Arthur Mynett

Linking SWAT and SOBEK Using Open Modeling Interface (OpenMI) for Sediment Transport Simulation in the Blue Nile River Basin

Computer models assist basin-scale decision making by taking into account upstream-downstream interdependencies. The SWAT (hydrological) model code was developed into an OpenMI-compliant version and linked with the SOBEK (hydrodynamic) model to extend SWATs simulations of basin-scale streamflow and sediment transport. The development of an OpenMI-compliant version of SWAT involved reorganizing the SWAT model code and wrapping it with the OpenMI wrapper utility. The modified SWAT model was linked to the SOBEK model and applied to simulate sediment transport in the Blue Nile River basin. The SWAT model simulated the streamflow and soil erosion in the upstream catchment, while the SOBEK model routed the streamflow and sediment downstream to the basin outlet. Prior to the linking, both the SWAT and SOBEK models were individually calibrated. The results showed that the coupled models simulated the observed hydrodynamics and sediment deposition due to backwater effects, which would not be possible with the SWAT model alone. The developed OpenMI-compliant SWAT model can further be linked to groundwater, climate change, and socioeconomic models to address integrated water resources management needs.

Comparison and evaluation of model structures for the simulation of pollution fluxes in a tile-drained river basin.

The European Union Water Framework Directive requires an integrated pollution prevention plan at the river basin level. Hydrological river basin modeling tools are therefore promising tools to support the quantification of pollution originating from different sources. A limited number of studies have reported on the use of these models to predict pollution fluxes in tile-drained basins. This study focused on evaluating different modeling tools and modeling concepts to quantify the flow and nitrate fluxes in the Odense River basin using DAISY-MIKE SHE (DMS) and the Soil and Water Assessment Tool (SWAT). The results show that SWAT accurately predicted flow for daily and monthly time steps, whereas simulation of nitrate fluxes were more accurate at a monthly time step. In comparison to the DMS model, which takes into account the uncertainty of soil hydraulic and slurry parameters, SWAT results for flow and nitrate fit well within the range of DMS simulated values in high-flow periods but were slightly lower in low-flow periods. Despite the similarities of simulated flow and nitrate fluxes at the basin outlet, the two models predicted very different separations into flow components (overland flow, tile drainage, and groundwater flow) as well as nitrate fluxes from flow components. It was concluded that the assessment on which the model provides a better representation of the reality in terms of flow paths should not only be based on standard statistical metrics for the entire river basin but also needs to consider additional data, field experiments, and opinions of field experts.

Flood inference simulation using surrogate modelling for the Yellow River multiple reservoir system

The Yellow River, in China, is one of the largest hydro systems in the world. Flooding is a major problem for the river, and therefore over the last 50 years a large number of interventions have been made in its reaches and tributaries, in order to control the flooding events in the lowland area, downstream of the Huayuankou hydrological station. The development of new technologies and approaches to decision support has raised possibilities for creating new ways of managing the river and reducing loss of life, in the case of flooding, for the people living within the embankment area of the river. Given the importance of the river for the development of economic activity in China, it is essential to increase the understanding of the general flooding processes triggered by several reservoir operation scenarios, and then, after applying them to a flooding model of a specific area, to test the findings. The main goal of the research presented here is to investigate and develop the statistical inference between the operation of reservoirs on the Yellow River and a set of variables related to the downstream flooding, such as the total flooding volume and the peak discharge. The research shows that it is possible to use such inference models as decision support tools, by reducing the number of explanatory variables to be included in the simulations carried out to determine the appropriate reservoir operation.

PROPAGATION OF DISCHARGE UNCERTAINTY IN A FLOOD DAMAGE MODEL FOR THE MEUSE RIVER

Uncertainty analysis plays an important role in the decision- making process. It can give decision makers a complete idea of how different measures will affect the whole river system. Thus it helps decision makers to make a better choice among measures in a more systematic manner. In case of flood damage reduction projects, uncertainty analysis helps to evaluate the main decision criterion – expected annual damage. The aim of this paper is to investigate the propagation of discharge uncertainty, which is one of the main uncertainty sources in a damage model, into expected annual damage. The discharge uncertainty considered here includes model uncertainty (choice of different probability distributions) and sampling errors due to finite gauge record lengths. The calculated uncertainty in the discharge varies between 17 percent for a return period of 5 year and 30 percent for a return period of 1250 year. A first order method is used here to explore the role of discharge uncertainty in the expected annual damage model. The results from the damage model indicate that both model uncertainty and sampling errors are important, with the latter being somewhat more important. The Log-Pearson Type 3 gives a much smaller uncertainty range of the expected annual damage than the other three distribution models used. The uncertainty is aggravated when propagated into the damage results. The uncertainty in the damage reduces a great amount when the sample size increases to n=80. The results derived from the first order method in fact give two bounds of uncertainty, which is an overestimate in this case.

Unstructured cellular automata for modelling macrophyte dynamics

Due to the complexity of ecohydraulic systems, it is hard to derive general physical equations that describe all processes in sufficient detail. Quite often non-linear local interactions play a dominant role, in particular for ecosystems in the aquatic environment. In recent years, the cellular automata (CA) paradigm was successfully applied to ecohydraulic systems and proved to be a useful approach in, e.g. population dynamics modelling. CA constitute a mathematical system in which many simple components act together to produce complicated patterns of behaviour. Most of the previous applications of CA in ecohydraulic modelling are conventionally based on regularly spaced, structured meshes. However, hydraulic flow and transport modelling nowadays are often making use of unstructured computational meshes that provide more flexibility for fitting complicated geometries and that can be locally refined if needed to deal with, e.g. patchiness of the vegetation. In this paper, the concept of CA is extended to unstructured meshes, using a model for water lily growth and decay in a small pond during half a year as a sample case study. Two types of unstructured cellular automata (UCA) were developed to capture growth patterns of water lily plants. One is referred to as spatial-based UCA modelling, the other as individual-based UCA modelling. The modelling results are compared with high-resolution photographs obtained on a weekly basis. In addition, a three-dimensional UCA model is outlined in which the evolution of water lilies in the vertical direction can be taken into account as well.

Effects of submerged tropical macrophytes on flow resistance and velocity profiles in open channels

In this paper, the results of flume experiments are presented, conducted to investigate the effect of different submerged flexible plant species on flow resistance and flow patterns in open channels. Three common plant types in tropical regions were selected: Cabomba caroliniana, a quite flexible fully submerged species; Echinodorus grandiflorus, a somewhat less flexible, fully submerged species; and Nymphaea rubra, a rooted species with floating leaves. For each plant type, three different densities were tested for various discharges, water depths, and depths of plant submergence. The flow resistance was expressed in terms of the commonly used Manning coefficient n. The results indicate that among the particular plant species investigated here, the floating leaf species N. rubra exhibits the lowest flow resistance (Mannings n = 0.014), viz. less than half the values for C. caroliniana and E. grandiflorus, respectively. A detailed analysis showed that this is due to the particular plant morphology, consisting of relatively large biomass (floating leaves) with only small stem density. It was observed that the flow resistance not only strongly and inversely depends on the Reynolds number, but also on the degree of plant submergence (i.e. water depth/deflected plant height ratio), and on the density of the vegetated plant beds. It appears that the biomass/drag force ratio seems of less importance. From the measured velocity profiles, the influence of the various types of vegetation species could clearly be observed. These factors are important for the design and management of vegetated open channels in tropical urban areas like Singapore.

Lessons of climate change, stories of solutions. The Netherlands: Innovative technology

While there is little dissent in the scientific community that climate change directly correlates to human-caused greenhouse-gas emissions, action to reduce those emissions has not followed from the United States and many other governments around the world. Meanwhile, climate changes are already underway, and will continue to some degree even if emissions are drastically curtailed, thanks to emissions already in the atmosphere. Some countries and states are making their own plans to adapt to expected impacts including higher sea levels, more intense rainfall, droughts, heat waves, and loss of water supplies—and to reduce their local emissions. In this Global Forum, three experts highlight efforts by national and local governments in planning for 2100 and beyond. From the Netherlands, Arthur Mynett; from Bangladesh, Saleemul Huq (2011); and from California, Martha Krebs (2011). Over the months of January and February, this forum will continue at www.thebulletin.org.

Enhancing the SWAT model for simulating denitrification in riparian zones at the river basin scale

Abstract Riparian zones have significant impact on nitrate removal despite their small areas. Most research on riparian zones have been implemented at small scales. Direct measurement at large scale is infeasible, thus using models is a good alternative. This study introduces a modified SWAT model, referred as SWAT_LS. Two modifications were implemented: (i) adding hydrological routing from upland areas to riparian zones; and (ii) adding a module to simulate denitrification in riparian zones based on the Riparian Nitrogen Model. SWAT_LS was applied to the Odense river basin in Denmark, a densely tile-drained agricultural river basin. Compared to SWAT, SWAT_LS provides an equally good performance for streamflow, and a significant improvement in nitrate predictions. SWAT_LS predicts that current riparian zones remove only 4–17% of nitrate loads because 70% of the riparian areas are bypassed due to subsurface drainage implementation. This ability would dramatically increase to 25–85% if riparian zones are entirely undrained.

Uncertainty Analysis of Hydrodynamic Modeling of Flooding in the Lower Niger River Under Sea Level Rise Conditions

Uncertainty in modeling results can be introduced via different sources including: the input data, the modeling assumptions, simulations based on hypothetical scenarios, etc. In this paper the uncertainty in modeling results of 1D and 1D/2D hydrodynamic Sobek models of flooding in the Niger River are analyzed. The models were set up with discharge data as upstream boundary conditions and tidal water level data as downstream boundary conditions. The models were run for the years 1998, 2005, 2006, and 2007. Data available for 1998, 2006, and 2007 were for flooding, while 2005 data represents normal flow data. The model setup included 48 cross sections located between Lokoja and the two ends of the rivers Forcados and Nun. The boundary conditions were varied downstream at the mouths of rivers Forcados and Nun using sea level rise (SLR) values adopted from the Rahmstorf predicted values; the simulations were projected for the years 2030 and 2050. Five modeling scenarios were set up to simulate the interaction of river flooding with downstream rise in sea levels. The scenarios were: sea level rise with normal year flow from upstream, sea level rise with a flooding year flow from upstream, sea level rise with flash floods from upstream, sea level rise with subsidence and flooding year flow from upstream, and sea level rise with subsidence and flash floods from upstream. The use of predicted SLR values introduces uncertainties in the model outputs. Another source of uncertainty was the value for land subsidence (25 mm/yr) adopted from estimates by local experts (the exact value is not yet known and might vary within the area). Uncertainty analysis of the modeling results were carried out using probability-based sampling methods in order to determine the uncertainties in modeling results for effects of downstream SLR on flooding extent, flooding time, and change in water depth in the Niger delta.