Reconstructing river planform is crucial to understanding ancient fluvial systems on Earth and other planets. Paleo-planform is typically interpreted from qualitative facies interpretations of fluvial strata, but these can be inconsistent with quantitative approaches. We tested three well-known hydraulic planform predictors in Cretaceous fluvial strata (in Utah, USA) where there is a facies-derived consensus on paleo-planform. However, the results of each predictor are inconsistent with facies interpretations and with each other. We found that one of these predictors is analytically best suited for geologic application but favors single-thread planforms. Given that this predictor was originally tested using just 53 data points from natural rivers, we compiled a new data set of hydraulic geometries in natural rivers (n = 1688), which spanned >550 globally widespread, sand- and gravel-bed rivers from various climate and vegetative regimes. We found that the existing criteria misclassified 65% of multithread rivers in our data set, but modification resulted in a useful predictor. We show that depth/width (H/W) ratio alone is sufficient to discriminate between single-thread (H/W > 0.02) and multithread (H/W < 0.02) rivers, suggesting bank cohesion may be a critical determinant of planform. Further, we show that the slope/Froude (S/Fr) ratio is useful to discriminate process in multithread rivers; i.e., whether generation of new threads is an avulsion-dominated (anastomosing) or bifurcation-dominated (braided) process. Multithread rivers are likely to be anastomosing when S/Fr < 0.003 (shallower slopes) and braided when S/Fr > 0.003 (steeper slopes). Our criteria successfully discriminate planform in modern rivers and our geologic examples, and they offer an effective approach to predict planform in the geologic past on Earth and on other planets.River planforms constitute a fundamental element of fluvial landscapes and reflect the quasi-equilibrium form of channels in response to water discharge, sediment flux, and slope. In ancient fluvial systems, their reconstruction is crucial to determine river response to climate and land-cover change (Gibling and Davies, 2012; Gibling et al., 2014; Colombera et al., 2017), water, sediment, and biogeochemical fluxes (Ganti et al., 2019; Lyster et al., 2021), and pre-vegetation landscape dynamics on Earth and other planets (Ielpi and Rainbird, 2016; Ielpi et al., 2018; Ganti et al., 2019; Ielpi and Lapôtre, 2019a; Lapôtre et al., 2019; Lapôtre and Ielpi, 2020). In fluvial strata, facies interpretations provide qualitative insights into paleo-planform (e.g., Miall, 1993, 1994; Adams and Bhattacharya, 2005; Hampson et al., 2013); however, quantitative planform predictors are important complements to these approaches. They are particularly important where exposure of fluvial strata is limited (Fielding et al., 2018; Chamberlin and Hajek, 2019), where paleohydraulic calculations are required (Lyster et. al., 2021), and where facies interpretations may be equivocal (Fielding et al., 2018). Recent debates about the implication of “sheet-braided” facies models for pre-vegetation rivers underscore this latter issue (Gibling and Davies, 2012; Gibling et al., 2014; Ielpi and Rainbird, 2016; Ganti et al., 2019).Planform predictors include empirical relationships (e.g., van den Berg, 1995) and theoretical approaches, where the onset of meandering and braiding is predicted by mathematical models of channel stability and bar formation (e.g., Parker, 1976; Crosato and Mosselman, 2009). However, insights from these predictors can contrast stratigraphic interpretations (Ganti et al., 2019; Lyster et al., 2021). In stratigraphy, the discriminatory power of these predictors is unclear because (1) they are tested on modern data sets that lack natural river data (relative to experimental and man-made channels) and are biased toward North American and gravel-bed rivers; and (2) they often discriminate only single-thread and multithread rivers, neglecting to distinguish between anastomosing and braided planforms (Schumm, 1985; Church, 2006; Church and Ferguson, 2015).We assessed how the predictors postulated by Parker (1976), Crosato and Mosselman (2009), and van den Berg (1995) performed when applied to fluvial strata with consensus facies interpretations of planform, and we established the approach that is most suitable for geologic application. We then compiled a new data set of hydraulic geometries in natural rivers and used these data to propose new criteria for paleo-planform prediction.We focused on three Cretaceous formations in Utah, USA (Fig. 1A), where distinct planforms have been interpreted from facies analyses and plan-view exposures: (1) the Ferron Sandstone preserves meandering trunk channels (Fig. 1B; Cotter, 1971; Wu et al., 2015; Bhattacharyya et al., 2015); (2) the Blackhawk Formation preserves single-thread and multithread channels (Fig. 1C; Adams and Bhattacharya, 2005; Hampson et al., 2013); and (3) the Castlegate Sandstone preserves mostly braided channels (Fig. 1C; Miall, 1993, 1994).For individual cross-sets in the Blackhawk Formation (n = 81), Castlegate Sandstone (n = 146), and Ferron Sandstone (n = 190), we determined mean cross-set thickness, hxs, and median grain size, D50 (Figs. 1D and 1E), and we used an established quantitative framework (cf. Lyster et al., 2021; see the Supplemental Material1) to reconstruct flow depth (H), slope (S), flow velocity (U), and Froude number (Fr). We also required wetted channel width (W), which is difficult to constrain from geologic outcrops. To address this, we (1) implemented plausible lower and upper values of W (Wmin and Wmax) based on published estimates; and (2) evaluated the sensitivity of each predictor to uncertainty in channel aspect ratio (H/W) using identical data inputs for hxs and D50 and using a Monte Carlo method to estimate error (see the Supplemental Material).For each cross-set, we used three predictors to reconstruct planform (Table 1). First, we used the predictor of Parker (1976), where the planform parameter (ε) is <1 for single-thread rivers, ε > 1 for multithread rivers with 1–10 threads, and ε > 10 for multithread rivers with >10 threads (Equation 1 in Table 1). Second, we used the predictor of Crosato and Mosselman (2009) to estimate the bar mode (m) of rivers, where m ≤ 1.5 for single-thread rivers, m ≥ 2.5 for multithread rivers, and 1.5 < m < 2.5 for transitional rivers (Equation 2 in Table 1). Third, we used the predictor of van den Berg (1995) to estimate a specific stream power parameter (ω) to discriminate between single-thread and multithread rivers (Equation 3 in Table 1).We compiled data on hydraulic geometries in natural rivers. We focused on appropriate modern analogues for ancient rivers, i.e., rivers that can plausibly be preserved in the rock record, including globally widespread sand- and gravel-bed rivers from various climate and vegetative regimes (see the Supplemental Material). We included rivers with reported values of W, H, S, U, and discharge (Q); we calculated Fr (see the Supplemental Material). Our data set contained 1688 data points for more than 550 rivers from 87 sources, with 758 observations of multithread rivers, including braided (n = 402), anastomosing (n = 124), and transitional (n = 232) planforms, which represent meandering–anastomosing and sinuous–braided transitions, and 930 observations of single-thread rivers, which represent meandering and sinuous planforms. With these data, we tested existing predictors, and we analyzed data distributions to propose new criteria that honor both modern and stratigraphic observations.For each formation, we present the planforms implied using Wmin and Wmax (Fig. 2; Table 1). We found that the Parker (1976) predictor favored single-thread planforms, even for Wmax (Figs. 2A–2C), which is inconsistent with interpretations of multithread Blackhawk and Castlegate channels. The Crosato and Mosselman (2009) predictor strongly favored multithread planforms (Figs. 2E–2G), which is inconsistent with interpretations of single-thread Blackhawk and Ferron channels. Finally, the van den Berg (1995) predictor also favored single-thread planforms (Figs. 2I and 2J), which, for Wmin, is inconsistent with multithread Blackhawk and Castlegate channels. Ultimately, the predictors were inconsistent with one another, and no predictor was consistent with stratigraphic consensus for all three geologic examples.We evaluated the sensitivity of each predictor to H/W to demonstrate how the implied planform (y axis) varied with uncertainty in H/W (x axis; Figs. 2D, 2H, and 2L). Despite identical data inputs, we found that the threshold H/W between multithread and single-thread rivers varied for each predictor. For Parker (1976), Crosato and Mosselman (2009), and van den Berg (1995), these H/W values were ~0.002, ~0.03, and ~0.005, respectively (or W/H values of ~500, ~33, and ~200; Figs. 2D, 2H, and 2L). This difference arises analytically: in Parker (1976), the threshold between multithread and single-thread rivers is dependent on H/W, whereas in Crosato and Mosselman (2009) and van den Berg (1995), it is independent of H/W, which implicitly assumes that H/W is known. This is not an issue in modern rivers, where H/W is known, but it is problematic in geologic applications, where W is hardly measurable.For geologic applications, the Parker (1976) predictor is analytically most appropriate because it requires the fewest assumptions, and its threshold is dependent on H/W (Table 1). However, the Parker (1976) predictor favored single-thread planforms; we therefore tested this predictor with our new data set.In our data set, the Parker (1976) predictor correctly predicted planform in 93% of single-thread rivers but only in 35% of multithread rivers (Fig. 3A), so the existing Parker (1976) calibration requires improvement. Significantly, for single-thread and multithread rivers, our data showed that H/W distributions are statistically distinct, whereas S/Fr distributions have similar medians and interquartile ranges. Consequently, a simple H/W threshold can effectively discriminate between single-thread (H/W > 0.02) and multithread (H/W < 0.02) rivers (Fig. 3A). This threshold correctly predicted planform in 82% of single-thread rivers (90% predicted by H/W >0.014) and 84% of multithread rivers (90% predicted by H/W <0.027) (Fig. 3A).Further, the Parker (1976) predictor does not discriminate between braiding and anastomosing styles, but our data set enabled this kind of prediction. We found that braided and anastomosing rivers had similar median H/W but distinct S/Fr distributions (Fig. 3B). In braided rivers, S/Fr spans ~0.001–0.1, whereas in anastomosing rivers, S/Fr spans ~0.0001–0.001 (Fig. 3B). In transitional rivers, S/Fr values of ~0.001–0.01 overlap with braided and anastomosing rivers, as these data span sinuous–braided and meandering–anastomosing transitions. We found that a simple threshold could discriminate between braided (S/Fr > 0.003) and anastomosing (S/Fr < 0.003) rivers, which correctly predicted planform in 84% of braided rivers (90% predicted by S/Fr >0.002) and 85% of anastomosing rivers (90% predicted by S/Fr <0.0034) (Fig. 3B).Using these thresholds together (i.e., H/W < 0.02 and S/Fr < 0.003 for anastomosing rivers, H/W < 0.02 and S/Fr > 0.003 for braided rivers, and H/W > 0.02 for single-thread rivers), we correctly predicted 70% of anastomosing rivers, 65% of braided rivers, and 82% of single-thread rivers in our data set.Applying these criteria to our geologic data, Ferron rivers plotted as single-thread channels (triangles in Fig. 3), consistent with facies interpretations (Cotter, 1971; Wu et al., 2015), whereas Blackhawk and Castlegate rivers plotted as anastomosing channels (squares and bold open circles in Fig. 3B), which is inconsistent with interpretation of these multithread rivers as braided but consistent with them being characterized by sand beds, shallow slopes, high suspended sediment loads, and a propensity to avulsion (e.g., Miall, 1993, 1994; Chamberlin and Hajek, 2019; Lyster et al., 2021), features typical of anastomosing rivers. Further, assuming Wmin, Blackhawk channels plotted on the single-thread transition, consistent with interpretations of single-thread Blackhawk channels (Hampson et al., 2013).For our geologic examples, we showed that existing planform predictors disagree with each other and with facies interpretations. While the Parker (1976) approach was the most suitable paleo-planform predictor, it favored single-thread planforms (Figs. 2A–2D) and incorrectly classified two thirds of multithread rivers in our data set (Fig. 3A). We note that theory-based predictors, such as the Parker (1976) predictor, often assume straight channels with rectangular cross sections and nonerodible banks. Consequently, they may not capture the wide variability of natural rivers, minimizing the potential importance of factors beyond this geometry. Moreover, the original data set used to validate the Parker (1976) predictor was small and heavily relied on experimental and man-made channels. In our new data set, H/W was the most important discriminator of planform, rather than S/Fr, with H/W >0.02 in single-thread rivers and H/W <0.02 in multithread rivers (Fig. 3A). We hypothesize that the apparent connection between H/W and planform may indicate that bank cohesion is a critical determinant of planform (Ielpi and Lapôtre, 2019b; Lapôtre et al., 2019; Dunne and Jerolmack, 2020; Ielpi and Lapôtre, 2020) as opposed to channel slope.Further, while our data showed that S/Fr could not discriminate between single- and multithread rivers, S/Fr could discriminate multithread planform style. In multithread rivers, new threads may have multiple origins, including avulsion in anastomosing rivers and bifurcation in braided rivers (Jerolmack and Mohrig, 2007; Kleinhans et al., 2013; Carling et al., 2014). Our data suggest that S/Fr may capture a process transition, where multithread rivers are likely to be anastomosing when S/Fr < 0.003 (shallower slopes) and braided when S/Fr > 0.003 (steeper slopes) (Fig. 3B). These thresholds are easy to apply to geologic data, where paleoslope can be reconstructed (e.g., Trampush et al., 2014), and they are a better fit to modern and stratigraphic observations of multithread rivers.While estimates of H from geologic outcrops are robust (e.g., Lyster et al., 2021), estimating W remains difficult because it requires preservation of channel architecture and/or channel fill (Toonen et al., 2012; Ielpi and Ghinassi, 2014) and knowledge of the number of active threads. Paleo-planform prediction therefore remains limited by uncertainties in H/W, and we advise that our criteria should be implemented for a range of plausible widths. Moreover, while our criteria resolve inconsistencies between facies interpretations and planform predictors, it is important to couple these approaches. For Blackhawk and Castlegate channels, reconstructed planforms are broadly similar (Fig. 2), but their stratigraphic architectures are distinct. Consequently, understanding the kinematic and stratigraphic controls on the geologic preservation of planforms, as opposed to their geomorphic equivalents, is now a pressing research need.Where hydraulic geometries can be reconstructed from fluvial strata, our new criteria provide a simple and effective way to predict paleo-planform. The results are important given ongoing discussions regarding the limited preservation potential of planform in the rock record (Fielding et al., 2018; Best and Fielding, 2019), and they are particularly useful where outcrop is limited or facies interpretations are equivocal, such as unvegetated fluvial systems of early Earth and Mars. Our criteria will improve the fidelity of water, sediment, and biogeochemical flux reconstructions from fluvial strata, which are crucial to decipher river responses to tectonic and climatic forcing (e.g., Lyster et al., 2021), and they will provide new insights into channel-forming processes and channel stability. Together, these constraints will help to build a more complete picture of fluvial landscape evolution in the geologic past.This work was supported by the UK Natural Environment Research Council, Imperial College London, and U.S. National Science Foundation award 1935513. We are grateful to three anonymous reviewers for their feedback, which improved this manuscript.

中文翻译：

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古平面图问题

重建河流平面图对于了解地球和其他行星上的古代河流系统至关重要。古平面通常从河流地层的定性相解释中解释，但这些可能与定量方法不一致。我们在白垩纪河流地层（美国犹他州）中测试了三个著名的水力平面预测器，在这些地层中，对古平面形成了相派生的共识。然而，每个预测变量的结果与相解释和彼此不一致。我们发现其中一个预测因子在分析上最适合地质应用，但更适合单线程平面图。鉴于该预测器最初仅使用来自天然河流的 53 个数据点进行测试，我们编制了一个新的天然河流水力几何数据集 (n = 1688)，其跨越 > 550 条来自不同气候和植被状态的全球分布的沙质和砾石河床。我们发现现有标准对我们数据集中 65% 的多线程河流进行了错误分类，但修改后产生了有用的预测器。我们表明，仅深度/宽度 (H/W) 比率就足以区分单线 (H/W > 0.02) 和多线 (H/W < 0.02) 河流，这表明河岸凝聚力可能是平面形态的关键决定因素。此外，我们表明斜率/弗劳德 (S/Fr) 比可用于区分多线程河流中的过程；即，新线程的生成是撕脱主导（吻合）还是分叉主导（编织）过程。当 S/Fr < 0.003（较浅的斜坡）时，多线河流可能是吻合的，而当 S/Fr > 0.003（较陡的斜坡）时，可能会形成辫状。我们的标准成功区分了现代河流的平面形态和我们的地质例子，它们提供了一种有效的方法来预测地球和其他行星上地质过去的平面形态。河流平面形态构成河流景观的基本要素，反映了河流的准平衡形式水流、泥沙通量和坡度的响应。在古代河流系统中，它们的重建对于确定河流对气候和土地覆盖变化的响应至关重要（Gibling 和 Davies，2012；Gibling 等，2014；Colombera 等，2017）、水、沉积物和生物地球化学通量（ Ganti 等人，2019 年；Lyster 等人，2021 年），以及地球和其他行星上的植被前景观动态（Ielpi 和 Rainbird，2016 年；Ielpi 等人，2018 年；Ganti 等人，2019 年；Ielpi 和 Lapôtre ，2019a；Lapôtre 等人，2019；Lapôtre 和 Ielpi，2020）。在河流地层中，相解释提供了对古平面形态的定性见解（例如，Miall，1993、1994；Adams 和 Bhattacharya，2005；Hampson 等，2013）；然而，定量的平面图预测器是这些方法的重要补充。它们在河流地层暴露有限（Fielding 等人，2018 年；Chamberlin 和 Hajek，2019 年）、需要古水力计算（Lyster 等人，2021 年）以及相解释可能模棱两可的情况下尤其重要（Fielding等人，2018）。最近关于“片状编织”相模型对植被前河流的影响的辩论强调了后一个问题（Gibling 和 Davies，2012；Gibling 等，2014；Ielpi 和 Rainbird，2016；Ganti 等，2019）。平面图预测器包括经验关系（例如，van den Berg，1995 年）和理论方法，其中蜿蜒和编织的开始由通道稳定性和条形形成的数学模型预测（例如，Parker，1976 年；Crosato 和 Mosselman，2009 年）。然而，来自这些预测变量的见解可以对比地层解释（Ganti 等人，2019；Lyster 等人，2021）。在地层学中，这些预测变量的区分能力尚不清楚，因为（1）它们是在缺乏天然河流数据（相对于实验和人造河道）并且偏向北美和砾石河床的现代数据集上进行的；(2) 他们通常只区分单线程和多线程河流，而忽略区分吻合和编织平面图 (Schumm, 1985; Church, 2006; Church and Ferguson, 2015)。我们评估了 Parker (1976) 假设的预测因子如何, Crosato 和 Mosselman (2009) 以及 van den Berg (1995) 在应用于河流地层时对平面形态进行了一致的相解释，我们建立了最适合地质应用的方法。然后，我们编制了一个新的天然河流水力几何数据集，并使用这些数据提出了古平面形态预测的新标准。我们专注于美国犹他州的三个白垩纪地层（图 1A），其中不同的平面形态已被解释为相分析和平面图出露：（1）Ferron 砂岩保留了蜿蜒的主干河道（图 1B；Cotter，1971；Wu 等，2015；Bhattacharyya 等，2015）；(2) 黑鹰组保留了单线和多线通道（图 1C；Adams 和 Bhattacharya，2005；Hampson 等，2013）；(3) Castlegate 砂岩主要保留辫状河道 (图 1C; Miall, 1993, 1994)。对于 Blackhawk 组 (n = 81)、Castlegate 砂岩 (n = 146) 和 Ferron 砂岩 ( n = 190），我们确定了平均交叉组厚度 hxs 和中值粒度 D50（图 1D 和 1E），并且我们使用了已建立的定量框架（参见 Lyster 等人，2021；参见补充材料 1 ) 重建流动深度 (H)、坡度 (S)、流速 (U) 和弗劳德数 (Fr)。我们还需要润湿河道宽度 (W)，这很难受到地质露头的限制。为了解决这个问题，我们 (1) 根据已发布的估计值实现了 W 的合理下限值和上限值（Wmin 和 Wmax）；(2) 使用 hxs 和 D50 的相同数据输入并使用 Monte Carlo 方法估计误差（参见补充材料），评估每个预测器对通道纵横比 (H/W) 不确定性的敏感性。对于每个交叉集，我们使用三个预测器来重建平面图（表 1）。首先，我们使用了 Parker (1976) 的预测器，其中平面参数 (ε) 对于单线河流来说 <1，对于具有 1-10 个线的多线河流，ε > 1，对于 > 10 的多线河流，ε > 10螺纹（表 1 中的公式 1）。其次，我们使用 Crosato 和 Mosselman (2009) 的预测器来估计河流的条形模式 (m)，其中 m ≤ 1.5 为单线河流，m ≥ 2.5 为多线河流，1.5 < m < 2.5 为过渡河流（表 1 中的公式 2）。第三，我们使用 van den Berg (1995) 的预测器来估计特定的流功率参数 (ω) 以区分单线和多线河流（表 1 中的公式 3）。我们汇编了天然河流水力几何形状的数据。我们专注于古代河流的适当现代类似物，即可以合理地保存在岩石记录中的河流，包括来自各种气候和植物状态的全球广泛分布的砂砾床河流（见补充材料）。我们包括报告了 W、H、S、U 和流量 (Q) 值的河流；我们计算了 Fr（见补充材料）。我们的数据集包含来自 87 个来源的 550 多条河流的 1688 个数据点，对多线程河流进行了 758 次观测，​​包括编织 (n = 402)、吻合 (n = 124) 和过渡 (n = 232) 平面图，代表蜿蜒 - 吻合和蜿蜒 - 编织的过渡，以及对单线河流的 930 次观测，​​代表蜿蜒和蜿蜒的平面图。使用这些数据，我们测试了现有的预测变量，并分析了数据分布以提出尊重现代和地层观测的新标准。对于每个地层，我们展示了使用 Wmin 和 Wmax 隐含的平面图（图 2；表 1）。我们发现 Parker (1976) 预测器偏爱单线程平面图，即使对于 Wmax（图 2A-2C）也是如此，这与多线程 Blackhawk 和 Castlegate 通道的解释不一致。Crosato 和 Mosselman (2009) 预测器强烈支持多线程平面图（图 2E-2G），这与单线程 Blackhawk 和 Ferron 通道的解释不一致。最后，van den Berg (1995) 预测器也支持单线程平面图（图 2I 和 2J），对于 Wmin，这与多线程 Blackhawk 和 Castlegate 通道不一致。最终，预测变量彼​​此不一致，并且没有一个预测变量与所有三个地质示例的地层共识一致。我们评估了每个预测变量对 H/W 的敏感性，以证明隐含的平面图（y 轴）如何随 H 中的不确定性而变化/W（x 轴；图 2D、2H 和 2L）。尽管数据输入相同，但我们发现多线程和单线程河流之间的阈值 H/W 因每个预测变量而异。对于 Parker (1976)、Crosato 和 Mosselman (2009) 以及 van den Berg (1995)，这些 H/W 值分别为 ~0.002、~0.03 和 ~0.005（或 W/H 值 ~500、~33 , 和 ~200; 图 2D、2H 和 2L)。这种差异是通过分析产生的：在 Parker (1976) 中，多线程和单线程河流之间的阈值取决于 H/W，而在 Crosato 和 Mosselman (2009) 和 van den Berg (1995) 中，它与 H/W 无关，这隐含地假设 H/W 是已知的。这在已知 H/W 的现代河流中不是问题，但在 W 难以测量的地质应用中却是个问题。对于地质应用，Parker (1976) 预测器在分析上是最合适的，因为它需要最少的假设，其阈值取决于 H/W（表 1）。然而，Parker (1976) 预测器偏爱单线程平面图。因此，我们用我们的新数据集测试了这个预测器。在我们的数据集中，Parker (1976) 预测器在 93% 的单线河流中正确预测了平面形态，但仅在 35% 的多线河流中正确预测了平面形态（图 3A），因此现有的 Parker (1976) 校准需要改进。值得注意的是，对于单线和多线河流，我们的数据显示 H/W 分布在统计上是不同的，而 S/Fr 分布具有相似的中位数和四分位间距。因此，一个简单的 H/W 阈值可以有效地区分单线程（H/W > 0.02）和多线程（H/W < 0.02）河流（图 3A）。该阈值正确预测了 82% 的单线河流（H/W > 0.014 预测的 90%）和 84% 的多线河流（H/W <0.027 预测的 90%）的平面形态（图 3A）。 Parker (1976) 预测器不区分编织和吻合样式，但我们的数据集启用了这种预测。我们发现辫状河流和吻合河流具有相似的 H/W 中值，但 S/Fr 分布不同（图 3B）。在辫状河流中，S/Fr 跨度约为 0.001-0.1，而在吻合河流中，S/Fr 跨度约为 0.0001-0.001（图 3B）。在过渡河流中，~0.001-0.01 的 S/Fr 值与辫状和吻合的河流重叠，因为这些数据跨越了蜿蜒的辫状和曲折的吻合过渡。我们发现一个简单的阈值可以区分辫状（S/Fr > 0.003）和吻合（S/Fr < 0.003）河流，正确预测了 84% 的辫状河流的平面形态（90% 由 S/Fr >0.002 预测）和85% 的吻合河流（90% 由 S/Fr <0.0034 预测）（图 3B）。将这些阈值一起使用（即，H/W < 0.02 和 S/Fr <0.003 用于吻合河流，H/W < 0。02 和 S/Fr > 0.003（辫状河），H/W > 0.02（单线河），我们在我们的数据中正确预测了 70% 的吻合河流、65% 的辫状河和 82% 的单线河将这些标准应用于我们的地质数据，Ferron 河流绘制为单线通道（图 3 中的三角形），与相解释一致（Cotter，1971；Wu 等，2015），而 Blackhawk 和 Castlegate 河流绘制为吻合河道（图 3B 中的正方形和粗体空心圆），这与将这些多线河流解释为辫状的解释不一致，但与它们的特征是沙床、浅坡、高悬浮沉积物负荷和撕脱倾向一致（例如, Miall, 1993, 1994; Chamberlin and Hajek, 2019; Lyster et al., 2021)，具有典型的吻合河流特征。更远，假设 Wmin，Blackhawk 通道绘制在单线程过渡上，与单线程 Blackhawk 通道的解释一致（Hampson 等人，2013）。对于我们的地质示例，我们表明现有的平面预测变量彼​​此不一致，并且与相解释. 虽然 Parker (1976) 方法是最合适的古平面图预测器，但它偏爱单线平面图（图 2A-2D），并且在我们的数据集中错误地分类了三分之二的多线河流（图 3A）。我们注意到基于理论的预测器，例如 Parker (1976) 预测器，通常假设具有矩形横截面和不可侵蚀堤岸的直通道。因此，它们可能无法捕捉到天然河流的广泛变异性，从而最大限度地减少了超出该几何形状的因素的潜在重要性。而且，用于验证 Parker (1976) 预测器的原始数据集很小，并且严重依赖于实验和人造渠道。在我们的新数据集中，H/W 是平面形态最重要的判别器，而不是 S/Fr，单线河流中 H/W > 0.02，多线河流中 H/W <0.02（图 3A）。我们假设 H/W 和平面图之间的明显联系可能表明银行凝聚力是平面图的关键决定因素（Ielpi 和 Lapôtre，2019b；Lapôtre 等，2019；Dunne 和 Jerolmack，2020；Ielpi 和 Lapôtre，2020）与河道坡度相反。此外，虽然我们的数据显示 S/Fr 不能区分单线和多线河流，但 S/Fr 可以区分多线平面样式。在多线程河流中，新线程可能有多个来源，包括吻合河流的撕脱和辫状河流的分叉（Jerolmack 和 Mohrig，2007；Kleinhans 等，2013；Carling 等，2014）。我们的数据表明，S/Fr 可能捕捉到一个过程过渡，当 S/Fr < 0.003（较浅的斜坡）时，多线河流可能是吻合的，而当 S/Fr > 0.003（较陡的斜坡）时，多线河流可能是编织的（图 3B）。这些阈值很容易应用于可以重建古斜坡的地质数据（例如，Trampush 等人，2014 年），并且它们更适合对多线河流的现代和地层观测。虽然从地质露头对 H 的估计是稳健的（例如，Lyster 等人，2021），估计 W 仍然很困难，因为它需要保留通道架构和/或通道填充（Toonen 等人，2012；Ielpi 和 Ghinassi，2014）和活动线程数的知识。因此，古平面预测仍然受到 H/W 不确定性的限制，我们建议我们的标准应该在一系列合理的宽度范围内实施。此外，虽然我们的标准解决了相解释和平面预测变量之间的不一致，但将这些方法结合起来很重要。对于 Blackhawk 和 Castlegate 河道，重建的平面图大致相似（图 2），但它们的地层结构不同。因此，理解运动学和地层学控制对平面地质保存的控制，而不是它们的地貌等价物，现在是一项紧迫的研究需要。在可以从河流地层重建水力几何形状的地方，我们的新标准提供了一种简单有效的预测方法古平面图。鉴于正在进行的关于岩石记录中平面图保存潜力有限的讨论（Fielding 等人，2018 年；Best 和 Fielding，2019 年），这些结果非常重要，并且在露头有限或相解释模棱两可的情况下，它们特别有用，例如早期地球和火星的无植被河流系统。我们的标准将提高河流地层的水、沉积物和生物地球化学通量重建的保真度，这对于破译河流对构造和气候强迫的响应至关重要（例如，Lyster 等人，2021），它们将为河道提供新的见解-形成过程和渠道稳定性。总之，这些限制将有助于构建更完整的地质历史河流景观演变图景。这项工作得到了英国自然环境研究委员会的支持，