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.     

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.     

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.     

Glacial and Holocene terrestrial temperature variability in subtropical east Australia as inferred from branched GDGT distributions in a sediment core from Lake McKenzie

Branched glycerol dialkyl glycerol tetraether (GDGT) distributions observed in a sediment core from Lake McKenzie were utilized to quantitatively reconstruct the pattern of mean annual air temperature (MAAT) from coastal subtropical eastern Australia between 37 and 18.3 cal ka BP and 14.0 cal ka BP to present. Both the reconstructed trend and amplitude of MAAT changes from the top of the sediment core were nearly identical to a local instrumental MAAT record from Fraser Island, providing confidence that in this sediment core branched GDGTs could be used to produce a quantitative record of past MAAT. The reconstructed trend of MAAT during 37 to 18.3 cal ka BP and timing of the Last Glacial Maximum (LGM) in the Lake McKenzie record were in agreement with previously published nearby marine climate records. The amplitude of lower-than-present MAAT during the LGM potentially provides information on the latitude of separation of the Tasman Front from the East Australian current in the subtropical western Pacific. The Lake McKenzie record shows an earlier onset of near modern day warm temperatures in the early Holocene compared to marine records and the presence of a warmer than present day period during the mid-Holocene.     

The free surface assumption for marine data‐driven demultiple methods*

In the past, integral formulations for marine data‐driven demultiple methods have been derived from reciprocity theorems. Two fundamental assumptions in these derivations were that the sea‐surface is flat and has a known reflection coefficient, often taken to be minus one. In this paper, we show that for dual sensor data these assumptions can be relaxed. The sea‐surface has to obey the same conditions as any other reflecting boundary in the subsurface: it must be constant in time but shape and reflection strength can vary in space. For both surface‐related multiple elimination, and multiple attenuation by multi‐dimensional deconvolution, we derive integral equations that depend only on the measured pressure and particle velocity fields. Finally, we show there is an intimate connection between the integral equations for the methods.     

Neighborhood-Based social capital and life satisfaction: the case of Rotterdam,The Netherlands

ABSTRACT

In this study, we examine the relationship between neighborhood-based social capital and residents’ life satisfaction by considering resident heterogeneity. Using a database of the city of Rotterdam, The Netherlands, we find a small but significant positive association between neighborhood-based social capital and individual life satisfaction. However, we also find considerable differences among residents because neighborhood-based social capital is important mainly for people who are more likely to spend considerable time in the neighborhood or who are more neighborhood dependent (i.e. less-educated people, people who live on welfare, people with poor health, retired people, and those who are divorced or widowed). Our results confirm the importance of neighborhood-based social capital for residents’ life satisfaction in terms of both actual social contacts with neighbors and the perceived social cohesion within a neighborhood. At the same time, the importance of neighborhood-based social capital varies among different groups of residents. These findings have important implications for policy-makers.     

Wave dissipation by vegetation with layer schematization in SWAN

The energy of waves propagating through vegetation is dissipated due to the work done by the waves on the vegetation. Dalrymple et al. (1984) estimated wave dissipation by integrating the force on a cylinder over its vertical extent. This was extended by Mendez and Losada (2004) to include varying depths and the effects of wave damping due to vegetation and wave breaking for narrow-banded random waves. This paper describes the wave dissipation over a vegetation field by the implementation of the Mendez and Losada formulation in a full spectrum model SWAN, with an extension to include a vertical layer schematization for the vegetation. The present model is validated with the original equation and results from Mendez and Losada (2004). The sensitivity of the model to the shape of the frequency spectrum, directional spreading and layer schematization are investigated. The model is then applied to field measurements by using a vegetation factor. This model has the ability to calculate two-dimensional wave dissipation over a vegetation field including some important aspects such as breaking and diffraction as used in SWAN model.