IWRAM: An integrated toolbox for considering impacts of development and land use change in Northern Thailand

The IWRAM Decision Support System was developed to consider economic, environmental, and sociocultural trade-offs involved with resource competition and development in the Mae Chaem catchment in Northern Thailand. IWRAM contains two modelling toolboxes utilising a nodal network structure for catchment analysis: a Biophysical Toolbox, for considering the biophysical (erosion, streamflow, crop) implications of 'painted on' land use scenarios; and, an Integrated Modelling Toolbox, which links models of household decision making with the biophysical toolbox to allow for consideration of socioeconomic and environmental trade-offs of many development and policy scenarios. This paper describes the Integrated Modelling Toolbox within the IWRAM system. Links between household decision models, a socioeconomic impacts model and the biophysical toolbox are described and results for a number of forest encroachment scenarios are demonstrated using key indicators of social, economic and environmental performance. The potential for reapplication of the modelling framework to a large number of catchment situations is also discussed. (Résumé d'auteur

Predicting daily streamflow using rainfall forecasts, a simple loss module and unit hydrographs: two Brazilian catchments

The performance of a simple, spatially-lumped, rainfallestreamflow model is compared with that of a more complex, spatially-distributedmodel. In terms of two model-fit statistics it is shown that for two catchments in Brazil (about 30,000 km2and 34,000 km2) with different flowregimes, the simpler catchment models, which are unit hydrograph-based and require only rainfall, streamflow and air temperature data for cal-ibration, perform about as well as more complex catchment models that require additional information from satellite images and digitized mapsof elevation, land-use and soils. Simple catchment models are applied in forecasting mode, using daily rainfall forecasts from a regional weatherforecasting model. The value of the rainfall forecasts, relative to the case where rainfall is known, is assessed for both catchments. The results arediscussed in the context of on-going work to compare different modelling approaches for many other Brazilian catchments, and to apply im-proved forecasting algorithms based on the simple modelling approach to the same, and other, catchments

Integrated assessment of meso-level watershed development: progress of an integrated evaluation project in Andhra Pradesh

In Sarala, C. (Ed.). Proceedings of the 3rd International Conference on Hydrology and Watershed Management (ICHWAM-2010), with a focal theme on climate change - water, food and environmental security, 3-6 February 2010. Vol.2. Hyderabad, India: Jawaharlal Nehru Technological University, Institute of Science and Technology, Centre for Water ResourcesThe issue of scale has become paramount for the effective evaluation of WSD programs. Shile terms vary from state to state, the following definitions have been adopted for this study and are deemed appropriate for Andhra Pradesh. Micro scale - less than 1500 hectares; Meso scale 1500 - 10000 hectares; Macro level over 10000 hectares (including basin level investigations). There is a need for a meso-scale benefit and cost evaluation of the WSD programs so that unintended impacts are avoided and that the implementation of programs is improved. Operating at a meso-scale will also provide more effective opportunities to link and address micro and macro scale biophysical and institutional issues. This project will integrate environmental, economic, social, equity and dimensions at meso levels to help ensure that WSD contributes positively to the Indian government's sustainable livelihoods goal and provide the foundations for a resilient and sustainable WSD. Success will not only be determined by spatial scale (e.g. micro versus meso) but will also be determined by the disciplinary scale of analysis (e.g. focusing on short term economic efficiency alone runs considerable risk of ignoring longer term trends in natural and social capital). This paper describes early progress on developing such an evaluation model

Good Modelling Practice

Best-practice guidelines for Modelling have been developed by a numbers of organizations to promote better understanding of model development and application, facilitate tests of model quality and provide a framework for documenting and communicating modelling activities among modellers and decision makers. Good practice within a Data Mining paradigm is presented in Chapter 12

Characterising performance of environmental models

In order to use environmental models effectively for management and decision-making, it is vital to establish an appropriate level of confidence in their performance. This paper reviews techniques available across various fields for characterising the performance of environmental models with focus on numerical, graphical and qualitative methods. General classes of direct value comparison, coupling real and modelled values, preserving data patterns, indirect metrics based on parameter values, and data transformations are discussed. In practice environmental modelling requires the use and implementation of workflows that combine several methods, tailored to the model purpose and dependent upon the data and information available. A five-step procedure for performance evaluation of models is suggested, with the key elements including: (i) (re)assessment of the model's aim, scale and scope; (ii) characterisation of the data for calibration and testing; (iii) visual and other analysis to detect under- or non-modelled behaviour and to gain an overview of overall performance; (iv) selection of basic performance criteria; and (v) consideration of more advanced methods to handle problems such as systematic divergence between modelled and observed values