We present an analysis of the sensitivity of three key crops (alfalfa, barley and winter wheat) produced in the northwestern United States to climatic and agricultural market anomalies using widely used standardized indices. Rather than investigating sensitivity of crop yields (production per unit area), we focus on agricultural production (yield * harvested area) anomalies, which captures both variations in yield and the effect of decisionmaking factors such as allocation of cropping area. We used two well-known standardized precipitation and reference evapotranspiration (ETo) indices (SPI and EDDI, respectively) and a standardized crop value index in a multivariate linear regression analysis to determine the characteristic timing and time-scales of precipitation and ETo anomalies that best explain annual crop production anomalies. Since climatic and market factors are standardized, regression coefficients are interpreted as a sensitivity measure that captures the relative effect of climatic and agricultural markets on agricultural production. Results show that alfalfa production was most sensitive climatic anomalies while barley and wheat production was more responsive to crop prices. Sensitivity to precipitation anomalies followed gradients in precipitation, temperature, and soil moisture regimes across the study area where drier and warmer climates were associated with increased sensitivity to climatic anomalies. We found that irrigation decoupled alfalfa production from climatic variability, but the effect of irrigation on decoupling barley production was less clear. Winter wheat production was most sensitive to price anomalies, and alfalfa was least sensitive. Omitting agricultural market conditions and other farmer incentives may introduce biases in our understanding of how drought and climate change impact agricultural production.

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 the 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.

While many studies on tribal water resources of individual tribal lands in the United States (US) have been conducted, the importance of tribal water resources at a national scale has largely gone unrecognized because their combined totals have not been quantified. Thus, we sought to provide a numerical estimate of major water budget components on tribal lands within the conterminous US and on USGS hydrologic unit codes (HUC2) regions. Using existing national-scale data and models, we estimated mean annual precipitation, evapotranspiration, excess precipitation, streamflow, and water use for the period 1971–2000. Tribal lands represent about 3.4 percent of the total land area of the conterminous US and on average account for 1.9 percent of precipitation, 2.4 percent of actual evapotranspiration, 0.95 percent of excess precipitation, 1.6 percent of water use, and 0.43 percent of streamflow origination. Additionally, approximately 9.5 and 11.3 percent of US streamflow flows through or adjacent as boundaries to tribal lands, respectively. Streamflow through or adjacent to tribal lands accounts for 42 and 48 percent of streamflow in the Missouri region, respectively; and for 86 and 88 percent in the Lower Colorado region, respectively. On average, 5,600 million cubic meters of streamflow per year was produced on tribal lands in the Pacific Northwest region, nearly five times greater than tribal lands in any other region. Tribal lands in the Great Lakes, Missouri, Arkansas-White-Red, and California regions all produced between 1,000 and 1,400 million cubic meters per year.

No abstract

No abstract