A framework to identify appropriate spatial and temporal scales for modeling N flows from watersheds

20-03-2008 | Publication

Many different large-scalewatershed nitrogen (N) flowmodels exist, which describe processes related to the horizontal movement of N through large drainage networks of river basins. Equations of such models can be applied on different scales. This modeling scale is important because it affects the processes that can bewell described, the required input data, the scenarios that can be simulated, and usefulness of resulting predictions. Modeling scale can be measured as a combination of support, extent, and stream order of model parts.


We describe a framework (FAMOS) to identify the appropriate spatial and temporal scales for nitrogen (N) flow models. FAMOS has been developed for models of N export from large watersheds. With FAMOS, modelers can identify the appropriate scale for model predictions and for independently scalable model parts.

FAMOS is based upon four criteria to check the appropriateness of modeling scales. Modeling scales thus have to correspond with (A) data and scenarios, (B) model assumptions, (C) available resources for modeling, and (D) appropriately scaled predictions. We present 12 indicators to test these criteria. A user of FAMOS may use all or a selection of these, to identify the appropriateness of a modeling scale for his purpose. The indicators vary between 0 and 1 as a function of scale, and are to be quantified and weighted by the user.

A successful application of FAMOS is illustrated for a global model of dissolved inorganic nitrogen (DIN) export from watersheds to coastal waters. Ranges of appropriate scales are determined for model predictions and five independently scalable model parts, which model the (1) surface N balance, (2) point sources, (3) N flow in sediments and small streams, (4) retention in dammed reservoirs, and (5) riverine DIN retention.

We conclude that FAMOS can contribute substantially to a well-balanced and comprehensive identification of appropriate modeling scales.