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Comparison of validation studies of wave-penetration models using open benchmark datasets of Deltares
This paper presents a collection of open benchmark datasets. These datasets are made available by Deltares for numerical model validation studies, including port applications such as wave penetration models and tools for computing wave forces exerted on moored ships. The paper summarises the contents and characteristics of each available dataset. Furthermore, the paper makes a comparison of different validation studies that have used specific parts of these datasets to this date. This comparison is made to illustrate the possibilities of using these datasets, but it also highlights remaining questions and challenges related to numerical model validation. Researchers, engineers and advisors working on related topics are encouraged to contact Deltares to explore cooperation possibilities using these benchmark datasets.
On the resilience of small-island freshwater lenses: Evidence of the long-term impacts of groundwater abstraction on Bonriki Island, Kiribati
Groundwater on islands occurs in the form of freshwater lenses that serve as an important water resource for local inhabitants. These lenses are highly vulnerable to salinization due to natural recharge variations and groundwater abstraction. Determining the sustainable yield from freshwater lenses is challenging because the lens response during drought periods and the long-term effects of pumping are both difficult to predict. The exceptionally detailed and long data record for Bonriki Island of the Tarawa atoll (Kiribati) made it possible to develop a three-dimensional variable-density model of the island. Field data and modelling results highlight the strong control of rainfall variability and pumping on the temporal dynamics of the freshwater lens. The model reproduces the salinity observations in both monitoring and pumping wells reasonably well, and provides a rare example of physically based island simulation based on an extensive data set. It enables the analysis of freshwater volume and fluxes of submarine groundwater discharge, which is impossible based on the field observations alone. Under natural as well as abstraction conditions, submarine groundwater discharge responds rapidly and almost proportionally to recharge. Theoretical model scenarios with scaled abstraction rates show that lens contraction caused by pumping is a nearly linear function of the total pumped volume, whereby the abstraction rate and the timing of depletion are approximately inversely proportional. Modelling indicates that when monthly recharge inputs fall below around 2500 m3/d (i.e., a flux of 1.7 mm/d) plus the abstraction rate, the lens tends to contract. Thus, despite the highly distributed and extensive abstraction network on Bonriki Island, a significant amount of recharge is eventually lost to submarine groundwater discharge. The long-term freshwater storage trend indicates that Bonriki Island’s lens is still contracting after 27.5 years of pumping, and lens thinning is threatening to impact the water supply salinity. This means that even permeable, small islands like Bonriki may take at least two decades to realise new equilibrium conditions that reflect pumping stresses, which is an important consideration in assessing the sustainable yield of small islands, in particular those less resilient to pumping than Bonriki.
Celebrating 50 years of SWIMs (Salt Water Intrusion Meetings)
The Salt Water Intrusion Meetings, or SWIMs, are a series of meetings that focus on seawater intrusion in coastal aquifers and other salinisation processes. 2018 marks the 50th year of the SWIM and the 25th biennial meeting. The SWIM proceedings record half a century of research progress on site characterisation, geophysical and geochemical techniques, variable-density flow, modelling, and water management. The SWIM is positioning itself to remain a viable platform for discussing the coastal aquifer management challenges of the next 50 years.
Reading landscape design representations as an interplay of validity, readability and interactivity : a framework for visual content analysis
Considering the importance of visual representations for communication between stakeholders in landscape planning and design processes, the authors identify a lack of critical visual research methods supportive of the disciplines involved. As part of such a method, they have developed an analytical framework based on semiotic and iconographic theory that enables a visual content analysis and iconographic interpretation of landscape design representations. Two projects from Rebuild by Design, a participatory transdisciplinary design competition organized in the New York City area after hurricane Sandy, were analysed to demonstrate this framework. The article presents a semiotic vocabulary based on four categories: medium, mode, formulation and knowledge with which to ‘read’, discuss and potentially create design representations. This enables a syntactic analysis for assessing the semiotic complexity of design representations in terms of validity, readability and interactivity. This assessment enables further qualitative study of the production and interpretation of landscape design representations in practice.
Statistical analysis of the stability of rock armoured slopes
Physical model tests were performed in a wave flume at Deltares with rock armoured slopes. A shallow foreshore was present. At deep water the same wave conditions were used but, by applying different water levels, the wave loading on the rock armoured slopes increased considerably with increasing water levels. This allows the assessment of effects of sea level rise. Damage has been measured by using Digital Stereo Photography (DSP) which provides information on each individual stone that has been displaced. Two test series have been performed five times. This allows for a statistical analysis of the damage to rock armoured slopes. The statistical analysis demonstrates the need to take the spreading around a mean damage into account in the design of rock armoured slopes. This is important in addition to characterising the damage itself by erosion areas and erosion depths. The relation between damage parameters such as erosion area and erosion depth has been obtained from the tests. Besides tests with a straight slope also tests with a berm in the seaward slopes have been performed. A method to take the so-called length effect into account has been proposed to extrapolate results from physical model tests to real structures. Use is made of standard deviations based on the presented model tests.
Evaluating strategies to improve process efficiency of denitrification-based MICP
Microbially induced carbonate precipitation (MICP) through denitrification can potentially be applied as a bio-based ground improvement technique. Two strategies involving multiple batch treatments in a modified triaxial test setup were used to study the process efficiency. Both strategies aim to achieve 1 weight percentage (% by weight) of precipitated calcium carbonate (CaCO3) and differ in number of flushes, hydraulic residence time, and substrate concentrations. In the experiment with few flushes and high substrate concentrations the microbial process was inhibited, only 0.28% by weight CaCO3 was measured in the sand after 5 weeks of treatment. The regime with many flushes and low substrate concentrations stimulated microbial growth resulting in 0.65% by weight CaCO3 within the same time period. Biomass growth and nitrogen gas production were stable throughout the experiment at low concentration, reducing the hydraulic conductivity of the sand, which eventually led to clogging. Precipitation rates up to 0.26% by weight/day CaCO3 were observed. Applying a suitable substrate regime and residence time is important to limit inhibition and maintain the cell activity, allow for an efficient conversion, and generate a good precipitation rate.
Rainfall frequency analysis for ungauged regions using remotely sensed precipitation information
Rainfall frequency analysis, which is an important tool in hydrologic engineering, has been traditionally performed using information from gauge observations. This approach has proven to be a useful tool in planning and design for the regions where sufficient observational data are available. However, in many parts of the world where ground-based observations are sparse and limited in length, the effectiveness of statistical methods for such applications is highly limited. The sparse gauge networks over those regions, especially over remote areas and high-elevation regions, cannot represent the spatiotemporal variability of extreme rainfall events and hence preclude developing depth-duration-frequency curves (DDF) for rainfall frequency analysis. In this study, the PERSIANN-CDR dataset is used to propose a mechanism, by which satellite precipitation information could be used for rainfall frequency analysis and development of DDF curves. In the proposed framework, we first adjust the extreme precipitation time series estimated by PERSIANN-CDR using an elevation-based correction function, then use the adjusted dataset to develop DDF curves. As a proof of concept, we have implemented our proposed approach in 20 river basins in the United States with different climatic conditions and elevations. Bias adjustment results indicate that the correction model can significantly reduce the biases in PERSIANN-CDR estimates of annual maximum series, especially for high elevation regions. Comparison of the extracted DDF curves from both the original and adjusted PERSIANN-CDR data with the reported DDF curves from NOAA Atlas 14 shows that the extreme percentiles from the corrected PERSIANN-CDR are consistently closer to the gauge-based estimates at the tested basins. The median relative errors of the frequency estimates at the studied basins were less than 20% in most cases. Our proposed framework has the potential for constructing DDF curves for regions with limited or sparse gauge-based observations using remotely sensed precipitation information, and the spatio-temporal resolution of the adjusted PERSIANN-CDR data provides valuable information for various applications in remote and high elevation areas.
An effective modelling approach to support probabilistic flood forecasting in coastal cities : case study Can Tho, Mekong Delta, Vietnam
Probabilistic flood forecasting requires flood models that are simple and fast. Many of the modelling applications in the literature tend to be complex and slow, making them unsuitable for probabilistic applications which require thousands of individual simulations. This article focusses on the development of such a modelling approach to support probabilistic assessment of flood hazards, while accounting for forcing and system uncertainty. Here, we demonstrate the feasibility of using the open-source SWMM (Storm Water Management Model), focussing on Can Tho city, Mekong Delta, Vietnam. SWMM is a dynamic rainfall-runoff simulation model which is generally used for single event or long-term (continuous) simulation of runoff quantity and quality and its application for probabilistic riverflow modelling is atypical. In this study, a detailed SWMM model of the entire Mekong Delta was built based on an existing ISIS model containing 575 nodes and 592 links of the same study area. The detailed SWMM model was then systematically reduced by strategically removing nodes and links to eventually arrive at a level of detail that provides sufficiently accurate predictions of water levels for Can Tho for the purpose of simulating urban flooding, which is the target diagnostic of this study. After a comprehensive assessment (based on trials with the varying levels of complexity), a much reduced SWMM model comprising 37 nodes and 40 links was determined to be able to provide a sufficiently accurate result while being fast enough to support probabilistic future flood forecasting and, further, to support flood risk reduction management.
Understanding epistemic uncertainty in large-scale coastal flood risk assessment for present and future climates
An upscaling of flood risk assessment frameworks beyond regional and national scales has taken place during recent years, with a number of large-scale models emerging as tools for hotspot identification, support for international policy-making and harmonization of climate change adaptation strategies. There is, however, limited insight on the scaling effects and structural limitations of flood risk models and, therefore, the underlying uncertainty. In light of this, we examine key sources of epistemic uncertainty in the Coastal Flood Risk (CFR) modelling chain: (i) the inclusion and interaction of different hydraulic components leading to extreme sea-level (ESL); (ii) inundation modelling; (iii) the underlying uncertainty in the Digital Elevation Model (DEM); (iv) flood defence information; (v) the assumptions behind the use of depth-damage functions that express vulnerability; and (vi) different climate change projections. The impact of these uncertainties to estimated Expected Annual Damage (EAD) for present and future climates is evaluated in a dual case study in Faro, Portugal and in the Iberian Peninsula. The ranking of the uncertainty factors varies among the different case studies, baseline CFR estimates, as well as their absolute/relative changes. We find that uncertainty from ESL contributions, and in particular the way waves are treated, can be higher than the uncertainty of the two greenhouse gas emission projections and six climate models that are used. Of comparable importance is the quality of information on coastal protection levels and DEM information. In the absence of large-extent datasets with sufficient resolution and accuracy the latter two factors are the main bottlenecks in terms of large-scale CFR assessment quality.
Assessing the contribution of porewater discharge in carbon export and CO2 evasion in a mangrove tidal creek (Can Gio, Vietnam)
Although mangrove forests are efficient natural carbon sinks, most of the atmospheric carbon dioxide (CO2) fixed by its vegetation is believed to be exported via tidal exchange, rather than stored in the vegetative biomass and sediment. However, the magnitude of tidal export is largely unknown because direct measurements are scarce. We deployed a novel experimental design that combined automated high-resolution measurements of hydrodynamic, hydrogeochemical and biogeochemical parameters during the dry season in a mangrove tidal creek in the Can Gio Mangrove Forest in Vietnam. The objective was to quantify the tide-controlled water, porewater, DIC and DOC exchange, and estimate the CO2 evasion throughout tidal cycles contrasted by amplitude. Data from three 25-h time series showed a clear peak of DIC, DOC, pCO2, and 222Rn at low tide, particularly during tidal cycles of large amplitude, which directly relate to porewater discharge. Our mass balance models revealed that the tidal creek was a net exporter of dissolved carbon to coastal waters, with an important contribution (38%) coming from DIC in porewater discharge. Porewater exchange varied from 3.1 ± 1.6 to 7.1 ± 2.4 cm day−1. DIC exchange ranged from 352 ± 34 to 678 ± 79 mmolCm−2 day−1; DOC exchange, 20.6 ± 1.9 to 67.7 ± 7.9 mmol Cm−2 day−1; and CO2 evasion, 69.9 ± 10.5 to 173.7 ± 26.1 mmolCm−2 day−1. These estimates were in the high range of previous carbon assessments and were explained by (i) the monitoring station being located at equal distance from the head and the mouth of the creek, which minimized carbon degradation and losses associated to transport in water; and (ii) the site being a highly productive mangrove within South East Asia.