Coordination between deformation, precipitation, and erosion during orogenic growth

Domain: earth_science
Published: 2024-11-28
Editorial outcome: minor_revision

Abstract
Crustal thickening associated with orogenic growth elevates topography, causing orographic enhancement of precipitation, which in turn facilitates local erosion and possibly intensifies localization of deformation. How these three processes—deformation, precipitation, and erosion—coordinate during orogenic growth remains unknown. Here, we present a numerical model where tectonics, surface processes, and orographic precipitation are tightly coupled, and explore the impact on low, intermediate, and high erodibility orogens. We show that, for intermediate erodibility models, rock uplift rates and precipitation rates correlate well with erosion rates during the formation of orogenic plateaus with high correlation coefficients of ~0.9 between rock uplift and erosion rates, and ~0.8 between precipitation and erosion rates. We demonstrate a cyclicity of correlation evolution among uplift, precipitation, and erosion rates through the development of new faults propagating outward. These results shed insights into the relative tectonic or climatic control on erosion in active orogens (e.g., Himalayas, Central Andes, and Southern Alps of New Zealand), and provide a plausible explanation for several conflicting data and interpretations in the Himalayas, which depend on the stage of maturity of the newest fault and the relative locations to old faults.

Introduction
In convergent orogens, deformation, surface uplift, and erosion closely interact: deformation induces surface uplift, and surface uplift leads to an increase in erosion rate through orographic enhancement of precipitation1–4. Mountain height and shape thus result from the interrelationship between tectonic uplift, uplift-enhanced precipitation, and erosion. The orographic climate-tectonics-erosion feedback exists in small orogens such as the Southern Alps of New Zealand (SANZ) and Olympic Mountains of Washington State, USA1,5, and may be even stronger under some circumstances in active orogens on the margins of large, high-elevation plateaus such as the Himalayas, the Tibetan Plateau, and the Central Andes1–4,6. Uplift-enhanced precipitation causes rapid erosion, denudation, and thus weakening of the orogenic margins which intensifies the localization of the deformation7–9. The notion of tectonics-climate-erosion coupling and feedbacks has been repeatedly proposed and challenged over the past two decades2,10–14 and remains one of the largest uncertainties in Earth science research.

Along the Himalayas, between roughly 77° and 87° E longitude, there is a general correlation between high rainfall, high relief, and rapid exhumation recorded in young apatite fission-track ages2,8,11. This causes an entrenched debate about climatic and tectonic controls on localization of strain and erosion2,8–13,15 mainly because the orographic enhancement of precipitation likely produces spatial correlations between enhanced precipitation and rapid rock uplift, even in the absence of a tectonic response to climate and erosion. A related more fundamental question is why do orogenic systems ‘self-organize’ such that all three processes—deformation, precipitation, and erosion—appear to be correlated in active orogens?10. Since nature does not provide ideal experiments to test these hypotheses, interpretations of spatial correlations among topography, precipitation, erosion, and active deformational structures are speculative2. Consequently, demonstration of a cause-and-effect relationship among these processes remains elusive.

Previous numerical models study how feedback between erosion and rheology may alter climate-tectonic interactions by using a simplified uniform erosion efficiency16,17 or by imposing a kinematic denudation focused on one side of orogenic topography1,7,18. These simplifications neglect important dynamic feedbacks among deformation, orographic precipitation, and erosion during mountain building, and thus the response of large orogenic systems to spatio-temporally tectonic and climatic change has not yet been systematically explored. One way of testing and disentangling the proposed links among deformation, climate, and erosion is to have a physics-based evolutionary model that couples deformation, climate, and surface processes1,2,7,17,19,20.

In this work, we present a coupled model that links three codes specialized in modeling tectonics, surface processes, and orographic precipitation. We address one fundamental question with three (low, intermediate, and high) erodibility models: How do deformation, orographic precipitation, and erosion coordinate during orogenic growth? Then we show how the intermediate erodibility models and correlation among deformation, precipitation, and erosion evolve in detail, and how they compare to observations.

Results
Model of coupled tectonics, surface process, and orographic precipitation
We use the thermo-mechanical tectonic model ASPECT21–24 coupled with the landscape evolution model FastScape25–27 and the physics-based orographic precipitation model LFPM28 acting on the topographic surface, to resolve the interaction among tectonic deformation, surface processes, and orographic precipitation at a high resolution. ASPECT computes the non-linear brittle-plastic and ductile-viscous deformation of materials (“Methods”). FastScape solves for fluvial erosion, sediment transport and deposition, and hillslope processes. LFPM considers advection, dispersion, and interaction of water contents (i.e., vapor and cloud water) in atmosphere and fallout as orographic precipitation responding to topography (“Methods”).

The erosional efficiency K = K pem (“Methods”, Eq. 10) depends on rainfall and its variability pe29, drainage area exponent m, and mostly on bedrock erodibility Kf, varying several orders of magnitude (10−7–10−4 m0.2/yr) owing to its dependence on lithology, fracturation, vegetation cover, and abrasive agents30–32. We present three representative models with low erodibility (Kf = 1 × 10−6 m0.2/yr, Fig. 1a, b), medium erodibility (1 × 10−5 m0.2/yr, Fig. 1c, d), and high erodibility (5 × 10−5 m0.2/yr, Fig. 1e, f) over a large range of observed values.

We also test the regional climate and orographically enhanced precipitation in two cases1: dominant wind in the direction of subducting plate motion (Fig. 1a, c, and e), and the opposite direction of subducting plate motion (Fig. 1b, d, and f). For simplicity, we use the same influx of vapor and cloud water and the same length scales in all models (e.g., reference height, condensation length of vapor to cloud water, fallout length of cloud water, decay length, and dispersion length of precipitation, see “Methods”). The actual precipitation in different orogens (e.g., the Himalayas, the Central Andes, and the SANZ) depends on the above parameters, the dominant wind direction, and topographic evolution. Tests of the precipitation model with the influx and length-scale parameter values (see “Methods”) agree with the maximum (~6 m/yr, Fig. 1a) and minimum (0.1 m/yr) precipitation rates that have been measured in the Himalaya-Tibet region33. Note that the Himalayas exhibit extraordinarily high precipitation due to the combined effects of Asian monsoon and orography. We run the orogenic growth model for 50 Myr with a constant convergence rate of v = 10 mm/yr (5 mm/yr on both model sides, Supplementary Fig. S1). The models in this work are not designed to reproduce the details of the geology and geometry of natural examples, and aim at the relations among rock uplift rates, precipitation rates, erosion rates, and exhumation, rather than their accurate magnitudes.

Three erodibility models and correlation analysis
In all models, shortening is accommodated by one-sided subduction of the lower crust and lithospheric mantle, and orogens grow through crustal thickening (Fig. 1, Supplementary Figs. S2–S4 and S8–S10, and Supplementary Movies 1-6). During convergence, low and medium erodibility models first grow to a maximum elevation of ~5 km, and then widen outward through thrust-faulting (Fig. 1a–d). For the low erodibility model, rock uplift and erosion rates are very low, and unbalanced at the active orogen margin (Fig. 1a, b). This case does not achieve an equilibrium between rock uplift and erosion rates, and it is in a transient growth stage. The orographic enhancement of precipitation occurs on the windward side of the orogen and retreats due to outward orogenic growth. However, the orographic precipitation does not efficiently affect rock uplift and erosion rates, nor the orogen cross-sectional geometry or exhumation rates (Fig. 1a, b).

For the medium erodibility model, both rock uplift and erosion rates are higher than those of the low erodibility model. They are balanced in the orogen center, but mostly unbalanced at the orogen margin above the new propagating faults (Fig. 1c, d). The cycles of propagating faults occur throughout orogenic growth, and the model does not reach an equilibrium between rock uplift and erosion rates throughout the 50-Myr model run. Orographic enhancement of precipitation increases the rock uplift and erosion rates and affects the geometry and shape of the orogen. In the medium erodibility model, the orientation of atmospheric moisture flux across the orogen influences its evolution, due to the orogen’s elevation, which produces a strong orographic effect on precipitation. High exhumation rates occur across the topographic surface of the orogen on the windward side. A higher orographic precipitation rate causes a narrower orogen width on the pro-side of the orogen when the dominant wind is in the direction of subducting plate motion.

The high erodibility model exhibits a balance between rock uplift and erosion rates (Fig. 1e, f), and relatively constant orogen width (~100 km, Fig. 2c). In this case, we expect perpetual cycles of thrust inception and growth on the side of the subducting plate (Supplementary Fig. S4; Supplementary Movie 3). The small size of the orogen and specifics of the orographic model produce generally symmetric rainfall patterns, which make the orogen fairly insensitive to the wind direction. Thus, the shape of this small orogen is not significantly affected by the dominant wind directions. Tests with slope exponent n ≠ 1 in the stream power model do not significantly change our modeling results (see Supplementary Discussion, Supplementary Fig. S5), but there are some trade-offs between n values and the representative Kf values, consistent with previous findings34.

We further show quantitative correlations among deformation, precipitation, and erosion by calculating the evolution of the Pearson correlation coefficient RUe_ between rock uplift and erosion rates, and correlation coefficient RPe_ between precipitation and erosion rates (see Methods for details). By testing various erodibilities in the observed range30 and more complete correlation analyzes among deformation, precipitation, and erosion, we show that given our model setup and particular convergence rate, the correlation coefficients (RUe_ and RPe_) are low (<~0.25) when the erodibility is in the range of 1 × 10−7–1 × 10−6 m0.2/yr. The correlations increase when the erodibility increases from 1 × 10−6 to 1 × 10−5 m0.2/yr (Figs. 2 and S6). Above the medium erodibility of 1 × 10−5 m0.2/yr, both correlation coefficients are relatively high (>~0.75). The correlation between the rock uplift and erosion rates is very high (RUe_ ≈ 1) for erodibilities larger than 2 × 10−5 m0.2/yr, to which narrow orogens will form rather than wide orogenic plateaus (Fig. 1e, f, Supplementary Fig. S6). The correlation RUe_ < 1 reflects an orogen in a transient growth stage (Fig. 2d), as also shown by the evolution of orogen width for different erodibilities (Fig. 2a, b, Supplementary Fig. S6). Rock uplift and erosion rates tend to be poorly correlated unless the orogen as a whole approaches a dynamic equilibrium between convergence and erosion fluxes.

Methods
We use the two-dimensional arbitrary Langrangian-Eulerian (ALE), finite-element geodynamic model ASPECT (Advanced Solver for Planetary Evolution, Convection, and Tectonics; refs. 21–24), computing the thermo-mechanical flow coupled, in an incompressible, plane-strain growth, using viscous-plastic rheology, in continent-continent collision (Supplementary Fig. S1). The ASPECT is coupled to the two-dimensional landscape evolution model FastScape25,26, which is further coupled to the orographic precipitation model28. FastScape with orographic precipitation acting on surface processes directly interacts with the thermo-mechanical model, in that any fluvial erosion and deposition feeds back to the thermo-mechanical computation through its effect on gravitational stress redistribution and rheology. The two-way coupling between ASPECT and FastScape works through a back-and-forth transfer of surface velocities and surface topography (ref. 27).

Geodynamic model
The geodynamic code ASPECT assumes an extended Boussinesq approximation with an infinite Prandtl number (i.e., no inertial term) and solves the following conservation equations (refs. 21–24),

−∇·(2ηε̇) + ∇P = ρg (1)

∇·u = 0 (2)

ρ0Cp(∂T/∂t + u·∇T) − ∇·k∇T = ρ0H + αT(u·∇P) (3)

∂ci/∂t + u·∇ci = qi (4)

where Eq. 1 is the conservation of momentum, with the effective viscosity η, the deviator of the strain rate tensor ε̇, the velocity u, the pressure P, the density ρ, and the gravity g. Eq. 2 describes the conservation of mass. Eq. 3 is the conservation of energy where ρ0 is the reference adiabatic density, Cp the specific heat capacity, T the temperature, k the thermal conductivity, H the radiogenic heating, and α the thermal expansivity. As right-hand-side heating terms, we include radioactive heating and adiabatic heating, respectively. Eq. 4 is the advection equation for each compositional field ci (e.g., upper crust, sediment age, and accumulated plastic strain), with reaction rate qi nonzero for the plastic strain, viscous strain, and sediment age fields.

The model uses a viscoplastic rheology that includes both plastic and viscous weakening24. The viscous portion of the model is a harmonically averaged composite of diffusion and dislocation creep (Supplementary Table S1) following refs. 24, 42:

ηdiff/dis = 0.5A diff/dis−1/n ε̇(1−n)/n exp(E diff/dis + PV diff/dis / RT) (6)

where Adiff/dis is the pre-exponential factor rescaled from uniaxial experiments (diff: diffusion, dis: dislocation). n, d, and m are the stress exponent, the grain size, and grain-size exponent, respectively, with n = 1 for the diffusion creep case and m = 0 for the dislocation creep case. ε̇ is the effective deviatoric strain rate. Ediff/dis and Vdiff/dis are the energy and volume of activation, respectively. P, R, and T are the pressure, the gas constant, and the temperature, respectively.

When the stress is higher than the yield stress, plastic deformation occurs which is described by the Drucker-Prager yield criterion:

σy = Ccos(ϕ) + Psin(ϕ) (7)

where C is the cohesion, P is the pressure, and ϕ is the internal friction angle. The effective plastic viscosity is then calculated by:

ηplas = σy / 2ε̇ (8)

To simulate plastic weakening, the friction angle is weakened by 75% from an initial value of 20° to 5.2° as plastic strain accumulates over the interval of 0 to 1. Viscous weakening reduces the pre-exponential factor by 75% over an accumulated viscous strain interval of 0 to 1.

Landscape evolution model
FastScape solves for stream power river incision, sediment transport and deposition in rivers, hillslope diffusion, and filling of local depressions, that is, lakes and mountain foreland basins. It changes the topographic elevation through uplift, the stream-power law (SPL) fluvial erosion, sediment transport and deposition, and hillslope diffusion (refs. 25, 26), which are described by

dh/dt = U − KAmSn + G(dh/dt)dA + Kd ∇2h (9)

where h is the topographic elevation (m), U is the uplift rate (m/yr), K is the erosion efficiency (m1-2m/yr), A is the drainage area (m2), S is the local slope in the steepest-descent direction of water flow (dimensionless), m is the drainage area exponent, n is the slope exponent, G is the deposition coefficient (dimensionless), and Kd is the diffusion coefficient (m2/yr). In the following, we use m = 0.4, n = 1 (ref. 30), and G = 1 following previous studies26, 43. The fluvial erosion efficiency K is expressed by29:

K = Kf pem (10)

where Kf is bedrock erodibility that is independent of rainfall, but still encapsulates several factors including rock properties. pe = P̅/P0 is the ratio of the upstream average mean precipitation P̅ relative to a referential precipitation P0 = 1 m/yr (ref. 44). Therefore, the overall erosion efficiency (i.e., K) consists of two main parts, including non-precipitation erodibility (i.e., lithologies and other minor erosion factors) and precipitation rate. The erodibility Kf is characterized by large uncertainty and spans a wide range, as it incorporates variations as a function of rock type, vegetation, and abrasive agents. Typical values lie between 10−7 and 10−4 m0.2/yr (refs. 30–32), assuming m = 0.4 and n = 1. We designed three models with low Kf = 1 × 10−6 m0.2/yr, medium Kf = 1 × 10−5 m0.2/yr, and high Kf = 5 × 10−5 m0.2/yr. The hillslope diffusion coefficient is constant with Kd = 1 × 10−2 m2/yr.

Orographic precipitation model
We use the orographic precipitation model (i.e., the linear feedback precipitation model; ref. 28), which considers spatially variable water contents and the respective fluxes (cloud water and hydrometeors) transported at a given wind velocity, and flux condensation and fallout over long distances. The governing equations of the model are as follows:

−∂Fv/∂x + Ld ∂2Fv/∂y2 − Fv/Lc + ϵFc/Lf = 0 (11a)

−∂Fc/∂x + Ld ∂2Fc/∂y2 + Fv/Lc − Fc/Lf = 0 (11b)

β = (1 − Lc Ll−1) e−H/H0 (12)

P = (1 − ϵ) Fc/Lf + Pb (13)

where the subscript v/c means the relation for vapor (v) or cloud water (c), F is the advective flux (m2/yr), Ld is the dispersion length of precipitation (m), Lc is the condensation length of vapor to cloud water (m), β is an equilibrium coefficient (dimensionless), Lf is the fallout length of cloud water (m), Ll is the decay length of precipitation (m), H0 is the reference height used in the precipitation model, ϵ is the evapotranspiration fraction (dimensionless), P is the precipitation rate (m/yr), and Pb is the background precipitation rate (m/yr), representing the precipitation rate contributed by others sources (e.g., local lakes) in the orographic precipitation model. Eq. 11 describes vertically integrated moisture balance for each component, Eq. 12 reflects condensation of vapor and re-evaporation of cloud water as competing processes, and Eq. 13 describes the expression of precipitation rate.

By changing the precipitation rate P (Eq. 13) to the upstream average mean precipitation P̅ and the variability pe = P̅/P0, we couple the above orographic precipitation model to the landscape evolution model (Eq. 10). In this work, we use the total influx 0.8 km2/yr of vapor and cloud water from the dominant wind boundary in the direction or in the opposite direction of subducting plate motion, the length scale Lc and Lf are both 25 km, the length scale of the decay Ll is 375 km, the dispersion length Ld is 25 km, the evapotranspiration fraction ϵ is 50%, and the background precipitation rate Pb is 0.1 m/yr. We chose this parameter setting45 as it produces a good match with the observed precipitation rates in the Himalayas (ref. 33).

Pearson correlation analysis
Pearson correlation analysis calculates a correlation coefficient that measures linear correlation between two sets of data. When applied to a sample, it is commonly represented by Rxy and may be referred to as the sample correlation coefficient or the sample Pearson correlation coefficient. Given paired data xi, yi, x2, y2, ..., xn, yn consisting of n pairs, Rxy is defined as

Rxy = Σni=1 (xi − x̅)(yi − y̅) / sqrt(Σni=1 (xi − x̅)2 Σni=1 (yi − y̅)2) (14)

where xi, yi are the individual sample points indexed with i, x̅ = 1/n Σni=1 xi and y̅ = 1/n Σni=1 yi are the sample mean for x and y sample points, respectively.

It is the ratio between the covariance of two variables and the product of their standard deviations; thus, it is essentially a normalized measurement of the covariance, such that the result always has a value between −1 and 1. The correlation sign is determined by the Rxy value: a value of 1 implies that all data points lie on a line for which y increases as x increases, and vice versa for −1. A value of 0 implies that there is no linear dependency between the variables. In this work, we calculate the Pearson correlation coefficient RUe_ for the uplift rate U and the erosion rate e̅, and the correlation coefficient RPe_ for the precipitation rate P and the erosion rate e̅.

Model limitations
Some limitations have to be kept in mind when interpreting our model results. First, we assume a constant boundary influx of vapor and cloud water in the precipitation model and a constant convergence rate in the tectonic model, whereas it is well known that the long-term Asian climate changes over time46 and that the convergence rate varies between the Indian and Eurasian plates47. Our models also do not compare quantitatively the magnitudes of precipitation observed in the Central Andes and the SANZ, which would require changing the influx and length-scale parameters of the reference orographic model. Second, to simplify our modeling, the threshold effect of fluvial erosion, in which extreme events may dominate the precipitation and water discharge48, is not considered in our long-term fluvial erosion-deposition model and precipitation model. Last but not least, our model does not consider the influence of glaciers in high-elevation domains where glaciers are likely more efficient erosion agents than rivers2, 49. Nevertheless, this study shows agreement with the first-order observed pattern of orogenic growth with dynamic interaction among deformation, orographic precipitation, and erosion.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Review of Yuan et al. “Coordination between deformation, precipitation, and erosion during orogenic growth” for consideration in Nature Communications.\nSummary of Study:\nYuan and colleagues conduct a numerical modeling study where they couple geodynamic (ASPECT), landscape evolution (FastScape), and orographic rainfall (LFPM 1.0) models to explore the dynamics and co-evolution of deformation, erosion, and precipitation during convergent orogenesis. Motivated by the ambiguity of past studies aiming to test the exciting hypothesis of tectonic-climate-erosion coupling and feedbacks. This study conducts three general experiments (high, intermediate, and low landscape erodibility) designed to span a range of conditions in natural orogens. In these experiments, relevant parameters are tracked in space and time (e.g., strain, erosion, exhumation, elevation, precipitation), and correlations between uplift, erosion, and precipitation rate are tracked. The results show distinct behaviors among the different models, where low erodibility models show weak correlations between these parameters, and as erodibility increases, uplift, erosion, and precipitation rates are more strongly correlated. Within the context of previous work by Wolf et al. (2022), the increasing correlation is associated with the transition from a strength-limited to erosion-limited orogenic system defined by the non-dimensional “Beaumont number”.\nThe results are argued to demonstrate systems where tectonic-climate-erosion feedbacks are strong (erosion-limited case) and where they are expected to be weak (strength-limited case), and natural example orogens that might meet these conditions are noted. The authors emphasize the importance of results from the intermediate erodibility case in an attempt to reconcile contradictory interpretations of tectonic-climate-erosion coupling, or lack thereof, in the Himalayas, a setting where the debate over these feedbacks has been active for decades. The authors demonstrate that the intermediate erodibility models transition between erosion- and strength-limited as new faults propagate outward through time. There are transient periods where the windward flank of the modeled orogen is locally in steady state, and climate appears to “control erosion”. Other times, when a new thrust breaks, the system is perturbed, and tectonics locally “controls erosion” and surface uplift before orography catches up and temporarily slows thrust propagation, and a local steady-state is once again achieved. This cycle (climate-moduled inch-worm orogenesis?) is argued to help explain apparently contradictory results in the Himalayas, where some locations are in the steady-state phase while others are in the thrust-propagation phase of the intermediate erodibility orogenic cycle.\nMajor Comments and Recommendations:\nThis is an impressive study. The technical achievement of the model coupling is eye-catching and of broad interest. The results are exciting, building upon the excellent work of Wolf et al. (2022) with new and creative insights. This work will be of interest to a wide range of earth scientists, making it well-suited for the broad readership of Nature Communications. The modeling presented improves understanding of how earth surface processes (via erodibility) and climate can impact convergent orogensis. An important element of the study is the sensitivity of the system to climate (more precisely here, orographic rainfall), at least as parameterized in the models used here, is a function of “bulk landscape erodiblity” and characteristics of tectonics (i.e., convergence velocity, crustal strength). The study provides important insight into where we might or might not expect to see systems with tectonic-climate-erosion coupling and feedbacks.\nI have a few comments and questions the authors might consider in revision. I’ve broken these out into “major comments” which I provide in this section and line-by-line comments below.\n(1) The manuscript abstract and intro promise to address tectonic vs. climate controls on erosion. With the sophisticated modeling approach, it seems like it should be possible to quantify the relative strengths of tectonic vs climate in modulating topographic growth, strain localization, and erosional focusing, specifically along the windward thrust front. I assume a modified Beaumont number could encapsulate this by including precipitation in the erodibility calculation and only focusing on the windward part of the model domain (provided it makes sense to do so). If it is easy to come up with a parameter like this, it could be tracked through time and used to show how the relative importance of orographic rainfall changes through time in the intermediate erodibility models. Furthermore, I mention this because I wasn’t convinced that the correlations between U & E and P & E fully demonstrated tectonics vs. climate, and I’m not sure this is a well-posed question. I’m not criticizing the authors; the community has rallied around this “question” for better or worse, even though it is not clearly testable. Tectonic, climate, and surface processes all drive the dynamics of the orogenic system, as elegantly shown in this work, and therefore, I don’t think one can easily test for “climate vs tectonics”. A more precise question is the relative strength of climate and tectonic (and surface) processes in strain and erosion localization in a tectonically active system. So, from these model results, I am wondering if it is possible to quantify the relative strength of tectonics and climate in localizing strain and erosion. I hope this is possible with these models because then we can design field experiments to measure relevant quantities and test these ideas in natural systems.\n(2) I really liked the insights generated from the intermediate erodibility models and the comparison to the Himalayas. However, one question kept arising in my mind – in sections of the orogen that are in “the youthful stage,” is there evidence that the MBT and MCT are both active? What about the ramp-flat-ramp models for the orogenic development of the Himalayas? Are they consistent with the model results? What I am probing for here is (1) can existing data or new data test the applicability of this “cyclic” model for different parts of the Himalayas, and (2) are there alternative explanations for the variability of observations throughout the orogen?\n(3) This is a relatively small “major comment”, but for the high-erodibility models, the orographic model doesn’t seem to be able to reproduce the asymmetry in precipitation observed in places like the Southern Alps of New Zealand. The precip pattern in both of the high erodibility models is quite symmetric about the topographic divide, which is distinct from the stark asymmetry across the divide in NZ. This is important because there is a statement regarding how the wind direction doesn’t affect the orogen asymmetry much in the high erodibility models. However, it seems that this is likely due to the specifics of the orographic model and its initial conditions rather than a generalizable statement.\n(4) What about glaciers? Any speculation on how they will affect results and how not including them is a limitation but an exciting area for future research?\nBeyond these three comments, I have some comments, questions, and suggested revisions below. Despite my few criticisms, I think this is a great study. The model coupling is impressive, as are the experiments and scientific insights. Importantly, my comments don’t require additional model runs, but only perhaps some relatively minor analysis of the existing model outputs and some small tweaks to the text.\nGreat work!\nAll the best,\n- Sean F. Gallen\nDetailed line-by-line comments:\nL12: Maybe “elevates” rather than “increases”?\nL15-16: I agree that this is much debated, but I’m not convinced it’s the best framing for a scientific question.\nL17-20: Can this be more specific to the intermediate erosion models, as this isn’t universally true, correct?\nL25: I think it is a little bold to say that the results reconcile conflicting data and interpretations. Rather, I think they provide potentially testable hypotheses for reconciling conflicting data and interpretations.\nL30-31: sometimes these aren’t balanced, correct? Maybe replace “balanced” with “interrelationship”?\nL45: “A related more fundamental question” rather than “A more related fundamental question”?\nL61-62: See major comment 1. I’m not sure this is a testable question because both affect erosion, so I don’t think this is a binary. Rather, I think with this modeling, there is a chance to be more precise and emphasize that both act together to affect erosion, but it is the relative importance of climate and tectonics in driving strain and erosional localization that affect orogen kinematics.\nL66: “a physics-based” rather than “the physics-based” or name the model.\nL64-93: Can this be broken up into several paragraphs? Paragraph breaks at lines 72, 78, and 84 might make it a little easier for the reader.\nL104: I found the phrase “the geometry of the orogenic shape” a little hard to understand. Can this be rephrased to something like “orogen cross-sectional geometry”? I don’t know why I got stuck on this phrase. Also, can a new paragraph start at the end of this sentence?\nL111: Can a new paragraph be added here?\nL113-114: Seem major comment 3. I think this is a result of the specific orographic model and its initial conditions. The result is a relatively symmetric rainfall pattern about the main divide, which is different from what is observed in the SANZ. The link to the Southern Alps shouldn’t be raised here, but it is certainly in the discussion. However, I do think it is important to highlight here that the small size of the orogen and the specifics of the orographic model produce generally symmetric rainfall patterns, which makes the orogen fairly insensitive to the wind direction.\nL120: Figure 1 – it is really hard to see the depositional time in the model plots. Is that color ramp needed? Can arrows show the prevailing wind direction be added for clarity?\nL176: Sorry to be nitpicky, but can the type of steady-state be defined (e.g., flux, thermal, exhumational sensu Willett and Brandon, 2002)?\nL198: Figure 2 – can a note in the figure cation be added that states the erodibility used or the Bm for these models?\nL219-223: Does this imply that the authors think the MBT and MFT are both active in these sections of the Himalayas? Clarifying this point might help point to some field studies that can test these ideas.\nL248-253: See major comment 3. This might be a result of the orographic model and its initial conditions because the precip in the models is very symmetric about the divide in the models. In the SANZ, the precipitation pattern is more asymmetric than in the results of these models.\nL269: Figure 4 – what is the difference between the black and red squares in A? Does the modeling imply that the MBT and MCT are both active?\nL295-300: Do these results have any bearing on the out-of-sequence thrust (e.g., Wobus et al., 2005) versus ramp-flat-ramp (e.g., Lavé and Avouac, 2001) debate, or are both of those ideas generally consistent with these modeling results?\nL305-306: Can this sentence be clarified? Perhaps just adding “patterns and” before “magnitudes” would help me better understand.\nL341-343: I’m not entirely convinced that the results reconcile this, but they certainly provide a plausible explanation that can be tested with more data.\nReferences cited in the review:\nLavé, J. and Avouac, J.P., 2001. Fluvial incision and tectonic uplift across the Himalayas of central Nepal. Journal of Geophysical Research: Solid Earth, 106(B11), pp.26561-26591.\nWillett, S.D. and Brandon, M.T., 2002. On steady states in mountain belts. Geology, 30(2), pp.175-178.\nWobus, C., Heimsath, A., Whipple, K. and Hodges, K., 2005. Active out-of-sequence thrust faulting in the central Nepalese Himalaya. Nature, 434(7036), pp.1008-1011.", "reviewer_2": "Coordination between deformation, precipitation, and erosion during orogenic growth is a good paper that extends the state of the art on modeling the coupled climate/surface/processes/tectonics of active orogens. The writing is clear, the methods and results are comprehensively explained, given the short format (note the generous additional materials) and the problem is something that has long been of interest in the community.\nThe modelling seems like a pretty clear incremental improvement on the prior work by some of the authors (thinking here of the 2022 Nature paper Topography of mountain belts controlled by rheology and surface processes) and many others, with new rheological and climate models, although it should of course be noted that coupled orographic/surface process/geodynamic modelling has a long tradition.\nIt’s not very clear that the high correlations between rock uplift and erosion and precipitation and erosion, are especially important, beyond what the authors note (“The strong correlations indicate that the orogen has reached a high degree of steady state”). The modeling is consistent with these orogens being close to steady state. High correlations are expected in this case as erosion matches uplift, and since most of the erosion is stream power driven in the model, we expect, and observe, a high but slightly lower correlation for precipitation and uplift as well (with diffusive/landslide processes explaining the rest of the relief lowering).\nI very much disagree that “Our modeling results can resolve the major debate about whether tectonics or climate controls erosion in large orogens” (257). In the first place, modeling alone can’t resolve this debate. In the second place, this study is an incremental improvement on previous coupled models, so if this paper was capable of resolving this debate, these prior works would’ve resolved it before this paper was written. And finally, a critic might claim that the surface process and climate models present are insufficient to make firm claims.\nThis goes beyond the fact that the stream power laws themselves remain empirically undemonstrated (although they clearly create appropriate dendritic landscapes) despite their ubiquity in numerical modeling studies. To state the obvious, the current climate and surface process conditions of the orogens investigated here are not the typical or average climate conditions at the Myr scale.\nFor most of the relevant period, most of these mountain ranges have been glaciated. Not only were the temperatures lower everywhere, wind direction and precipitation patterns varied by location. Heavily glaciated mountain ranges are not fluvially (and thus stream-powered model related) eroded, they are glacially eroded. It could be argued that erosion correlates with total water flow, be it solid or liquid, but at a minimum stream power would not be the right framing and sub-glacial temperatures (especially whether the ice is frozen at the bed) is very important. Furthermore, if orogenic precipitation is very important (and so having a sophisticated orographic model is important), then shifting climate patterns are also highly relevant, and using current wind and precipitation patterns are also, on average, quite different. Although not present in the paper’s model, other workers have focused on threshold effects with fluvial erosion, in which case even changes in the pattern of precipitation events (to or from extreme events dominating the precipitation load) could be significant. At a minimum, the cold air of the quaternary contained less moisture which, on average, reduces precipitation (which is falling as snow).", "reviewer_3": "HIGH-LEVEL COMMENTS\nIn this manuscript, the authors report a series of experiments with a coupled numerical model of mountain chain formation by plate collision, erosion (and deposition), and orographic precipitation. The study uses the model to examine the degree of correlation between rock uplift rate, erosion rate, and precipitation rate, and how this varies dynamically during different stages in process of generating new thrusts at the margins of the orogen. The experiments, which are beautifully illustrated with colour images as well as animation in the supplemental material, provide insight into the dynamic nature of orogenesis, and the transient cycles that arise around the creation of each new outer thrust. They also illustrate the potential influence of erosional efficiency on orogen form and scale.\nThe computational effort behind these experiments is surely substantial. I don't know whether the software engineering to couple ASPECT, FastScape, and the orographic precipitation model was undertaken specifically for this study or had been done previously for other work, but in any event it seems like a major technical achievement. Other studies have reported coupled deformation and erosion models, but this is the first I have seen that uses this particular combination of models.\nRegarding the significance of the problem addressed: The possibility of a dynamic feedback between mountain building and precipitation climatology has been an exciting but unproven hypothesis going back at least 30 years. Investigators have tested for correlations between quantities like tectonic motion rates, precipitation rates, and denudation rates. One barrier has been in interpreting the meaning of such correlations (or lack of correlations). To do so arguably requires a mechanistic theoretical framework, and that's part of what this paper contributes. Although numerical modeling that integrates theory for crustal strain, orographic precipitation, erosion, sediment transport, and sediment deposition has been done before, one thing I have not seen previously is examination of statistical correlations between tectonic, precipitation, and erosion rates under different scenarios. These correlations are among the things one can actually measure in the field, and the model provides a framework with which to ask what those correlations ought to look like.\nOne of the interesting findings is that stages of transience, when a new thrust fault (or shear zone) is forming at the margin of a growing orogen, can effectively interrupt an otherwise strong correlation between tectonics, precipitation, and erosion, even though a dynamic feedback is still operating. Because this is a numerical model, we know already that the processes of deformation, precipitation, and erosion are tightly coupled, so the novelty lies in asking how that coupling would manifest in the kinds of data that we can actually collect from real orogens. The finding implies that lack of correlation among rates of tectonic motion, erosion, and precipitation could just be symptoms of transient adjustment, rather than a lack of dynamic coupling.\nA comment about framing: The central concern of the paper is stated in the abstract as 'whether tectonics or climate controls erosion in active orogens is much debated.' With all due respect, this phrasing, which appears repeatedly in the manuscript, is imprecise and could be framed more clearly. The following is going to sound like picking on language rather than the technical substance of the manuscript (which it is), but I believe language matters. In this particular case, the authors are following in a long tradition of describing orogens as being 'controlled' (or alternatively, 'driven') either by tectonics or climate. The either-or phrasing implies that only one of those two things - tectonics or climate - can 'control' erosion in an active orogen. But it seems undeniable that both should influence a convergent orogen. After all, erosion would not occur on a planet without a climate system (or at least not in ways it happens on earth). And without tectonics, you wouldn't have an orogen to erode in the first place. In that sense, erosion on earth requires both climate and tectonics, and answer to the question 'are orogens controlled by tectonics or climate?' must surely be 'yes'!\nI think what the authors are really asking is something more nuanced, maybe something more along the lines of: given the natural range of plate convergence rates and precipitation rates on planet earth, do the morphology and erosion rates/patterns in a convergent orogen tend to be more sensitive to changes in convergence rate or to equivalent changes (relative to their natural range) in advective moisture flux? In other words, the 'tectonics versus climate' question can be made more precise and therefore more useful by framing it in terms of changes in a rate normalized by a natural range in rates.\nAlternatively, maybe the key question is more along the lines of: under what conditions would the orientation of atmospheric moisture flux across an orogen have the most (or least) influence on the orogen evolution, and why? The results obviously speak to this. Contrary to the findings of previous, simpler models, they find that a smaller, equilibrated orogen will tend to be less sensitive to moisture source direction, whereas a larger, transient-growth orogen will to tend to be more sensitive. If this is the main intended focus, I would love to see the authors say more about why. To what extent does the difference in sensitivity arise from orogen size (the low-erodibility case producing MUCH bigger orogens, which therefore produce a bigger orographic effect on precipitation), as opposed to orogen age or stage of evolution?\nWhatever the case, I recommend adding text to the paper that articulates a more precise version of the tectonics-versus-climate question. Framing the question in a way that could be clearly answered with the right data would be in the spirit of one of the key strengths of the paper, which is that it makes predictions about things one can actually measure. (While we are on the topic of wording, I appreciate the use of the word 'coordinate' in the title, because it conveys a sense of dynamic interaction.)\nExperimental setup: The experiments are run for a fixed duration of 50 million years. That is a reasonable choice, but if I understand correctly, it means that two out of the three main experiments reported in the manuscript are in a state of transient growth, while the other has reached dynamic equilibrium between convergence flux and erosional flux. To what extent, if any, do the conclusions rest on this choice of run time? For example, if the models had been run for only 1 million years, would the high erodibility case also show transient de-correlation between rock uplift and erosion rates? Or if they had been run to 100 my, would the other two cases reach a quasi-equilibrium, and if so would they still produce cycles of thrust birth? Or is it less a question of time than of orogen width, with transient thrust growth only being significant when the orogen is wider than N crustal thicknesses (or whatever the relevant length scale is)? It would be great to see some discussion of these issues in the text. It is an important issue because it relates to the generalizability of the results. For example, are the cycles of thrust birth restricted to the initial transient stage of the orogen, and therefore not expected for an orogen that has reached dynamic equilibrium ('steady state')? Or, as the high-erodibility movies suggest, should we expect perpetual cycles of thrust birth and growth on the side of the subducting plate?\nSPECIFIC COMMENTS ON TEXT, BY LINE NUMBER\n12 'topography' is a feature rather than a quantity, so I do not think it can be 'increased,' though it could be 'raised'.\n20 'three processes' - what are they?\n29 'increase in erosion' - the word erosion by itself could be read in any of several ways (e.g., a volume or mass, a depth, or a rate of removal). Please specify which you mean.\n37 'this notion' - not totally clear which of the foregoing ideas is referred to here, please clarify. Up to this sentence, the concepts have been presented as facts rather than hypotheses. This paragraph would be a logical place to re-phrase the tectonics-versus-climate question, as suggested above.\n40-41 I think this would read more readable if phrased as something like 'Along the Himalayas, which run from roughly 77 to 87 E longitude, there is…'\n42 'whether tectonics or climate controls erosion' - see comment above\n45-47 Yes, this is a nice way to frame it! And a great point that you'd expect these correlations even if erosion were insensitive to precipitation or deformation were insensitive to erosion. That seems like the central challenge: how do you tell whether deformation rates/patterns are actually responding to erosion, as models imply they should?\n55-58 Didn't Beaumont et al. 1992 basically have all these elements (orographic precipitation, deformation, erosion)? The list of reference on line 58 seems like a small subset of the various tectonics-climate-erosion models in the literature.\n60-62 Question (i) seems well phrased but question (ii) could be re-phrased along the lines noted above.\n68-72 It would be good to both justify and caveat the model formulations. I understand the temptation to simply state the equations used and leave it at that. The risk is that readers of the paper who aren't experts in all the relevant domains involved (physics of crustal and lithospheric deformation; physics of orographic precipitation; physics of erosion by water and gravity) will not know whether these models are well-established and reliable representations of well-understood processes, or speculative attempts to quantify poorly understood processes, or somewhere in between. This seems like an important thing to communicate.\n76-78 Only one, now rather old, reference is given for the range in erodibility values. I believe there is more recent work that adds a lot more data (papers that cite the Stock and Montgomery paper would be a good place to look).\n100-101 Can you elaborate on this? Based on other models in the literature, one might expect a balance between crustal convergence rate and erosion rate. From this wording, it sounds as if that is not achieved here? Or not achieved at the orogen margin? One thing that would help is to specify somewhere whether erosion rate means depth per time or volume per time (because if it is volume per time, then equilibrium implies a balance between convergence volume and erosion volume rates; but if it is depth per time, then a wider orogen would presumably produced a lower depth-per-time rate than a narrower one, all else equal).\nFollowing on from that, it sounds as if the low erodibility model in Fig 1A and 1B has not reached equilibrium between the mass input rate from convergence and the mass output rate by erosion (in other words, it is in a transient growth stage), but that is not explicitly stated. For each experiment, please say whether or not it has reached an approximate equilibrium at the time shown (50 My) (as you do for the high erodibility case).\n108-110 wording: exhumation could be rapid, or its rate could be high. Precipitation rate is higher.\n96-117 Looks like one outcome is that erodibility influences orogen width. I think that's consistent with previous models based on critical-wedge theory; consider pointing this out with appropriate citation(s). Also, there's an obvious implication that the time scale for equilibrium scales inversely with the erodibility, which may also be worth commenting on.\nFigure 1: The color images are gorgeous, and the cutaway portion is very helpful in visualizing the orogen simulations in 3D. However, I found the lines on the graphs below difficult to read, even when zoomed in on a computer screen. They are thin and in many places they obscure one another. I suggest experimenting with different line styles, weights, transparencies, etc. For example, using some kind of dotted lines for a variable, where the dots are thicker than other lines on the plot, might help readers trace an otherwise partly obscured curve.\nAlso, it would be helpful to state in the text or caption what the averaging time is for rock uplift and erosion rates.\nFigure 2: the lines in A-C are difficult to distinguish on a grayscale device (yes, these still exist ... I know several geoscientists who read papers on grayscale tablets). Suggest using a dashed line or something like that for the orogen width.\n153-163 The correlation analysis is interesting. It would be even more interesting if the authors could add some commentary about why these patterns emerge in the model experiments. To what extent does the de-correlation reflect an orogen that is still in a transient growth stage as a whole? Would it be correct to say that, in this model, rates of rock uplift and erosion will tend to be poorly correlated until and unless the orogen as a whole approaches a dynamic equilibrium between convergence and erosion fluxes? Or is that only true for the outermost thrusts?\nRegarding correlation between precipitation and erosion rates, the model imposes a direct (albeit nonlinear) relationship between these two quantities. Why then should they not be perfectly correlated? Is it because the water that accomplishes erosion is sourced from an upstream drainage area, so that the average runoff rate at any given point in the stream network is not necessary the same as the locally generated runoff rate at that point? And/or does the nonlinearity in the actually mathematical relationship between precipitation rate and erosion rate reduce the apparent (linear) correlation?\n167-170 Please state the complete definition of the Beaumont number.\n174 'respective models' - do you mean the model experiments with Bm in the same range? Can you remind us which experiment(s) this is?\n178-180 'could be a coincidence' - I am struggling to understand the point here. Because this is a numerical model, presumably you can determine whether it actually is just coincidental, no? (For example, you could run a version in which precipitation rate is uniform in space and time, then run the orographic precipitation model on the final topography and examine the resulting 'one-way' correlation). Are you saying that a such a correlation would occur regardless of whether the precipitation field actually had any effect on erosion or not? Is the point then that the existence of such a correlation is uninformative because it would occur with or without a dynamic interaction between the precipitation field and tectonic deformation?\nFigure 3: same suggestion regarding line styles as with Figure 1\n192-195 Please clarify what 'orographic precipitation advances fully' means. Is the idea that the two rainfall peaks in 3C merge again into a single peak more like 3A? Why does that happen?\nActually that leads to a related question, which would be great to discuss in this section/paragraph: At all three stages in Figure 3, the terrain is broken into fault-bounded (or shear-zone-bounded) blocks, with valleys between them. Yet despite this step-like topography, there is basically just one main rainfall peak in A, with a minor subtle one further in the interior. Why does the orographic precipitation model not produce multiple peaks corresponding to the multiple range-like blocks in the model? Is Fig 3A a case of most of the moisture getting 'rained out' before it reaches the next major block?\nFigure 4: the text discusses two types of topographic profile, a two-step one characteristic of the central Himalayas, and a single-rise profile characteristic of the far western and eastern parts. I was disappointed that Figure 4 only shows one of these types. I realize that manuscript space is probably at a premium but given that the text is describing an important contrast in morphology that the model results provide a possible explanation for, it seems reasonable to show examples of both. Otherwise, we have to take the authors' word for it. I found myself wondering why, for example, the Shillong Plateau in the east or the Kashmir Valley in the west do not create stepped profiles; showing an actual profile(s) would help clear this up.\n216-219 The idea that intermittent growth of individual thrust blocks creates two-step topography is interesting, and the model runs provide a wonderful illustration of how transient formation of thrust blocks at the orogen margins can influence topography, erosion rates/patterns, and precipitation patterns. One thing that confused me however is that all three panels in Figure 3 seem show stepped topography, or at least topographic profiles with multiple peaks and valleys. For example, the central and left-hand parts of the model orogen look like some type of pop-up structures, with a prominent valley between them. To the right are several thrust-bounded slabs, each associated with its own topographic peak. In frame B, a new block starts to form, but at the 'Mature' stage in C the gap between it and the adjacent and higher interior range still exists. So I can see that the model illustrates how a multi-step topography forms, but I do not see in Figure 3 or Figure 4 a case without steps. Maybe it would help to carefully define what 'step' means (e.g., does it only counts as a step if there is a certain minimum difference in mean or peak elevation from one thrust block to the next?).\n224-237 I like the use of the dimensionless Beaumont number as a single value that can be used to compare orogens and model experiments. And the discussion here of the Central Andes as a contrast to the Himalayas is interesting. However, it is difficult for me as a reader to make much of it the Andes discussion because no data are shown for that setting. So the paragraph comes across as rather speculative. I guess that's ok for a Discussion section, but it left me wanting to see more. Consider expanding on this - as is, it feels like not enough analysis to do justice to the comparison.\n228-230 It is not clear to me why the presence of volcanic and sedimentary rocks imply an orogen that is 'further away from steady state than Himalaya-Tibet'. Please explain.\n241 'small orogen' - suggest supporting this by saying what is considered small, e.g., '(<300 km)' or '(less than a few crustal thicknesses)'\n248-253 Interesting that the findings are different than what previous (presumably simpler) models suggested. It would be great to have some analysis and explanation about why there is such a difference. Is it for example the inclusion of the lithosphere and upper asthenosphere in the model domain that somehow reduces sensitivity to an asymmetry in erosional efficiency?\n257-267 This is one of the key insights of the paper: that the cycle of breaking a new thrust at the orogen margin creates transience, with a weak correlation between rock uplift and erosion rates as the new thrust propagates. Nice!\n333-334 Sentence unclear, please re-phrase.\n499 is the colon in equation 3 a typo?\n525-7 redundant?\n575-6 what does the background precipitation represent physically?\n626-641 good idea to test this", "reviewer_1_round_2": "Review of Yuan et al., “Coordination between deformation, precipitation, and erosion during orogenic growth” for consideration in Nature Communications.\nI read through the revised manuscript and the response to the reviewers' comments. Since the manuscript has not changed significantly from the original submission I reviewed, I referred the editor to my first review for my study summary.\nThe authors have done a good job addressing my comments and, in my opinion, the comments raised by the two other reviewers. In this revision, the authors revised some aspects of the framing of the manuscript to avoid “tectonics vs. climate” phrases, provided additional details on comparisons to natural examples, added a section in the methods regarding model limitations, and softened some of the language around correlations between model variables (uplift, exhumation, precip) and interpretations/implications of results. These changes strengthen what was already an excellent manuscript. At this point, I think that this manuscript is ready for publication, pending very minor revisions. Below I have just a few line-by-line comments for the author’s to consider, but they are all easy to address.\nI look forward to seeing this work published.\nAll the best,\n- Sean F. Gallen\nLine-by-line comments:\nL18-19: A critical aspect of this work is the different erodibility models (low, intermediate, and high). It seems pertinent to mention this approach in the abstract. I suggest adding something to this effect at the end of this sentence to provide more context for the following sentence. For example, adding “, and explore the impact on low, intermediate, and high erodibility orogens.”\nL20: should “erosion” be replaced with “erodibility” when describing the intermediate models?\nL39: feedbacks rather than feedback?\nL117: High exhumation rates rather than Large exhumation?\nL269-274: I do wish this could be caveated a little more in the main text as opposed to just in the new methods section, but I assume the authors are running into length restrictions for the main text. It still reads to me that this is universally true, but I am not convinced that it is.", "reviewer_3_round_2": "I feel the authors have done a good job responding to my first round of comments and suggestions. They have clearly taken the reviews seriously, and the resulting revised manuscript is stronger as a result. At this point, I have no further issues, and recommend the manuscript be accepted for publication.", "reviewer_4": "Response letter to reviewer comments\nWe thank the three reviewers for their constructive comments. These comments are of great help\nin improving our manuscript. Following these comments, we have made thorough modifications\nto a new version. In the following, we summarized the major comments and replied point by point\nto the comments raised by the three reviewers. In the response letter, our answers to each point are\nin cyan text, and line numbers are shown in red to increase clarity. The revised text is highlighted\nin yellow in the revised manuscript and Supplementary Information.\nMajor comments from the reviewers and our replies are summarized below.\nThe reviewer #1 raised four major comments: (1) additional analysis on the relative strength of\nclimate and tectonic processes in strain and erosion localization; (2) several questions on the\ncomparison of the observations in the Himalayas; (3) model compared to the precipitation\npatterns in the Southern Alps of New Zealand; and (4) influence of glaciers. For the major\ncomment (1), which is similar to the comment raised by reviewer #3 on improving the\nwording, we think the best way is to remove all statements related to “Whether tectonics or\nclimate controls erosion?”, or “Do tectonics or climate control erosion?” (questioned by the\ntwo reviewers) throughout the revised manuscript, so additional analysis is not required. We\nhave addressed all other major comments, please see the detailed response in the response\nletter.\nThe reviewer #2’s comments are mainly about an overstated sentence in the previous manuscript,\nand several common model limitations in the Landscape Evolution Modeling community. We\nhave removed the overstated sentence and added some model limitations in the revised\nmanuscript.\nThe reviewer #3 had two main comments: (1) improving wording; and (2) expanding discussions\non the observed dynamics and the experimental setup of a fixed duration of 50 million years.\nWe have improved the wording and expanded the discussion on the observed dynamics\naccording to the reviewer’s suggestions."}, "author_response": "We thank the three reviewers for their constructive comments. These comments are of great help in improving our manuscript. Following these comments, we have made thorough modifications to a new version. In the following, we summarized the major comments and replied point by point to the comments raised by the three reviewers. In the response letter, our answers to each point are in cyan text, and line numbers are shown in red to increase clarity. The revised text is highlighted in yellow in the revised manuscript and Supplementary Information.\nMajor comments from the reviewers and our replies are summarized below.\nThe reviewer #1 raised four major comments: (1) additional analysis on the relative strength of climate and tectonic processes in strain and erosion localization; (2) several questions on the comparison of the observations in the Himalayas; (3) model compared to the precipitation patterns in the Southern Alps of New Zealand; and (4) influence of glaciers. For the major comment (1), which is similar to the comment raised by reviewer #3 on improving the wording, we think the best way is to remove all statements related to “Whether tectonics or climate controls erosion?”, or “Do tectonics or climate control erosion?” (questioned by the two reviewers) throughout the revised manuscript, so additional analysis is not required. We have addressed all other major comments, please see the detailed response in the response letter.\nThe reviewer #2’s comments are mainly about an overstated sentence in the previous manuscript, and several common model limitations in the Landscape Evolution Modeling community. We have removed the overstated sentence and added some model limitations in the revised manuscript.\nThe reviewer #3 had two main comments: (1) improving wording; and (2) expanding discussions on the observed dynamics and the experimental setup of a fixed duration of 50 million years. We have improved the wording and expanded the discussion on the observed dynamics according to the reviewer’s suggestions."}]

Decision letter