Coupling SKS and SWMM to Solve the Inverse Problem Based on Artificial Tracer Tests in Karstic Aquifers
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study site and Field Data
2.2. Modeling Approach
2.2.1. Conduit Network Simulation
- Building a geological model of the studied area. It covered about 1 km2. Only the two main geological formations were considered: the slaty flysch in the southern part of the area and the Jurassic to Cretaceous metamorphic limestones in the northern part of the area. The contact between these two formations is oriented in the west-east direction. The calcareous formation was numerically considered as a homogeneous formation affected by structural heterogeneities (faults and fractures). Then, bedding planes, inception horizons, or even foliation were not considered for implementation of geological constraints in conduit networks simulation with SKS. This constitutes a strong hypothesis but seems to be acceptable regarding the small extension of the simulation area. Moreover, slaty formations constituted a boundary condition for the development of the conduit networks.
- The structural heterogeneities (faults and fractures) over the area were considered in the SKS model. The main discontinuity direction was recognized from the satellite image, running 170° N to 10° N orientations [57,58,59] as well as the faults and fractures reported by the French geological survey (BRGM) in the BD_CHARM database [54]. The fracture model includes the main structures identified in the area and a set of stochastic fractures that is different for every simulation and generated following the statistical distributions derived from the field data. Besides, the observations made through speleological investigations [44] have been considered as conditional data in the conduit network simulations; thus, SKS reproduces this known conduit.
- The inlets and outlets can be identified and imposed in SKS. The inlets are composed of La Peyrère, P2 Loss, La Hillière and Moulo de Jaur. Moreover, some additional potential inlets can be randomly added over the area to ensure more physical realism and to allow potential feeding branches along with the solute transport to be considered. Then, Las Hountas, which is the perennial outlet of the Baget system, constitutes the only outlet of the synthetic conduits networks.
2.2.2. Flow Simulation
2.2.3. Solute Transport Modeling
3. Results
3.1. Model Setup
3.2. Statistical Analysis
3.3. Conduit Geometry and Spatial Distribution of Flow
4. Discussion and Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Descriptive Statistics | Mean Flow Section Area (m2) | Mean Flow Velocity (m/s) | Transport Length (m) |
---|---|---|---|
Min | 8.42 | 0.09 | 772.7 |
Max | 9.45 | 0.41 | 1007.0 |
Mean | 9.01 | 0.16 | 905.5 |
Standard Deviation | 0.20 | 0.06 | 43.1 |
Variation Coefficient | 0.02 | 0.14 | 0.05 |
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Sivelle, V.; Renard, P.; Labat, D. Coupling SKS and SWMM to Solve the Inverse Problem Based on Artificial Tracer Tests in Karstic Aquifers. Water 2020, 12, 1139. https://doi.org/10.3390/w12041139
Sivelle V, Renard P, Labat D. Coupling SKS and SWMM to Solve the Inverse Problem Based on Artificial Tracer Tests in Karstic Aquifers. Water. 2020; 12(4):1139. https://doi.org/10.3390/w12041139
Chicago/Turabian StyleSivelle, Vianney, Philippe Renard, and David Labat. 2020. "Coupling SKS and SWMM to Solve the Inverse Problem Based on Artificial Tracer Tests in Karstic Aquifers" Water 12, no. 4: 1139. https://doi.org/10.3390/w12041139