Design of a Sediment-Monitoring Gaging Network on Ephemeral Tributaries of the Colorado River in Glen, Marble, and Grand Canyons, Arizona

Abstract

Management of sediment in rivers downstream from dams requires knowledge of both the sediment supply and downstream sediment transport. In some dam-regulated rivers, the amount of sediment supplied by easily measured major tributaries may overwhelm the amount of sediment supplied by the more difficult to measure lesser tributaries. In this first class of rivers, managers need only know the amount of sediment supplied by these major tributaries. However, in other regulated rivers, the cumulative amount of sediment supplied by the lesser tributaries may approach the total supplied by the major tributaries. The Colorado River downstream from Glen Canyon has been hypothesized to be one such river. If this is correct, then management of sediment in the Colorado River in the part of Glen Canyon National Recreation Area downstream from the dam and in Grand Canyon National Park may require knowledge of the sediment supply from all tributaries. Although two major tributaries, the Paria and Little Colorado Rivers, are well documented as the largest two suppliers of sediment to the Colorado River downstream from Glen Canyon Dam, the contributions of sediment supplied by the ephemeral lesser tributaries of the Colorado River in the lowermost Glen Canyon, and Marble and Grand Canyons are much less constrained. Previous studies have estimated amounts of sediment supplied by these tributaries ranging from very little to almost as much as the amount supplied by the Paria River. Because none of these previous studies relied on direct measurement of sediment transport in any of the ephemeral tributaries in Glen, Marble, or Grand Canyons, there may be significant errors in the magnitudes of sediment supplies estimated during these studies. To reduce the uncertainty in the sediment supply by better constraining the sediment yield of the ephemeral lesser tributaries, the U.S. Geological Survey Grand Canyon Monitoring and Research Center established eight sediment-monitoring gaging stations beginning in 2000 on the larger of the previously ungaged tributaries of the Colorado River downstream from Glen Canyon Dam. The sediment-monitoring gaging stations consist of a downward-looking stage sensor and passive suspended-sediment samplers. Two stations are equipped with automatic pump samplers to collect suspended-sediment samples during flood events.

Directly measuring discharge and collecting suspended-sediment samples in these remote ephemeral streams during significant sediment-transporting events is nearly impossible; most significant run-off events are short-duration events (lasting minutes to hours) associated with summer thunderstorms. As the remote locations and short duration of these floods make it prohibitively expensive, if not impossible, to directly measure the discharge of water or collect traditional depth-integrated suspended-sediment samples, a method of calculating sediment loads was developed that includes documentation of stream stages by field instrumentation, modeling of discharges associated with these stages, and automatic suspended-sediment measurements. The approach developed is as follows (1) survey and model flood high-water marks using a two-dimensional hydrodynamic model, (2) create a stage-discharge relation for each site by combining the modeled flood flows with the measured stage record, (3) calculate the discharge record for each site using the stage-discharge relation and the measured stage record, and (4) calculate the instantaneous and cumulative sediment loads using the discharge record and suspended-sediment concentrations measured from samples collected with passive US U-59 samplers and ISCO^TM pump samplers. This paper presents the design of the gaging network and briefly describes the methods used to calculate discharge and sediment loads. The design and methods herein can easily be used at other remote locations where discharge and sediment loads are required.

First posted July 18, 2014