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Abstract. Progress in better understanding and modeling Earth surface systems requires an ongoing integration of data and numerical models. Advances are currently hampered by technical barriers that inhibit finding, accessing, and executing modeling software with related datasets. We propose a design framework for Data Components, which are software packages that provide access to particular research datasets or types of data. Because they use a standard interface based on the Basic Model Interface (BMI), Data Components can function as plug-and-play components within modeling frameworks to facilitate seamless data–model integration. To illustrate the design and potential applications of Data Components and their advantages, we present several case studies in Earth surface processes analysis and modeling. The results demonstrate that the Data Component design provides a consistent and efficient way to access heterogeneous datasets from multiple sources and to seamlessly integrate them with various models. This design supports the creation of open data–model integration workflows that can be discovered, accessed, and reproduced through online data sharing platforms, which promotes data reuse and improves research transparency and reproducibility.

 

Hillslope topographic change in response to climate and climate change is a key aspect of landscape evolution. The impact of short‐duration rainstorms on hillslope evolution in arid regions is persistently questioned but often not directly examined in landscape evolution studies, which are commonly based on mean climate proxies. This study focuses on hillslope surface processes responding to rainstorms in the driest regions of Earth. We present a numerical model for arid, rocky hillslopes with lithology of a softer rock layer capped by a cliff‐forming resistant layer. By representing the combined action of bedrock and clast weathering, cliff‐debris ravel, and runoff‐driven erosion, the model can reproduce commonly observed cliff‐profile morphology. Numerical experiments with a fixed base level were used to test hillslope response to cliff‐debris grain size, rainstorm intensities, and alternation between rainstorm patterns. The persistence of vertical cliffs and the pattern of sediment sorting depend on rainstorm intensities and the size of cliff debris. Numerical experiments confirm that these two variables could have driven the landscape in the Negev Desert (Israel) toward an observed spatial contrast in topographic form over the past 10⁵–10⁶ years. For a given total storm rain depth, short‐duration higher‐intensity rainstorms are more erosive, resulting in greater cliff retreat distances relative to longer, low‐intensity storms. Temporal alternation between rainstorm regimes produces hillslope profiles similar to those previously attributed to Quaternary oscillations in the mean climate. We suggest that arid hillslopes may undergo considerable geomorphic transitions solely by alternating intra‐storm patterns regardless of rainfall amounts.

 

Abstract. Computational modeling occupies a unique niche in Earth and environmental sciences. Models serve not just as scientific technology and infrastructure but also as digital containers of the scientific community's understanding of the natural world. As this understanding improves, so too must the associated software. This dual nature – models as both infrastructure and hypotheses – means that modeling software must be designed to evolve continually as geoscientific knowledge itself evolves. Here we describe design principles, protocols, and tools developed by the Community Surface Dynamics Modeling System (CSDMS) to promote a flexible, interoperable, and ever-improving research software ecosystem. These include a community repository for model sharing and metadata, interface and ontology standards for model interoperability, language-bridging tools, a modular programming library for model construction, modular software components for data access, and a Python-based execution and model-coupling framework. Methods of community support and engagement that help create a community-centered software ecosystem are also discussed. 

Bedrock landslides shape topography and mobilize large volumes of sediment. Yet, interactions between landslide‐produced sediment and fluvial systems that together govern large‐scale landscape evolution are not well understood. To explain morphological patterns observed in steep, landslide‐prone terrain, we explicitly model stochastic landsliding and associated sediment dynamics. The model accounts for several common landscape features such as slope frequency distributions, which include values in excess of regional stability limits, quasi‐planar hillslopes decorated with straight, closely spaced channel‐like features, and accumulation of sediment in valley networks rather than on hillslopes. Stochastic landsliding strongly affects the magnitude and timing of sediment supply to the fluvial system. We show that intermittent sediment supply is ultimately reflected in topography. At dynamic equilibrium, landslide‐derived sediment pulses generate persistent landscape dynamism through the formation and breaching of landslide dams and epigenetic gorges as landslides force shifts in channel positions. Our work highlights the importance of interactions between landslides and sediment dynamics that ultimately control landscape‐scale response to environmental change.

 

Cosmogenic nuclide analysis of river sediment provides insight into catchment‐wide erosion rates and dynamics. Here, we investigate spatial patterns and controls on¹⁰Be‐inferred erosion rates in Madagascar, a moderately seismically active microcontinent surrounded by passive margins with locally steep topography and a climate that varies from humid tropical to semiarid. We use a compiled dataset of 99 detrital¹⁰Be measurements, 63 of which are new, covering more than 30% of the country and a wide range of topographic, bioclimatic and geologic characteristics. Overall,¹⁰Be erosion rates are low (2.4–51.1 mm kyr⁻¹), with clear differences between regions. The lowest rates are measured on the central highlands ( 8 mm kyr⁻¹), in the Alaotra–Ankay graben ( 11 mm kyr⁻¹) and in the large north‐central catchments ( 11 mm kyr⁻¹). Higher rates are found on the steep eastern escarpment ( 20 mm kyr⁻¹), in the northwest ( 31 mm kyr⁻¹) and in the southwest ( 29 mm kyr⁻¹). A stepwise linear regression model identified elevation as the main factor associated with variations in¹⁰Be erosion rates (lower rates for higher catchments). Random within‐between statistical models (REWB), on the other hand, indicated that the differences between different regions can be explained by differences in river concavity, seismic events and gully (lavaka) densities, whereas additional variation within regions is only linked to seismicity. We find no correlation between catchment or river steepness and¹⁰Be‐inferred erosion rates. Our results indicate that in Madagascar, long‐term erosion rates are overall low and that simple topography‐based models do not explain variations in rates of landscape change inferred from¹⁰Be concentrations in river sediment. We demonstrate that identifying different regions aids in interpreting spatial patterns of erosion rates and that REWB models can be a powerful tool in deciphering environmental controls on¹⁰Be erosion rates.

 

Abstract. Landslides are the main source of sediment in most mountain ranges. Rivers then act as conveyor belts, evacuating landslide-derived sediment. Sediment dynamics are known to influence landscape evolution through interactions among landslide sediment delivery, fluvial transport and river incision into bedrock. Sediment delivery and its interaction with river incision therefore control the pace of landscape evolution and mediate relationships among tectonics, climate and erosion. Numerical landscape evolution models (LEMs) are well suited to study the interactions among these surface processes. They enable evaluation of a range of hypotheses at varying temporal and spatial scales. While many models have been used to study the dynamic interplay between tectonics, erosion and climate, the role of interactions between landslide-derived sediment and river incision has received much less attention. Here, we present HyLands, a hybrid landscape evolution model integrated within the TopoToolbox Landscape Evolution Model (TTLEM) framework. The hybrid nature of the model lies in its capacity to simulate both erosion and deposition at any place in the landscape due to fluvial bedrock incision, sediment transport, and rapid, stochastic mass wasting through landsliding. Fluvial sediment transport and bedrock incision are calculated using the recently developed Stream Power with Alluvium Conservation and Entrainment (SPACE) model. Therefore, rivers can dynamically transition from detachment-limited to transport-limited and from bedrock to bedrock–alluvial to fully alluviated states. Erosion and sediment production by landsliding are calculated using a Mohr–Coulomb stability analysis, while landslide-derived sediment is routed and deposited using a multiple-flow-direction, nonlinear deposition method. We describe and evaluate the HyLands 1.0 model using analytical solutions and observations. We first illustrate the functionality of HyLands to capture river dynamics ranging from detachment-limited to transport-limited conditions. Second, we apply the model to a portion of the Namche Barwa massif in eastern Tibet and compare simulated and observed landslide magnitude–frequency and area–volume scaling relationships. Finally, we illustrate the relevance of explicitly simulating landsliding and sediment dynamics over longer timescales for landscape evolution in general and river dynamics in particular. With HyLands we provide a new tool to understand both the long- and short-term coupling between stochastic hillslope processes, river incision and source-to-sink sediment dynamics.