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Interfaces gráficas em auxílio à implementação e ao uso de modelos hidrológicos
Abstract
Distributed hydrological models are useful to understand and to simulate land use change impacts on surface water balance and river discharge. Implementing a distributed hydrological model can be a hard task for those who have just basic knowledge of programming techniques, especially regarding to some specific components of hydrological models such as the conservation of mass throughout the timesteps and along the surface grid cells. Implementing and running a model on command lines seems not to be the most flexible and comprehensive way to work with hydrological models, once the processes can not be easily understood directly on script languages. Because of this, the use of modeling platforms with visual resources such as graphical interfaces can be helpful to understand the processes being modeled and to make the use of models friendlier. In this paper we discuss the implementation of some basic components of the "Terrestrial Hydrology Model with Biogeochemistry", THMB (Coe et al., 2007), as a way to improve model comprehensiveness and usability. The model was built on Dinamica EGO modeling platform, which has visual resources on its graphical user interface (GUI). Those resources were considered especially helpful considering: (a) creation of models on a intuitive data flow perspective; (b) modular organization of the model, including the creation of groups of functions and comments to organize ideas; (c) quick launch of a Map Viewer through the interface helping on visualizing results; (d) a Wizard editor to help on describing the model concepts and to assist model use. Palavras-chave: Modelagem hidrológica, plataformas de modelagem, interfaces gráficas.
Forests, through the regulation of regional water balances, provide a number of ecosystem services, including water for agriculture, hydroelectric power generation, navigation, industry, fisheries, and human consumption. Large-scale deforestation triggers complex non-linear interactions between the atmosphere and biosphere, which may impair such important ecosystem services. This is the case for the Southwestern Amazon, where three important river basins (Juruá, Purus, and Madeira) are undergoing significant land-use changes. Here, we investigate the potential impacts of deforestation throughout the Amazon on the seasonal and annual water balances of these river basins using coupled climatic and hydrologic models under several deforestation scenarios. Simulations without climate response to deforestation show an increase in river discharge proportional to the area deforested in each basin, whereas those with climate response produce progressive reductions in mean annual precipitation over all three basins. In this case, deforestation decreases the mean annual discharge of the Jurua´ and Purus rivers, but increases that of the Madeira, because the deforestation-induced reduction in evapotranspiration is large enough to increase runoff and thus offset the reduction in precipitation. The effects of Amazon deforestation on river discharge are scale-dependent and vary across and within river basins. Reduction in precipitation due to deforestation is most severe at the end of the dry season. As a result, deforestation increases the dry-season length and the seasonal amplitude of water flow. These effects may aggravate the economic losses from large droughts and floods, such as those experienced in recent years (2005, 2010 and 2009, 2012, respectively).
Simulation models can be envisaged as a heuristic device useful for assessing, from long and short-terms, the outcomes from a variety of scenarios, translated as different socioeconomic, political, and environ-mental frameworks. A special class among them, spatially explicit models simulate the dynamics of an environ-mental system, reproducing the way its spatial patterns evolve, to project the probable ecological and socioeco-nomic consequences from the system dynamics. In this context, we have developed a spatially explicit simula-tion model of landscape dynamics – Dinamica, as a tool to investigate trajectory of landscapes and dynamics of spatial phenomena. In this paper, we present its new version called Dinamica EGO – acronym for Environment for Geoprocessing Objects. In this version, Dinamica was totally reengineered. The software environment holds a series of algorithms called functors. Each algorithm performs an algebra map algebra operator. To date, we have implemented the most common spatial analysis operators available in commercial GIS, plus a series of operators especially designed for spatial simulations, including calibration and validation methods. These func-tors are sequenced to establish a data flow in form of a graph. Through this graphical interface one can create models by simply dragging and connecting functors via their ports, which represent connectors to types of data, such as maps, tables, matrices, mathematical expressions, and constants. Thus models can be designed as a dia-gram and execution follows a data flow chain. This friendly interface allows the design from simple to very complex spatial models that are saved in a script language. As a result, Dinamica EGO software favors simplic-ity, flexibility, and performance, optimizing speed and computer resources, such as memory and parallel proc-essing. To illustrate its application potential, we present a version of SimAmazonia deforestation model imple-mented on Dinamica EGO platform, describing the functors employed in the design of this model. Palavras-chave: Dinamica EGO, spatial simulation model, environmental modeling, deforestation, SimAma-zon, modelagem de sistemas ambientais, modelo de simulação espacial, desmatamento, SimAmazonia.
This paper describes the impacts of new river geomorphic and flow parameterizations on the simulated surface waters dynamics of the Amazon River basin. Three major improvements to a hydrologic model are presented: (1) the river flow velocity equation is expanded to be dependent on river sinuosity and friction in addition to gradient forces; (2) equations defining the morphological characteristics of the river, such as river height, width and bankfull volume, are derived from 31 622 measurements of river morphology and applied within the model; (3) 1 km resolution topographic data from the Shuttle Radar Topography Mission (SRTM) are used to provide physically based fractional flooding of grid cells from a statistical representation of sub-grid-scale floodplain morphology. The discharge and floodplain inundation of the Amazon River is simulated for the period 1968–1998, validated against observations, and compared with results from a previous version of the model. These modifications result in considerable improvement in the simulations of the hydrological features of the Amazon River system. The major impact is that the average wet-season flooded area on the Amazon mainstem for the period 1983–1988 is now within 5% of satellite-derived estimates of flooded area, whereas the previous model overestimates the flooded area by about 80%. The improvements are a consequence of the new empirical river geomorphologic functions and the SRTM topography. The new formulation of the flow velocity equation results in increased river velocity on the mainstem and major tributaries and a better correlation between the mean monthly simulated and observed discharge. Copyright © 2007 John Wiley & Sons, Ltd.
In this study, results from two sets of numerical simulations are evaluated and presented; one with the land surface model IBIS forced with prescribed climate and another with the fully coupled atmospheric general circulation and land surface model CCM3-IBIS. The results illustrate the influence of historical and potential future deforestation on local evapotranspiration and discharge of the Amazon River system with and without atmospheric feedbacks and clarify a few important points about the impact of deforestation on the Amazon River. In the absence of a continental scale precipitation change, large-scale deforestation can have a significant impact on large river systems and appears to have already done so in the Tocantins and Araguaia Rivers, where discharge has increased 25% with little change in precipitation. However, with extensive deforestation (e.g. >30% of the Amazon basin) atmospheric feedbacks, brought about by differences in the physical structure of the crops and pasture replacing natural vegetation, cause water balance changes of the same order of magnitude as the changes due to local land surface processes, but of opposite sign. Additionally, changes in the water balance caused by atmospheric feedbacks are not limited to those basins where deforestation has occurred but are spread unevenly throughout the entire Amazon by atmospheric circulation. As a result, changes to discharge and aquatic environments with future deforestation of the Amazon will likely be significant and a complex function of how much vegetation has been removed from that particular watershed and how much has been removed from the entire Amazon Basin.
Here we present a new terrestrial biosphere model (the Integrated Biosphere Simulator - IBIS) which demonstrates how land surface biophysics, terrestrial carbon fluxes, and global vegetation dynamics can be represented in a single, physically consistent modeling framework. In order to integrate a wide range of biophysical, physiological, and ecological processes, the model is designed around a hierarchical, modular structure and uses a common state description throughout. First, a coupled simulation of the surface water, energy, and carbon fluxes is performed on hourly timesteps and is integrated over the year to estimate the annual water and carbon balance. Next, the annual carbon balance is used to predict changes in the leaf area index and biomass for each of nine plant functional types, which compete for light and water using different ecological strategies. The resulting patterns of annual evapotranspiration, runoff, and net primary productivity are in good agreement with observations. In addition
Este trabalho apresenta a base matemática do modelo chamado Autômatos Celulares Aninhados (Nested-CA), um modelo de computação destinado ao desenvolvimento de modelos de mudança de uso e cobertura do solo em múltiplas escalas. As principais propriedades do modelo nested-CA são descritas e comparadas aos modelos de computação baseados em agentes e em autômatos celulares. O modelo nested-CA foi implementado em uma ambiente computacional, chamado TerraME, que oferece uma linguagem de alto nível para a descrição de modelos, um conjunto de estruturas de dados espaço-temporais para a representação e simulação dos modelos, um modulo para o gerenciamento e análise de dados espaço-temporais integrado a um sistema de informações geográficas, e um conjunto de funções para calibração e validação dos modelos. As decisões de projetos envolvidas no desenvolvimento do ambiente de modelagem TerraME são descritas. A arquitetura do ambiente é detalhada e suas principais propriedades são comparadas com outras plataformas de modelagem: Swarm, STELLA, e GEONAMICA. Finalmente, o conceito de nested-CA e o ambiente TerraME são demonstrados em duas aplicações de mudança de cobertura do solo para a Amazônia brasileira. ABSTRACT: This work presents the mathematical foundations of the Nested Cellular Automata (nested-CA) model, a model of computation for multiple scale Land Use and Land Cover Change studies. The main properties of nested-CA model are described and compared to the agent-based and cellular automata models of computation. The nested- CA model has been implemented in a software environment, called TerraME (Terra Modeling Environment), which provides a high-level modeling language for model description, a set of spatiotemporal data structures for model representation and simulation, a module for spatiotemporal data management and analysis integrated to a geographic information system, and a set of functions for model calibration and validation. We describe the main design choices involved in the development of the TerraME modeling environment. Its architecture is detailed and the main properties are compared with other modeling tools: Swarm, STELLA, and GEONAMICA. Finally, the concept of nested-CA and the TerraME architecture are demonstrated in two applications of land cover change in the Brazilian Amazon. Number of Pages: 114
Expansion of the cattle and soy industries in the Amazon basin has increased deforestation rates and will soon push all-weather highways into the region's core. In the face of this growing pressure, a comprehensive conservation strategy for the Amazon basin should protect its watersheds, the full range of species and ecosystem diversity, and the stability of regional climates. Here we report that protected areas in the Amazon basin--the central feature of prevailing conservation approaches--are an important but insufficient component of this strategy, based on policy-sensitive simulations of future deforestation. By 2050, current trends in agricultural expansion will eliminate a total of 40% of Amazon forests, including at least two-thirds of the forest cover of six major watersheds and 12 ecoregions, releasing 32 +/- 8 Pg of carbon to the atmosphere. One-quarter of the 382 mammalian species examined will lose more than 40% of the forest within their Amazon ranges. Although an expanded and enforced network of protected areas could avoid as much as one-third of this projected forest loss, conservation on private lands is also essential. Expanding market pressures for sound land management and prevention of forest clearing on lands unsuitable for agriculture are critical ingredients of a strategy for comprehensive conservation.
A terrestrial ecosystem model (integrated biosphere simulator (IBIS)) and a hydrological routing algorithm (HYDRA) are used in conjunction with long time series climate data to simulate the river discharge and flooded area of the Amazon/Tocantins River basin over the last 60 years. Evaluating the results of this modeling exercise over the entire basin yields three major results: (1) Observations at 121 stations throughout the basin show that discharge is well simulated for most tributaries originating in Brazil. However, the discharge is consistently underestimated, by greater than 20%, for tributaries draining regions outside of Brazil and the main stem of the Amazon. The discharge underestimation is most likely a result of underestimated precipitation in the data set used as model input. (2) A new flooding algorithm within HYDRA captures the magnitude and timing of the river height and flooded area in relatively good agreement with observations, particularly downstream of the confluence of the Negro and Solimões Rivers. (3) Climatic variability strongly impacts the hydrology of the basin. Specifically, we find that short (∼3–4 years) and long (∼28 years) modes of precipitation variability drive spatial and temporal variability in river discharge and flooded area throughout the Amazon/Tocantins River basins.
dinamica, a spatially explicit simulation model of landscape dynamics has been developed. dinamica is a cellular automata model that presents multi-scale vicinity-based transitional functions, incorporation of spatial feedback approach to a stochastic multi-step simulation engine, and the application of logistic regression to calculate the spatial dynamic transition probabilities. This model was initially conceived for the simulation of Amazonian landscape dynamics, particularly the landscapes evolved in areas occupied by small farms. For testing its performance, the model was used to simulate spatial patterns of land-use and land-cover changes produced by the Amazonian colonists in clearing the forest, cultivating the land, and eventually abandoning it for vegetation succession. The study area is located in an Amazonian colonization frontier in the north of Mato Grosso state, Brazil. The model was run for two sub-areas of colonization projects, using an 8-year time span, from 1986 to 1994. The simulated maps were compared with land-use and land-cover maps, obtained from digital classification of remote sensing images, using the multiple resolution fitting procedure and a set of landscape structure measures, including fractal dimension, contagion index, and the number of patches for each type of land-use and land-cover class. The results from the validation methods for the two areas showed a good performance of the model, indicating that it can be used for replicating the spatial patterns created by landscape dynamics in Amazonian colonization regions occupied by small farms. Possible applications of dinamica include the evaluation of landscape fragmentation produced by different architectures of colonization projects and the prediction of a region's spatial pattern evolution according to various dynamic phases.
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