Certain vegetation types (e.g., deciduous shrubs, deciduous trees, grasslands) have distinct life cycles marked by the growth and senescence of leaves and periods of enhanced photosynthetic activity. Where these types exist, recurring changes in foliage alter the reflectance of electromagnetic radiation from the land surface, which can be measured using remote sensors. The timing of these recurring changes in reflectance is called land surface phenology (LSP). During recent decades, a variety of methods have been used to derive LSP metrics from time series of reflectance measurements acquired by satellite-borne sensors. In contrast to conventional phenology observations, LSP metrics represent the timing of reflectance changes that are driven by the aggregate activity of vegetation within the areal unit measured by the satellite sensor and do not directly provide information about the phenology of individual plants, species, or their phenophases. Despite the generalized nature of satellite sensor-derived measurements, they have proven useful for studying changes in LSP associated with various phenomena. This chapter provides a detailed overview of the use of satellite remote sensing to monitor LSP. First, the theoretical basis for the application of satellite remote sensing to the study of vegetation phenology is presented. After establishing a theoretical foundation for LSP, methods of deriving and validating LSP metrics are discussed. This chapter concludes with a discussion of major research findings and current and future research directions.

State-and-Transition Simulation Modeling (STSM) is a quantitative analysis method that can consolidate a wide array of resource management issues under a “what-if” scenario exercise. STSM can be seen as an ensemble of models, such as climate models, ecological models, and economic models that incorporate human dimensions and management options. This chapter presents STSM as a tool to help synthesize information on social–ecological systems and to investigate some of the management issues associated with exotic annual Bromus species, which have been described elsewhere in this book. Definitions, terminology, and perspectives on conceptual and computer-simulated stochastic state-and-transition models are given first, followed by a brief review of past STSM studies relevant to the management of Bromus species. A detailed case study illustrates the usefulness of STSM for land management. As a whole, this chapter is intended to demonstrate how STSM can help both managers and scientists: (a) determine efficient resource allocation for monitoring nonnative grasses; (b) evaluate sources of uncertainty in model simulation results involving expert opinion, and their consequences for management decisions; and (c) provide insight into the consequences of predicted local climate change effects on ecological systems invaded by exotic annual Bromus species.

Natural resource managers consistently identify invasive species as one of the biggest challenges for ecological adaptation to climate change. Yet climate change is often not considered during their management decision making. Given the many ways that invasive species and climate change will interact, such as changing fire regimes and facilitating the migration of high priority species, it is more critical than ever to integrate climate adaptation science and natural resource management. The coupling of climate adaptation and invasive species management remains limited by a lack of information, personnel, and funding. Those working on ecological adaptation to climate change have reported that information is not available or is not presented in a way that informs invasive species management. This project will expand the successful model of the Northeast Regional Invasive Species and Climate Change Management Network to the North Central region of the U.S. This effort will integrate the research and management of invasive species, climate change, and fire under one umbrella. Stakeholders in the North Central region have identified invasive species, woody encroachment, wildfire, and habitat and ecological transformation as key management issues which this project will address. A primary activity will be to host two Science Integration Workshops to pair management needs with research directions. From these workshops, strategic scientific products will be derived that include synthesis of existing information in a workshop report, summaries on management challenges adapted for the region, blog posts for managers, and collaboration with land managers to access and utilize existing climate and invasive species information and tools. The research team will work together with managers to understand key management needs surrounding invasive plant species in a changing climate.

Agent-based models (ABMs) and state-and-transition simulation models (STSMs) have proven useful for understanding processes underlying social-ecological systems and evaluating practical questions about how systems might respond to different scenarios. ABMs can simulate a variety of agents (i.e., autonomous units, such as wildlife, people, or viruses); agent characteristics, decision-making, adaptive behavior, and mobility; and interactions between agents and their environment. STSMs are flexible and intuitive stochastic models of landscape dynamics that can track scenarios and landscape attributes, and integrate diverse data types. Both can be run spatially and track metrics of management success. Due to the complementarity of these approaches, we sought to couple them through a dynamic linkage and demonstrate the relevance of this advancement for modeling landscape processes and patterns. We developed analytical techniques and software tools to couple these modeling approaches using NetLogo, R, and the ST-Sim package for SyncroSim. We demonstrated the capabilities and value of this coupled approach through a proof-of-concept case study of bison-vegetation interactions in Badlands National Park.The coupled approach: 1) streamlined handling of model inputs and outputs; 2) allowed representation of processes at multiple temporal scales; 3) minimized assumptions; and 4) generated spatial and temporal patterns that better reflected agent-environment interactions. These developments constitute a new approach for representing agent-environment feedbacks; modelers can now use output from an ABM to dictate landscape changes within an STSM that in turn influence agents. This facilitates experimentation across domains (agent and environment) and creation of more realistic and management-relevant projections.

Water resources are critical for ecosystems, agriculture, and communities, and potential climate impacts to hydrologic budgets and cycles are arguably the most consequential to society. Apart from precipitation, evapotranspiration makes up the most significant component of the hydrologic budget. Evapotranspiration is a primary metric for identifying Ecological Drought, a deficit in water availability that negatively impacts ecosystems and ecosystem services. Through an agreement between the USGS Earth Resources Observation and Science (EROS) Center Land Cover Monitoring, Assessment and Projection (LCMAP) program and the North Central CASC, Dr. Senay works to integrate and apply remotely sensed data for eco- and agro-hydrologic modeling. He promotes and advances the use of satellite-derived multi-scale evapotranspiration products by the key stakeholders in the irrigation and water resources community for climate adaptation planning.

Reliable information on water use and availability at basin and field scales are important to ensure the optimized constructive uses of available water resources. This study was conducted with the specific objective to estimate Landsat-based actual evapotranspiration (ETa) using the Operational Simplified Surface Energy Balance (SSEBop) model across the state of South Dakota (SD), USA for the 1986–2018 (33-year) period. Validated ETa estimations (r2 = 0.91, PBIAS = −4%, and % RMSE = 11.8%) were further used to understand the crop water-use characteristics and existing historic mono-directional (increasing/decreasing) trends over the eastern (ESD) and western (WSD) regions of SD. The crop water-use characteristics indicated that the annual cropland water uses across the ESD and WSD were more or less met by the precipitation amounts in the area. The ample water supply and distribution have led to high rainfed and low percentage of irrigated cropland (2.5%) in the state. The WSD faced greater crop-water use reductions than the ESD during drought periods. The landscape ETa responses across the state were found to be more sensitive than precipitation for the drought impact assessments. The Mann Kendall trend analysis revealed the absence of a significant trend (p > 0.05) in annual ETa at a regional scale due to the varying weather conditions in the state. However, about 12% and 9% cropland areas in the ESD and WSD, respectively, revealed a significant mono-directional trend at pixel scale ETa. Most of the pixels under significant trend showed an increasing trend that can be explained by the shift in agricultural practices, increased irrigated cropland area, higher productions, moisture regime shifts, and decreased risk of farming in the dry areas. The decreasing trend pixels were clustered in mid-eastern SD and could be the result of dynamic conversion of wetlands to croplands and decreased irrigation practices in the region. This study also demonstrates the tremendous potential and robustness of the SSEBop model, Landsat imagery, and remote sensing-based ETa modelling approaches in estimating consistent spatially distributed evapotranspiration.

Upper Klamath Lake (UKL) is the source of the Klamath River that flows through southern Oregon and northern California. The UKL Basin provides water for 81,000+ ha (200,000+ acres) of irrigation on the U.S. Bureau of Reclamation Klamath Project located downstream of the UKL Basin. Irrigated agriculture also occurs along the tributaries to UKL. During 2013–2016, water rights calls resulted in various levels of curtailment of irrigation diversions from the tributaries to UKL. However, information on the extent of curtailment, how much irrigation water was saved, and its impact on the UKL is unknown. In this study, we combined Landsat-based actual evapotranspiration (ETa) data obtained from the Operational Simplified Surface Energy Balance model with gridded precipitation and U.S. Geological Survey station discharge data to evaluate the hydrologic impact of the curtailment program. Analysis was performed for 2004, 2006, 2008–2010 (base years), and 2013–2016 (target years) over irrigated areas above UKL. Our results indicate that the savings from the curtailment program over the June to September time period were highest during 2013 and declined in each of the following years. The total on-field water savings was approximately 60 hm3 in 2013 and 2014, 44 hm3 in 2015, and 32 hm3 in 2016 (1 hm3 = 10,000 m3 or 810.7 ac-ft). The instream water flow changes or extra water available were 92, 68, 45, and 26 hm3, respectively, for 2013, 2014, 2015, and 2016. Highest water savings came from pasture and wetlands. Alfalfa showed the most decline in water use among grain crops. The resulting extra water available from the curtailment contributed to a maximum of 19% of the lake inflows and 50% of the lake volume. The Landsat-based ETa and other remote sensing datasets used in this study can be used to monitor crop water use at the irrigation district scale and to quantify water savings as a result of land-water management changes.

Satellite-based actual evapotranspiration (ETa) is becoming increasingly reliable and available for various water management and agricultural applications from water budget studies to crop performance monitoring. The Operational Simplified Surface Energy Balance (SSEBop) model is currently used by the US Geological Survey (USGS) Famine Early Warning System Network (FEWS NET) to routinely produce and post multitemporal ETa and ETa anomalies online for drought monitoring and early warning purposes. Implementation of the global SSEBop using the Aqua satellite’s Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature and global gridded weather datasets is presented. Evaluation of the SSEBop ETa data using 12 eddy covariance (EC) flux tower sites over six continents indicated reasonable performance in capturing seasonality with a correlation coefficient up to 0.87. However, the modeled ETa seemed to show regional biases whose natures and magnitudes require a comprehensive investigation using complete water budgets and more quality-controlled EC station datasets. While the absolute magnitude of SSEBop ETa would require a one-time bias correction for use in water budget studies to address local or regional conditions, the ETa anomalies can be used without further modifications for drought monitoring. All ETa products are freely available for download from the USGS FEWS NET website.

In this research, we characterized the changes in the Gravity Recovery and Climate Experiment (GRACE) monthly total water storage anomaly (TWSA) in 18 surface basins and 12 principal aquifers in the conterminous United States during 2003–2016. Regions with high variability in storage were identified. Ten basins and four aquifers showed significant changes in storage. Eight surface basins and eight aquifers were found to show decadal stability in storage. A pixel-based analysis of storage showed that the New England basin and North Atlantic Coastal Plain aquifer showed the largest area under positive storage change. By contrast, the Lower Colorado and California basins showed the largest area under negative change. This study found that historically wetter regions (with more storage) are becoming wetter, and drier regions (with less storage) are becoming drier. Fourier analysis of the GRACE data showed that while all basins exhibited prominent annual periodicities, significant sub-annual and multi-annual cycles also exist in some basins. The storage turnover period was estimated to range between 6 and 12 months. The primary explanatory variable (PEV) of TWSA was identified for each region. This study provides new insights on several aspects of basin or aquifer storage that are important for understanding basin and aquifer hydrology.