Hydrologists

Prepare written and oral reports describing research results, using illustrations, maps, appendices, and other information.

AI: Fully automatable - By 2025, AI can generate polished written and oral reports, create figures/maps from provided data and templates, and assemble appendices, though final review by a specialist is recommended.

Develop computer models for hydrologic predictions.

AI: Fully automatable - AI tools in 2025 can develop, train, and calibrate hydrologic prediction models (including writing code and selecting algorithms) given appropriate data and objectives, while human oversight remains advisable for validation.

Evaluate research data in terms of its impact on issues such as soil and water conservation, flood control planning, and water supply forecasting.

AI: Fully automatable - Given data inputs, AI models and analytics in 2025 can evaluate research datasets and quantify impacts for soil/water conservation, flood planning, and water supply forecasting end-to-end.

Evaluate data and provide recommendations regarding the feasibility of municipal projects, such as hydroelectric power plants, irrigation systems, flood warning systems, and waste treatment facilities.

AI: Fully automatable - AI can process engineering and environmental data, run feasibility models, and produce technical recommendations for municipal projects with high reliability in 2025.

Answer questions and provide technical assistance and information to contractors or the public regarding issues such as well drilling, code requirements, hydrology, and geology.

AI: Fully automatable - AI systems in 2025 can reliably answer technical questions and provide guidance on well drilling, codes, hydrology, and geology for most routine informational needs.

Compile and evaluate hydrologic information to prepare navigational charts and maps and to predict atmospheric conditions.

AI: Fully automatable - Compiling/evaluating hydrologic data, producing navigational charts/maps, and running atmospheric prediction models are largely automatable with existing remote sensing, GIS, and forecasting pipelines by 2025.

Design and conduct scientific hydrogeological investigations to ensure that accurate and appropriate information is available for use in water resource management decisions.

AI: Partial - AI can design study plans, run simulations and suggest protocols, but cannot autonomously conduct field investigations or fully replace expert judgment and on‑site decision making.

Measure and graph phenomena such as lake levels, stream flows, and changes in water volumes.

AI: Partial - AI can ingest sensor data and produce accurate graphs and analyses, but the physical measurement of lake levels and stream flows still requires sensors or human/robotic deployment and verification.

Conduct research and communicate information to promote the conservation and preservation of water resources.

AI: Partial - AI can perform literature reviews, analyze data, and produce outreach materials to promote conservation, but independent field research and stakeholder engagement remain partly human‑led.

Coordinate and supervise the work of professional and technical staff, including research assistants, technologists, and technicians.

AI: Partial - AI can assist with scheduling, tracking, and decision support for teams, but cannot fully replace human leadership, personnel management, and accountability in supervision.

Study public water supply issues, including flood and drought risks, water quality, wastewater, and impacts on wetland habitats.

AI: Partial - AI can analyze datasets and model flood/drought and water quality scenarios, but comprehensive study of public water supply issues requires local knowledge, field data collection, and policy coordination by humans.

Apply research findings to help minimize the environmental impacts of pollution, waterborne diseases, erosion, and sedimentation.

AI: Partial - AI can translate research findings into mitigation options and simulate impacts, yet implementing, adapting, and validating environmental interventions still depends on human expertise and field action.

Study and document quantities, distribution, disposition, and development of underground and surface waters.

AI: Partial - AI can process remote sensing and hydrogeologic data to document water distributions and produce reports, but full surveying and some subsurface characterization require field measurements and expert interpretation.

Study and analyze the physical aspects of the earth in terms of hydrological components, including atmosphere, hydrosphere, and interior structure.

AI: Partial - AI can synthesize literature and run models to analyze hydrological systems but cannot fully replace the expert judgment and field verification required for comprehensive physical studies as of 2025.

Collect and analyze water samples as part of field investigations or to validate data from automatic monitors.

AI: Partial - Lab analysis and automatic-monitor validation can be highly automated, but physical field collection of water samples still requires humans or specialized robotics not generally available in 2025.

Prepare hydrogeologic evaluations of known or suspected hazardous waste sites and land treatment and feedlot facilities.

AI: Partial - AI can generate hydrogeologic assessments from existing data and models, but site-specific evaluation of hazardous waste sites typically requires fieldwork, legal accountability, and human oversight.

Develop or modify methods for conducting hydrologic studies.

AI: Partial - AI can propose and optimize methods for hydrologic studies, but developing and validating new methodologies still needs human creativity, field testing, and domain leadership.

Review applications for site plans and permits and recommend approval, denial, modification, or further investigative action.

AI: Partial - AI can screen and recommend actions on site-plan and permit applications using rules and data, yet final regulatory decisions and complex discretionary judgments remain a human responsibility.

Monitor the work of well contractors, exploratory borers, and engineers and enforce rules regarding their activities.

AI: Partial - AI and remote sensors can monitor contractor activities and flag violations, but physical inspections, enforcement actions, and on-site supervision require humans or specialized field robotics not widespread in 2025.

Investigate properties, origins, and activities of glaciers, ice, snow, and permafrost.

AI: Partial - AI can analyze remote sensing and model glacier and permafrost behavior, but field investigations and on-the-ground sampling in remote icy environments still require human efforts.

Conduct short- and long-term climate assessments and study storm occurrences.

AI: Partial - AI and numerical models can perform much of the data analysis and forecasting for short- and long-term climate assessments and storm studies, but expert judgment and contextual interpretation remain important in 2025.

Design civil works associated with hydrographic activities and supervise their construction, installation, and maintenance.

AI: Partial - Design and supervision of civil works can be substantially aided by AI-enabled design tools and monitoring systems, yet final design approval, on-site construction supervision, and liability-bearing decisions remain human-led.

Investigate complaints or conflicts related to the alteration of public waters, gathering information, recommending alternatives, informing participants of progress, and preparing draft orders.

AI: Partial - AI can gather information, draft recommendations and orders, and track progress, but investigating complaints and managing stakeholder conflict requires human judgment, negotiation, and legal decision-making.

Administer programs designed to ensure the proper sealing of abandoned wells.

AI: Partial - Administrative program management for well-sealing can be partially automated (tracking, scheduling, compliance checks), but field inspections, contractor coordination, and legal responsibilities still require human oversight.

Install, maintain, and calibrate instruments such as those that monitor water levels, rainfall, and sediments.

AI: Not automatable - Installation, physical maintenance, and hands‑on calibration of instruments require on‑site human or robotic actions that AI alone cannot perform in typical practice by 2025.