Analysis of Triphenyltin in Fish

A procedure to analyse triphenyltin and other organotins in fish tissues is described. The method consists of the following steps: homogenization of the fish, extraction by heating under reflux in a water/hexane mixture, centrifugation, separation of the hexane layer followed by reduction of the volume by evaporation, methylation of the organotin with a Grignard reaction, clean-up of the fish extract by column chromatography, and detection by gas chromatography with flame photometric detection. The extraction was carried out without adding acid or base to the aqueous phase, as the extraction efficiency was independent of pH. The methylation was successfully carried out in the fish extract. For clean-up of the fish extract a florisil column was used, from which the triphenylmethyltin was eluted with hexane. Using this method, triphenyltin has a recovery of 77 ± 10%, with a limit of detection of 0·8 ng/g for 0·1 g fish samples.     

Comparative Assessment of Sludge Pre‐Treatment Techniques to Enhance Sludge Dewaterability and Biogas Production

Effectiveness of ultrasonication, microwave technologies, and enzyme addition prior to anaerobic digestion is investigated using sludge samples taken from the secondary settling tank of a domestic wastewater treatment plant to improve methane production, enhance dewaterability characteristics of the sludge, and to reduce excess sludge. Microwave pre‐treatment (1500 W, 10 min at 175 °C) results in better extra digester performance (compared to the control reactor) in terms of methane production (25 m³ ton^?1 suspended solids (SS)) than ultrasound (no improvement) and enzyme pre‐treatment (11 m³ ton^?1 SS). While methane production is not improved as a result of ultrasonication pre‐treatment (15 000 kJ kg^?1 SS), a noticeable increase (19%) is observed in the case of microwave pre‐treatment. Higher compactibility values are obtained after ultrasonication and microwave application compared to the control (i.e., from 7.1 to 8.7 and 9.2%, respectively) before anaerobic digestion. Although ultrasonication and microwave application decrease the dewaterability of the raw sludge (capillary suction time (CST) from 827 to 1364 and 2290 s, respectively), similar dewaterability results are obtained at the end of the anaerobic digestion process for all pre‐treated sludge samples. An economic assessment of this study shows that pre‐treatment with microwave results in more than 10‐fold less net cost compared to the enzyme application.     

MODFLOW as a Configurable Multi-Model Hydrologic Simulator

MODFLOW 6 is the latest in a line of six “core” versions of MODFLOW released by the U.S. Geological Survey. The MODFLOW 6 architecture supports incorporation of additional hydrologic processes, in addition to groundwater flow, and allows interaction between processes. The architecture supports multiple model instances and multiple types of models within a single simulation, a flexible approach to formulating and solving the equations that represent hydrologic processes, and recent advances in interoperability, which allow MODFLOW to be accessed and controlled by external programs. The present version of MODFLOW 6 consolidates popular capabilities available in MODFLOW variants, such as the unstructured grid support in MODFLOW-USG, the Newton-Raphson formulation in MODFLOW-NWT, and the support for partitioned stress boundaries in MODFLOW-CDSS. The flexible multi-model capability allows users to configure MODFLOW 6 simulations to represent the local-grid refinement (LGR) capabilities available in MODFLOW-LGR, the multi-species transport capabilities in MT3DMS, and the coupled variable-density capabilities available in SEAWAT. This paper provides a new, holistic and integrated overview of simulation capabilities made possible by the MODFLOW 6 architecture, and describes how ongoing and future development can take advantage of the program architecture to integrate new capabilities in a way that is minimally invasive and automatically compatible with the existing MODFLOW 6 code.     

Uncertainty analysis in statistical modeling of extreme hydrological events

With the increase of both magnitude and frequency of hydrological extreme events such as drought and flooding, the significance of adequately modeling hydrological extreme events is fully recognized. Estimation of extreme rainfall/flood for various return periods is of prime importance for hydrological design or risk assessment. However, due to knowledge and data limitation, uncertainty involved in extrapolating beyond available data is huge. In this paper, different sources of uncertainty in statistical modeling of extreme hydrological events are studied in a systematic way. This is done by focusing on several key uncertainty sources using three different case studies. The chosen case studies highlight a number of projects where there have been questions regarding the uncertainty in extreme rainfall/flood estimation. The results show that the uncertainty originated from the methodology is the largest and could be >40% for a return period of 200 years, while the uncertainty caused by ignoring the dependence among multiple hydrological variables seems the smallest. In the end, it is highly recommended that uncertainty in modeling extreme hydrological events be fully recognized and incorporated into a formal hydrological extreme analysis.     

Phytoplankton as an Indicator of Improving Water Quality in the Golden Horn Estuary

The variation in phytoplankton community as a response to improving water quality has been studied in the severely polluted Golden Horn Estuary (GHE). Phytoplankton data collected monthly for 4 years and a detailed set of environmental parameters clearly showed the remarkable change in the GHE. The GHE ecosystem did not respond to numerous rehabilitation efforts to improve water quality, unless strict measures were taken to enhance water circulation. The opening of a bridge operating on large buoys and release of high amounts of fresh water from a dam acted as the turning point for the whole system. The weakening of light limitation and anoxia at upper regions is followed by consecutive blooms of different species/groups and resulted in super-saturated dissolved oxygen concentrations and a significant decrease in nutrient concentrations. When compared to the pre-remediation period, average total eukaryotic phytoplankton abundance increased 11-fold in the lower estuary, while the increase in the upper estuary was over 3 × 10⁴ in the post-remediation period. In addition, species richness continuously increased through the study period and community structure showed very strong variability. Since the estuarine ecosystem is controlled by precipitation in the last decade, the increase in anthropogenic/terrestrial inputs following heavy rainfall had adversely affected water quality and phytoplankton.     

Quantification of parametric uncertainty of ANN models with GLUE method for different streamflow dynamics

This study describes the parametric uncertainty of artificial neural networks (ANNs) by employing the generalized likelihood uncertainty estimation (GLUE) method. The ANNs are used to forecast daily streamflow for three sub-basins of the Rhine Basin (East Alpine, Main, and Mosel) having different hydrological and climatological characteristics. We have obtained prior parameter distributions from 5000 ANNs in the training period to capture the parametric uncertainty and subsequently 125,000 correlated parameter sets were generated. These parameter sets were used to quantify the uncertainty in the forecasted streamflow in the testing period using three uncertainty measures: percentage of coverage, average relative length, and average asymmetry degree. The results indicated that the highest uncertainty was obtained for the Mosel sub-basin and the lowest for the East Alpine sub-basin mainly due to hydro-climatic differences between these basins. The prediction results and uncertainty estimates of the proposed methodology were compared to the direct ensemble and bootstrap methods. The GLUE method successfully captured the observed discharges with the generated prediction intervals, especially the peak flows. It was also illustrated that uncertainty bands are sensitive to the selection of the threshold value for the Nash–Sutcliffe efficiency measure used in the GLUE method by employing the Wilcoxon–Mann–Whitney test.     

Identification of appropriate lags and temporal resolutions for low flow indicators in the River Rhine to forecast low flows with different lead times

The aim of this paper is to assess the relative importance of low flow indicators for the River Rhine and to identify their appropriate temporal lag and resolution. This is done in the context of low flow forecasting with lead times of 14 and 90 days. First, the Rhine basin is subdivided into seven sub‐basins. By considering the dominant processes in the sub‐basins, five low flow indicators were selected: precipitation, potential evapotranspiration, groundwater storage, snow storage and lake storage. Correlation analysis was then carried out to determine the relationship between observed low flows and preselected indicators with varying lags (days) and temporal resolutions (from 1 day to 7 months). The results show that the most important low flow indicators in the Alpine sub‐basins for forecasts with a lead time of 14 days are potential evapotranspiration with a large lag and temporal resolution, and lake levels with a small lag and temporal resolution. In the other sub‐basins groundwater levels with a small lag and temporal resolution are important in addition to potential evapotranspiration with a large lag and temporal resolution. The picture is slightly different for forecasts with a lead time of 90 days. The snow storage in the Alpine sub‐basins and the precipitation in the other sub‐basins also become relevant for low flows. Consequently, the most important low flow indicators in the Alpine sub‐basins for forecasts with a lead time of 90 days are potential evapotranspiration with a large lag and temporal resolution, lake levels with a small lag and temporal resolution and snow storage with a small lag and large temporal resolution. The resultant correlation maps provide appropriate lags and temporal resolutions for indicators to forecast low flows in the River Rhine with different lead times. Copyright © 2012 John Wiley & Sons, Ltd.     

Attribution of changes in the water balance of a tropical catchment to land use change using the SWAT model

Changes in the water balance of the Samin catchment (277.9 km²) on Java, Indonesia, can be attributed to land use change using the Soil Water Assessment Tool model. A baseline‐altered method was used in which the simulation period 1990–2013 was divided into 4 equal periods to represent baseline conditions (1990–1995) and altered land use conditions (1996–2001, 2002–2007, and 2008–2013). Land use maps for 1994, 2000, 2006, and 2013 were acquired from satellite images. A Soil Water Assessment Tool model was calibrated for the baseline period and applied to the altered periods with and without land use change. Incorporating land use change resulted in a Nash–Sutcliffe efficiency of 0.7 compared to 0.6 when land use change is ignored. In addition, the model performance for simulations without land use change gradually decreased with time. Land use change appeared to be the important driver for changes in the water balance. The main land use changes during 1994–2013 are a decrease in forest area from 48.7% to 16.9%, an increase in agriculture area from 39.2% to 45.4%, and an increase in settlement area from 9.8% to 34.3%. For the catchment, this resulted in an increase of the runoff coefficient from 35.7% to 44.6% and a decrease in the ratio of evapotranspiration to rainfall from 60% to 54.8%. More pronounced changes can be observed for the ratio of surface runoff to stream flow (increase from 26.6% to 37.5%) and the ratio of base flow to stream flow (decrease from 40% to 31.1%), whereas changes in the ratio of lateral flow to stream flow were minor (decrease from 33.4% to 31.4%). At sub‐catchment level, the effect of land use changes on the water balance varied in different sub‐catchments depending on the scale of changes in forest and settlement area.     

Market regulation versus co-management?: Two perspectives on regulating fisheries compared

The crisis of fisheries management is also a crisis of governability; somehow governments almost everywhere seem to run into trouble while managing fisheries. This article compares two alternative styles of regulation that are put forward as solutions to this crisis: market-based regulation and comanagement. In particular the contradiction is analyzed between an apparently strong theoretical basis for market-based regulation and actual practice which often opts for co-management. The theoretical basis of the market-based perspective is challenged and on the basis of an analysis of flatfishery management in the Netherlands, it is concluded that there are often sound arguments for restructuring the management responsibilities between public authorities and civil society.