Land-Surface Parameters for Spatial Predictive Mapping and Modeling

Land-surface parameters derived from digital land surface models (DLSMs) (for example, slope, surface curvature, topographic position, topographic roughness, aspect, heat load index, and topographic moisture index) can serve as key predictor variables in a wide variety of mapping and modeling tasks relating to geomorphic processes, landform delineation, ecological and habitat characterization, and geohazard, soil, wetland, and general thematic mapping and modeling. However, selecting features from the large number of potential derivatives that may be predictive for a specific feature or process can be complicated, and existing literature may offer contradictory or incomplete guidance. The availability of multiple data sources and the need to define moving window shapes, sizes, and cell weightings further complicate selecting and optimizing the feature space. This review focuses on the calculation and use of DLSM parameters for empirical spatial predictive modeling applications, which rely on training data and explanatory variables to make predictions of landscape features and processes over a defined geographic extent. The target audience for this review is researchers and analysts undertaking predictive modeling tasks that make use of the most widely used terrain variables. To outline best practices and highlight future research needs, we review a range of land-surface parameters relating to steepness, local relief, rugosity, slope orientation, solar insolation, and moisture and characterize their relationship to geomorphic processes. We then discuss important considerations when selecting such parameters for predictive mapping and modeling tasks to assist analysts in answering two critical questions: What landscape conditions or processes does a given measure characterize? How might a particular metric relate to the phenomenon or features being mapped, modeled, or studied? We recommend the use of landscape- and problem-specific pilot studies to answer, to the extent possible, these questions for potential features of interest in a mapping or modeling task. We describe existing techniques to reduce the size of the feature space using feature selection and feature reduction methods, assess the importance or contribution of specific metrics, and parameterize moving windows or characterize the landscape at varying scales using alternative methods while highlighting strengths, drawbacks, and knowledge gaps for specific techniques. Recent developments, such as explainable machine learning and convolutional neural network (CNN)-based deep learning, may guide and/or minimize the need for feature space engineering and ease the use of DLSMs in predictive modeling tasks

An Experimental Study of Auctions Versus Grandfathering to Assign Pollution Permits

We experimentally study auctions versus grandfathering in the initial assignment of pollution permits that can be traded in a secondary spot market. Low and high emitters compete for permits in the auction, while permits are assigned for free under grandfathering. In theory, trading in the spot market should erase inefficiencies due to initial mis-allocations. In the experiment, high emitters exercise market power in the spot market and permit holdings under grandfathering remain skewed towards high emitters. Furthermore, the opportunity costs of “free” permits are fully “passed through.” In the auction, the majority of permits are won by low emitters, reducing the need for spot-market trading. Auctions generate higher consumer surplus and slightly lower product prices in the laboratory arkets. Moreover, auctions eliminate the large “windfall profits” that are observed in the treatment with free, grandfathered permit allocations.market-based regulation, emissions trading, allocation, auctions, grandfathering, climate policy, windfall profits

River Erosion In Block-Controlled Landscapes

Rivers are the backbone of the landscape. The efficiency of fluvial bedrock erosion and sediment transport sets the longevity of high topography, and represents the boundary conditions experienced by the rest of the landscape. The rate at which rivers respond to tectonic, climatic, and anthropogenic perturbations governs the extent to which those events are recorded in remnant topography and the stratigraphic record. The past two decades have seen substantial progress on quantifying and understanding river incision processes and what controls them, including the effects of realistic hydrology, sediment flux, and rock strength. In addition, some progress has been made on understanding the effects of sediment grain size on river erosion. However, much work remains to be done on how sediment dynamics govern fluvial incision. In particular, despite a long tradition of speculation based on qualitative field observations, there has been very little work on how rivers react to the delivery of very large (&gt; 1 m) sediment grains, and how large grains modulate the long-term dynamics of river and landscape evolution. In this thesis I present five studies with the goal of understanding how sediment size and sediment flux interact to influence river incision and long-term landscape change. In Chapter 1, I briefly lay out previous work exploring links among sediment flux, sediment size, river erosion and landscape evolution outcomes. Chapter 2 lays out a conceptual and numerical model for how large sediment grains, "blocks" of rock delivered from hillslopes to channels, alter river channel form and change how baselevel perturbations are transmitted along channel profiles. The model is compared with observations from Boulder Creek, Colorado. I extend this work in Chapter 3 to explore how the distribution of river discharge interacts with the presence of hillslope-derived blocks to set steady-state scaling between erosion rate and river channel steepness. I develop a simplified framework to account for the role of blocks and compare its predictions against measured erosion rate-channel steepness relationships. In Chapter 4, I couple the numerical model for block-influenced river erosion with a previously published model for block-influenced hillslopes, and show that block transport feedbacks between channels and hillslopes can explain observations of river canyon morphology in layered rock landscapes. I further show that these feedbacks play an important role in modulating baselevel perturbations as they travel through block-influenced landscapes. I use a well-constrained field site in Chapter 5 to evaluate whether lithologically controlled channel steepening could be caused by boulder delivery to channels occurring in one lithology but not in others, and suggest that boulder delivery may be a mechanism by which lithology leaves its mark on landscapes. In Chapter 6 I develop a new numerical model to simulate erosion in bedrock-alluvial rivers, which until recently have been oversimplified in models of landscape evolution. I conclude by pointing out future research directions related to sediment size, river incision, and topographic change at Earth's surface.</p

The Art of Landslides: How Stochastic Mass Wasting Shapes Topography and Influences Landscape Dynamics

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

An Experimental Analysis of Auctioning Emissions Allowances under a Loose Cap

The direct sale of emissions allowances by auction is an emerging characteristic of cap-and-trade programs. This study is motivated by the observation that all of the major implementations of cap-and-trade regulations for the control of air pollution have started with a generous allocation of allowances relative to recent emissions history, a situation we refer to as a “loose cap.” Typically more stringent reductions are achieved in subsequent years of a program. We use an experimental setting to investigate the effects of a loose cap environment on a variety of auction types. We find all auction formats studied are efficient in allocating emissions allowances, but auction revenues tend to be lower relative to competitive benchmarks when the cap is loose. Regardless of whether the cap is tight or loose, the different auction formats tend to yield comparable revenues toward the end of a series of auctions. However, aggressive bidding behavior in initial discriminatory auctions yields higher revenues than in other auction formats, a difference that disappears as bidders learn to adjust their bids closer to the cutoff that separates winning and losing bids.auction, carbon dioxide, greenhouse gases, allowance trading, Regional Greenhouse Gas Initiative, RGGI, cap and trade

Price Discovery in Emissions Permit Auctions

Auctions are increasingly being used to allocate emissions allowances (“permitsâ€) for cap and trade and common-pool resource management programs. These auctions create thick markets that can provide important information about changes in current market conditions. This paper reports a laboratory experiment in which half of the bidders experienced unannounced increases in their willingness to pay for permits. The focus is on the extent to which the predicted price increase due to the demand shift is reflected in sales prices under alternative auction formats. Price tracking is comparably good for uniform-price sealed-bid auctions and for multi-round clock auctions, with or without end-of-round information about excess demand. More price inertia is observed for “pay as bid†(discriminatory) auctions, especially for a continuous discriminatory format in which bids could be changed at will during a pre-specified time window, in part because “sniping†in the final moments blocked the full effect of the demand shock.auction, greenhouse gases, price discovery, cap and trade, emission allowances, laboratory experiment

Collusion in Auctions for Emission Permits: An Experimental Analysis

Environmental markets have several institutional features that provide a new context for the use of auctions and which have not been studied previously. This paper reports on laboratory experiments testing three auction forms -– uniform and discriminatory price sealed bid auctions and an ascending clock auction. We test the ability of subjects to tacitly or explicitly collude in order to maximize profits. Our main result is that the discriminatory and uniform price auctions produce greater revenues than the clock auction, both without and with explicit communication. The clock appears to be more subject to successful collusion because of its sequential structure and because it allows bidders to focus on one dimension of cooperation (quantity) rather than two (price and quantity).auctions, collusion, experiments, carbon dioxide, greenhouse gases

An Experimental Analysis of Auctioning Emission Allowances Under a Loose Cap

The direct sale of emission allowances by auction is an emerging characteristic of cap-and-trade programs. This study is motivated by the observation that all of the major implementations of cap-and-trade regulations for the control of air pollution have started with a generous allocation of allowances relative to recent emissions history, a situation we refer to as a “loose cap.†Typically more stringent reductions are achieved in subsequent years of a program. We use an experimental setting to investigate the effects of a loose cap environment on a variety of auction types. We find that all auction formats studied are efficient in allocating emission allowances, but auction revenues tend to be lower relative to competitive benchmarks when the cap is loose. Regardless of whether the cap is tight or loose, the different auction formats tend to yield comparable revenues toward the end of a series of auctions. However, aggressive bidding behavior in initial discriminatory auctions yields higher revenues than in the other auction formats, a difference that disappears as bidders learn to adjust their bids closer to the cut-off that separates winning and losing bids.auction, carbon dioxide, greenhouse gases, allowance trading, Regional Greenhouse Gas Initiative, RGGI, cap and trade, Environmental Economics and Policy, Resource /Energy Economics and Policy,

Thickness of Fluvial Deposits Records Climate Oscillations

Fluvial deposits offer Earth’s best-preserved geomorphic record of past climate change over geological timescales. However, quantitatively extracting this information remains challenging in part due to the complexity of erosion, sediment transport and deposition processes and how each of them responds to climate. Furthermore, sedimentary basins have the potential to temporarily store sediments, and rivers subsequently rework those sediments. This may introduce time lags into sedimentary signals and obscure any direct correlation with climate forcing. Here, using a numerical model that combines all three processes—and a new analytical solution—we show that the thickness of fluvial deposits at the outlet of a mountain river can be linked to the amplitude and period of rainfall oscillations but is modulated by the mountain uplift rate. For typical uplift rates of a few mm/yr, climate oscillations at Milankovitch periods lead to alluvial sediment thickness of tens of meters as observed in nature. We also explain the time lag of the order of 20%–25% of the forcing period that is commonly observed between the timing of maximum rainfall and erosion. By comparing to field datasets, our predictions for the thickness and time lag of fluvial deposits are broadly consistent with observations despite the simplicity of our modeling approach. These findings provide a new theoretical framework for quantitatively extracting information on past rainfall variations from fluvial deposits