Of those gauges that are still in operation, most are located on rivers that are highly modified by human activities and gauge records prior to impacts are limited. These limitations can be partially overcome with modeling approaches to predict the attributes of natural stream flow expected in the absence of human influence. The predictions can then be compared to measured stream flow at gauging locations, or they can be used to estimate natural flow conditions in ungauged streams. In 2010, Carlisle et al. developed a modeling technique to predict natural attributes of stream flow and assessed stream flow alteration at gauges throughout the United States . Soon after, UC and TNC scientists began using the approach to expand and further refine the technique for applications in California . The models have evolved over time, but all rely on stream flow monitoring data from USGS gauges located on streams with minimal influence from upstream human activities. These are referred to as reference gauges. Some reference gauge data come from historical measurements made before significant modification of flows occurred, such as the years prior to the building of a dam. The remaining data are from reference gauges located in California watersheds that remain minimally altered by human influence. Once reference gauges were identified and flow records obtained from the USGS web-based retrieval system, we used geographic information systems to characterize the watersheds above each reference gauge based on their physical attributes, such as topography, geology and soils . We also assembled monthly precipitation and temperature climate data for the past 65 years for each watershed. The watershed variables and climate data were then compiled and statistically evaluated in relation to observed flow conditions at the reference sites using a machine-learning approach that uses the power of modern computers to search for predictive relationships in large data sets. An advantage of machine-learning techniques is the ability to make predictions from multiple model iterations ,vertical hydroponic garden which tends to increase accuracy.

Once we had developed and evaluated models using observed stream flow data from reference gauges, we could predict stream flow attributes for any portion of a stream or river in California for which the climate and watershed characteristics were known . Additional technical details of the modeling approach are provided in Carlisle et al. 2016 and Zimmerman et al. 2018.In a study led by Zimmerman et al. , we applied the machine-learning technique to assess patterns of stream flow modification in California. We did this by predicting natural monthly flows at 540 streams throughout California with long-term USGS gauging stations and comparing those predictions with observed conditions. We then assessed how observed flow conditions at the gauges deviated from predictions and recorded the frequency and degree to which flows were either higher or lower than natural expected levels, while considering the uncertainty of model predictions. We found evidence of widespread stream flow modification in California . The vast majority of sites experienced at least 1 month of modified flows over the past 20 years and many sites were modified most of the time . When stream flows were modified, the magnitude of modification tended to be high. On average, inflated stream flows were 10 times higher than natural expected levels, whereas depleted stream flows were 20% of natural expected levels. Overall, stream flow modification in California reflects a loss of natural seasonal variability by shifting water from the wet season to the dry season and from wet areas of the state to the drier south.Conversely, flow depletion was most common in winter and spring months and for annual maximum flows. Unaltered sites tended to occur in places with relatively low population density and water management infrastructure, such as the North Coast, whereas greater magnitude and frequency of alteration was seen in rivers that feed the massive water infrastructure in the Central Valley and the populated Central Coast and South Coast regions. A key water management goal in California is to manage river flows to support native freshwater biodiversity. By estimating natural river flows and the degree to which they are modified, our work provides a foundation for assessing “ecological flow” needs, or the river flows necessary to sustain ecological functions, species and habitats.

Assessments of ecological flow needs are generally performed at stream reach to regional scales , but rarely for an area as large and geographically complex as California. In 2017, a technical team that includes scientists from UC, TNC, USGS, California Trout, Southern California Coastal Water Research Project and Utah State University began developing a statewide approach for assessing ecological flows. The team has identified a set of ecologically relevant stream flow attributes for California streams that reflect knowledge of specific flow requirements for key freshwater species and habitats . Our modeling technique is now being extended to predict natural expectations for these new stream flow attributes. Model predictions of the natural range of variability for these ecologically relevant stream flow attributes will provide the basis for setting initial ecological flow criteria for all streams and rivers in California by the State Water Resources Control Board and other natural resource agencies. These ecological flow criteria will be based on unimpaired hydrologic conditions, but they can be refined in locations where management and ecological objectives require a more detailed approach. For example, refined approaches would likely be required in rivers that must be managed for species listed under the Endangered Species Act or in rivers where substantial flow and physical habitat alteration makes reference hydrology less relevant for setting ecological flow criteria, such as in the Central Valley or in populated watersheds of coastal California. Our technical team also was involved in establishing the California Environmental Flows Work group of the California Water Quality Monitoring Council . The mission of the Work group is to advance the science of ecological flows assessment and to provide guidance to natural resource management agencies charged with balancing environmental water needs with consumptive uses. The Work group is comprised of representatives from state and federal agencies, tribes, and nongovernmental organizations involved in the management of ecological flows. It serves as a forum to facilitate communication between science and policy development and to provide a common vision for the use of tools and science-based information to support decision-making in the evaluation of ecological flow needs and allocation of water for the environment.

The modeling technique described above has also been used to evaluate statewide water allocations. Grantham and Viers analyzed California’s water rights database to evaluate where and to what extent water has been allocated to human uses relative to natural supplies. They calculated the maximum annual volume of water that could be legally diverted according to the face value of all appropriative water rights in the SWRCB’s water rights database. Water rights were distributed according to their location of diversion, and the permitted diversion volumes were aggregated at the watershed scale to estimate a maximum water demand for each of the state’s watersheds. These permitted water diversion volumes were compared with modeled predictions of average annual supplies to estimate the degree of appropriation of surface water resources throughout the state . The study found that appropriative water rights exceed average supplies in more than half of the state’s large river basins, including most of the major watersheds draining to the Central Valley, such as the Sacramento, Feather, Yuba, American, Mokelumne, Tuolumne, Merced and Kern rivers. In the San Joaquin River,plant bench indoor appropriative water rights were eight times the volume of estimated natural water supplies . The volume of water rights allocations would be much higher if pre-1914 and riparian water rights had been included, but these data were not available at the time. The analysis also revealed that water rights allocations poorly represent actual water use by water rights holders. For example, comparisons of allocations with water use suggest that in most of California only a fraction of claimed water is being used. In a well-functioning water rights system where allocations are closely tracked and verified, an excess of water rights relative to supplies is not necessarily a problem. During water shortages, holders of junior appropriative rights would be required to curtail their water use. When water is abundant, most water rights holders should be able to fully exercise their claims. Uncertainty in when, how and where water is being used, however, threatens the security of water rights — particularly when water is substantially over allocated relative to natural supplies. During the 2012–2016 drought, for example, the SWRCB issued notices of curtailment to water rights holders to protect endangered fish species within priority watersheds. Less controversial targeted cutbacks to individuals might have been sufficient if the agency had more accurate information on how water rights were being exercised. As the 2012–2016 drought progressed, flaws in the state’s accounting system for tracking water rights became more apparent. This study, together with other policy reports , articulated the need for water accounting reforms, raised public awareness and helped to mobilize support for new legislation in 2015 , which significantly increased water-use monitoring and reporting requirements for water rights holders. The new regulations also extended reporting requirements to senior water rights holders , which are among the largest individual water users in the state.

The legalization of recreational cannabis in 2016 with passage of State Proposition 64 prompted state agencies to develop new policies to regulate the production, distribution and use of the plant. For example, California Senate Bill 837 directed the SWRCB to establish a new regulatory program to address potential water quality and quantity issues related to cannabis cultivation. The subsequently enacted California Water Code Section 13149 in 2016 obliged the SWRCB, in consultation with the California Department of Fish and Wildlife, to develop both interim and long-term principles and guidelines for water diversion and water quality in cannabis cultivation. As a result, in 2017, the SWRCB adopted the Cannabis Cultivation Policy: Principles and Guidelines for Cannabis Cultivation . The Cannabis Cultivation Policy’s goal is to provide a framework to regulate the diversion of water and waste discharge associated with cannabis cultivation such that it does not negatively affect freshwater habitats and water quality. A key element of the Cannabis Cultivation Policy is the establishment of environmental flow thresholds, below which diversions for cannabis irrigation are prohibited . During the dry season , no surface water diversions are permitted for cannabis cultivation. Diversions from surface water sources to off-stream storage are allowed between Nov. 1 and March 31. However, water may only be extracted from streams when flow exceeds the amount needed to maintain adult salmon passage and spawning and winter rearing conditions for juvenile salmon. Environmental flow requirements for the winter diversion season were determined by an approach known as the Tessmann Method , which uses proportions of historical mean annual and mean monthly natural flows to set protective thresholds. Because flows are not measured continuously in most streams in California , including at most points of diversion, the Cannabis Cultivation Policy instead relies on using the predictions of natural flows from the models described above. Predicted natural mean monthly and annual flows are used by the SWRCB at compliance gauge points to calculate the Tessmann thresholds. Cannabis cultivators seeking a Cannabis Small Irrigation Use Registration permit from the SWRCB are assigned a compliance gauge near their operation and can legally divert water only when flows recorded at the gauge meet or exceed the Tessmann thresholds during the diversion season . The motivation for developing natural stream flow models and data rests on the premise that rivers and streams can be managed to preserve features of natural stream flow patterns critical to biological systems while still providing benefits to human society . For any stream of interest, balancing the needs of humans and nature requires an understanding of its natural flows, whether observed conditions are modified relative to natural patterns and what degree of modification harms its health. As noted in the examples above, this work has both direct and indirect implications for policy and decision-making. A database of natural stream flows developed by machine-learning models was used to help define cannabis policy to set minimum flow targets — a direct application of the technique. However, this work also influenced policy and decision-making in more subtle ways, including building awareness of shortcomings in the state’s water rights accounting system.