WP7 - Integrated Modeling


Objectives

1. To develop methods for estimation of the geometry of hydrogeological units based on integrated interpretation of geological, hydrogeological, and geophysical data.


2. To assess the uncertainty on geological models based on the uncertainty of the underlying geophysical data.


3. To provide sub-models for local areas where specific measurements are carried out on water balance elements and test the consistency of the new data and the impact on model simulations.


4. To integrate the new data and findings into the catchment model for Skjern River and provide new consolidated model simulations and water balance estimates.


5. To prepare guidelines for estimating water balances including recommendations for use of data on precipitation, evapotranspiration and groundwater outflow.


6. To simulate the hydrological consequences of climate change.


Work content
Task 1: Joint interpretation of geological, hydraulic and geophysical data

A general inversion algorithm for inversion of very large geophysical datasets will be developed. It will use a 3D model defined spatially in a grid divided into rectangular or triangular grid cells.
The algorithm will have the fundamental extensions: 1) the basic formulation is in 3D, 2) scalable to large datasets and 3) the model description is moved from the physical measurement positions of the geophysical data to a uniformly distributed model grid. The grid based inversion algorithm will be extended to include geological a priori information not only in the nodes but also in between.


Task 2: Hydrological modeling and integration
A fully integrated hydrological model for the entire catchment will be developed from the existing model using MIKE SHE. This state of the art model will be able to describe the diurnal cycle of hydrological fluxes while accounting for the catchment scale dynamics and water balance. The land surface parameterization will largely be based on remote sensing data. The model will form the basis of a multi-constraint optimization framework utilizing the unique suite of observational data time series available in HOBE including multiple point measurements of key hydrological variables and spatial information obtained from satellite sensors.


Scaling will be a key component of the modeling work both regarding model parameterization, regionalization and evaluation against point measurements and spatial observations and other models.


Task 3: Hydrological modeling of climate change

The hydrological consequences of future climate change and related changes in land use and irrigation will be analyzed. The integrated hydrological model will be used for the hydrological predictions and the climate model HIRHAM will be used for obtaining predictions of future climatic scenarios.

The climatic scenarios will be used as input to the hydrological model. As the climate model operates on a coarse resolution, there is a need to downscale the climate data for the hydrological model. Here, new downscaling methods will be developed and tested. With changing climatic conditions the land use will change and other crop rotations will be implemented in agriculture. We will analyze the hydrological consequences of such changes by incorporating the land use changes in the model and simulate the associated changes in evapotranspiration and irrigation requirements. Land-surface-atmosphere interactions and the feedback mechanisms will also be examined.

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