Abstract Peatlands are important global carbon stores, but it is unclear whether they will continue as carbon sinks under future climates, or degrade, leaking carbon to the atmosphere. We used the DigiBog peatland development model to explore this question for a blanket peatland in Glen Affric, Scotland, investigating how topography and climate have affected net peat accumulation across this complex landscape. DigiBog accurately captured spatial variation in measured modern peat thickness (Lin's Concordance Correlation Coefficient = 0.86). As expected, peat accumulated to greater depths in topographic basins compared to slopes and drainage divides over the Holocene. Simulations of the future suggest the study site will continue accumulating peat until 2100 CE under all Representative Concentration Pathways. However, DigiBog predicts greatest future peat accumulation away from basins, continuing a trend observed over the last c. 2000 years. We also tested Winter's (2000), https://doi.org/10.1111/j.1752‐1688.2000.tb04269.x conceptual model, which proposes that wetland vulnerability to climate change depends on position in the hydrologic landscape, by comparing peat thickness with the Topographic Wetness Index. While correlations were moderate to strong, our finding of greater recent accumulation away from basins contradicts Winter's model's predictions. Additionally, DigiBog shows that thin (<40 cm) hillslope peats persisted throughout the Holocene despite drier climatic phases, rather than experiencing complete loss and re‐establishment cycles. We conclude that process‐based ecohydrological models like DigiBog can complement simpler modeling approaches and should be used when assessing rates and spatial patterns of peat accumulation and loss in response to 21st Century climate change.

DigiBog is a numerical model that simulates peat accumulation in temperate peatlands. Here, we modify DigiBog for boreal peatlands (DigiBog_Boreal) by accounting for snow cover, short growing seasons and groundwater exchanges between the peat and the aquifer. DigiBog_Boreal is then used to replicate similar to 6500 years of peat accumulation at two high boreal latitude peatlands in Quebec, Canada. DigiBog_Boreal was driven with a weather generator and climate models, while peat cores from the sites were used to develop initial conditions and calibrate DigiBog_Boreal. Our results demonstrate that DigiBog_Boreal can replicate well peat thickness and age -depth profiles but cannot produce long-term fluctuations in water-table depths. Here, a possible explanation for DigiBog_Boreal's underperformance is the stability in the climatic drivers and less likely the new model de-velopments. The results also indicate that peat decomposition and accumulation in DigiBog_Boreal are sensitive to water stored on the peat surface.

The role of subtropical peatlands as a source for methane gas is not well understood, partly due to uncertainties surrounding environmental controls on gas ebullition patterns. Past studies have pointed to an array of environmental factors controlling ebullition, although we have found that ebullition patterns can be replicated by a model considering only physical parameters of the peat matrix. Here we tested a computer model for gas ebullition and storage against a natural system for the first time, using a suite of field measurements in the Florida Everglades. Modeled ebullition showed patterns similar to those observed in the field in terms of frequency distribution and magnitude, specifically from areas of higher density peat fabric. These results suggest that the internal structure of the peat soil is an important control on spatial and temporal patterns of ebullition in the Everglades and should be considered when investigating environmental controls on ebullition patterns.

Flood risks are dynamically changing over time. Over decades and centuries, the main drivers for flood risk change are influenced either by perturbations or slow alterations in the natural environment or, more importantly, by socio-economic development and human interventions. However, changes in the natural and human environment are intertwined. Thus, the analysis of the main drivers for flood risk changes requires a disentangling of the individual risk components. Here, we present a method for isolating the individual effects of selected drivers of change and selected flood risk management options based on a model experiment. In contrast to purely synthetic model experiments, we built our analyses upon a retro-model consisting of several spatio-temporal stages of river morphology and settlement structure. The main advantage of this approach is that the overall long-term dynamics are known and do not have to be assumed. We used this model setup to analyse the temporal evolution of the flood risk, for an ex-post evaluation of the key drivers of change, and for analysing possible alternative pathways for flood risk evolution under different governance settings. We showed that in the study region the construction of lateral levees and the consecutive river incision are the main drivers for decreasing flood risks over the last century. A rebound effect in flood risk can be observed following an increase in settlements since the 1960s. This effect is not as relevant as the river engineering measures, but it will become increasingly relevant in the future with continued socio-economic growth. The presented approach could provide a methodological framework for studying pathways for future flood risk evolvement and for the formulation of narratives for adapting governmental flood risk strategies to the spatio-temporal dynamics in the built environment.

We investigated the effect of sample size and sampling duration on methane bubble flux (ebullition) estimates from peat using a computer model. A field scale (10 m), seasonal (>100 days) simulation of ebullition from a two-dimensional (2-D) structurally varying peat profile was modeled at fine spatial resolution (1 mm x 1 mm). The spatial and temporal scale of this simulation was possible because of the computational efficiency of the reduced-complexity approach that was implemented, and patterns of simulated ebullition were consistent with those found in the field and laboratory. The simulated ebullition from the peat profile suggested that decreases in peat porositywhich cause increases in gas storageproduce ebullition that becomes increasingly patchy in space and erratic in time. By applying different amounts of spatial and temporal sampling effort, it was possible to determine the uncertainty in ebullition estimates from the peatland. The results suggest that traditional methods to measure ebullition can equally overestimate and underestimate flux by 20% and large ebullition events can lead to large overestimations of flux when sampling effort is low. Our findings support those of field studies, and we recommend that ebullition should be measured frequently (hourly to daily) and at many locations (n>14).

Surat city of India, situated 100 km downstream of Ukai Dam and 19.4 km upstream from the mouth of River Tapi, has experienced the largest flood in 2006. The peak discharge of about 25,770 m 3 s −1 released from the Ukai Dam was responsible for a disaster. To assess the flood and find inundation in low-lying areas, simulation work is carried out under the 1D/2D couple hydrodynamic modeling. Two hundred ninety-nine cross sections, two hydraulic structures and five major bridges across the river are considered for 1D modeling, whereas a topographic map at 0.5 m contour interval was used to produce a 5 m grid, and SRTM (30 and 90 m) grid has been considered for Surat and the Lower Tapi Basin. The tidal level at the river mouth and the release from the Ukai Dam during 2006 flood are considered as the downstream and upstream boundaries, respectively. The model is simulated under the unsteady flow condition and validated for the year 2006. The simulated result shows that 9th August was the worst day in terms of flooding for Surat city and a maximum 75–77% area was under inundation. Out of seven zones, the west zone had the deepest flood and inundated under 4–5 m. Furthermore, inundation is simulated under the bank protection work (i.e., levees, retaining wall) constructed after the 2006 flood. The simulated results show that the major zones are safe against the inundation under 14,430 m 3 s −1 water releases from Ukai Dam except for the west zone. The study shows the 2D capability of new HEC-RAS 5 for flood inundation mapping and management studies.

Abstract. Surat, India is a coastal city with a population of approximately 4.5 million people that lies on the banks of the river Tapi and is located 100 km downstream from the Ukai dam. Given Surat's geographic location the city is repeatedly exposed to flooding caused by large emergency dam releases into the Tapi river combined with high tide water levels. Flood events of this type occur twice a decade, but their frequency and magnitude may increase due to the urbanization, encroachment in flood plain and climate change. A first step towards strengthening resilience in Surat requires a robust method for mapping flood exposure at fine spatial resolution. Here, in this study we have developed such a method for Surat using a reduced-complexity hydrodynamic model to simulate flooding, but is easily transferable to other urban locations. Our method features three distinct phases that involve: (1) modelling dam release discharge from the Ukai dam arriving at Surat, (2) modelling flooding within Surat caused by the combination of dam release and tides, and, (3) identifying Surat critical infrastructure, population, and income groups exposed to flooding. Our flood model of Surat utilizes topography produced using elevation data collected from an extensive survey. Within the city we have modelled flood scenarios that represent the uncertainty in flood peak discharge and duration resulting from possible climate change. These scenarios include catastrophic conditions that flood 50 % of the city and expose > 60 % of the population and critical infrastructure to deep flooding. Finally, we highlight how our modelling has contributed to changes in flood risk management within the city following a major flood and resulted in actions that have increased community resilience to flood hazard.

The controls on methane (CH4) bubbling (ebullition) from peatlands are uncertain, but evidence suggests that physical factors related to gas transport and storage within the peat matrix are important. Variability in peat pore size and the permeability of layers within peat can produce ebullition that ranges from steady to erratic in time and can affect the degree to which CH4 bubbles bypass consumption by methanotrophic bacteria and enter the atmosphere. Here we investigate the role of peat structure on ebullition in structurally different peats using a physical model that replicates bubble production using air injection into peat. We find that the frequency distributions of number of ebullition events per time and the magnitude of bubble loss from the physical model were similar in shape to ebullition from peatlands and incubated peats. This indicates that the physical model could be a valid proxy for naturally occurring ebullition from peat. For the first time, data on bubble sizes from peat were collected to conceptualize ebullition, and we find that peat structure affects bubble sizes. Using a new method to measure peat macrostructure, we collected evidence that supports the hypothesis that structural differences in peat determine if bubble release is steady or erratic and extreme. Collected pore size data suggest that erratic ebullition occurs when large amounts of gas stored at depth easily move through shallower layers of open peat. In contrast, steady ebullition occurs when dense shallower layers of peat regulate the flow of gas emitted from peat.

Storm tide (combination of storm surge and the astronomical tide) flooding is a natural hazard with significant global social and economic consequences. For this reason, government agencies and stakeholders need storm tide flood maps to determine population and infrastructure at risk to present and future levels of inundation. Computer models of varying complexity are able to produce regional-scale storm tide flood maps and current model types are either static or dynamic in their implementation. Static models of storm tide utilize storm tide heights to inundate locations hydrologically connected to the coast, whilst dynamic models simulate physical processes that cause flooding. Static models have been used in regional-scale storm tide flood impact assessments, but model limitations and coarse spatial resolutions contribute to uncertain impact estimates. Dynamic models are better at estimating flooding and impact but are computationally expensive. In this study we have developed a dynamic reduced-complexity model of storm tide flooding that is computationally efficient and is applied at hyper-resolutions (<100 m cell size) over regional scales. We test the performance of this dynamic reduced-complexity model and a separate static model at three test sites where storm tide observational data are available. Additionally, we perform a flood impact assessment at each site using the dynamic reduced-complexity and static model outputs. Our results show that static models can overestimate observed flood areas up to 204 % and estimate more than twice the number of people, infrastructure, and agricultural land affected by flooding. Overall we find that that a reduced-complexity dynamic model of storm tide provides more conservative estimates of coastal flooding and impact.

The hydraulic modelling of tidal estuarine environments has been largely limited to complex 3D models that are computationally expensive. This makes them unsuitable for applications which make use of live data to make real/near time forecasts, such as the modelling of storm surge propagation and associated flood inundation risks. To address this requirement for a computationally efficient method a reduced complexity, depth-integrated 2D storage cell model (Lisflood-FP) has been applied to the Humber Estuary, UK. The capability of Lisflood-FP to reproduce the tidal heights of the Humber Estuary has been shown by comparing modelled and observed tidal stage heights over a period of a week. The feasibility of using the Lisflood-FP model to forecast flood inundation risk from a storm surge is demonstrated by reproducing the major storm surge that struck the UK East Coast and Humber Estuary on 5 December 2013. Results show that even for this 2013 extreme event the model is capable of reproducing the hydraulics and tidal levels of the estuary. Using present day flood defences and observed flooding extents, the modelled flood inundation areas produced by the model were compared, showing agreement in most areas and illustrating the model's potential as a now-casting early warning system when driven by publically available data, and in near real-time. The Lisflood-FP model used was incorporated into the CAESAR-Lisflood GUI, with the calibration and verification of the estuarine hydraulics reported herein being a key step in creating an estuary evolution model, capable of operating in the decadal to century timescales that are presently underrepresented in estuarine predictive capability, and ultimately developing a model to predict the evolution of flood risk over the longer term.

Bubble dynamics in porous media are of great importance in industrial and natural systems. Of particular significance is the impact that bubble‐related emissions (ebullition) of greenhouse gases from porous media could have on global climate (e.g., wetland methane emissions). Thus, predictions of future changes in bubble storage, movement, and ebullition from porous media are needed. Methods exist to predict ebullition using numerical models, but all existing models are limited in scale (spatial and temporal) by high computational demands or represent porous media simplistically. A suitable model is needed to simulate ebullition at scales beyond individual pores or relatively small collections (<10−4 m3) of connected pores. Here we present a cellular automaton model of bubbles in porous media that addresses this need. The model is computationally efficient, and could be applied over large spatial and temporal extent without sacrificing fine‐scale detail. We test this cellular automaton model against a physical model and find a good correspondence in bubble storage, bubble size, and ebullition between both models. It was found that porous media heterogeneity alone can have a strong effect on ebullition. Furthermore, results from both models suggest that the frequency distributions of number of ebullition events per time and the magnitude of bubble loss are strongly right skewed, which partly explains the difficulty in interpreting ebullition events from natural systems.

Bubbling (ebullition) of greenhouse gases, particularly methane, from peatlands has been attributed to environmental forcings, such as changes in atmospheric pressure. However, observations from peat soils suggest that ebullition and environmental forcing may not always be correlated and that interactions between bubbles and the peat structure may be the cause of such decoupling. To investigate this possibility, we used a simple computer model (Model of Ebullition and Gas storAge) to simulate methane ebullition from a model peat. We found that lower porosity peat can store methane bubbles for lengthy periods of time, effectively buffering or moderating ebullition so that it no longer reflects bubble production signals. Our results suggest that peat structure may act as a signal shredder and needs to be taken into account when measuring and modeling ebullition.

Human migration north through Africa is contentious. This paper uses a novel palaeohydrological and hydraulic modelling approach to test the hypothesis that under wetter climates c.100,000 years ago major river systems ran north across the Sahara to the Mediterranean, creating viable migration routes. We confirm that three of these now buried palaeo river systems could have been active at the key time of human migration across the Sahara. Unexpectedly, it is the most western of these three rivers, the Irharhar river, that represents the most likely route for human migration. The Irharhar river flows directly south to north, uniquely linking the mountain areas experiencing monsoon climates at these times to temperate Mediterranean environments where food and resources would have been abundant. The findings have major implications for our understanding of how humans migrated north through Africa, for the first time providing a quantitative perspective on the probabilities that these routes were viable for human habitation at these times.

Insect pollination benefits over three quarters of the world's major crops. There is growing concern that observed declines in pollinators may impact on production and revenues from animal pollinated crops. Knowing the distribution of pollinators is therefore crucial for estimating their availability to pollinate crops; however, in general, we have an incomplete knowledge of where these pollinators occur. We propose a method to predict geographical patterns of pollination service to crops, novel in two elements: the use of pollinator records rather than expert knowledge to predict pollinator occurrence, and the inclusion of the managed pollinator supply. We integrated a maximum entropy species distribution model (SDM) with an existing pollination service model (PSM) to derive the availability of pollinators for crop pollination. We used nation-wide records of wild and managed pollinators (honey bees) as well as agricultural data from Great Britain. We first calibrated the SDM on a representative sample of bee and hoverfly crop pollinator species, evaluating the effects of different settings on model performance and on its capacity to identify the most important predictors. The importance of the different predictors was better resolved by SDM derived from simpler functions, with consistent results for bees and hoverflies. We then used the species distributions from the calibrated model to predict pollination service of wild and managed pollinators, using field beans as a test case. The PSM allowed us to spatially characterize the contribution of wild and managed pollinators and also identify areas potentially vulnerable to low pollination service provision, which can help direct local scale interventions. This approach can be extended to investigate geographical mismatches between crop pollination demand and the availability of pollinators, resulting from environmental change or policy scenarios.

ABSTRACTLandscape evolution models (LEMs) simulate the geomorphic development of river basins over long time periods and large space scales (100s–1000s of years, 100s of km2). Due to these scales they have been developed with simple steady flow models that enable long time steps (e.g. years) to be modelled, but not shorter term hydrodynamic effects (e.g. the passage of a flood wave). Nonsteady flow models that incorporate these hydrodynamic effects typically require far shorter time steps (seconds or less) and use more expensive numerical solutions hindering their inclusion in LEMs. The recently developed LISFLOOD‐FP simplified 2D flow model addresses this issue by solving a reduced form of the shallow water equations using a very simple numerical scheme, thus generating a significant increase in computational efficiency over previous hydrodynamic methods. This leads to potential convergence of computational cost between LEMs and hydrodynamic models, and presents an opportunity to combine such schemes. This paper outlines how two such models (the LEM CAESAR and the hydrodynamic model LISFLOOD‐FP) were merged to create the new CAESAR‐Lisflood model, and through a series of preliminary tests shows that using a hydrodynamic model to route flow in an LEM affords many advantages. The new model is fast, computationally efficient and has a stronger physical basis than a previous version of the CAESAR model. For the first time it allows hydrodynamic effects (tidal flows, lake filling, alluvial fans blocking valley floor) to be represented in an LEM, as well as producing noticeably different results to steady flow models. This suggests that the simplification of using steady flow in existing LEMs may bias their findings significantly. Copyright © 2013 John Wiley & Sons, Ltd.

Precipitation intensities and the frequency of extreme events are projected to increase under climate change. These rainfall changes will lead to increases in the magnitude and frequency of flood events that will, in turn, affect patterns of erosion and deposition within river basins. These geomorphic changes to river systems may affect flood conveyance, infrastructure resilience, channel pattern, and habitat status as well as sediment, nutrient and carbon fluxes. Previous research modelling climatic influences on geomorphic changes has been limited by how climate variability and change are represented by downscaling from global or regional climate models. Furthermore, the non-linearity of the climatic, hydrological and geomorphic systems involved generate large uncertainties at each stage of the modelling process creating an uncertainty "cascade". This study integrates state-of-the-art approaches from the climate change and geomorphic communities to address these issues in a probabilistic modelling study of the Swale catchment, UK. The UKCP09 weather generator is used to simulate hourly rainfall for the baseline and climate change scenarios up to 2099, and used to drive the CAESAR landscape evolution model to simulate geomorphic change. Results show that winter rainfall is projected to increase, with larger increases at the extremes. The impact of the increasing rainfall is amplified through the translation into catchment runoff and in turn sediment yield with a 100% increase in catchment mean sediment yield predicted between the baseline and the 2070–2099 High emissions scenario. Significant increases are shown between all climate change scenarios and baseline values. Analysis of extreme events also shows the amplification effect from rainfall to sediment delivery with even greater amplification associated with higher return period events. Furthermore, for the 2070–2099 High emissions scenario, sediment discharges from 50-yr return period events are predicted to be 5 times larger than baseline values.

The Mediterranean Sea provides a major route for heat and freshwater loss from the North Atlantic and thus is an important cause of the high density of Atlantic waters. In addition to the traditional view that loss of fresh water via the Mediterranean enhances the general salinity of the North Atlantic, and the interior of the eastern North Atlantic in particular, it should be noted that Mediterranean water outflowing at Gibraltar is in fact cooler than compensating inflowing water. The consequence is that the Mediterranean is also a region of heat loss from the Atlantic and contributes to its large‐scale cooling. Uniquely, this system can be understood physically via the constraints placed on it by a single hydraulic structure: the Gibraltar exchange. Here we review the existing knowledge about the physical structure of the Gibraltar exchange today and the evidential basis for arguments that it has been different in the past. Using a series of quantitative experiments, we then test prevailing concepts regarding the potential causes of these past changes. We find that (1) changes in the vertical position of the plume of Mediterranean water in the Atlantic are controlled by the vertical density structure of the Atlantic; (2) a prominent Early Holocene “contourite gap” within the Gulf of Cadiz is a response to reduced buoyancy loss in the eastern Mediterranean during the time of “sapropel 1” deposition; (3) changes in buoyancy loss from the Mediterranean during MIS3 caused changes in the bottom velocity field in the Gulf of Cadiz, but we note that the likely cause is reduced freshwater loss and not enhanced heat loss; and (4) strong exchange at Gibraltar during Atlantic freshening phases implies that the Gibraltar exchange provides a strong negative feedback to reduced Atlantic meridional overturning. Given the very counterintuitive way in which the Strait of Gibraltar system behaves, we recommend that without quantitative supporting work, qualitative interpretations of how the system has responded to past external forcing are unlikely to be robust.

Northern peatlands are one of the largest natural sources of atmospheric methane (CH4), and it is important to understand the mechanisms of CH4 loss from these peatlands so that future rates of CH4 emission can be predicted. CH4 is lost to the atmosphere from peatlands by diffusion, by plant transport, and as bubbles (ebullition). We argue that ebullition has not been accounted for properly in many previous studies, both in terms of measurement and the conceptualization of the mechanisms involved. We present a new conceptual model of bubble buildup and release that emphasizes the importance of near-surface peat as a source of atmospheric CH4. We review two possible approaches to modeling bubble buildup and loss within peat soils: the recently proposed bubble threshold approach and a fully computational-fluid-dynamics approach. We suggest that neither satisfies the needs of peatland CH4 models, and we propose a new reduced-complexity approach that conceptualizes bubble buildup and release as broadly similar to an upside down sandpile. Unlike the threshold approach, our model allows bubbles to accumulate at different depths within the peat profile according to peat structure, yet it retains the simplicity of many cellular (including cellular automata) models. Comparison of the results from one prototype of our model with data from a laboratory experiment suggests that the model captures some of the key dynamics of ebullition in that it reproduces well observed frequency-magnitude relationships. We outline ways in which the model may be further developed to improve its predictive capabilities.