Predicting regime shifts in flow of the Colorado River

Abstract

[1] The effects of continued global warming on water resources are a concern for water managers and stake holders. In the western United States, where the combined climatic demand and consumptive use of water is equal to or greater than the natural supply of water for some locations, there is growing concern regarding the sustainability of future water supplies. In addition to the adverse effects of warming on water supply, another issue for water managers is accounting for, and managing, the effects of natural climatic variability, particularly persistently dry and wet periods. Analyses of paleo-reconstructions of Upper Colorado River basin (UCRB) flow demonstrate that severe sustained droughts, and persistent pluvial periods, are a recurring characteristic of hydroclimate in the Colorado River basin. Shifts between persistently dry and wet regimes (e.g., decadal to multidecadal variability (D2M)) have important implications for water supply and water management. In this study paleoreconstructions of UCRB flow are used to compute the risks of shifts between persistently wet and dry regimes given the length of time in a specific regime. Results indicate that low frequency variability of hydro-climatic conditions and the statistics that describe this low frequency variability can be useful to water managers by providing information about the risk of shifting from one hydrologic regime to another. To manage water resources in the future water managers will have to understand the joint hydrologic effects of natural climate variability and global warming. These joint effects may produce future hydrologic conditions that are unprecedented in both the instrumental and paleoclimatic records. Citation: Gangopadhyay, S., and G. J. McCabe (2010), Predicting regime shifts in flow of the Colorado River, Geophys.

Predicting regime shifts in flow of the Gunnison River under changing climate conditions

“…The time interval ( T ) between wet and dry regimes is assumed here to be a stochastic process that can be fitted to a given probability distribution [ Enfield and Cid‐Serrano , ; Gangopadhyay and McCabe , ]. As in Gangopadhyay and McCabe [], a two‐parameter gamma distribution is used to study the shift between wet and dry regimes. Gamma distributions have been previously used to model the distribution of regime intervals [ Gangopadhyay and McCabe , ; Salas et al ., ].…”

“…As in Gangopadhyay and McCabe [], a two‐parameter gamma distribution is used to study the shift between wet and dry regimes. Gamma distributions have been previously used to model the distribution of regime intervals [ Gangopadhyay and McCabe , ; Salas et al ., ]. From the defined probability distribution function ( P ), a cumulative distribution function may be derived.…”

“…Using an assumption of timepass, water resource managers may use the cumulative distribution to determine the conditional probability of a regime shift over an assumed subsequent period of time [ Enfield and Cid‐Serrano , ; Gangopadhyay and McCabe , ]. As such, given the time elapsed since a previous regime shift, t 1 , the conditional probability that a regime shift will occur within a future time horizon, t 2 , can be expressed as equation (1) from Gangopadhyay and McCabe [] and described prior by Enfield and Cid‐Serrano []. where t = t 1 + t 2 is the current climate regime interval and Γ [ t ] is the two‐parameter gamma cumulative distribution function.…”

“…As the impacts of climate change are realized, it is important to investigate how shifting hydrologic regimes may change in the future. Here, the methodology presented in Gangopadhyay and McCabe [] is applied to a paleoreconstruction of streamflow developed over the Gunnison River Basin [ Woodhouse et al ., ] and compared to an ensemble of future streamflow projections presented in Miller et al . [].…”

The role of palaeoecological records in assessing ecosystem services

“…This transfer function was then applied to tree-ring records dating back to 1482 to determine the long-term variability in the river flow. This is in itself an interesting study on baseline conditions; however, the authors also used the data to build a river flow regime model capable of predicting the probability of a regime shift between persistently wet or dry states in the river given the number of years since the previous shift (Gangopadhyay and McCabe, 2010). This provides an exceptionally useful tool for managers aiming to allocate water to the many users across the basin.…”