|Project Title||Organization / Affiliation||Category (Open Source / Non-Open Source)||Description||List of Datasets Used||Link to Slides||Link to Submission (1)||Link to Submission (2)||Link to Submission (3)||Link to Submission (4)|
|WaterBudget||Bayes Impact||Open Source||Water is a scarce and restricted commodity and it has to be managed as such. Inspired by personal finance applications such as Mint and Level, and powered by machine learning techniques, we have created a proof-of-concept application, WaterBudget, to assist water districts to manage and plan their water usage and conservation plans. By analyzing the historical water usage patterns in each district, WaterBudget predicts total monthly and annual water usage, and compares it to the set target. The water usage prediction allows water districts to be proactive and implement necessary water conservation measures to ensure reaching the water conservation targets. In the prototype we've developed, the targets set by the State (2015) were used, however, in practice, they could be set by local administrations too. In addition to budgeting and planning purposes, this application allows the residents to easily follow their respective water suppliers' performance in water conservation.||•Urban Water Supplier Report Dataset|
•California Environmental Health Tracking Program (CEHTP) Drinking Water Systems Geographic Reporting Tool
•Water supplier PWD ID master list from CA Department of Water Resources
|Coping with the California Drought: 2014-2016||Stanford University||Open Source||Our submission contains interactive visualizations that allow the user to explore how effectively California water utilities conserved water over the past 3 years, a critical period of historical drought. By visualizing and exploring the relationships between water conservation in 2014, 2015, and 2016 in almost 400 utilities from around the state, we provide an interesting perspective of the ongoing drought. For these visualizations, we define "conservation" and "water savings" as the difference in water production between a timeframe of interest in a given supplier's service area and its respective water production in 2013. This exploratory analysis includes statewide data to show overall water use trends, as well as data for each of the 10 hydrologic regions in California and individual utilities in those regions. The comparison between conservation efforts in 2014, 2015, and 2016 also provides insight on the responsiveness of different utilities to different incentives: a voluntary call for conservation in 2014, a state mandate in 2015, and the replacement of the state mandate by adjusted self-certified goals in 2016.|
Several key lessons can be drawn from these visualizations: (1) The reporting requirements put in place during the drought created an even platform for water utilities to keep track of important data, which in turn allows tools like this one to identify water use and conservation trends, drivers, and opportunities for enhanced water management at a variety of different scales. Further standardized tracking and reporting methods could facilitate the use of data for decision-making; (2) Water utilities collectively achieved significant water savings in the period between 2014 and 2016. While policies and regulations seem to have been significant drivers of water conservation throughout the state (e.g. higher water savings during the state mandate or in response to local watering restrictions), these visualizations show that water use and conservation are very site-dependent and utility-specific; (3) Many uncertainties remain about the human-water dynamics that made water savings possible between 2014 and 2016. A better understanding of local population behaviors towards water use, and responsiveness to different conservation incentives, could help water planners and managers tailor their conservation campaigns more effectively in the future, not only during drought, but also as a long-term water reliability strategy.
|•Water conservation data: All water conservation data was obtained from the State Water Resources Control Board (SWRCB) Water Conservation Portal - Emergency Conservation Regulation, and pre-processed using the Pandas library in Python. Only utilities who were required to report to the SWRCB, and who had complete data for the summers of 2014, 2015, and 2016 (June-August) are included in this analysis. This includes a total of 378 utilities form around the state. We use summer months for comparison between different years. |
•Media data: Media data was retrieved by a novel open-source algorithm Articulate written in Python by our group. The algorithm uses Google Custom Search Engine API to retrieve and tally news articles that contain terms of interest over a specified time period. For this visualization project we show the number of articles that contain the term “California drought” or a combination of “California”,” drought(s)”, and water-related terms such as “water”, “snow”, or “rain.” Only articles from the following state and national newspapers (chosen for high circulation) are included: Wall Street Journal, New York Times, USA Today, Los Angeles Times, Sacramento Bee, Orange County Register, San Diego Union-Tribune, San Francisco Chronicle (SF Gate).
•Google Trends data: Google Trends data is used as a metric of public interest. Google Trends is a free online tool that shows how often a word or term is searched forover a certain period. The number of searches is in relative terms, with the period with the most searches for that topic having a value of 100. For a comparison between media coverage and public interest, we extracted data for how often the term “California Drought” was entered into the Google search bar over the period July 2005- November 2016 within the state of California. Search frequencies were tallied at both monthly and weekly time scales.
|Sustainable Floodplain Habitat Finder||FlowWest||Open Source||Chinook salmon in California's Central Valley are struggling to survive. During their epic migration from the ocean into the tributary streams draining the Central Valley, salmon contend with depleted streamflows, migration barriers, predators, degraded habitat, lack of nutrients, and a host of other challenges. Baby salmon are especially vulnerable during their long migration from the spawning grounds downstream to the ocean. Additional floodplain habitat may be the key to restoring dwindling salmon populations; by providing food, cover from predators; and higher rates of survival. But - restoring floodplain habitat requires a careful balance of current and future streamflow conditions, groundwater basin conditions, and, of course, baby salmon migration patterns.|
Our entry is an open source combination of data visualization and decision support tools for water resources and fishery managers who must constantly make difficult decisions about how to allocate streamflows to meet a wide range of human and ecosystem needs. Our tool is an R Shiny application that incorporates the Leaflet map service, Plotly charting tools, the National Oceanic and Atmospheric Administration River Forecast web service, and R-based statistical evaluation interfaces to evaluate, in a real-time data-driven way, the relative potential for floodplain habitat creation at a given site.
|1) California Statewide Groundwater Elevation Monitoring (CASGEM) Program|
2) Water Data Library (WDL)
3) California Data Exchange Center (CDEC)
4) USGS Surface-Water Data for California
5) California Nevada River Forecast Center (http://www.cnrfc.noaa.gov/espTrace.php?id=SHDC1)
6) USFWS Juvenile Salmon Rotary Screw Trap Counts (http://www.cbr.washington.edu/sacramento/data/query_redbluff_daily.html)
|An Automated Water Resources Tracking System: Near Real-Time Decision Support for Water and Wetland Managers||Point Blue Conservation Science||Open Source||Competition for water is likely to intensify as California is projected to experience continued increases in demand due to population growth, more arid growing conditions, and reduced or modified water supply due to climate change. As water resources become increasingly limited, water use needs to be optimized across many competing demands while also promoting multiple-benefits. Though sophisticated water optimization models can be useful for tracking water volume allocations, how the results translate into habitat availability for wildlife and ecosystem services for people is not known. A framework is needed to better understand the spatial distribution of water in near real-time for managers to adapt to changing conditions on the landscape and to maximize the value of the water used.|
We are integrating remote sensing of satellite data, classification modeling, bioinformatics, optimization, and ecological analyses to develop an automated near real-time water resources tracking and decision-support system for the Central Valley of California. The system provides information on open surface water every 16-days and delineates between wetland types and flooded agriculture. Data are made freely available online for download 3-6 days post acquisition as well as through online summary and map visualization applications. Data are also summarized specifically for wetland wildlife habitats within federal and state management areas. These data will be used by water and wetland managers to enhance landscape scale coordination of limited water supplies for wildlife, particularly during drought. In our complete vision for this system, water managers will be able to get near-real time and forecasted recommendations for where to put water on the landscape to achieve multiple wildlife habitat targets but to also provide ecosystem services (e.g. groundwater recharge).
Our innovative system has applications for water management in the Central Valley to support people, places, and wildlife and is already being used for understanding the factors that drive variation in the distribution and abundance of water resources at multiple spatial and temporal scales. Specifically data generated as part of this system are being applied to assess the impact of the most recent drought in California, to understand the effect of disease vector control on water distribution, to quantify the groundwater recharge potential of current surface water management for wildlife, to develop an avian influenza risk map, and to identify where to put water and when on agricultural lands to benefit migratory birds.
|• Landsat 8 OLI |
• National Agricultural Statistics Service Crop Data Layer
• National Land Cover Database (NLCD)
|CaDC Efficiency Explorer||California Data Collaborative (and 501c3 Nonprofit ARGOLabs)||Open Source||The Governor’s May 16 Executive Order (B-37-16) calls for the development of water use targets customized to the unique conditions of each urban water agency as part of a new, permanent efficiency framework. The CaDC Efficiency Explorer is an interactive dashboard that supports the California water community in analyzing the impact of those new standards through a easy to use scenario explorer tool.|
The video in the attached powerpoint demonstrates the Efficiency Explorer’s functionality at an inter-agency level and at an intra-agency level.
o State Water Board Monthly Reporting Archive (Implemented)
o CIMIS Station Reports (Implemented)
o NAIP Imagery (Planned)
• (Currently) Private
o Intra-Agency Data
Note: Though the intra-agency tool requires private data, since the Efficiency Explorer is open-source, the only barrier to an agency deploying for internal usage is preliminary data processing.
The app combines the steps that staff in the Division of Water Rights take to create a water supply report, which is part of the water availability analysis performed for new appropriative water right proposals. The user selects the proposed point of diversion and USGS Tracer finds the downstream flowline to the Pacific Ocean. The user then selects which existing water rights near the flowline to include in the analysis. The app delineates a watershed at each existing water right diversion point and generates a table that shows two pieces of information the user would otherwise have to calculate in Excel: the area of each watershed, and the sum of all existing water right diversions within that watershed. We think this has potential to save staff significant time in calculating water supply, especially if riparian rights' statements of diversion and use could be included in the SWRCB dataset.
This demo version filters water rights for active appropriative rights, but future versions could offer more filter functionality, such as the diversion season. Also, this demo is strictly a front-end project, but ideally the server would send the finished table to the user for download so that the rest of the water availability analysis can be completed.
|CaDC Rate Comparison tool||California Data Collaborative (staffed by 501c3 Nonprofit ARGO Labs)||Open Source||With declining water sales, water managers have lost over $675 million of revenue in the current drought. The CaDC rate comparison tool provides a quick way to see the implications that a rate shift or a drought surcharge would have on revenue and typical customer bills. The tool quickly illustrates the impact of a shift before a utility hires a rate consultant and goes through a full, labor intensive Prop 218 process. |
You can see a video demo of the tool in action here: https://youtu.be/mYv-OOBGJ28
|The tool is designed to be compatible with properly formatted customer billing data from any water utility. The only publicly available billing data that the authors are aware of is that provided by the City of Santa Monica ( https://data.smgov.net/Public-Services/Water-Usage/4nnq-5vzx ). A properly formatted subset of this data is included in the /data/ subdirectory of the project Github repository.||https://drive.google.com/open?id=0B5n4IeHrVBinODNsWnpxLUQwRms||https://github.com/California-Data-Collaborative/RateComparison||–||–||–|
|Providing Context to a Proposed Shasta Dam Expansion||–||Open Source||California’s recent drought has placed unprecedented demands on our freshwater resources, renewing enthusiasm for surface water infrastructure investments such as raising dams to capture more water in wet years. Using historical data of storage levels and inflows of Shasta Dam, our group wanted to estimate how successful the Bureau of Reclamation’s expansion of Shasta Dam would be. We graphed past patterns of data and modeled potential future scenarios. Our entry is in the categories of data visualization and insights and Decision Support, Data Sharing and Information Communication Tools.||–||https://drive.google.com/open?id=0B5n4IeHrVBinaWRleWZ1QVJRZ0k||http://storageaf.wixsite.com/shastadam||–||–||–|