Enhancing a GIS Cellular Automata Model of Land Use Change: Bayesian Networks, Influence Diagrams and Causality

Cellular Automata (CA) models at present do not adequately take into account the relationship and interactions between variables. However, land use change is influenced by multiple variables and their relationships. The objective of this study is to develop a novel CA model within a geographic information system (GIS) that consists of Bayesian Network (BN) and Influence Diagram (ID) sub‐models. Further, the proposed model is intended to simplify the definition of parameter values, transition rules and model structure. Multiple GIS layers provide inputs and the CA defines the transition rules by running the two sub‐models. In the BN sub‐model, land use drivers are encoded with conditional probabilities extracted from historical data to represent inter‐dependencies between the drivers. Using the ID sub‐model, the decision of changing from one land use state to another is made based on utility theory. The model was applied to simulate future land use changes in the Greater Vancouver Regional District (GVRD), Canada from 2001 to 2031. The results indicate that the model is able to detect spatio‐temporal drivers and generate various scenarios of land use change making it a useful tool for exploring complex planning scenarios.     

多辐射源地空瞬变电磁响应三维数值模拟研究

地空瞬变电磁法结合地面和航空电磁法的优点,可实现探测深度和工作效率的平衡.当前地空瞬变电磁法采用单一线源激发电磁辐射场,仅能从一个侧面与地质体耦合,难以获得地质体的全息影像.采用多辐射源是解决这一问题的途径.本文采用三维矢量有限元法对两个不同地质体多个辐射源情况下的地空瞬变电磁响应开展了模拟研究,分析了多辐射源在不同辐射方向、不同飞行高度电磁响应的分布特征.研究表明,由多辐射场源作为地空电磁法的发射源,通过分散布设的线源,可以在地下激发与地质体多方位耦合的电磁场,能够获得地下地质体多方位不同高度情况下的耦合信息.同时,多辐射场源能够增强源电磁场的辐射强度,减少单一线源体积效应影响,飞行高度较低时可获得较强的响应幅值,研究结果为多辐射地空瞬变电磁法深部精细探测提供理论依据.

     

A method for using a fully coupled climate system model to generate detailed surface boundary conditions for paleoclimate modeling investigations: an early Paleogene example

Although fully coupled models of the earth system are now common, simpler model architectures maintain significant utility, and scientific investigations aimed at understanding paleoclimates are frequently conducted with fixed sea surface temperature (SST) or slab ocean modeling experiments. One of the challenges facing the paleoclimate community is that the proxy data used to generate SST boundary conditions exist at a finer resolution and with very limited spatial coverage when compared to a climate model. In addition, SST proxy estimates often represent a single season or annual average conditions. This mismatch in coverage and resolution frequently results in paleoclimate modelers using SST distributions that have very limited spatial and temporal variability. In many regions, a spatially and temporally detailed SST distribution may be necessary for the accurate reproduction of paleoclimatic conditions. Here we borrow from the concept of flux correction and, using available proxy estimates of SST as our guide, force a fully coupled earth system model to produce a spatially and temporally detailed SST distribution for the paleoclimate of the early Paleogene (45–65 Ma). The SST values we produce represent a conservative estimate of early Paleogene high latitude SSTs and match tropical temperatures for this time period well. In addition to matching proxy estimates, our model-derived SST distribution has spatial and temporal variability that meshes well with global climate model resolution. This detailed SST distribution is now available to us as we investigate the causes and sensitivities of early Paleogene climate in fixed SST and slab ocean modeling experiments. The method we used to generate this spatially and temporally detailed SST distribution may prove useful for those investigating other time periods in the past, or the future, for which detailed model boundary conditions are unavailable.     

Spatial analysis of the invasion of lionfish in the western Atlantic and Caribbean

Pterois volitans and Pterois miles, two sub-species of lionfish, have become the first non-native, invasive marine fish established along the United States Atlantic coast and Caribbean. The route and timing of the invasion is poorly understood, however historical sightings and captures have been robustly documented since their introduction. Herein we analyze these records based on spatial location, dates of arrival, and prevailing physical factors at the capture sights. Using a cellular automata model, we examine the relationship between depth, salinity, temperature, and current, finding the latter as the most influential parameter for transport of lionfish to new areas. The model output is a synthetic validated reproduction of the lionfish invasion, upon which predictive simulations in other locations can be based. This predictive model is simple, highly adaptable, relies entirely on publicly available data, and is applicable to other species.     

A New Modification to the Chemical Mass Balance Receptor Model for Volatile Organic Compound Source Apportionment

In this study, a modification to the chemical mass balance (CMB) receptor model presented in an earlier work was expanded to account for the changes in volatile organic compound (VOC) source fingerprints due to atmospheric reactions of VOCs that take place after being emitted to the atmosphere. The photochemical reactions consume VOCs that participate in, causing changes in the source fingerprints. These changes are of considerable magnitude when the travel durations from the source to the receptor (measurement point) are considered. The current study focuses on expansion of the integrated reaction rates of VOCs with ambient reactive species such as OH ^? , O₃, NO₃, and O ^? in order to estimate the source emission profiles simultaneously at the receptor site. Two test cases with different travel times and with different ambient OH ^? , O₃, and NO₃ concentrations were also provided to compare the standard model, the modified model suggested in the previous work, and the current modification. F‐tests were also performed to determine whether the changes in source compositions are significant or not. The results from both the standard model and the modified model were evaluated in terms of χ², R², percent mass apportioned (MA), and a best fit (BF) measure. Maximum values of BF for the test cases from the three models were 0.70 ± 0.03, 0.74 ± 0.05, and 1.000 ± 0.00, respectively, indicating that the current modification increases the performance of two previous models and was better in explaining the effects of chemical reactions of VOCs.     

Structure and Dynamics of Katabatic Flow Jumps: Idealised Simulations

For the first time, results from a high-resolution numerical simulation (with horizontal grid spacing of 35m) were used to reveal the detailed structure near an atmospheric katabatic jump over an idealized slope. The simulation represents flow over the slopes of Coats Land, Antarctica for austral winter conditions. The katabatic jump is characterised by an updraft with vertical velocities of order 1ms⁻¹ and serves as a possible forcing mechanism for the gravity waves frequently observed over the ice shelves around the Antarctic. Results also indicate that strong turbulence is generally confined within a mixing zone near the top of the katabatic layer upstream of the jump and extends downstream through the top of the strong updraft associated with the jump. Detailed analyses of momentum and heat budgets across the katabatic jump indicate that, upstream of the jump, turbulent mixing is important in decelerating the upper part of the katabatic layer, while within the jump the upslope pressure gradient force associated with the pool of cold air plays a role in decelerating the flow near the surface. The heat budget near the jump reveals a simple two-term balance: the turbulent heat flux divergence is balanced by the advection. A comparison of model results with available theories indicates that mixing between layers of different potential temperature structure indeed plays some role in the development of katabatic flow jumps, especially for strong jumps. Theories used to study katabatic jumps should include this mixing process, of which the amount depends on the intensity of the jump. A conceptual model of a katabatic jump, including the main dynamical processes, is constructed from these detailed analyses.     

Modeling scale-dependent runoff generation in a small semi-arid watershed accounting for rainfall intensity and water depth

Observed scale effects of runoff on hillslopes and small watersheds derive from complex interactions of time-varying rainfall rates with runoff, infiltration and macro- and microtopographic structures. A little studied aspect of scale effects is the concept of water depth-dependent infiltration. For semi-arid rangeland it has been demonstrated that mounds underneath shrubs have a high infiltrability and lower lying compacted or stony inter-shrub areas have a lower infiltrability. It is hypothesized that runoff accumulation further downslope leads to increased water depth, inundating high infiltrability areas, which increases the area-averaged infiltration rate. A model was developed that combines the concepts of water depth-dependent infiltration, partial contributing area under variable rainfall intensity, and the Green–Ampt theory for point-scale infiltration. The model was applied to rainfall simulation data and natural rainfall–runoff data from a small sub-watershed (0.4 ha) of the Walnut Gulch Experimental Watershed in the semi-arid US Southwest. Its performance to reproduce observed hydrographs was compared to that of a conventional Green–Ampt model assuming complete inundation sheet flow, with runon infiltration, which is infiltration of runoff onto pervious downstream areas. Parameters were derived from rainfall simulations and from watershed-scale calibration directly from the rainfall–runoff events. The performance of the water depth-dependent model was better than that of the conventional model on the scale of a rainfall simulator plot, but on the scale of a small watershed the performance of both model types was similar. We believe that the proposed model contributes to a less scale-dependent way of modeling runoff and erosion on the hillslope-scale.