What cannot be measured cannot be managed. Poor water management poses major risks to agriculture, industry and local communities. However, there is a critical lack of information available about local water conditions — making better management difficult. WRI’s Water Program studies local water data and governance and shares best practices in order to advance context-driven, meaningful water management.
WRI and the Pacific Institute are currently working to map public water risk by harmonizing and sharing water risk information among industrial water users on the following criteria:
Access to information on water quantity and quality
State of infrastructure
Existence and enforcement of allocations and caps
Local pricing systems
This Technical Note documents the results of a pilot with 6 companies and 41 facilities, and creates an updated question set to better understand conditions of public water management.
Scalability: Crowdsourcing data from industrial water users through the distribution of this standardized question set is a feasible and scalable method to collect information. An average response time of 17 minutes suggests that information can be crowdsourced effectively with partnered industrial water users.
Validity: The field validation exercises shown in this Technical Note identify how stakeholders view the generated dataset as credible and valuable for informing local actions. In addition to a high rate of accuracy, validation exercises suggest that the generated data is a reasonable proxy for local water management conditions.
Many water crises are, at their root, crises of water governance and management. To effectively respond to water crises driven by governance and management failures, there is a need for empirical, comparable, global information on the state of public water management.
In an effort to fill this data gap, this Technical Note tests a novel data collection approach that relies on crowdsourcing data from multinational enterprises with operations across many geographies. The approach was piloted with six contributing multinational companies, and the results were validated in eight locations in Southern California (United States) and the state of Maharashtra (India).
The pilot study suggests that the new data collection approach is scalable and has the potential to generate a global dataset of public water management capacity. The field validation exercise suggests that the collected data are mostly viewed as valid by local experts and stakeholders, but the exercise also identifies a number of weaknesses. Based on these findings, this paper presents an updated survey that improves upon the original survey used in the pilot study.