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This paper deals with a landscape evolution model to compute cockpit karsts landforms. The CHILD model is used to model geomorphic processes at regional scale. After examining briefly CHILD's principles and equations of limestone dissolution processes, the denudation model is detailed. The relation between subcutaneous dissolution and denudation of the topography is introduced by means of an empirical equation associated with epikarst processes: the denudation is taken to be proportional to the dissolution in the subcutaneous zone. The model takes into account an anisotropic dissolution in space according to what is observed in reality or described by scenarios of cockpit karst landscape evolution. Simulated cockpit karst terrains are compared with real landscapes by means of several morphometric criteria: slope, relative relief and scaling properties. Results confirm the importance of anisotropic dissolution processes and could provide a numerical validation of the epikarst processes to describe cockpit karst genesis.

This paper deals with a landscape evolution model to compute cockpit karsts landforms. The CHILD model is used to model geomorphic processes at regional scale. After examining briefly CHILD's principles and equations of limestone dissolution processes, the denudation model is detailed. The relation between subcutaneous dissolution and denudation of the topography is introduced by means of an empirical equation associated with epikarst processes: the denudation is taken to be proportional to the dissolution in the subcutaneous zone. The model takes into account an anisotropic dissolution in space according to what is observed in reality or described by scenarios of cockpit karst landscape evolution. Simulated cockpit karst terrains are compared with real landscapes by means of several morphometric criteria: slope, relative relief and scaling properties. Results confirm the importance of anisotropic dissolution processes and could provide a numerical validation of the epikarst processes to describe cockpit karst genesis.

Funding Information: The CMB-S4 collaboration ( https://cmb-s4.org/ ) is working to plan, construct, and operate a next-generation, multisite CMB experiment in the 2020s. The collaboration is led by an elected Governing Board, Spokespeople, Committee Chairs, and Executive Team. Funding for the CMB-S4 Integrated Project Office is provided by the Department of Energy's Office of Science (project level CD-0) and by the National Science Foundation through the Mid-Scale Research Infrastructure-R1 award OPP-1935892. This research used resources of Argonne National Laboratory, a U.S. Department of Energy (DOE) Office of Science User Facility operated under Contract No. DE-AC02-06CH11357. This document was prepared by the CMB-S4 collaboration using the resources of the Fermi National Accelerator Laboratory (Fermilab), a U.S. Department of Energy, Office of Science, HEP User Facility. Fermilab is managed by Fermi Research Alliance, LLC (FRA), acting under Contract No. DE-AC02-07CH11359. Work at Lawrence Berkeley National Laboratory was supported by the Office of Science, Office of Basic Energy Sciences, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. Work at SLAC National Accelerator Laboratory is supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences under Contract No. DE-AC02-76SF00515. This research used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. In the United States, work on CMB-S4 by individual investigators has been supported by the National Science Foundation (awards 1248097, 1255358, 1815887, 1835865, 1852617, 2009469), the Department of Energy (awards DE-SC0009919, DE-SC0009946, DE-SC0010129, DE-SC0011784), and the National Aeronautics and Space Administration (award ATP-80NSSC20K0518). In Australia, the Melbourne authors acknowledge support from an Australian Research Council Future Fellowship (FT150100074). In Canada, R.H. is supported by the Discovery Grants program from NSERC, and acknowledges funding from CIFAR, the Sloan Foundation, and the Dunlap family. In Italy, C.B. acknowledges support under the ASI COSMOS and INFN INDARK programs. In the Netherlands, D.M. acknowledges NWO VIDI award number 639.042.730. In Switzerland, J.C. is supported by an SNSF Eccellenza Professorial Fellowship (No. 186879). In the United Kingdom, A.L., G.F., and J.C. are supported by the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013)/ERC grant Agreement No. [616170]. A.L. also acknowledges STFC award ST/P000525/1. S.M. is supported by the research program Innovational Research Incentives Scheme (Vernieuwingsimpuls), which is financed by the Netherlands Organization for Scientific Research through the NWO VIDI grant No. 639.042.612-Nissanke and the Labex ILP (reference ANR-10-LABX-63) part of the Idex SUPER, received financial state aid managed by the Agence Nationale de la Recherche,as part of the program Investissements d'avenir under the reference ANR-11-IDEX-0004-02. Some computations in this paper were run on the Odyssey cluster, supported by the FAS Science Division Research Computing Group at Harvard University. Publisher Copyright: © 2022. The Author(s). Published by the American Astronomical Society. ; CMB-S4-the next-generation ground-based cosmic microwave background (CMB) experiment-is set to significantly advance the sensitivity of CMB measurements and enhance our understanding of the origin and evolution of the universe. Among the science cases pursued with CMB-S4, the quest for detecting primordial gravitational waves is a central driver of the experimental design. This work details the development of a forecasting framework that includes a power-spectrum-based semianalytic projection tool, targeted explicitly toward optimizing constraints on the tensor-to-scalar ratio, r, in the presence of Galactic foregrounds and gravitational lensing of the CMB. This framework is unique in its direct use of information from the achieved performance of current Stage 2-3 CMB experiments to robustly forecast the science reach of upcoming CMB-polarization endeavors. The methodology allows for rapid iteration over experimental configurations and offers a flexible way to optimize the design of future experiments, given a desired scientific goal. To form a closed-loop process, we couple this semianalytic tool with map-based validation studies, which allow for the injection of additional complexity and verification of our forecasts with several independent analysis methods. We document multiple rounds of forecasts for CMB-S4 using this process and the resulting establishment of the current reference design of the primordial gravitational-wave component of the Stage-4 experiment, optimized to achieve our science goals of detecting primordial gravitational waves for r > 0.003 at greater than 5 sigma, or in the absence of a detection, of reaching an upper limit of r < 0.001 at 95% CL. ; Peer reviewed