Understanding how different crops use water over time is essential for planning and managing water allocation, water rights, and agricultural production. The main objective of this paper is to characterize the spatiotemporal dynamics of crop water use in the Central Valley of California using Landsat-based annual actual evapotranspiration (ETa) from 2008 to 2018 derived from the Operational Simplified Surface Energy Balance (SSEBop) model. Crop water use for 10 crops is characterized at multiple scales. The Mann–Kendall trend analysis revealed a significant increase in area cultivated with almonds and their water use, with an annual rate of change of 16,327 ha in area and 13,488 ha-m in water use. Conversely, alfalfa showed a significant decline with 12,429 ha in area and 13,901 ha-m in water use per year during the same period. A pixel-based Mann–Kendall trend analysis showed the changing crop type and water use at the level of individual fields for all of Kern County in the Central Valley. This study demonstrates the useful application of historical Landsat ET to produce relevant water management information. Similar studies can be conducted at regional and global scales to understand and quantify the relationships between land cover change and its impact on water use. 

The evaluation of historical water use in the Upper Rio Grande Basin (URGB), United States and Mexico, using Landsat-derived actual evapotranspiration (ETa) from 1986 to 2015 is presented here as the first study of its kind to apply satellite observations to quantify long-term, basin-wide crop consumptive use in a large basin. The rich archive of Landsat imagery combined with the Operational Simplified Surface Energy Balance (SSEBop) model was used to estimate and map ETa across the basin and over irrigated fields for historical characterization of water-use dynamics. Monthly ETa estimates were evaluated using six eddy-covariance (EC) flux towers showing strong correspondence (r2 > 0.80) with reasonable error rates (root mean square error between 6 and 19 mm/month). Detailed spatiotemporal analysis using peak growing season (June–August) ETa over irrigated areas revealed declining regional crop water-use patterns throughout the basin, a trend reinforced through comparisons with gridded ETa from the Max Planck Institute (MPI). The interrelationships among seven agro-hydroclimatic variables (ETa, Normalized Difference Vegetation Index (NDVI), land surface temperature (LST), maximum air temperature (Ta), potential ET (ETo), precipitation, and runoff) are all summarized to support the assessment and context of historical water-use dynamics over 30 years in the URGB. 

We used long-term observations of grassland aboveground net plant production (ANPP, 1939– 2016), growing seasonal advanced very-high-resolution radiometer remote sensing normalized difference vegetation index (NDVI) data (1982–2016), and simulations of actual evapotranspiration (1912–2016) to evaluate the impact of Pacific Decadal Oscillation (PDO) and El Nino~ –Southern Oscillation (ENSO) sea surface temperature (SST) anomalies on a semiarid grassland in northeastern Colorado. Because ANPP was well correlated (R2 = 0.58) to cumulative April to July actual evapotranspiration (iAET) and cumulative growing season NDVI (iNDVI) was well correlated to iAET and ANPP (R2 = 0.62 [quadratic model] and 0.59, respectively), we were able to quantify interactions between the long-duration (15–30 yr) PDO temperature cycles and annual-duration ENSO SST phases on ANPP. We found that during cold-phase PDOs, mean ANPP and iNDVI were lower, and the frequency of low ANPP years (drought years) was much higher, compared to warm-phase PDO years. In addition, ANPP, iNDVI, and iAET were highly variable during the cold-phase PDOs. When NINO-3 (ENSO index) values were negative, there was a higher frequency of droughts and lower frequency of wet years regardless of the PDO phase. PDO and NINO-3 anomalies reinforced each other resulting in a high frequency of above-normal iAET (52%) and low frequency of drought (20%) when both PDO and NINO-3 values were positive and the opposite pattern when both PDO and NINO-3 values were negative (24% frequency of above normal and 48% frequency of drought). Precipitation variability and subsequent ANPP dynamics in this grassland were dampened when PDO and NINO-3 SSTs had opposing signs. Thus, primary signatures of these SSTs in this semiarid grassland are (1) increased interannual variability in ANPP during cold-phase PDOs, (2) drought with low ANPP occurring in almost half of those years with negative values of PDO and NINO-3, and (3) high precipitation and ANPP common in years with positive PDO and NINO-3 values

Since the passage of the U.S Global Change Research Act of 1990, several actions have been carried out in the Great Plains, including development of the first Great Plains regional climate assessment (National Climate Assessment Synthesis Team 2001, Ojima and Lackett 2002), and the establishment of several research centers to support understanding, communication, and response to climate change impacts and consequences. Among these efforts are the Regional Integrated Science and Assessment Centers, National Institute of Global Environmental Change which has been restructured as National Institute on Climate Change Research, North Central Climate Science Center, and other activities supported by state, federal, nongovernmental organizations (NGOs), and local entities.

Most nations around the world set aside some lands from where people live and work for the benefit of nature. Wildland ecosystems are those lands occupied chiefly by native plants and animals, not intensively used as urban or residential areas, and not intensively managed for the production of domesticated plants or animals (Kalisz and Wood 1995). Public parks, forests, grasslands, seashores, and other wildland ecosystems are central to the global strategy for the conservation of nature. These areas are also vital to the well-being of people. They provide essential ecosystem services, such as provisioning of food and water, supporting pollination and nutrient cycling, regulating floods and other disturbances, and providing aesthetic and recreational services (Wilkie et al. 2006; Friedman 2014).

The chapters of this book have delved into the timely and important topic of science and management of wildland ecosystems in the face of climate and land use change. The period of the book’s development (2011–2015) was one of rapid advancement in science, policy, agency infrastructure, and understanding of climate change adaptation (chaps. 2, 3, and 13). During this period, evidence of climate change and its consequences was ever more apparent. This was the warmest five-year period on record (http://www.ncdc.noaa.gov). Extreme climate events, such as droughts in California, Amazonia, and Australia, caused fundamental changes in allocating water to people and managing human risk from fire. Evidence of the ecological impacts of climate change became pervasive, including forest die-offs in many parts of the world and massive bleaching of coral ecosystems.

Grassland loss has been extensive worldwide, endangering the associated biodiversity and human well-being that are both dependent on these ecosystems. Ecologists have developed approaches to restore grassland communities and many have been successful, particularly where soils are rich, precipitation is abundant, and seeds of native plant species can be obtained. However, climate change adds a new filter needed in planning grassland restoration efforts. Potential responses of species to future climate conditions must also be considered in planning for long-term resilience. We demonstrate this methodology using a site-specific model and a maximum entropy approach to predict changes in habitat suitability for 33 grassland plant species in the tallgrass prairie region of the U.S. using the Intergovernmental Panel on Climate Change scenarios A1B and A2. The A1B scenario predicts an increase in temperature from 1.4 to 6.4°C, whereas the A2 scenario predicts temperature increases from 2 to 5.4°C and much greater CO2 emissions than the A1B scenario. Both scenarios predict these changes to occur by the year 2100. Model projections for 2040 under the A1B scenario predict that all but three modeled species will lose ~90% of their suitable habitat. Then by 2080, all species except for one will lose ~90% of their suitable habitat. Models run using the A2 scenario predict declines in habitat for just four species by 2040, but models predict that by 2080, habitat suitability will decline for all species. The A2 scenario appears based on our results to be the less severe climate change scenario for our species. Our results demonstrate that many common species, including grasses, forbs, and shrubs, are sensitive to climate change. Thus, grassland restoration alternatives should be evaluated based upon the long-term viability in the context of climate change projections and risk of plant species loss.

Evaporative demand (E0) both drives and responds to droughts based on interactions across the land surface-atmosphere interface, and can be exploited to signal agricultural, hydrologic, and ecological droughts. In this chapter, we argue that using a fully physically based measure of E0 moves the drought community toward a more complete understanding of drought processes that will enhance its abilities with regard to early warning and drought monitoring in the present day and drought-risk assessment under future climate change scenarios. We examine regional characteristics in E0 and their behavior during droughts in the recent historical period across different hydroclimates. We review physical mechanisms driving extremes in E0 and how climate change could influence their behavior in both driving and responding to extreme droughts in the 21st century. Finally, we discuss plant physiological responses under elevated atmospheric CO2 and their consequences for drought and heat stress on plants.

This paper describes the motivation for the creation of the Vulnerability, Impacts, Adaptation and Climate Services (VIACS) Advisory Board for the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6), its initial activities, and its plans to serve as a bridge between climate change applications experts and climate modelers. The climate change application community comprises researchers and other specialists who use climate information (alongside socioeconomic and other environmental information) to analyze vulnerability, impacts, and adaptation of natural systems and society in relation to past, ongoing, and projected future climate change. Much of this activity is directed toward the co-development of information needed by decision-makers for managing projected risks. CMIP6 provides a unique opportunity to facilitate a two-way dialog between climate modelers and VIACS experts who are looking to apply CMIP6 results for a wide array of research and climate services objectives. The VIACS Advisory Board convenes leaders of major impact sectors, international programs, and climate services to solicit community feedback that increases the applications relevance of the CMIP6-Endorsed Model Intercomparison Projects (MIPs). As an illustration of its potential, the VIACS community provided CMIP6 leadership with a list of prioritized climate model variables and MIP experiments of the greatest interest to the climate model applications community, indicating the applicability and societal relevance of climate model simulation outputs. The VIACS Advisory Board also recommended an impacts version of Obs4MIPs and indicated user needs for the gridding and processing of model output.

Scenario planning is a useful tool for identifying key vulnerabilities of ecological systems to changing climates, informed by the potential outcomes for a set of divergent, plausible, and relevant climate scenarios. We evaluated potential vulnerabilities of grassland communities to changing climate in the Southern Great Plains (SGP) and the Landscape Conservation Design pilot area (LCD) for the U.S. Fish and Wildlife Service, Science Applications Program, Great Plains Landscape Conservation Cooperative. Four climate scenarios (warm-dry, warm-wet, hot-dry, and hot-wet) from atmospheric-ocean general circulation models were selected to represent a suite of plausible future climatic conditions. For each scenario, and for contemporary climatic conditions, we predicted the spatial patterns of relative productivity for indicator grass species using statistical models of relative above-ground net primary productivity (hereafter, productivity) based on temperature, precipitation, and soil texture (percent sand, silt, or clay). Two indicator grass species were selected to represent each of four focal grassland communities: semi-desert grasslands, shortgrass prairie, mixed-grass prairie, and tallgrass prairie. Changes in spatial patterning of bioclimatic conditions conducive for each indicator species as predicted for each climate scenario relative to current land use were used to evaluate potential vulnerability and conservation opportunities for grassland communities. Specifically, the following questions were addressed for each focal grassland community: (1) Where is the productivity of each species predicted to increase, decrease, or remain stable relative to estimated contemporary productivity for the SGP and LCD pilot area, (2) where is the productivity of the two indicator species for each community predicted to increase, decrease, or remain stable, (3) which grassland communities are most vulnerable to changes in composition and vertical structure, (4) how do current land-use patterns contribute to potential vulnerabilities of grassland communities for the climate scenarios evaluated, and (5) how can managers use the vulnerabilities identified to evaluate conservation opportunities in the SGP and LCD? Current land-use patterns, in combination with the potential effects of a changing climate, pose greater risks to mixed-grass and tallgrass prairies of the SGP compared to semi-desert grasslands and shortgrass prairie. For most climate scenarios evaluated, bioclimatic conditions conducive to the taller species were predicted to contract within some or all the current distribution of mixed-grass and tallgrass prairies within the SGP. An increase in precipitation, however, could potentially ameliorate the negative effects of increasing temperatures as evidenced by higher productivity for the hot-wet scenario compared to the other scenarios for the most vulnerable species. Compounding their greater vulnerability to increasing temperatures coupled with decreasing precipitation, the mixed-grass and tallgrass prairies have been greatly fragmented and converted, primarily by agriculture. In contrast, the climate scenarios evaluated are generally conducive to stable or increasing productivity of indicator species for semi-desert grasslands and shortgrass prairie. In addition, conversion and fragmentation of semi-desert grasslands and shortgrass prairie were relatively low. These results suggest that the synergistic effects of land use and changing climatic conditions could have the greatest effects on the composition and structure of mixed-grass and tallgrass prairies in the SGP.