Incorporating field wind data to improve crop evapotranspiration parameterization in heterogeneous regions

Accurate parameterization of reference evapotranspiration ( ET0) is necessary for optimizing irrigation scheduling and avoiding costs associated with over-irrigation (water expense, loss of water productivity, energy costs, and pollution) or with under-irrigation (crop stress and suboptimal yields or quality). ET0 is often estimated using the FAO-56 method with meteorological data gathered over a reference surface, usually short grass. However, the density of suitable ET0 stations is often low relative to the microclimatic variability of many arid and semi-arid regions, leading to a potentially inaccurate ET0 for irrigation scheduling. In this study, we investigated multiple ET0 products from six meteorological stations, a satellite ET0 product, and integration (merger) of two stations’ data in Southern California, USA. We evaluated ET0 against lysimetric ET observations from two lysimeter systems (weighing and volumetric) and two crops (wine grapes and Jerusalem artichoke) by calculating crop ET ( ETc) using crop coefficients for the lysimetric crops with the different ET0. ETc calculated with ET0 products that incorporated field-specific wind speed had closer agreement with lysimetric ET, with RMSE reduced by 36 and 45% for grape and Jerusalem artichoke, respectively, with on-field anemometer data compared to wind data from the nearest station. The results indicate the potential importance of on-site meteorological sensors for ET0 parameterization; particularly where microclimates are highly variable and/or irrigation water is expensive or scarce

The Neural Representation of Prospective Choice during Spatial Planning and Decisions

We are remarkably adept at inferring the consequences of our actions, yet the neuronal mechanisms that allow us to plan a sequence of novel choices remain unclear. We used functional magnetic resonance imaging (fMRI) to investigate how the human brain plans the shortest path to a goal in novel mazes with one (shallow maze) or two (deep maze) choice points. We observed two distinct anterior prefrontal responses to demanding choices at the second choice point: one in rostrodorsal medial prefrontal cortex (rd-mPFC)/superior frontal gyrus (SFG) that was also sensitive to (deactivated by) demanding initial choices and another in lateral frontopolar cortex (lFPC), which was only engaged by demanding choices at the second choice point. Furthermore, we identified hippocampal responses during planning that correlated with subsequent choice accuracy and response time, particularly in mazes affording sequential choices. Psychophysiological interaction (PPI) analyses showed that coupling between the hippocampus and rd-mPFC increases during sequential (deep versus shallow) planning and is higher before correct versus incorrect choices. In short, using a naturalistic spatial planning paradigm, we reveal how the human brain represents sequential choices during planning without extensive training. Our data highlight a network centred on the cortical midline and hippocampus that allows us to make prospective choices while maintaining initial choices during planning in novel environments

Reproducible research in vadose zone sciences

A significant portion of present-day soil and Earth science research is computational, involving complex data analysis pipelines, advanced mathematical and statistical models, and sophisticated computer codes. Opportunities for scientific progress are greatly diminished if reproducing and building on published research is difficult or impossible due to the complexity of these computational systems. Vadose Zone Journal (VZJ) is launching a Reproducible Research (RR) program in which code and data underlying a research article will be published alongside the article, thereby enabling readers to analyze data in a manner similar to that presented in the article and build on results in future research and applications. In this article, we discuss reproducible research, its background and use across other disciplines, its value to the scientific community, and its implementation in VZJ

Soil-water and solute movement under precision irrigation: knowledge gaps for managing sustainable root zones

Precision irrigation involves the accurate and precise application of water to meet the specific requirements of individual plants or management units and minimize adverse environmental impact. Under precision irrigation applications, water and associated solute movement will vary spatially within the root zone and excess water application will not necessarily result in deep drainage and leaching of salt below the root zone. This paper estimates that 10% of the irrigated land area (producing as much as 40% of the total annual revenue from irrigated land) could be adversely affected by root zone salinity resulting from the adoption of precision irrigation within Australia. The cost of increases in root zone salinisation due to inappropriate irrigation management in the Murray and Murrumbidgee irrigation areas was estimated at AUD 245 million (in 2000/01) or 13.5% of the revenue from these cropping systems. A review of soil–water and solute movement under precision irrigation systems highlights the gaps in current knowledge including the mismatch between the data required by complex, process-based soil–water or solute simulation models and the data that is easily available from soil survey and routine soil analyses. Other major knowledge gaps identified include: (a) effect of root distribution, surface evaporation and plant transpiration on soil wetted patterns, (b) accuracy and adequacy of using simple mean values of root zone soil salinity levels to estimate the effect of salt on the plant, (c) fate of solutes during a single irrigation and during multiple irrigation cycles, and (d) effect of soil heterogeneity on the distribution of water and solutes in relation to placement of water. Opportunities for research investment are identified across a broad range of areas including: (a) requirements for soil characterisation, (b) irrigation management effects, (c) agronomic responses to variable water and salt distributions in the root zone, (d) potential to scale or evaluate impacts at various scales, (e) requirements for simplified soil–water and solute modelling tools, and (f) the need to build skills and capacity in soil–water and solute modelling