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Global re-analysis datasets to improve hydrological assessment and snow water equivalent estimation in a Sub-Arctic watershed
Hydrological modelling in the Canadian Sub-Arctic is hindered by sparse meteorological and snowpack data. Snow Water Equivalent (SWE) of the winter snowpack is a key predictor and driver of spring flow, but the use of SWE data in hydrological applications is limited due to high uncertainty. Global re-analysis datasets that provide gridded meteorological and SWE data may be well suited to improve hydrological assessment and snowpack simulation. To investigate representation of hydrological processes and SWE for application in hydropower operations, global re-analysis datasets covering 1979–2014 from the European Union FP7 eartH2Observe project are applied to global and local conceptual hydrological models. The recently developed Multi-Source Weighted-Ensemble Precipitation (MSWEP) and the Watch Forcing Data applied to ERA-Interim data (WFDEI) are used to simulate snowpack accumulation, spring snowmelt volume and annual streamflow. The GlobSnow-2 SWE product funded by the European Space Agency with daily coverage from 1979–2014 is evaluated against in-situ SWE measurement over the local watershed. Results demonstrate the successful application of global datasets for streamflow prediction, snowpack accumulation and snowmelt timing in a snowmelt driven Sub-Arctic watershed. The GlobSnow-2 product is found to under-predict late season snowpack over the study area, and shows a premature decline of SWE prior to the true onset of the snowmelt. Of the datasets tested, the MSWEP precipitation results in annual SWE estimates that are better predictors of snowmelt volume and peak discharge than the WFDEI or GlobSnow-2. This study demonstrates the operational and scientific utility of the global re-analysis datasets in the Sub-Arctic, although knowledge gaps remain in global satellite based datasets for snowpack representation.
Pile tunnel interaction : pile settlement vs ground settlements
The underground space of densely populated cities contains parts of buildings, utility installations, deep foundations, tunnels, and deep excavations. It is possible, and increasing more probable, that new underground constructions will be built within proximity of existing pile foundations. This paper analyses how a new a framework for pile analysis, a modified version of the load transfer method, can be used to predict the consequences of the tunnelling induced settlements on existing piles. The soil settlements are calculated with an analytical solution, and the pile settlements are calculated for different pile lengths, loading conditions, and distances between the pile and the tunnel centreline. The results indicate a wide range of possible pile settlements, in relation to the greenfield settlement trough. A simple interpretation scheme is used to understand the results, showing the importance of the profile of soil settlements along the pile.
The economic impact of irrigation water scarcity from climate change : a CGE analysis distinguishing between surface and ground water
Future climate change brings with it many challenges to agriculture. The impact of climate change on agricultural production would in large part depend on the possibility of farmers to adapt by intensifying irrigation and changing cropping patterns. Depending on their location farmers may have access to surface water, ground water or both as their irrigation source. These different irrigation sources have distinctive characteristics for agricultural and non-agricultural uses that water managers need to consider in making allocation decisions while keeping in mind that the ability to increase irrigation in times of water scarcity may determine the success of agricultural adaptation to climate change. The importance of distinguishing between various type irrigation water sources is illustrated by using the Netherlands as a case study. The majority of irrigation in Northwest-Europe is fully reliant on groundwater which has a limited supply and is slow to recover when depleted. Areas close to rivers, such as the low lying areas of the Netherlands, can however also be supplied by river water allowing for additional adaptation possibilities not enjoyed to the same extent by other countries in the region. Access to river water, mainly from the Rhine, to supplement ground water supplies for irrigation could make the Dutch agricultural producers more successful in adapting to a warmer drier climate and giving The Netherlands a competitive advantage over its neighbors in the region. To determine the extent of the benefit of increased access to river water in times of water scarcity we employ the multi-regional computable general equilibrium model GTAP-W (Calzadilla et al., 2010), which includes water as an explicit input in agricultural production. The model has been expanded to allow for differentiation between surface and groundwater endowments within individual regions in order to quantify the importance of increased surface water in irrigation as an adaptation response to climate change and to allow for different allocation policies with respect to surface and groundwater endowments. The model has been applied to analyze the impact of a drier climate on the agricultural sector and the economy as a whole both in The Netherlands and its upstream neighbors in the Rhine and Meuse river basin, Belgium and Germany. We further examine the benefit of increased water irrigation infrastructure as an additional adaptation response for Dutch agricultural producers and the subsequent effect that the Dutch adaptation response might have on the agricultural markets for the upstream countries Belgium and Germany. The results show that a limited increase in surface water irrigation infrastructure increases the output of all crop sectors including rain fed sectors. However a much larger expansion of irrigated areas increases the demand and price for labor and capital to such an extent that rain fed agricultural sectors decrease as a result. The impacts on the upstream countries are limited but non-negligible.
Global economic analysis in the 21st century - challenges and opportunities : 20th Annual conference on global economic analysis (June 7-9, 2017, Purdue University, West Lafayette, USA)
Improving nitrate load estimates in an agricultural catchment using Event Response Reconstruction
Low-frequency grab sampling cannot capture fine dynamics of stream solute concentrations, which results in large uncertainties in load estimates. The recent development of high-frequency sensors has enabled monitoring solute concentrations at sub-hourly time scales. This study aimed to improve nitrate (NO3) load estimates using high-resolution records (15-min time interval) from optical sensors to capture the typical concentration response to storm events. An empirical model was developed to reconstruct NO3 concentrations during stormevents in a 100-km2 agricultural catchment in Germany. Two years (Jan 2002 to Dec 2002 and Oct 2005 to Sep 2006) of high-frequency measurements of NO3 concentrations, discharge and precipitation were used. An Event Response Reconstruction (ERR) model was developed using NO3 concentration descriptor variables and predictor variables calculated from discharge and precipitation records. Fourteen events were used for calibration, and 27 events from four periods of continuous records of high-frequency measurement were used for validation. During all selected storm events, NO3 concentration decreased during flow rise and increased during the recession phase of the hydrograph. Three storm descriptor variables were used to describe these dynamics: relative change in concentration between initial and minimum NO3 concentrations (rdN), time to maximum change in NO3 concentration (TdN) and time to 50% recovery of NO3 concentration (TNrec). The ERR consisted of building linear models of discharge and precipitation to predict these three descriptors. The ERR approach greatly improved NO3 load estimates compared to linear interpolation of grab sampling data (error decreased from 10 to 1%) or flow-weighted estimation of load (error is 7%). This study demonstrated that ERR based on a few months of high-resolution data enables accurate load estimates from low-frequency NO3 data.
NCR-days 2018 (Delft, February 8-9, 2018) - The future river : book of abstracts
The impact of climate change on the morphology of a tidal freshwater wetland affected by tides, discharge, and wind
Tidal freshwater wetlands are threatened by climate change, especially by rising sea levels. Until now, research in these wetlands has focused mostly on determining historical and present‐day accretion rates without analysing the influence of climate change on future developments. We study a recently constructed freshwater wetland under influence of tides, wind, and riverine discharges and carry out a scenario analysis to evaluate the impact of climate change on morphodynamics. We use a numerical model that describes the hydrodynamics and morphology in the study area and includes the impact of vegetation and carry out transient scenario runs for the period 2015–2050 with gradually changing boundary conditions. We conclude that the simulated accretion rates are significantly lower than the rate of sea level rise, meaning that the wetland will gradually convert to open water. We also find that the morphological changes can largely be attributed to morphological stabilization of the constructed wetland and not to climate change. Wind plays an important role through resuspension and redistribution of fine sediment, and neglecting it would lead to a significant overestimation of accretion rates on the flats.
Collaborative Risk Informed Decision Analysis : a water security case study in the Philippines
More frequent and intense hydrologic events under climate change are expected to enhance challenges for water security and flood risk management worldwide. Traditional planning approaches must be adapted to address climate change and develop solutions with an appropriate level of robustness and flexibility. The Collaborative Risk Informed Decision Analysis (CRIDA) method is a novel planning approach embodying a suite of complementary methods, including decision scaling and adaptation pathways, in a stakeholder driven process which guides decision makers through the planning and decision process, taking into account how the confidence in the available science, the consequences in the system, and the capacity of institutions should influence strategy selection. The purpose of this study is to apply the CRIDA approach to a water supply case study in Central Cebu, the Philippines in order to evaluate the added benefits of the method for planning and design under climate change uncertainty. This work will equip practitioners and decision makers with an example of a structured process for decision making under climate uncertainty that can be scaled as needed to the problem at hand.
Proposed methodology for risk analysis of interdependent critical infrastructures to extreme weather events
Growing scientific evidence suggests that risks due to failure of critical infrastructures (CIs) will increase worldwide, as the frequency and intensity of extreme weather events (EWEs) induced by climate change increases. Such risks are difficult to estimate due to the increasing complexity and interconnectedness of CIs and because information sharing regarding the vulnerabilities of the different CIs is limited. This paper proposes a methodology for risk analysis of systems of interdependent CIs to EWEs. The methodology is developed and carried out for the Port of Rotterdam area in the Netherlands, which is used as a case study. The case study includes multiple CIs that belong to different sectors and can be affected at the same time by an initiating EWE. The proposed methodology supports the assessment of common cause failures that cascade across CIs and sectors. It is based on a simple, user-friendly approach that can be used by CIs owners and operators. The implementation of the methodology has shown that the severity of cascading effects is strongly influenced by the recovery time of the different CIs due to the initiating EWE and that cascading effects that result from a disruption in a single CI develop differently from cascading effects that result from common cause failures. For most CIs, vulnerabilities from EWEs on the CI level will be higher than the cascading risks of common cause failures on the system of CIs; moreover, cascading risks for a CI will increase after its recovery from the event.
Rheological characterisation of concentrated domestic slurry
The much over-looked element in new sanitation, the transport systems which bridge the source and treatment facilities, is the focus of this study. The knowledge of rheological properties of concentrated domestic slurry is essential for the design of the waste collection and transport systems. To investigate these properties, samples were collected from a pilot sanitation system in the Netherlands. Two types of slurries were examined: black water (consisting of human faecal waste, urine, and flushed water from vacuum toilets) and black water with ground kitchen waste. Rheograms of these slurries were obtained using a narrow gap rotating rheometer and modelled using a Herschel-Bulkley model. The effect of concentration on the slurry are described through the changes in the parameters of the Herschel-Bulkley model. A detailed method is proposed on estimating the parameters for the rheological models. For the black water, yield stress and consistency index follow an increasing power law with the concentration and the behaviour index follows a decreasing power law. The influence of temperature on the viscosity of the slurry is described using an Arrhenius type relation. The viscosity of black water decreases with temperature. As for the black water mixed with ground kitchen waste, it is found that the viscosity increases with concentration and decreases with temperature. The viscosity of black-water with ground kitchen waste is found to be higher than that of black water, which can be attributed to the presence of larger particles in the slurry.