Hydrologists

AI Overlap Index
51.0 / 100
Partially Exposed

Clear pressure on routine tasks. Composition of the role will shift within the decade.

SOC 19-2043 · Life Physical And Social Science

Bureau of Labor Statistics
Median pay
$92,060/yr
Hourly
$44/hr
Jobs 2024
6,300
Projected 2034
6,300
10-yr outlook
0% · Little or no change
Employment change
0
Entry education
Bachelor's degree
SOC code
19-2043

Signal composition

how the 0-100 score is assembled

Task Automation Impact weight 60%
51.3
contribution to AOI: 30.8
Automation Potential weight 10%
60.0
contribution to AOI: 6.0
Market Pressure weight 15%
60.0
contribution to AOI: 9.0
Entry Barrier Erosion weight 15%
35.0
contribution to AOI: 5.2

By seniority

multiplicative adjustment from category curve

Entry
60.2
mult 1.18x
Mid
51.0
mult 1.00x
Senior
40.8
mult 0.80x

Entry-level roles carry the brunt because they concentrate the most automatable subset of tasks. Senior work is insulated by judgment, relationships, and accountability.

Task-level analysis

scored 0-100 for current-generation AI feasibility, weighted by BLS-stated importance

10 tasks · model: claude-sonnet-4-5-20250929
Important t7

Use computer modeling programs to predict water conditions and analyze datasets

AI natively excels at running simulations, parameter optimization, and processing large hydrological datasets through modeling software; can automate scenario testing and sensitivity analysis with human direction on model selection and result interpretation.

BLS evidence: The page states hydrologists 'use computer modeling programs to predict water conditions and analyze complex datasets.'

75
automation
Core t3

Analyze data on environmental impacts such as pollution, erosion, and drought

AI excels at pattern recognition in environmental datasets, statistical analysis of pollution trends, and correlating multiple variables like erosion rates with precipitation data; human review ensures interpretation validity but AI handles most analytical work.

BLS evidence: The duties section states hydrologists 'analyze data on the impacts of pollution, erosion, drought, and other environmental problems.'

72
automation
Core t4

Forecast water supplies, pollution spread, floods, and other water-related events

Modern AI models demonstrate strong capability in time-series forecasting and multivariate prediction for hydrological events, integrating weather data, topography, and historical patterns; human oversight remains important for validating model assumptions and extreme events.

BLS evidence: Hydrologists 'forecast water supplies, the spread of pollution, floods, and other events' according to the duties section.

68
automation
Important t9

Write reports and present findings to technical and non-technical audiences

AI can draft technical reports from data, generate visualizations, and adapt language for different audiences; strong at synthesizing findings into structured documents, though human review ensures accuracy and appropriate emphasis for high-stakes water management decisions.

BLS evidence: Hydrologists 'write reports and present their findings' and 'may have to present their findings to audiences who do not have a technical background.'

66
automation
Important t6

Evaluate feasibility of water-related projects such as hydroelectric plants and irrigation systems

AI can model hydraulic performance, cost-benefit analysis, and environmental impacts of water projects using established engineering principles and datasets; human expertise needed for stakeholder considerations and site-specific constraints, but AI does heavy analytical lifting.

BLS evidence: Hydrologists 'evaluate the feasibility of water-related projects, such as hydroelectric power plants, irrigation systems, and wastewater treatment facilities.'

62
automation
Important t5

Research ways to minimize negative environmental impacts on people and ecosystems

AI can analyze literature, simulate impact scenarios, and propose mitigation strategies based on existing research, but developing novel approaches for complex ecosystem interactions requires human creativity and ethical judgment that AI supports rather than replaces.

BLS evidence: The duties section lists 'research ways to minimize negative impacts of environmental problems on people and ecosystems.'

58
automation
Supporting t10

Use specialized equipment like LiDAR and sonar systems to gather mapping data

While AI can process LiDAR/sonar data into maps and models, the physical deployment of equipment in field conditions, troubleshooting sensor issues, and making real-time decisions about data collection parameters require human presence and judgment in variable environments.

BLS evidence: The page mentions hydrologists 'may use light detection and ranging (LiDAR) or sound navigation and ranging (sonar) systems to gather data for mapping bodies of water.'

48
automation
Important t8

Collaborate with engineers, scientists, and public officials on water management

Requires real-time interpersonal negotiation, reading social dynamics among diverse stakeholders, building trust across disciplines, and navigating political considerations in water management decisions—capabilities where AI remains a communication aid rather than participant.

BLS evidence: The page notes that 'working with engineers, scientists, and public officials, hydrologists help to manage the water supply in a variety of ways.'

35
automation
Core t1

Measure streamflow, volume, and other water-cycle elements of bodies of water

Requires physical presence at water bodies with specialized equipment in variable outdoor conditions, plus real-time judgment about measurement locations and equipment calibration that AI+robotics cannot reliably automate in unpredictable natural environments.

BLS evidence: The duties section explicitly lists 'Measure streamflow, volume, and other water-cycle elements of bodies of water' as a primary task.

22
automation
Core t2

Collect water and soil samples to test for specific properties

Demands fine motor skills for proper sample collection technique, physical navigation of diverse terrain, and on-site judgment about sampling locations and contamination prevention that current robotics cannot match in field conditions.

BLS evidence: Hydrologists 'collect water and soil samples to test for specific properties, such as the pH or pollution levels' as stated in the duties section.

18
automation

Task heatmap

automation score by task, sorted by weighted contribution

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External signals and sources

category-level priors and BLS fields that feed the four non-task signals

Automation Potential
60
karpathy 6/10
  • Karpathy/BLS Digital AI Exposure (0-10 scale rescaled to 0-100)
Market Pressure
60
outlook: Little or no change
  • BLS projected outlook: Little or no change (0%)
  • Indeed demand signal (monthly refresh pending)
Entry Barrier Erosion
35
ed: Bachelor's degree
  • BLS typical entry-level education: Bachelor's degree
  • Credential trend signal (annual refresh)

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