Dynamic Information Framework (DIF) as the process of merging information from multiple sources

Complexities of Multi-scale Resource Management Practices

   Globally, landscapes and their downstream coastal zones are facing a series of challenges critical to their future, centered on the availability and distribution of water. Land use actions at a discrete spatial location can have hydrological flow impacts hundreds to thousands of miles away. Floods and droughts will impact biodiversity, freshwater resources, agriculture and livelihoods. Upstream development of hydropower will provide much-needed energy, but will alter the flow regime and sediment transport of the river. Climate variability and change is forcing changes in temperature and rainfall regimes, reduction of mountain glaciers, and possibly, the frequency and intensity of extreme events. Global economic impacts and food shortages are already growing concern; international effort must be made to predict and mitigate potential changes. Management options cover a range of issues, from bringing safe water to local villages for the rural poor, developing adaptation strategies for both rural and urban populations and large infrastructure, and sustaining environmental flows and services needed for natural and human-dominated ecosystems. 

   Environmental conservation and sustainability is functionally and practically expressed by how governmental Ministries address such questions as
• What effects would changing climate have on water resources and biodiversity?
• How would changes in land use practices affect water supply, water quality, and biodiversity?
• What would be the impacts of changes in agriculture (including irrigation) and forestry practices on local and regional water balances?
• How does biodiversity respond to altitude, soil, and climate gradients? What are the linkages between biodiversity and agricultural productivity?
• If some indication of climate over a growing season was provided, could crop selection (and fire management) be improved?
• Can floods or droughts be predicted, or at least anticipated, one or two months into the future, as an early-warning system?

   These targets represent a very complex set of intersecting issues of scale, cross-sector science (agriculture, biodiversity, forestry, water resources) and technology, education, politics, and economics. Implications transcend projects and Ministries. An immediate challenge is to incorporate the realities of changing environmental conditions in these sectors into the policies and projects of the Ministries nominally responsible, based on the absolute best understanding of the dynamics involved, and done in a way that optimizes a multi-stakeholder return. But, in practice, such information and even perspectives are virtually absent, in much of especially the developing world. Overall, this intersection is poorly-understood, verging on “black-box,” where the paucity of data and complexity in processes creates serious problems in decision making.

   The issues facing the development of the Mekong are extremely complex, involving the intersection of the “natural” environment (landscape structure, hydrologic cycle, fisheries) in the context of social and economic development, particularly hydropower. Analysis of this suite of issues poses information challenges, from the management and analysis of complex data to conveying the results to (non-technical) Decision Makers and a general public. The intent of a "Dynamic Information Frameowrk" (DIF) is to mobilize information from multiple sources to help meet the Mekong challenges.

Developing a Dynamic Information Framework for Scenario Generation and Decision Support

   A dynamic platform where decision-makers can consider rigorous scenarios of alternative futures and obtain decision support for complex environmental and economic decisions, is essential given near certain population growth to 9.2 billion by 2050 and significant but unpredictable climate change. To build such capabilities, information from multiple sources must converge, be organized and be evaluated (preferably according to ecosystem principles), and be easily accessible. A critical launch point is the development of baseline assessments of the current and past drivers and impacts of natural resource change. With such a baseline established, then future scenarios can be analyzed, and the evolution of key system drivers/forcers and impacts can be monitored.

   A Dynamic Information Framework (DIF) is a geospatial gateway for dynamic understanding, management, and planning of the landscape (beyond “business as usual”). The goal is to provide an instrument for a (quantitative) analysis of complex interdependent problems. A fundamental aspect to a DIF is not only the convergence of multi-sector information, but how that information can be conveyed, in the most compelling, and visual, manner. Essentially, a DIF is a numeric and quantitative “Commons,” or meeting place, which builds on the legacy of knowledge from experience, with the goal of “harmonizing” region function for multiple users.

   The DIF is based on how water and the landscape (topography, soils, vegetation, biodiversity) converge, in space and time. The central thread is that water provides spatial, time-based, and operational connectivity among the multitude of DIF layers, because everyone understands water (one has it or not, it is of adequate quality or not, it is available in the right place at the right time or not). Most important it is observable, measureable, ‘modelable’ as a function of known drivers and spatial-temporal relationships. 

   Very briefly, the functional components of DIF of include base data layers, directed data layers focused on synthetic objectives, geospatially-explicit, process-based, cross-sector simulation models (requiring data from the directed data layers), facilitated input/output (including visualizations), and decision support system and scenario testing capabilities. The objective is to provide a “time machine,” for multiple stakeholders.
The process of creating the DIF provides
• An integration of data from multiple sources (of interest to all stakeholders)
• Provides a means for interpolation of sparse data
• Provides quantitative baselines and an instrument for analysis of interdependent problems
• Provides the basis for cross- scale/ upscaling analyses
• Provides a foundation for “scenarios”
• Perhaps most importantly, the construction of a DIF promotes cooperation and communication between individuals and sectors that rarely, if ever, communicate.