Fig 5
Simulated upland basin with a simple straight channel used in initial spatial and temporal sensitivity tests. Results are shown of an aggregation into 5 units according to upslope contributing area. Bar plots shows the plan areal contribution for each unit.
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In 2001, Beven and Freer introduced a "dynamic" variant of TOPMODEL that addressed some of the limitations of the original model whilst retaining its computational and parametric efficiency. The original assumption of a quasi-steady water table was replaced by time-dependent kinematic routing within hydrological similar areas. The new formulation a...
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... shown at the start of the programme flowchart in Fig. 4. A conceptual model of a Hydrological Response Unit within the new implementation, along with linkages with other units and model components is shown in Fig. 3. The storages associated with HRU entities are defined in Table 3 and flows (shown by arrows linking entities in Fig. 3) in Table 4 (Figs. 5 and ...
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Images and text from an exhibition held in London in November 2015 on the potential use of historical spatial data for the UK, in the context of the intelligent cities debate.
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... TWI was estimated in R software using the upland.area function in the dynatopmodel package From the 10 m DEM (Metcalfe et al., 2015). Spatial Analyst in ArcGIS was used to calculate the curvature of a surface at each cell center relative to eight neighboring cells. ...
Rooting in deep regolith enables forests to withstand seasonal and annual precipitation shortfalls. Despite its ecological importance, spatial patterns in regolith thickness within forest ecosystems are scarcely documented. Regolith thickness was estimated at 66 sites throughout a 543‐ha watershed in the southern Sierra Nevada by hand auger to point of failure or a maximum depth of 7.5 m, describing a minimum thickness estimate. Regolith consists of 1–2 m of soil overlying thick and porous weathered granodiorite. Depth to auger failure ranged from 1.52 to an indeterminate depth beyond 7.5 m. A total of 27 points exceeded 7.5 m depth. Normal, lognormal, and gamma data distribution models were fitted to observations to extrapolate thickness across the watershed and estimate thicknesses beyond the measurement limitation. Predictions for the 95th percentile of regolith thickness varied substantially; 26.05 m for lognormal, 16.87 m for gamma, and 9.56 m for normal. Considering any best fit model, >55% of the watershed area was deeper than 5 m. Depth classes were formed to evaluate the extent to which topography is associated with spatial trends in regolith thickness. Spatial patterns were related to two covariate proxies (distance from stream channel and topographic wetness) with the general landscape trend of shallow depth classes (<3.3 m) in lowlands and deeper regolith classes (>7.5 m) in uplands. The normalized difference vegetation index signatures over the late stages of a 5‐year drought were greener in the lowlands. In contrast, upland forests displayed widespread tree die‐off, suggesting deep water storage does not maintain forests over long‐term drought.
... Topographic variables (30-m spatial resolution) used in this study include Slope, Aspect, Roughness, topographic position index (TPI), topographic roughness index (TRI), topographic heat-load index (THI), and topographic wetness index (TWI). These variables were computed from underlying digital terrain models from LIDAR data collected in 2007 (Washington State Department of Natural Resources (WSDNR), 2020) in R using the lidR (Roussel et al., 2020;Roussel & Auty, 2023), spatialEco (Evans & Murphy, 2021), raster (Hijmans & van Etten, 2012), and dynatopmodel (Metcalfe et al., 2015) packages. In addition to these gridded environmental data, we also collected temperature every 2 h using HOBO Pendant® loggers at 20 sites (five in each of the resurveyed subbasins; Figure 1) from September 2020 to September 2021 (Pradhan et al., 2023). ...
Recent studies highlight the potential of climate change refugia (CCR) to support the persistence of biodiversity in regions that may otherwise become unsuitable with climate change. However, a key challenge in using CCR for climate resilient management lies in how CCR may intersect with existing forest management strategies, and subsequently influence how landscapes buffer species from negative impacts of warming climate. We address this challenge in temperate coastal forests of the Pacific Northwestern United States, where declines in the extent of late-successional forests have prompted efforts to restore old-growth forest structure. One common approach for doing so involves selectively thinning forest stands to enhance structural complexity. However, dense canopy is a key forest feature moderating understory microclimate and potentially buffering organisms from climate change impacts, raising the possibility that approaches for managing forests for old-growth structure may reduce the extent and number of CCR. We used remotely-sensed vegetation indices to identify CCR in an experimental forest with control and thinned (restoration) treatments, and explored the influence of biophysical variables on buffering capacity. We found that remotely sensed vegetation indices commonly used to identify CCR were associated with understory temperature and plant community composition, and thus captured aspects of landscape buffering that might instill climate resilience and be of interest to management. We then examined the interaction between current restoration strategies and CCR, and found that selective thinning for promoting old-growth structure had only very minor, if any, effects on climatic buffering. In all, our study demonstrates that forest management approaches aimed at restoring old-growth structure through targeted thinning do not greatly decrease buffering capacity, despite a known link between dense canopy and CCR. More broadly, this study illustrates the value of using remote sensing approaches to identify CCR, facilitating the integration of climate change adaptation with other forest management approaches.
... We utilize dynamic TOPMODEL to simulate hydrologic fluxes and connectivity from hillslopes to the stream network (see reviews of dynamic TOPMODEL in Beven and Freer, 2001;Beven, 2011;Metcalfe et al., 2015). Dynamic TOPMODEL is a process-based hydrologic model that simulates hillslope hydrology using the variable upslope contributing area approach, building upon its widely applied predecessor, TOPMODEL (Beven and Kirkby, 1979), by incorporating an additional parameter, sd max , to represent disconnectivity of upland hillslope units during periods of extensive drying and abandoning the original assumption of a quasi-steady water table (Metcalfe et al., 2015). ...
... We utilize dynamic TOPMODEL to simulate hydrologic fluxes and connectivity from hillslopes to the stream network (see reviews of dynamic TOPMODEL in Beven and Freer, 2001;Beven, 2011;Metcalfe et al., 2015). Dynamic TOPMODEL is a process-based hydrologic model that simulates hillslope hydrology using the variable upslope contributing area approach, building upon its widely applied predecessor, TOPMODEL (Beven and Kirkby, 1979), by incorporating an additional parameter, sd max , to represent disconnectivity of upland hillslope units during periods of extensive drying and abandoning the original assumption of a quasi-steady water table (Metcalfe et al., 2015). Dynamic TOPMODEL solves a time-varying mass balance to simulate the change in subsurface and lateral flow between Hydrologic Response Units (HRUs) as: ...
... Lateral flow over the surface and through the subsurface is assumed in this study to follow the catchment topography, which likely holds true in systems with relatively steep slopes and shallow soil depths (Beven, 1997), albeit with some degree of uncertainty. Lateral connectivity to the stream network can be conceptualized using a weighted flow matrix, which maintains the structural contiguity of the hillslope by representing the proportion of flow from one landscape unit that flows into downstream landscape units, as discussed in Beven and Freer (2001) and Metcalfe et al. (2015). This matrix is defined as: ...
... This is the motivation for our paper. Here, we propose Generalised Multistep Dynamic (GMD) 101 TOPMODEL, by modifying and reformulating Dynamic-TOPMODEL of Metcalfe et al. (2015), and solve the 102 resulting system of equations using MATLAB's ODE suite. 103 Note that while there are core similarities between GMD-TOPMODEL proposed here and the Dynamic-104 TOPMODEL of Metcalfe et al. (2015), there are also key differences intended to: extend the model's appli-105 cability to a wider range of landscapes where previously Dynamic-TOPMODEL's assumptions would break 106 down; provide flexibility in better representing spatial heterogeneity; and improve physical process representa-107 tions. ...
... Here, we propose Generalised Multistep Dynamic (GMD) 101 TOPMODEL, by modifying and reformulating Dynamic-TOPMODEL of Metcalfe et al. (2015), and solve the 102 resulting system of equations using MATLAB's ODE suite. 103 Note that while there are core similarities between GMD-TOPMODEL proposed here and the Dynamic-104 TOPMODEL of Metcalfe et al. (2015), there are also key differences intended to: extend the model's appli-105 cability to a wider range of landscapes where previously Dynamic-TOPMODEL's assumptions would break 106 down; provide flexibility in better representing spatial heterogeneity; and improve physical process representa-107 tions. More specifically, these are: (i) an 'iso-basin' hillslope discretisation which allows flexibility to represent 108 spatial heterogeneity where such information is available or is the study focus; (ii) a flexible diffusion-wave hy- (vii) tilting the frame of reference to the more physically correct version, i.e., along the slope, as opposed to a 117 horizontal frame typically used, leading to extended applicability of the model to steeper catchments (previously 118 only applicable to moderate slopes). ...
There is a lack of Ordinary Differential Equation (ODE) formulations in numerical hydrology, contributing to the lack of application of canned adaptive timestep solvers; hence the continued dominance of fixed (e.g., Euler) timestep techniques despite their fundamental problems. In this paper, we reformulate Dynamic‐TOPMODEL into a constraint‐handling ODE form and use MATLAB's advanced adaptive ODE‐solvers to solve the resulting system of equations. For wider applicability, but based on existing research and/or first principles, we developed Generalized Multistep Dynamic TOPMODEL which includes: iso‐basin spatial discretization, diffusion wave routing, depth‐dependent overland flow velocity, relaxing the assumption of water‐table parallelism to the ground surface, a power‐law hydraulic conductivity profile, new unsaturated zone flux, and a reference frame adjustment. To demonstrate the model we calibrate it to a peat catchment case study, for which we also test sensitivity to spatial discretization. Our results suggest that (a) a five‐fold improvement in model runtime can result from adaptive timestepping; (b) the additional iso‐basin discretization layer, as a way to further constrain spatial information where needed, also improves performance; and (c) the common‐practice arbitrary Topographic Index (TI) discretization substantially alters calibrated parameters. More objective and physically constrained (e.g., top‐down) approaches to TI classification may be needed.
... DECIPHeR is a flexible hydrological modelling framework (Coxon et al., 2019) which is based on the dynamic TOP-MODEL (Beven and Freer, 2001;Metcalfe et al., 2015;Freer et al., 2004;Peters et al., 2003). The model can be spatially configured in any form, providing a distributed mosaic of interacting and spatially connected HRUs that allow different representations of water fluxes due to local conditions (i.e. ...
In this paper we implement a degree day snowmelt and glacier melt model in the Dynamic fluxEs and ConnectIvity for Predictions of HydRology (DECIPHeR) model. The purpose is to develop a hydrological model that can be applied to large glaciated and snow-fed catchments yet is computationally efficient enough to include model uncertainty in streamflow predictions. The model is evaluated by simulating monthly discharge at six gauging stations in the Naryn River catchment (57 833 km2) in central Asia over the period 1951 to a variable end date between 1980 and 1995 depending on the availability of discharge observations. The spatial distribution of simulated snow cover is validated against MODIS weekly snow extent for the years 2001–2007. Discharge is calibrated by selecting parameter sets using Latin hypercube sampling and assessing the model performance using six evaluation metrics. The model shows good performance in simulating monthly discharge for the calibration period (NSE is 0.74
... For the calculation, we coarsened the spatial resolution of the DEM from 1 m to 10 m to better represent hydrologic flow regimes at a point location (Quinn et al., 1995). We generated TWI with the formula below within the dynatop R package (Metcalfe et al., 2015). ...
Forest canopies can buffer seedlings from extreme climate conditions. Yet, how disturbed forest canopies influence microclimate is not well understood, despite the important implications of microclimate for seedling establishment and post-disturbance successional trajectories. Better understanding of the relationship between a forest canopy and sub-canopy temperature and moisture conditions requires easily acquired and continuous forest canopy data, which is increasingly available due to new technology. Here, we measured canopy height using a remotely piloted aircraft (RPA) and monitored microclimate with low-cost temperature and soil moisture sensors in a sub-boreal forest impacted by fires of variable severity. We used regression models to investigate how differences in canopy height influenced microclimate variables. Mean growing season temperatures at -8 cm (soil), 0 cm (surface), and 15 cm (near-surface) relative to the ground surface were higher under shorter more disturbed canopies. Soil temperature was most sensitive to canopy height differences: linear models for the observed data range predicted a 2.0 °C increase in mean growing season soil temperature with every 10 m decrease in canopy height. We observed a weak negative relationship between canopy height and mean growing season soil moisture. We found that canopy height summarized at moderate resolution (15 m) better explained differences in temperature in our disturbed landscape. This work informs future methods to produce gridded microclimate datasets and outlines the impact of disturbed forest structure on microclimate variables. Our results show that the characteristics of the forest canopy remaining after a burn impact microclimates, which has important implications for post-fire ecosystems.
... Topographic position influences forest structure and dynamics by affecting abiotic conditions like soil moisture and mechanical stability (Arriaga, 2000;Schwartz, Budsock, & Uriarte, 2019). We calculated the topographic wetness index (TWI) and slope from the lidar-derived digital terrain model at 26-m resolution using the package dynatopmodel in R (Metcalfe, Beven, & Freer, 2015). High TWI values indicate grid cells with topographical characteristics favorable for moisture accumulation, and slope affects both runoff and the type and location of human activities on the landscape. ...
Understanding the heterogeneity of biomass accumulation in second‐growth tropical forests following land use abandonment is important for informing ecosystem carbon models and forest restoration efforts. There is an urgent need for a broad sample of second‐growth forests to enhance our knowledge of carbon accumulation in human‐dominated landscapes, especially for older forests. Puerto Rico has predominantly second‐growth forests, ranging in age from approximately 25 to more than 80 years. We used an island‐wide sample of airborne lidar from the NASA Goddard Lidar, Hyperspectral, and Thermal (G‐LiHT) Airborne Imager collected on March 2017, forest inventory data, and data on forest age, precipitation, soils, and land use to estimate aboveground biomass stocks in moist and wet, second‐growth tropical forests. Biomass accumulation rates in Puerto Rico were lower, on average, than in other Neotropical forests. Median biomass across >16,700 ha of older second‐growth forests was 105 Mg ha ⁻¹ , and sampled biomass rarely surpassed 250 Mg ha ⁻¹ . Differences in biomass by age were large and persistent across different substrates and land uses, with a plateau in the pattern of island‐wide biomass accumulation after about 33 years. A spatial regression model showed that multiple factors were related to biomass accumulation, including time since abandonment, geologic substrate, past land use as coffee or pasture, precipitation, topographic wetness index, and slope. Our findings have important consequences for the total carbon storage and expected climate mitigation benefits of large‐scale reforestation efforts, and highlight the value of airborne lidar for quantifying biomass variability in complex tropical landscapes.
Abstract in Spanish is available with online material.
... DECIPHeR is a flexible hydrological modelling framework (Coxon et al., 2019) which is based on dynamic TOPMODEL (Beven and Freer, 2001;Metcalfe et al., 2015;Freer et al., 2004;Peters et al., 2003). The model can be spatially configured in any form, providing a distributed mosaic of interacting and spatially connected hydrological response units (HRU's) that allow different representations of water fluxes due to local conditions (i.e. ...
In this paper we implement a degree day snow and glacier melt model into the Dynamic fluxEs and ConnectIvity for Predictions of HydRology (DECIPHeR) model. The purpose is to develop a hydrological model that can be applied to large glaciated and snow-fed catchments, yet is computationally efficient enough to include model uncertainty in streamflow predictions. The model is evaluated by simulating monthly discharge at six gauging stations in the Naryn River catchment (57,833 km2) in Central Asia over the period 1951 to a variable end date between 1980 and 1995 depending on the availability of discharge observations. The spatial distribution of simulated snow cover is validated against MODIS weekly snow extent for the years 2001–2007. Discharge is calibrated by selecting parameter sets using Latin Hypercube sampling and assessing the model performance using six evaluation metrics. The model shows good performance at simulating monthly discharge for the evaluation period (NSE is 0.74
... After standardizing measures of elevation, slope, and convexity to a mean of 0 and standard deviation of 1, the three variables were used to classify the 3000 20 × 20-m quadrats into the three major habitats (plateau, slope, and low plain) using Ward hierarchical clustering ( Figure 1). Finally, we calculated the topographic wetness index (TWI), which reflects the ability of a landscape to retain water and is a strong predictor of savanna wildlife distributions [26], by integrating the total water catchment area and slope of each grid cell using build.layers in the dynatopmodel package [27]. Cells with high TWI tend to be flat or concave. ...
Do hotspots of plant biodiversity translate into hotspots in the abundance and diversity of large mammalian herbivores? A common expectation in community ecology is that the diversity of plants and animals should be positively correlated in space, as with the latitudinal diversity gradient and the geographic mosaic of biodiversity. Whether this pattern ‘scales down’ to landscape-level linkages between the diversity of plants or the activities of highly mobile megafauna has received less attention. We investigated spatial associations between plants and large herbivores by integrating data from a plant-DNA-barcode phylogeny, camera traps, and a comprehensive map of woody plants across the 1.2-km2 Mpala Forest Global Earth Observatory (ForestGEO) plot, Kenya. Plant and large herbivore communities were strongly associated with an underlying soil gradient, but the richness of large herbivore species was negatively correlated with the richness of woody plants. Results suggest thickets and steep terrain create associational refuges for plants by deterring megaherbivores from browsing on otherwise palatable species. Recent work using dietary DNA metabarcoding has demonstrated that large herbivores often directly control populations of the plant species they prefer to eat, and our results reinforce the important role of megaherbivores in shaping vegetation across landscapes.
... Grey-box and hybrid models have, to a degree, superseded white-box models. The most well-known grey-box and hybrid-models derive from TOPMODEL (Topographic Model) and its many variants which are based on very specific assumptions about the nature of the hydrological processes (e.g., Beven and Kirkby, 1979;Kirkby, 1997;Beven and Freer, 2001;Beven, 2012;Gao et al., 2015;Metcalfe et al., 2015). The Stanford Watershed Model is another early and well-known model of this type which is based on purely conceptual elements (Crawford and Lindsey, 1966;Beven, 2012). ...
