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Increasing climate aridity and drought, exacerbated by global warming, are increasing risks for western United States of America (U.S.A.) rainfed farming, and challenging producers’ capacity to maintain production and profitability. With agricultural water demand in the region exceeding limited supplies and fewer opportunities to develop new water sources, rainfed agriculture is under increasing pressure to meet the nation’s growing food demands. This study examines three major western U.S.A. rainfed crops: barley, spring wheat, and winter wheat. We analyzed the relationship between crop repurposing (the ratio of acres harvested for grain to the total planted acres) to seasonal climatic water deficit (CWD). To isolate the climate signal from economic factors, our analysis accounted for the influence of crop prices on grain harvest. We used historical climate and agricultural data between 1958 and 2020 to model crop repurposing (e.g. forage) across the observed CWD record using a fixed effect model. Our methodology is applicable for any region and incorporates regional differences in farming and economic drivers. Our results indicate that farmers are less likely to harvest barley and spring wheat for grain when the spring CWD is above average. Of the major winter wheat growing regions, only the Northern High Plainsmore »in Texas showed a trend of decreasing grain harvest during high CWD. For the majority of major crop growing regions, grain prices increased with lower levels of grain harvest. Interestingly, winter wheat repurposing is significantly higher in the southern Great Plains (∼50% harvested for grain) compared to the rest of the West (∼90%). Our results highlight that the major barley and spring wheat regions’ grain harvests are vulnerable to high spring CWD and low summer CWD, while winter wheat grain harvest is unaffected by variable CWD in most of the West.

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Forests face accelerating threats due to increases in the severity and frequency of drought and heat stress associated with climate change. In particular, changing patterns of forest regeneration after disturbance will be important in predicting future forest distribution across the western United States, where patterns of recurring fire and regrowth are important in establishing landscape dynamics. To predict shifting landscape patterns, it will be important to identify environmental boundaries for forest regeneration using environmental variables with clear consequences for seedling survival. Here, we explore soil surface temperature as an environmental variable with direct consequences for seedling survival and forest regeneration potential. We conducted a literature search to identify five previous laboratory experiments, spanning a period of 1924 to 1986, that exposed conifer seedlings to elevated soil surface temperatures for varying durations. We then synthesized the data from these studies to explore the survival of western U.S. conifer species in response to differing surface temperature levels. We found mortality thresholds consistent with previously reported measurements in field and lab studies, but found that as surface temperatures reach these lethal thresholds the duration of exposure matters greatly to survival outcomes. This work leverages an intuitive climate metric with clear consequences for seedlingmore »survival as an indicator of forest regeneration potential.« less

Abstract. Quantifying how vegetation mediates water partitioning at different spatialand temporal scales in complex, managed catchments is fundamental forlong-term sustainable land and water management. Estimations fromecohydrological models conceptualising how vegetation regulates theinterrelationships between evapotranspiration losses, catchment water storage dynamics, and recharge and runoff fluxes are needed to assess water availability for a range of ecosystem services and evaluate how these might change under increasing extreme events, such as droughts. Currently, the feedback mechanisms between water and mosaics of different vegetation and land cover are not well understood across spatial scales, and the effects of different scaleson the skill of ecohydrological models needs to be clarified. We used thetracer-aided ecohydrological model EcH2O-iso in an intensively monitored 66 km2 mixed land use catchment in northeastern Germany to quantify water flux–storage–age interactions at four model grid resolutions (250, 500, 750, and 1000 m). This used a fusion of field (including precipitation, soil water, groundwater, and stream isotopes) and remote sensing data in the calibration. Multicriteria calibration across the catchment at each resolution revealed some differences in the estimation of fluxes, storages, and water ages. In general, model sensitivity decreased and uncertainty increased with coarser model resolutions. Larger grids were unable to replicate observed streamflow andmore »distributed isotope dynamics in the way smaller pixels could. However, using isotope data in the calibration still helped constrain the estimation of fluxes, storage, and water ages at coarserresolutions. Despite using the same data and parameterisation for calibration at different grid resolutions, the modelled proportion of fluxes differed slightly at each resolution, with coarse models simulating higher evapotranspiration, lower relative transpiration, increased overland flow, and slower groundwater movement. Although the coarser resolutions also revealed higher uncertainty and lower overall model performance, the overall results were broadly similar. The study shows that tracers provide effective calibration constraints on larger resolution ecohydrological modelling and help us understand the influence of grid resolution on the simulation of vegetation–soil interactions. This is essential in interpreting associated uncertainty in estimating land use influence on large-scale “blue” (ground and surface water) and “green” (vegetation and evaporated water) fluxes, particularly for future environmental change.« less

Accurate monitoring of crop condition is critical to detect anomalies that may threaten the economic viability of agriculture and to understand how crops respond to climatic variability. Retrievals of soil moisture and vegetation information from satellite-based remote-sensing products offer an opportunity for continuous and affordable crop condition monitoring. This study compared weekly anomalies in accumulated gross primary production (GPP) from the SMAP Level-4 Carbon (L4C) product to anomalies calculated from a state-scale weekly crop condition index (CCI) and also to crop yield anomalies calculated from county-level yield data reported at the end of the season. We focused on barley, spring wheat, corn, and soybeans cultivated in the continental United States from 2000 to 2018. We found that consistencies between SMAP L4C GPP anomalies and both crop condition and yield anomalies increased as crops developed from the emergence stage (r: 0.4–0.7) and matured (r: 0.6–0.9) and that the agreement was better in drier regions (r: 0.4–0.9) than in wetter regions (r: −0.8–0.4). The L4C provides weekly GPP estimates at a 1-km scale, permitting the evaluation and tracking of anomalies in crop status at higher spatial detail than metrics based on the state-level CCI or county-level crop yields. We demonstrate that themore »L4C GPP product can be used operationally to monitor crop condition with the potential to become an important tool to inform decision-making and research.« less

Large-scale continuous crop monitoring systems (CMS) are key to detect and manage agricultural production anomalies. Current CMS exploit meteorological and crop growth models, and satellite imagery, but have underutilized legacy sources of information such as operational crop expert surveys with long and uninterrupted records. We argue that crop expert assessments, despite their subjective and categorical nature, capture the complexities of assessing the “status” of a crop better than any model or remote sensing retrieval. This is because crop rating data naturally encapsulates the broad expert knowledge of many individual surveyors spread throughout the country, constituting a sophisticated network of “people as sensors” that provide consistent and accurate information on crop progress. We analyze data from the US Department of Agriculture (USDA) Crop Progress and Condition (CPC) survey between 1987 and 2019 for four major crops across the US, and show how to transform the original qualitative data into a continuous, probabilistic variable better suited to quantitative analysis. Although the CPC reflects the subjective perception of many surveyors at different locations, the underlying models that describe the reported crop status are statistically robust and maintain similar characteristics across different crops, exhibit long-term stability, and have nation-wide validity. We discuss the originmore »and interpretation of existing spatial and temporal biases in the survey data. Finally, we propose a quantitative Crop Condition Index based on the CPC survey and demonstrate how this index can be used to monitor crop status and provide earlier and more precise predictions of crop yields than official USDA forecasts released midseason.« less

Abstract. The acceleration of urbanization requires sustainable, adaptive management strategies for land and water use in cities. Although the effects of buildings and sealed surfaces on urban runoff generation and local climate are well known, much less is known about the role of water partitioning in urban green spaces. In particular, little is quantitatively known about how different vegetation types of urban green spaces (lawns, parks, woodland, etc.) regulate partitioning of precipitation into evaporation, transpiration and groundwater recharge and how this partitioning is affected by sealed surfaces. Here, we integrated field observations with advanced, isotope-based ecohydrological modelling at a plot-scale site in Berlin, Germany. Soil moisture and sap flow, together with stable isotopes in precipitation, soil water and groundwater recharge, were measured over the course of one growing season under three generic types of urban green space: trees, shrub and grass. Additionally, an eddy flux tower at the site continuously collected hydroclimate data. These data have been used as input and for calibration of the process-based ecohydrological model EcH2O-iso. The model tracks stable isotope ratios and water ages in various stores (e.g. soils and groundwater) and fluxes (evaporation, transpiration and recharge). Green water fluxes in evapotranspiration increased in the ordermore »shrub (381±1mm)« less