
Laboratory Analysis
Some data acquired from field survey activities require further analysis in the laboratory.
- Evidence-led
- Traceable assumptions
- Decision-ready outputs
- Methods proportionate to risk
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Clarity before a decision is made
Laboratory Analysis
Clarity before a decision is made
Some data acquired from field survey activities require further analysis in the laboratory.
Laboratory analysis results from samples collected during surveys must have a high level of accuracy because these data will be used as model input data and will also support the model verification and validation process. In general, samples collected from field surveys are divided into three groups: physical, chemical, and biological samples.

Decision Supported
Define the approach, priorities, and actions for laboratory analysis using traceable evidence.

Risk Controlled
Inconsistent sampling, preservation, analysis, and interpretation.

Success Criteria
Quality-assured results with clear detection limits and reference comparability.
Choose the area that matches your need

Physical
Laboratory analysis of samples collected from field surveys for physical parameters includes the following:
Learn more →
Chemical
Laboratory analysis of samples collected from field surveys for chemical parameters includes the following:
Learn more →
Biological
Laboratory analysis of samples collected from field surveys for biological parameters includes the following:
Learn more →A traceable evidence base

Observations
Field surveys, in-situ measurements, laboratory results, historical records, and operating information as required.

Remote sensing & GIS
Satellite imagery, mapping, spatial analysis, temporal change, and integration of multiple data sources.

Modeling & scenarios
Model setup, calibration, validation, existing–planned–extreme scenarios, and sensitivity analysis.

Quality assurance
Metadata, quality controls, assumptions, limitations, data versions, and processing lineage are documented.
Decision-ready information

Initial assessment & data gaps
Objectives, study area, available data, additional needs, initial risks, and recommended level of detail.

Datasets, maps & indicators
Quality-controlled data, thematic maps, time series, indicators, and comparable visualizations.

Scenarios & risk evaluation
Comparison of existing conditions, alternatives, extremes, sensitivities, consequences, and mitigation options.

Report & executive brief
Methods, results, limitations, recommendations, action priorities, and stakeholder presentation materials.
Benefits for decision makers and policy leaders

Reduce uncertainty
Assumptions, data, variability, and limitations are stated so decision risk is not hidden.

Compare options objectively
Alternative locations, designs, operations, or policies are assessed using consistent indicators.

Optimize cost and time
Data needs and analysis depth are proportionate to risk so resources are used efficiently.

Increase stakeholder confidence
Findings and recommendations are transparent for technical, management, regulatory, and partner review.
A clear process from need to recommendation
- 01

Need definition
Objectives, users, location, project phase, problems, constraints, and the decision to support.
- 02

Scope & work plan
Methods, data, surveys, models, schedule, team, deliverables, review gates, and resource estimate.
- 03

Acquisition & quality control
Collection, inspection, harmonization, documentation, and data-sufficiency assessment.
- 04

Analysis & scenario testing
Processing, modeling, validation, option comparison, sensitivity, and risk evaluation.
- 05

Recommendation & handover
Maps, report, executive brief, presentation, supporting data, and follow-up plan.
Full technical basis and contextOpen this section to read the complete source technical narrative.
Some data acquired from field survey activities require further analysis in the laboratory. Samples collected during field surveys must be analyzed as soon as possible to prevent sample degradation. Various chemical analysis methods are applied to determine the concentration of specific parameters in the samples.
Laboratory analysis results from samples collected during surveys must have a high level of accuracy because these data will be used as model input data and will also support the model verification and validation process. In general, samples collected from field surveys are divided into three groups: physical, chemical, and biological samples. Each group is described in more detail as follows:
If support is needed to analyze survey samples in the laboratory, please complete the form below. The samples to be analyzed will be inspected before entering the laboratory to ensure that no damaged samples are processed.
Setelah diklik untuk mengisi isiannya maka akan muncul form aplikasi sebagai berikut:
Share the need, location, available data, and the decision to be supported.
The CORZ team will review the objective, scope, data availability, risk level, schedule, and required outputs to prepare a proportionate approach.
- Location and project phase
- Decision or objective to support
- Primary problems and risks
- Available data
- Expected outputs and schedule
