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Open-Source Transparent Water Management Data | OpenET — 18 websites ranked by shared content topics, category and on-page relevance.

Each result shows its full tech stack, contacts and AI-policy — not just a name · Browse all sites in Environment →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
nbswm.com ↗	68 match 1 shared topics	Nature-based Solutions in Water Management - Thammasat University Research Unit	en	environment	robotsllmsaihumans	emailphone	none
nalms.org ↗	66 match 1 shared topics	North American Lake Management Society (NALMS)	en	environment WordPress WooCommerce	robotsllmsaihumans	emailphone	none
countrysidemanagement.org.uk ↗	66 match 1 shared topics	Countryside Management Association - CMA	United Kingdom en	environment WordPress	robotsllmsaihumans	emailphone	none
at-ma.ai ↗	66 match 1 shared topics	Maai Makwa \|\| Deploying Artificial Intelligence & Consumer Engagement for Freshwater Resource Responsibility	en	environment	robotsllmsaihumans	emailphone	none
acrplus.org ↗	65 match 1 shared topics	Association of Cities and Regions for sustainable Resource management - Home	en	environment	robotsllmsaihumans	emailphone	partial · 1
amber.international ↗	65 match 1 shared topics	AMBER, Adaptive Management of Barriers in European River	en	environment WordPress WooCommerce	robotsllmsaihumans	emailphone	none
4countycwma.org ↗	65 match 1 shared topics	Cooperative Weed Management in Oregon & Washington	en	environment	robotsllmsaihumans	emailphone	none
cbitplatform.org ↗	65 match 1 shared topics	Climate Transparency Education for University Students - CBIT Platform	en	environment WordPress	robots llmsaihumans	emailphone	partial · 8
naturetech.solutions ↗	65 match 1 shared topics	NatureTech.Solutions – Rewarding innovations to improve resource management in the Caribbean	en	environment WordPress	robotsllmsaihumans	emailphone	none
ncdrought.org ↗	65 match 1 shared topics	North Carolina Drought Management Advisory Council	en	environment	robotsllmsaihumans	emailphone	partial · 8
erwig.org ↗	64 match 1 shared topics	Eel River Watershed Improvement Group - Home	en	environment Weebly	robotsllmsaihumans	emailphone	none
mysticriver.org ↗	64 match 1 shared topics	Mystic River Watershed Association \| MyRWA \| Boston	en	environment Squarespace Squarespace Commerce	robotsllmsaihumans	emailphone	none
eriscbo.org ↗	64 match 1 shared topics	ERIS CBO Turkana Kenya \| Sustainable Development, Water, Education & Health Programs	KE~ en	environment	robotsllmsaihumans	email phone	none
livingdata2025.com ↗	64 match 1 shared topics	Living Data 2025 - Information that together, transforms	Colombia~ en	environment	robotsllmsaihumans	emailphone	none
natureforwatersecurity.org ↗	64 match 1 shared topics	Water and Nature \| World Water Forum	en	environment Adobe Experience Manager	robotsllmsaihumans	emailphone	none
navarroriver.org ↗	64 match 1 shared topics	Navarro River Resource Center \| Fostering land stewardship in the Navarro River Watershed	United States~ en	environment WordPress	robotsllmsaihumans	emailphone	none
nbsforcircularity.org ↗	64 match 1 shared topics	NbS for Circularity – International Conference on Nature-Based Solutions for Water Circularity and Sustainability	en	environment WordPress	robotsllmsaihumans	emailphone	none
activeenvironmentalism.co.uk ↗	64 match 1 shared topics	Active Environmentalism – An open source site of ideas for the environment run by the Messums	United Kingdom en	environment WordPress	robotsllmsaihumans	emailphone	none

How the match score works

Each match is a 0–100 similarity score — the higher it is, the more two sites resemble one another. It’s computed automatically from our own crawl data (never from what a site says about itself) by combining several independent signals, so a high score means several of them point the same way:

shared topics how many of the same fine‑grained content topics (IAB sub‑categories) both sites cover — the main signal.
same category whether they sit in the same business / industry category.
content & title how closely their titles and page descriptions line up in wording and meaning.

No single signal decides the result — they’re blended together. Treat the score as a way to rank candidates rather than an absolute percentage; the chips on each result show which signals contributed.