SUBWATERSHED SPATIAL ANALYSIS TOOL: DISCRETIZATION OF A DISTRIBUTED HYDROLOGIC MODEL BY STATISTICAL CRITERIA1

ABSTRACT: Complex hydrologic models, designed for simulating larger watersheds, require a huge amount of input data. Most of these models use spatially distributed data as inputs. Spatial data can be aggregated or disaggregated for use as input to a model, which can impact model outputs. Although, it is efficient to minimize data redundancy by aggregating the spatial data, upscaling reduces the detail/resolution of input information and increases model uncertainty. On the other hand, a large number of model inputs with high degrees of disaggregation take more computer time and space to process. Hence, a balance between striving for a maximum level of aggregation and a minimum level of information loss has to be achieved. This study presents a definition of an appropriate level of discretization, derived by establishing a relationship between a model's efficiency and the number of subwater‐sheds modeled. An entropy based statistical approach/tool called Subwatershed Spatial Analysis Tool (SUSAT) was developed to find an objective choice of an appropriate level of discretization. The new approach/tool was applied to three watersheds, each representing different hydrologic conditions, using a hydrologic model. Coefficients of efficiency and entropy estimated at different levels of discretization were used to validate the success of the new approach.     

‘Dynamic behavioral fingerprinting’: what drives the deployment of environmental information and communication capabilities?

This article investigates the impact of organizational drivers for the implementation of business process and network information and communication capabilities (ICCs) supporting cleaner production in the Dutch food and beverage industry. We do so with the intention to promote ‘dynamic behavioral fingerprinting’.Survey results show, that sub-sectors of this industry are driven to adopt environmental ICCs to a different level. Responses range from compliance-oriented (Slaughterhouses & meat sub-sector) to market-oriented (Bakery and biscuits sub-sector). Knowledge of key drivers and their impact offers opportunities to adjust the environmental policy and instruments to sub-sector specifics so that its effectiveness is improved. We therefore propose ‘dynamic behavioral fingerprinting’: mapping “typical” patterns of managerial response towards environmental issues, in order to improve the effectiveness of public–private interaction and cooperation.