USING GIS AND ENVIRONMENTAL MONITORING TOOLS TO MANAGE SUSTAINABLE WATER SOURCES IN THE CIBOLA NATIONAL FOREST NM

Much of New Mexico’s climate is characterized as being arid; that is, there is very little moisture for much of the year with annual water distribution occurring primarily during early spring snow-melt, and during the late summer monsoons. In a region where water is relatively scarce, all potable sources are important enough to require monitoring, especially as climate forecast models suggest that the Southwest may experience further water supply challenges in the future.

In New Mexico, springs can be a hotspot for biodiversity and endemic species. In otherwise arid landscapes, a single spring can mean survival for plants, wildlife, and people. Also, springs create rich and diverse micro-habitats. In order to simultaneously utilize and protect springs on managed lands, it is important to monitor those springs’ baseline conditions, and to watch for changes in water quality and quantity.

Over the previous two summers, 2012-2013, we have taken a comprehensive water quality inventory of known springs within the Cibola National Forest. The Zuni, Sandia and Mt Taylor divisions of The Cibola National Forest have, thus far, been inventoried. At each site, our protocol is used to describe and catalogue the geohydrology. Each visit requires location of the exact orifice of the spring, which may drift over time. Locations are updated, and, if water is present, field parameters are measured and a sample is brought back to the lab.

Samples are analyzed to determine concentrations of key elements and to estimate each water systems buffering capacity. These data are then displayed and overlain with other pertinent geographic data using GIS software. On a map, concentrations of key elements are made visible using graduated symbols and layered on a geologic map; such that, a relationship between key-element concentrations and the associated geologic substrate, faults and hydrologic conditions, can be clearly, and easily observed. In this way, a robust round of sample data is archived and displayed with previous data so that we may better visualize, monitor and conserve this precious resource.