Irrigation accounts for ~70% of global freshwater withdrawals and ~90% of consumptive water use, driving myriad Earth system impacts. In this Review, we summarize how irrigation currently impacts key components of the Earth system. Estimates suggest that more than 3.6 million km² of currently irrigated land, with hot spots in the intensively cultivated US High Plains, California Central Valley, Indo-Gangetic Basin and northern China. Process-based models estimate that ~2,700 ± 540 km³ irrigation water is withdrawn globally each year, broadly consistent with country-reported values despite these estimates embedding substantial uncertainties. Expansive irrigation has modified surface energy balance and biogeochemical cycling. A shift from sensible to latent heat fluxes, and resulting land–atmosphere feedbacks, generally reduce regional growing season surface temperatures by ~1–3 °C. Irrigation can ameliorate temperature extremes in some regions, but conversely exacerbates moist heat stress. Modelled precipitation responses are more varied, with some intensive cropping regions exhibiting suppressed local precipitation but enhanced precipitation downstream owing to atmospheric circulation interactions. Additionally, irrigation could enhance cropland carbon uptake; however, it can also contribute to elevated methane fluxes in rice systems and mobilize nitrogen loading to groundwater. Cross-disciplinary, integrative research efforts can help advance understanding of these irrigation–Earth system interactions, and identify and reduce uncertainties, biases and limitations.

Modeling the climate of urban areas is of interest for studying urban heat islands (UHIs). Reliable assessment of the primary causes of UHIs and the efficacy of various heat mitigation strategies requires accurate prediction of urban temperatures and realistic representation of land surface physical characteristics in models. In this study, we expand the capabilities of the Weather Research and Forecasting (WRF) model by implementing high‐resolution, real‐time satellite observations of green vegetation fraction (GVF) and albedo. Satellite‐based GVF and albedo replace constant values that are assumed for urban pixels in the default version of WRF. Simulations of urban meteorology in Los Angeles using the improved model show marked improvements relative to the default model. The largest improvements are for nocturnal air temperatures, with a reduction in root‐mean‐square deviation between simulations and observations from 3.8 to 1.9°C. Utilizing the improved model, we quantify relationships between surface and 2 m air temperatures versus urban fraction, GVF, albedo, distance from the ocean, and elevation. Distance from the ocean is found to be the main contributor to variations in temperatures around Los Angeles. After conditionally sampling pixels to minimize the influence of distance from the ocean and elevation, we find that variations in GVF and urban fraction are responsible for up to 58 and 27% of the variance in temperatures. The satellite‐supported meteorological modeling framework reported here can be used for studying UHIs in other cities and can serve as a foundation for testing the efficacy of various heat mitigation strategies.

The California drought of 2012–2016 was a record‐breaking event with extensive social, political, and economic repercussions. The impacts were widespread and exposed the difficulty in preparing for the effects of prolonged dry conditions. Although the lessons from this drought drove important changes to state law and policy, there is little doubt that climate change will only exacerbate future droughts. To understand the character of future drought, this paper examines this recent drought period retrospectively and prospectively, that is, as it occurred historically and if similar dynamical conditions to the historical period were to arise 30 years later (2042–2046) subject to the effects of climate change. Simulations were conducted using the Weather Research and Forecasting model using the pseudo global warming method. The simulated historical and future droughts are contrasted in terms of temperature, precipitation, snowpack, soil moisture, evapotranspiration, and forest health. Overall, the midcentury drought is observed to be significantly worse, with many more extreme heat days, record‐low snowpack, increased soil drying, and record‐high forest mortality. With these findings in mind, the data sets developed in this study provide a means to structure future drought planning around a drought scenario that is realistic and modeled after a memorable historical analog.

The current research examines the influence of irrigation on urban hydrological cycles through the development of an irrigation scheme within the Noah land surface model (LSM)–Single Layer Urban Canopy Model (SLUCM) system. The model is run at a 30-m resolution for a 2-yr period over a 49 km2 urban domain in the Los Angeles metropolitan area. A sensitivity analysis indicates significant sensitivity relative to both the amount and timing of irrigation on diurnal and monthly energy budgets, hydrological fluxes, and state variables. Monthly residential water use data and three estimates of outdoor water consumption are used to calibrate the developed irrigation scheme. Model performance is evaluated using a previously developed MODIS–Landsat evapotranspiration (ET) and Landsat land surface temperature (LST) products as well as hourly ET observations through the California Irrigation Management Information System (CIMIS). Results show that the Noah LSM–SLUCM realistically simulates the diurnal and seasonal variations of ET when the irrigation module is incorporated. However, without irrigation, the model produces large biases in ET simulations. The ET errors for the nonirrigation simulations are −56 and −90 mm month−1 for July 2003 and 2004, respectively, while these values decline to −6 and −11 mm month−1 over the same 2 months when the proposed irrigation scheme is adopted. Results show that the irrigation-induced increase in latent heat flux leads to a decrease in LST of about 2°C in urban parks. The developed modeling framework can be utilized for a number of applications, ranging from outdoor water use estimation to climate change impact assessments.

More frequent and longer duration heat waves have been observed worldwide and are recognized as a serious threat to human health and the stability of electrical grids. Past studies have identified a positive feedback between heat waves and urban heat island effects. Anthropogenic heat emissions from buildings have a crucial impact on the urban environment, and hence it is critical to understand the interactive effects of urban microclimate and building heat emissions in terms of the urban energy balance. Here we developed a coupled-simulation approach to quantify these effects, mapping urban environmental data generated by the mesoscale Weather Research and Forecasting (WRF) coupled to Urban Canopy Model (UCM) to urban building energy models (UBEM). We conducted a case study in the city of Los Angeles, California, during a five-day heat wave event in September 2009. We analyzed the surge in city-scale building heat emission and energy use during the extreme heat event. We first simulated the urban microclimate at a high resolution (500 m by 500 m) using WRF-UCM. We then generated grid-level building heat emission profiles and aggregated them using prototype building energy models informed by spatially disaggregated urban land use and urban building density data. The spatial patterns of anthropogenic heat discharge from the building sector were analyzed, and the quantitative relationship with weather conditions and urban land-use dynamics were assessed at the grid level. The simulation results indicate that the dispersion of anthropogenic heat from urban buildings to the urban environment increases by up to 20% on average and varies significantly, both in time and space, during the heat wave event. The heat dispersion from the air-conditioning heat rejection contributes most (86.5%) of the total waste heat from the buildings to the urban environment. We also found that the waste heat discharge in inland, dense urban districts is more sensitive to extreme events than it is in coastal or suburban areas. The generated anthropogenic heat profiles can be used in urban microclimate models to provide a more accurate estimation of urban air temperature rises during heat waves.