermediate layer depth. Overall, the calculated jet mixing efficiency displayed higher values than comparable efficiencies for destratification with air-bubble plumes.     

Hyperactivity and changed diurnal activity in flounders,Platichthys flesus,exposed to DDT

Flounders (Platichthys flesus), which had been given oral doses of DDT, developed hyperactivity and abnormal diurnal activity 5–7 weeks after the dosage of DDT was terminated. For the flounder given the highest dose (12.5 mg DDT kg^?1 fresh body weight) a more than 20-fold increase in swimming activity was recorded. The levels of DDT found in various organs (axial muscle, liver and brain) are compared with levels of DDT found in wild populations of fish from the Baltic Sea. The results are also discussed in relation to results obtained in a parallel study on the physiological effects of DDT on the flounder.     

The intraseasonal oscillation in ECHAM4 Part I: coupled to a comprehensive ocean model

This study discusses the representation of the intraseasonal oscillation (ISO) in three simulations with the ECHAM4 atmosphere general circulation model (GCM). First, the model is forced by AMIP sea surface temperatures (SST), then coupled to the OPYC3 global ocean GCM and third forced by OPYC3 SSTs to clarify possible air-sea interactions and connections of the ISO and the ENSO cycle. The simulations are compared to ECMWF reanalysis data and NOAA outgoing longwave radiation (OLR) observations. Although previous studies have shown that the ECHAM4 GCM simulates an ISO-like oscillation, the main deficits are an overly fast eastward propagation and an eastward displacement of the main ISO activity, which is shown with a composite analysis of daily data between 1984 to 1988 for the reanalysis and the AMIP simulation, 25 years of the coupled integration, and a five year subset of the coupled SST output used for the OPYC3 forced atmosphere GCM experiment. These deficits are common to many atmospheric GCMs. The composites are obtained by principal oscillation pattern (POP). The POPs are also used to investigate the propagation speed and the interannual variability of the main ISO activity. The present coupled model version reveals no clear improvements in the ISO simulation compared to the uncoupled version forced with OPYC3 SSTs, although it is shown that the modeled ISO influences the simulated high-frequency SST variability in the coupled GCM. Within the current analysis, ECHAM4 forced by AMIP SSTs provides the most reasonable ISO simulation. However, it is shown that the maximum amplitudes of the annual cycle of the ISO variability in all analyzed model versions are reached too late in the year (spring and summer) compared to the observations (winter and spring). Additionally, the ENSO cycle influences the interannual variability of the ISO, which is revealed by 20 years of daily reanalysis data and 100 years of the coupled integration. The ENSO cycle is simulated by the coupled model, although there is a roughly 1 K cold bias in the East Pacific in the coupled model. This leads to a diminished influence of the ENSO cycle on the spatial variability of the modeled ISO activity compared to observations. This points out the strong sensitivity of the SST on the ISO activity. Small biases in the SST appear to cause large deterioration in the modeled ISO.     

Model Study on the Interannual Variability of Asian Winter Monsoon and Its Influence

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Application of uncertainty analysis to groundwater pollution modeling

Prediction and evaluation of pollution of the subsurface environment and planning remedial actions at existing sites may be useful for siting and designing new land-based waste treatment or disposal facilities. Most models used to make such predictions assume that the system behaves deterministically. A variety of factors, however, introduce uncertainty into the model predictions. The factors include model and pollution transport parameters and geometric uncertainty. The Monte Carlo technique is applied to evaluate the uncertainty, as illustrated by applying three analytical groundwater pollution transport models. The uncertainty analysis provides estimates of statistical reliability in model outputs of pollution concentration and arrival time. Examples are provided that demonstrate: (a) confidence limits around predicted values of concentration and arrival time can be obtained, (b) the selection of probability distributions for input parameters affects the output variables, and (c) the probability distribution of the output variables can be different from that of the input variables, even when all input parameters have the same probability distribution     

THE MAPPING OF NORTHERN GREENLAND

Approximately 110 sheets of orthophotomaps at a scale of 1:100000 covering all the ice, free area (300000 km²) of northern Greenland are to be produced by the Geodetic Institute of Denmark. Super-wide angle photography at a scale of 1:150 000 was acquired in 1978. Individual models are set up in a Wild B8S stereoplotter and, after carrying out aerial triangulation, a numerical method of absolute orientation is used. A digital ground model of the entire area is established in order to enable the interpolation of contour lines, for automatic plotting and to produce control data, for the orthophotoprojector. a Wild OR1. Methods of data handling and control, accuracies and typical errors are discussed.