Patuxent landscape model: 1. Hydrological model development

Voinov, Alexey; Fitz, Carl; Maxwell, T. A.

doi:10.1134/s0097807807020066

Cited by 12 publications

(8 citation statements)

References 9 publications

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“…This high level visual-oriented software and simulation language has been employed in a Downloaded by [New York University] at 07:00 09 June 2015 M a n u s c r i p t 4 number of hydrological modelling studies (e.g. Zhang and Mitsch 2005, Voinov et al 2007, Thompson et al 2013a. The model had a monthly time step with an initial baseline period of 1971-2000 being used to simulate river flows at the 13 gauging stations for which discharge records were acquired.…”

Section: Hydrological Modelmentioning

confidence: 99%

Projections of hydrology in the Tocantins-Araguaia Basin, Brazil: uncertainty assessment using the CMIP5 ensemble

Thompson

Brierley

2016

Hydrological Sciences Journal

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A semi-distributed hydrological model is developed, calibrated and validated against unregulated river discharge from the Tocantins-Araguaia River Basin, northern Brazil. Climate change impacts are simulated using projections from the 41 Coupled Model Intercomparison Project Phase 5 climate models for the period 2071-2100 under the RCP4.5 scenario. Scenario results are compared to a 1971-2000 baseline. Most climate models suggest declines in mean annual discharge although some predict increases. A large proportion suggest that the dry season experiences large declines in discharge, especially during the transition to the rising water period. Most models (>75%) suggest declines in annual minimum flows. This may have major implications for both current and planned hydropower schemes. There is greater uncertainty in projected changes in wet season and annual maximum discharges. Two techniques are investigated to reduce uncertainty in projections, but neither are able to provide more confidence in the simulated changes in discharge.

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Section: Hydrological Modelmentioning

confidence: 99%

Projections of hydrology in the Tocantins-Araguaia Basin, Brazil: uncertainty assessment using the CMIP5 ensemble

Thompson

Brierley

2016

Hydrological Sciences Journal

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“…The model was implemented using the STELLA systems modelling software (Version 10, isee systems) which provides a high level visual-oriented software and simulation language and has been employed in a number of catchment and wetland hydrological modelling studies (e.g. Zhang and Mitsch 2005, Voinov et al 2007, Ho et al 2015.…”

Section: Hydrological Modellingmentioning

confidence: 99%

GCM-related uncertainty for river flows and inundation under climate change: the Inner Niger Delta

Thompson

Crawley

Kingston

2016

Hydrological Sciences Journal

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A semi-distributed hydrological model of the Niger River above and including the Inner Delta is developed. GCM-related uncertainty in climate change impacts are investigated using seven GCMs for a 2°C increase in global mean temperature, the hypothesised threshold of "dangerous" climate change. Declines in precipitation predominate, although some GCMs project increases for some subcatchments, whilst PET increases for all scenarios. Inter-GCM uncertainty in projected precipitation is three to five times that of PET. With the exception of one GCM (HadGEM1), which projects a very small increase (3.9%), river inflows to the Delta decline. There is considerable uncertainty in the magnitude of these reductions, ranging from 0.8% (HadCM3) to 52.7% (IPSL). Whilst flood extent for HadGEM1 increases (mean annual peak +1405 km 2 /+10.2%), for other GCMs it declines. These declines range from almost negligible changes to a 7903 km 2 (57.3%) reduction in the mean annual peak.ARTICLE HISTORY

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“…This issue can be also seen in Figure (E), which depicts varying possibilities in Voinov et al 's () Patuxent landscape model, which models water flow between surrounding grid cells, where neighborhoods consist of (a) contiguous cells only, (b) a larger, second ring of cells, and (c) a dynamic structure where distance of flow from a cell is based on water depth. This example illustrates the complexities of linking neighborhood size, model resolution, and time step to the dynamic processes modeled.…”

Section: Spatial Thinking In Other Disciplinesmentioning

confidence: 93%

A theory of spatial system archetypes

BenDor

Kaza

2012

System Dynamics Review

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Historic reference behavior and archetypes of system structure are key tools for creating rigorous system dynamics (SD) models. Modelers often delineate causal relationships by employing common archetypes of dynamic system structure, which produce behaviors such as growth and decline, oscillation, and complex combinations thereof. We extend archetypes to spatial‐dynamic models, focusing on structural archetypes that exhibit changing spatial patterns in two‐dimensional landscapes. Although many fields employ spatial modeling techniques, analogy‐based, causally focused system archetypes remain confined to non‐spatial SD models. We draw on spatial analysis literature to explore the influence of space on dynamic relationships and archetypes, including methods for articulating “space” and expressing feedback. We offer simple examples of spatial system archetypes and explore network structures for spatially extending SD models. By doing this, we argue for spatial modeling techniques that parallel the learn‐by‐analogy environment that archetypes have promoted in aspatial SD research. Copyright © 2012 System Dynamics Society.

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Patuxent landscape model: 1. Hydrological model development

Cited by 12 publications

References 9 publications

Projections of hydrology in the Tocantins-Araguaia Basin, Brazil: uncertainty assessment using the CMIP5 ensemble

Projections of hydrology in the Tocantins-Araguaia Basin, Brazil: uncertainty assessment using the CMIP5 ensemble

GCM-related uncertainty for river flows and inundation under climate change: the Inner Niger Delta

A theory of spatial system archetypes

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