Subwatershed spatial analysis tool: Discretization of a distributed hydrologic model by statistical criteria Academic Article uri icon

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 subwatersheds 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.

published proceedings

  • JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION

author list (cited authors)

  • Haverkamp, S., Srinivasan, R., Frede, H. G., & Santhi, C.

citation count

  • 25

complete list of authors

  • Haverkamp, S||Srinivasan, R||Frede, HG||Santhi, C

publication date

  • December 2002

publisher