ABSTRACT:

As part of a larger collaboration between the USGS, USAID, and partners in Jordan and Lebanon, we developed an open-source and interactive web application that allows users to classify, weight, and combine layers to produce suitability maps easily and transparently. The user can choose how to make suitability classifications within each spatial layer, how to apply relative weights to different spatial layers, and observe how those changes affect the resulting suitability map and distribution of suitability scores across the landscape. The application has two pre-loaded spatial layers describing modeled runoff and surface slope and uses a simplified version of suitability mapping. Values within each input layer are classified as having either “Good” or “Poor” suitability, based on a user-supplied threshold value chosen using interactive sliders. Those layers are then weighted based on user-supplied weights and linearly aggregated to create a final suitability map.
The application is not meant as a substitute for more formal suitability mapping techniques. Rather, the web application is presented as a tool aimed at end-users and stakeholders as a way to increase transparency and process-understanding throughout the development of suitability mapping. We use example data from the Jordan Valley, a subset of our full project region to demonstrate the capabilities of the application. The web application was written in R (v 4.0.3) with shiny package (v 1.0.6). This resource will be updated with a link to the full project when the project report is published.

ABSTRACT:

We analyzed daily nitrate concentration (c) and discharge (Q) data for a four-year period (2016-2019) from five nested, agricultural watersheds in the Midwestern United States. We partitioned the hydrograph into stormflow and baseflow periods and examined the nitrate export patterns of those periods separately through the analysis of their concentration-discharge (c-Q) relationships. Baseflow showed consistently positive c-Q chemodynamic slope, while stormflow c-Q relationships showed a much weaker chemostatic pattern. This suggests that water source contributions during baseflow are nonstationary. Anomalous flow periods greatly influenced overall c-Q patterns, suggesting that understanding event-scale characteristics is critical when interpreting seasonal or annual patterns. The watersheds span two distinct landforms shaped by differences in geologic history resulting in natural landscape properties that necessitated different drainage infrastructure across the study area. The density of built drainage infrastructure was a strong predictor of c-Q relationship and nitrate load, with more drainage infrastructure associated with higher loads and more chemostatic export patterns across all watersheds. This suggests that how humans ‘replumb’ the subsurface in response to geologic conditions has implications for hydrologic connectivity, homogenization of source areas, and subsequently nutrient export. This resource is the time series of discharge and nitrate partitioned into stormflow ("siteeventsdataframe.RDS") and baseflow ("sitenonevents.RDS").