A technical approach that translates conceptual system knowledge into quantifiable scenarios
HİDROJEOTEK treats numerical models not as stand-alone calculation tools that replace field evidence or system understanding, but as decision-support tools that quantitatively test hydrogeological and hydrological conceptual models. The objective is to evaluate potential system responses under different influences in a comparable and traceable manner.
The modeling scope is defined according to the technical question, spatial and temporal scale, project stage, system dynamics and adequacy of available data. Model complexity is kept proportionate to the decision need, avoiding levels of detail or apparent precision that are not supported by the evidence.
Geological, hydrogeological, hydrometeorological, spatial and monitoring data are integrated within a common modeling framework. Assumptions and limitations are reported alongside calibration performance, water balance, sensitivity and uncertainty assessments, clearly defining the conditions under which the results can be used.
Integrated scope from model purpose to reliability assessment
Not every project requires the same model type or level of detail. The following components can be combined or structured as individual work packages according to the decision question and data adequacy.
Model objectives, data preparation and conceptual model
The decision question, spatial and temporal scale, processes to be represented and required level of evidence are defined; data from multiple sources are quality-checked and integrated into the conceptual model that underpins the numerical setup.
Groundwater flow and water-balance modeling
Aquifers, boundary conditions, recharge and discharge components, storage and abstraction are represented together; groundwater levels, flow directions, fluxes and water balance are assessed under steady-state or transient conditions.
Hydrological and rainfall–runoff modeling
Precipitation, evapotranspiration, infiltration, surface runoff, baseflow and storage processes are modeled to assess catchment response, water balance, flooding, low flows, drought and land-use change.
Groundwater–surface water and integrated-system analyses
Interactions between aquifers and rivers, lakes, reservoirs, springs and wetlands are assessed quantitatively, including water exchanges among system components and their combined responses to changing conditions.
Dewatering, drainage and inflow modeling
Potential inflows, drawdown, zones of influence and pumping requirements are estimated for excavations, mines, infrastructure and transport projects; drainage and operational alternatives are compared.
Contaminant transport and water-quality scenarios
Where supported by adequate data and an appropriate conceptual basis, contaminant advection, dispersion and attenuation are assessed, and source, receptor, intervention and remediation scenarios are compared.
Climate, abstraction, operation and mitigation scenarios
Climate variables, abstraction rates, project phases, operational conditions and mitigation options are translated into internally consistent scenarios and compared using common performance indicators.
Calibration, validation, sensitivity and uncertainty
Model performance is tested against observed heads, flows, time series and water balance; validation is undertaken where independent data are available, and decision-relevant sensitivities and uncertainties are explicitly reported.
A modeling process designed, tested and documented around the decision question
Before software is selected, the process defines how the system works and which decision the model is intended to support. Assumptions, data transformations and technical choices are documented at every stage.
Purpose, scale and data adequacy
The technical question, assessment criteria, model domain and time scale are defined; available borehole, well, flow, climate, land-use and monitoring data are reviewed for adequacy.
Conceptual model and numerical setup
System components, boundaries and processes are conceptualized; the model grid or subcatchments, layers, parameters, initial conditions and time-varying inputs are defined to suit the decision question.
Calibration and reliability checks
Simulated and observed values are compared, including residual patterns, performance metrics and water balance. Validation, sensitivity and uncertainty analyses are undertaken where the available data permit.
Scenario analysis and technical communication
Alternatives are compared using common indicators; zones of influence, thresholds, limitations and data needs are communicated through maps, graphs and tables, together with conditions for monitoring and future model updates.
An adaptable approach to quantitative questions involving water systems and project impacts
Although the model type may vary, the underlying objective remains the same: represent the existing system, compare potential outcomes under alternative conditions and make the evidence, assumptions and uncertainties supporting the decision transparent.
Outputs that make model results usable and auditable in decision-making
The work delivers more than a single prediction: it provides a technical chain of evidence showing how the model was developed, how reliable the results are and under which conditions the alternatives diverge.
Numerical model and traceable setup
The model domain, layers or subcatchments, boundary conditions, parameters, stress periods, data transformations and assumptions are documented within a technical structure that can be reviewed and updated.
Calibration, water balance and uncertainty evidence
Performance metrics, spatial and temporal residual patterns, water or mass balance, sensitive parameters and principal sources of uncertainty are presented together.
Scenario comparison and zone of influence
Water levels, flows, water balance, inflow, drawdown, transport or other decision indicators are compared across scenarios, with potential zones of influence and thresholds made explicit.
Data improvement and model-update plan
Critical data gaps, monitoring locations and frequencies, and the approach for incorporating new evidence into future model updates and reassessments are defined.
Related expertise and technical outputs
The conceptual and observational basis of a numerical model is developed through Hydrogeology & Hydrology, while spatial data preparation and visualization are integrated through Geoinformatics. Available report and project types are presented on the relevant technical-output pages.
Let’s define the right modeling scope for your project
Share the technical question, project location, available field and monitoring data, assessment period and alternatives to be compared so that an appropriate modeling approach can be defined.