Integration of spatio-temporal vegetation dynamics into a distributed ecohydrological model: application to optimality theory and real-time watershed simulations

Spatio-temporal vegetation dynamics are important drivers to characterize seasonal to annual water and carbon budgets. Spatial adjustment and evolution of the ecosystem is closely related to the geomorphic, climatic, and hydrologic settings. In particular, lateral hydrologic redistribution along flowpaths control the long-term joint adjustments of vegetation and soil over successional and quasi-geological time scales. For this reason, it is complex and challenging to incorporate the many relevant processes and feedbacks between ecological and hydrological systems for the full simulation of water, carbon, and nutrient cycling. Recent developments in remote sensing technology provide the potential to link dynamic canopy measurements with integrated process descriptions within distributed ecohydrological modeling frameworks. In this dissertation, three research studies are presented concerning estimation of spatio-temporal vegetation dynamics in application into a distributed ecohydrological model at the Coweeta Long Term Ecological Research site. In Chapter 2, we test whether the simulated spatial pattern of vegetation corresponds to measured canopy patterns and an optimal state relative to a set of ecosystem processes, defined as maximizing ecosystem productivity and water use efficiency at the catchment scale. A distributed ecohydrological model is simulated at a small catchment scale with various field measurements to see if the evolved pattern of vegetation density along the flowpaths leads to system-wide emergent optimality for carbon uptake over and above the individual patch. Lateral hydrological connectivity determines the degree of dependency on productivity and resource use with other patches along flowpaths, resulting in different system-wide carbon and water uptake by vegetation. In Chapter 3, phenological signals are extracted from global satellite products to find the topography-mediated controls on vegetation phenology in the study site. It provides a basis to understand spatial variations of local vegetation phenology as a function of microclimate, vegetation community types, and hillslope positions. In Chapter 4, near real-time vegetation dynamics are estimated by fusing multi-temporal satellite images, and integrated into the catchment scale distributed ecohydrological simulation. Integration of spatio-temporal vegetation dynamics into a distributed ecohydrological model helps to simulate ecohydrological feedbacks between vegetation patterns and lateral hydrological redistribution by reducing uncertainty related to state and flux variables

Ecosystem processes at the watershed scale: Extending optimality theory from plot to catchment

The adjustment of local vegetation conditions to limiting soil water by either maximizing productivity or minimizing water stress has been an area of central interest in ecohydrology since Eagleson's classic study. This work has typically been limited to consider one-dimensional exchange and cycling within patches and has not incorporated the effects of lateral redistribution of soil moisture, coupled ecosystem carbon and nitrogen cycling, and vegetation allocation processes along topographic gradients. We extend this theory to the hillslope and catchment scale, with in situ and downslope feedbacks between water, carbon and nutrient cycling within a fully transient, distributed model. We explore whether ecosystem patches linked along hydrologic flow paths as a catena evolve to form an emergent pattern optimized to local climate and topographic conditions. Lateral hydrologic connectivity of a small catchment is calibrated with streamflow data and further tested with measured soil moisture patterns. Then, the spatial gradient of vegetation density within a small catchment estimated with fine-resolution satellite imagery and field measurements is evaluated with simulated vegetation growth patterns from different root depth and allocation strategies as a function of hillslope position. This is also supported by the correspondence of modeled and field measured spatial patterns of root depths and catchment-level aboveground vegetation productivity. We test whether the simulated spatial pattern of vegetation corresponds to measured canopy patterns and an optimal state relative to a set of ecosystem processes, defined as maximizing ecosystem productivity and water use efficiency at the catchment scale. Optimal carbon uptake ranges show effective compromises between multiple resources (water, light, and nutrients), modulated by vegetation allocation dynamics along hillslope gradient

Ecosystem processes at the watershed scale: extending optimality theory from plot to catchment

[1] The adjustment of local vegetation conditions to limiting soil water by either maximizing productivity or minimizing water stress has been an area of central interest in ecohydrology since Eagleson's classic study. This work has typically been limited to consider one-dimensional exchange and cycling within patches and has not incorporated the effects of lateral redistribution of soil moisture, coupled ecosystem carbon and nitrogen cycling, and vegetation allocation processes along topographic gradients. We extend this theory to the hillslope and catchment scale, with in situ and downslope feedbacks between water, carbon and nutrient cycling within a fully transient, distributed model. We explore whether ecosystem patches linked along hydrologic flow paths as a catena evolve to form an emergent pattern optimized to local climate and topographic conditions. Lateral hydrologic connectivity of a small catchment is calibrated with streamflow data and further tested with measured soil moisture patterns. Then, the spatial gradient of vegetation density within a small catchment estimated with fine-resolution satellite imagery and field measurements is evaluated with simulated vegetation growth patterns from different root depth and allocation strategies as a function of hillslope position. This is also supported by the correspondence of modeled and field measured spatial patterns of root depths and catchmentlevel aboveground vegetation productivity. We test whether the simulated spatial pattern of vegetation corresponds to measured canopy patterns and an optimal state relative to a set of ecosystem processes, defined as maximizing ecosystem productivity and water use efficiency at the catchment scale. Optimal carbon uptake ranges show effective compromises between multiple resources (water, light, and nutrients), modulated by vegetation allocation dynamics along hillslope gradient. Citation: Hwang, T., L. Band, and T. C. Hales (2009), Ecosystem processes at the watershed scale: Extending optimality theory from plot to catchment, Water Resour. Res., 45, W11425

Seasonal variation of source contributions to eddy-covariance CO 2 measurements in a mixed hardwood-conifer forest

Net ecosystem exchange (NEE) measurements using the eddy covariance technique have been widely used for calibration and evaluation of carbon flux estimates from terrestrial ecosystem models as well as for remote sensing-based estimates across various spatial and temporal scales. Therefore, it is vital to fully understand the land surface characteristics within the area contributing to these flux measurements (i.e. source area) when upscaling plot-scale tower measurements to regional-scale ecosystem estimates, especially in heterogeneous landscapes, such as mixed forests. We estimated the source area of a flux tower at a mixed forest (Harvard Forest in US) using a footprint model, and analyzed the spatial representativeness of the source area for the vegetation characteristics (density variation and magnitude) within the surrounding 1- and 1.5-km grid cells during two decades (1993–2011). Semi-variogram and window size analyses using 19 years of Landsat-retrieved enhanced vegetation index (EVI) confirmed that spatial heterogeneity within the 1-km grid cell has been gradually increasing for leaf-on periods. The overall prevailing source areas lay toward the southwest, yet there were considerable variations in the extents and the directions of the source areas. The source areas generally cover a large enough area to adequately represent the vegetation density magnitude and variation during both daytime and nighttime. We show that the variation in the daytime NEE during peak growing season should be more attributed to variations in the deciduous forest contribution within the source areas rather than the vegetation density. This study highlights the importance of taking account of the land cover variation within the source areas into gap-filling and upscaling procedures

Characteristics of Spatiotemporal Changes in the Occurrence of Forest Fires

The purpose of this study is to understand the characteristics of the spatial distribution of forest fire occurrences with the local indicators of temporal burstiness in Korea. Forest fire damage data were produced in the form of areas by combining the forest fire damage ledger information with VIIRS-based forest fire occurrence data. Then, detrended fluctuation analysis and the local indicator of temporal burstiness were applied. In the results, the forest fire occurrence follows a self-organized criticality mechanism, and the temporal irregularities of fire occurrences exist. When the forest fire occurrence time series in Gyeonggi-do Province, which had the highest value of the local indicator of temporal burstiness, was checked, it was found that the frequency of forest fires was increasing at intervals of about 10 years. In addition, when the frequencies of forest fires and the spatial distribution of the local indicators of forest fire occurrences were compared, it was found that there were spatial differences in the occurrence of forest fires. This study is meaningful in that it analyzed the time series characteristics of the distribution of forest fires in Korea to understand that forest fire occurrences have long-term temporal correlations and identified areas where the temporal irregularities of forest fire occurrences are remarkable with the local indicators of temporal burstiness

Characteristics of Spatiotemporal Changes in the Occurrence of Forest Fires

The purpose of this study is to understand the characteristics of the spatial distribution of forest fire occurrences with the local indicators of temporal burstiness in Korea. Forest fire damage data were produced in the form of areas by combining the forest fire damage ledger information with VIIRS-based forest fire occurrence data. Then, detrended fluctuation analysis and the local indicator of temporal burstiness were applied. In the results, the forest fire occurrence follows a self-organized criticality mechanism, and the temporal irregularities of fire occurrences exist. When the forest fire occurrence time series in Gyeonggi-do Province, which had the highest value of the local indicator of temporal burstiness, was checked, it was found that the frequency of forest fires was increasing at intervals of about 10 years. In addition, when the frequencies of forest fires and the spatial distribution of the local indicators of forest fire occurrences were compared, it was found that there were spatial differences in the occurrence of forest fires. This study is meaningful in that it analyzed the time series characteristics of the distribution of forest fires in Korea to understand that forest fire occurrences have long-term temporal correlations and identified areas where the temporal irregularities of forest fire occurrences are remarkable with the local indicators of temporal burstiness

Downstream changes in river avulsion style are related to channel morphology: Data and Scripts

Data files and scripts necessary to replicate results from Nature Communications article entitled "Downstream changes in river avulsion style are related to channel morphology" by Valenza, J., Edmonds D., Hwang, T., and Roy, S. Files include annual composited, tasseled cap transformed geoTIFFs, parent and avulsion channel masks, and Matlab and Google Earth Engine scripts to produce and process data.See included Supplementary_Data1_Valenza_etal for details on file application, and comments within included scripts for further instruction

El Niño‐Southern Oscillation‐Induced Variability of Terrestrial Gross Primary Production During the Satellite Era

Terrestrial gross primary production (GPP) is the largest carbon flux entering the biosphere from the atmosphere, which serves as a key driver of global carbon cycle and provides essential matter and energy for life on land. However, terrestrial GPP variability is still poorly understood and difficult to predict, especially at the annual scale. As a major internal climate oscillation, El Niño‐Southern Oscillation (ENSO) influences global climate patterns and thus may strongly alter interannual terrestrial GPP variation. Using a remote sensing‐driven ecosystem model with long‐term satellite and climate data, we comprehensively examined the impacts of ENSO on global GPP dynamics from 1982 to 2016, focusing on lag effects of ENSO and their spatial heterogeneity. We found a clear seasonal lag effect of previous‐year ENSO indices on current‐year global GPP variability. The composite Oceanic Niño Index in the previous‐year's August‐October showed the strongest correlation with global annual GPP (R = −0.51, p < 0.01). Spatially, 20.1% and 11.7% of vegetated land area showed significant negative and positive correlations with the ENSO cycle, respectively. ENSO effects on annual GPP exhibited diverse seasonal evolutions, and the timings of peak ENSO influences were heterogeneous across the globe. Annual GPP from TRENDY land surface model ensemble did not capture the major lag effects of ENSO identified in the satellite‐derived GPP and top‐down‐based land sink. Despite the complexity of the climate system, our efforts linking ENSO with global GPP dynamics provide a simple framework to understand and project climatic influences on the terrestrial carbon cycle

Large Increase in Dissolved Inorganic Carbon in the East Sea (Japan Sea) From 1999 to 2019

The East Sea (also known as the Japan Sea; hereafter, EJS) has its own deep overturning circulation, that operates over a centurial timescale compared with a millennial timescale in the ocean. This allows the EJS to be used as a natural laboratory for investigating potential future changes in the oceanic system. Dissolved inorganic carbon (DIC), total alkalinity (TA), and pH were measured in 2019 in a wide area of the EJS to investigate the characteristics and changes of the carbonate system since the last extensive survey in 1999. In the layer below similar to 1,000 m, DIC and apparent oxygen utilization (AOU) was uniform implying rapid horizontal mixing within a few years. Since 1999, DIC concentration increased by similar to 11 mu mol kg(-1) in the layer deeper than 500 m. This increase accompanied a commensurate increase in AOU with the canonical ratio of 1.3, indicating that the accumulation of DIC was supplied from organic matter decomposition. This observation is consistent with a previous study suggesting that the slowed deep water ventilation was the cause of the increase in AOU and fast acidification. In the EJS, increase in DIC from the surface water to deep waters is much higher than that in TA, which is caused by high primary productivity and export production together with low rates of CaCO3 export. Thus, the DIC/TA ratio of deep waters, an indicator of vulnerability to acidification, is high. A recently reported change in deep water ventilation, namely, re-initiation of deep water formation reaching deeper depths to the Deep Water and the Bottom Water, implies that unexpected changes in the carbonate system may be detected in the future, which needs to be further monitored.N