Thermal and Hydrologic Signatures of Soil Controls on Evaporation: A Combined Energy and Water Balance Approach with Implications for Remote Sensing of Evaporation

The overall goal of this research is to examine the feasibility of applying a newly developed diagnostic model of soil water evaporation to large land areas using remotely sensed input parameters. The model estimates the rate of soil evaporation during periods when it is limited by the net transport resulting from competing effects of capillary rise and drainage. The critical soil hydraulic properties are implicitly estimated via the intensity and duration of the first stage (energy limited) evaporation, removing a major obstacle in the remote estimation of evaporation over large areas. This duration, or "time to drying" (t(sub d)), is revealed through three signatures detectable in time series of remote sensing variables. The first is a break in soil albedo that occurs as a small vapor transmission zone develops near the surface. The second is a break in either surface to air temperature differences or in the diurnal surface temperature range, both of which indicate increased sensible heat flux (and/or storage) required to balance the decrease in latent heat flux. The third is a break in the temporal pattern of near surface soil moisture. Soil moisture tends to decrease rapidly during stage 1 drying (as water is removed from storage), and then become more or less constant during soil limited, or "stage 2" drying (as water is merely transmitted from deeper soil storage). The research tasks address: (1) improvements in model structure, including extensions to transpiration and aggregation over spatially variable soil and topographic landscape attributes; and (2) applications of the model using remotely sensed input parameters

Emergent relation between surface vapor conductance and relative humidity profiles yields evaporation rates from weather data

The ability to predict terrestrial evapotranspiration (E) is limited by the complexity of rate-limiting pathways as water moves through the soil, vegetation (roots, xylem, stomata), canopy air space, and the atmospheric boundary layer. The impossibility of specifying the numerous parameters required to model this process in full spatial detail has necessitated spatially upscaled models that depend on effective parameters such as the surface vapor conductance (Csurf). Csurf accounts for the biophysical and hydrological effects on diffusion through the soil and vegetation substrate. This approach, however, requires either site-specific calibration of Csurf to measured E, or further parameterization based on metrics such as leaf area, senescence state, stomatal conductance, soil texture, soil moisture, and water table depth. Here, we show that this key, rate-limiting, parameter can be estimated from an emergent relationship between the diurnal cycle of the relative humidity profile and E. The relation is that the vertical variance of the relative humidity profile is less than would occur for increased or decreased evaporation rates, suggesting that land–atmosphere feedback processes minimize this variance. It is found to hold over a wide range of climate conditions (arid–humid) and limiting factors (soil moisture, leaf area, energy). With this relation, estimates of E and Csurf can be obtained globally from widely available meteorological measurements, many of which have been archived since the early 1900s. In conjunction with precipitation and stream flow, long-term E estimates provide insights and empirical constraints on projected accelerations of the hydrologic cycle

Changes in Summer Irrigated Crop Area and Water Use in Southeastern Turkey from 1993 to 2002: Implications for Current and Future Water Resources

Changes in summer irrigated cropland acreage and related water use are estimated from satellite remote sensing and ancillary data in semi-arid Southeastern Turkey where traditionally dry agricultural lands are being rapidly transformed into irrigated fields with the help of water from the Euphrates-Tigris Rivers. An image classification methodology based on thresholding of Landsat NDVI images from the peak summer period reveals that the total area of summer irrigated crops has increased three-fold (from 35,000 ha to over 100,000) in the Harran Plain between 1993 and 2002. Coupled analysis of annual irrigated crop area from remote sensing and potential evapotranspiration based estimates of irrigation water requirements for cotton indicate a corresponding increase in agricultural water use from about 370 million cubic meters to over one billion cubic meters, a volume in accordance with the state estimates. These estimates have important implications for understanding the rapid changes in current agricultural withdrawals in Southeastern Turkey and form a quantitative basis for exploring the changes in future water demands in the region. For example, expansion of irrigated lands have led to a steady decrease in potential evaporation due to increased roughness and decreased humidity deficit in the Harran Plain. Assuming that the changes in future evaporation conditions will be of similar nature, water use for irrigation is expected to decrease over 40 percent in future irrigation sites. Incorporating this decrease in overall planning of the irrigation projects currently under construction should lead to improved management, and by extension, sustainability of water resources in the region

Groundwater-surface water interaction and the climatic spatial patterns of hillslope hydrological response

International audienceA transient, mixed analytical-numerical model of hillslope hydrological behaviour is used to study the patterns of infiltration, evapotranspiration, recharge and lateral flow across hillslopes. Computational efficiency is achieved by treating infiltration and phreatic surface movement analytically. The influence of dynamic coupling of the saturated and unsaturated zones on the division of hillslopes into units of distinct hydrological behaviour is analyzed. The results indicate the importance of downhill groundwater flow on the lateral distribution of soil moisture and hydrological fluxes; unsaturated lateral flow is shown to be of relatively minor importance. For most conditions, the hillslope organizes itself into three distinct regions; an uphill recharge and a downhill discharge zone separated by a midline zone over which there is, on average, no recharge or discharge. A temporal perturbation analysis of the phreatic surface, made to quantify the deviations between the equivalent-steady water table derived by Salvucci and Entekhabi (1995) and the long-term mean water table, shows that the equivalent-steady water table effectively couples the unsaturated and saturated zone dynamics across storm and interstorm periods and divides the hillslope into distinct hydrological regions. The second order closure terms in the perturbation analysis, expressed as the gradient of water table variance, quantify the deviations and tend to make the hydrological zones relatively less distinct

(Re)introducing cognitive modeling to robotics

Presentation given at the UKC (US-Korea Conference), Durham, NC, August 2004. Retrieved 6/9/2006 from http://ksea.org/ukc2004/en/Proceedings/05RT/RT52_FrankLee.pdf.Presentation about potential applications of cognitive modeling to robotics

Differences in Multitask Resource Reallocation After Change in Task Values

International audienceObjective The objective was to characterize multitask resource reallocation strategies when managing subtasks with various assigned values.Background When solving a resource conflict in multitasking, Salvucci and Taatgen predict a globally rational strategy will be followed that favors the most urgent subtask and optimizes global performance. However, Katidioti and Taatgen identified a locally rational strategy that optimizes only a subcomponent of the whole task, leading to detrimental consequences on global performance. Moreover, the question remains open whether expertise would have an impact on the choice of the strategy.Method We adopted a multitask environment used for pilot selection with a change in emphasis on two out of four subtasks while all subtasks had to be maintained over a minimum performance. A laboratory eye-tracking study contrasted 20 recently selected pilot students considered as experienced with this task and 15 university students considered as novices.Results When two subtasks were emphasized, novices focused their resources particularly on one high-value subtask and failed to prevent both low-value subtasks falling below minimum performance. On the contrary, experienced people delayed the processing of one low-value subtask but managed to optimize global performance.Conclusion In a multitasking environment where some subtasks are emphasized, novices follow a locally rational strategy whereas experienced participants follow a globally rational strategy.Application During complex training, trainees are only able to adjust their resource allocation strategy to subtask emphasis changes once they are familiar with the multitasking environment

Volcanic cloud detection using Sentinel-3 satellite data by means of neural networks: the Raikoke 2019 eruption test case

The accurate automatic volcanic cloud detection by means of satellite data is a challenging task and of great concern for both scientific community and stakeholder due to the well-known issues generated by a strong eruption event in relation to aviation safety and health impact. In this context, machine learning techniques applied to recent spaceborne sensors acquired data have shown promising results in the last years. This work focuses on the application of a neural network based model to Sentinel-3 SLSTR (Sea and Land Surface Temperature Radiometer) daytime products in order to detect volcanic ash plumes generated by the 2019 Raikoke eruption. The classification of the clouds and of the other surfaces composing the scene is also carried out. The neural network has been trained with MODIS (MODerate resolution Imaging Spectroradiometer) daytime imagery collected during the 2010 Eyjafjallaj&ouml;kull eruption. The similar acquisition channels of SLSTR and MODIS sensors and the events comparable latitudes foster the robustness of the approach, which allows overcoming the lack in SLSTR products collected in previous mid-high latitude eruptions. The results show that the neural network model is able to detect volcanic ash with good accuracy if compared with RGB visual inspection and BTD (Brightness Temperature Difference) procedure. Moreover, the comparison between the ash cloud obtained by neural network and a plume mask manually generated for the specific SLSTR considered images, shows significant agreement. Thus, the proposed approach allows an automatic image classification during eruption events, which it is also considerably faster than time-consuming manually algorithms (e.g. find the best BTD product-specific threshold). Furthermore, the whole image classification indicates an overall reliability of the algorithm, in particular for meteo-clouds recognition and discrimination from volcanic clouds. Finally, the results show that the NN developed for the SLSTR nadir view is able to properly classify also the SLSTR oblique view images.</p

Nodulation capacity of Argentinean soybean (Glycine max L. Merr) cultivars inoculated with commercial strains of Bradyrhizobium japonicum.

The purpose of this research was to evaluate the nodulation potential of 31 Argentinean soybean commercial cultivars. Those with the highest nodulation capacity developed twice the amount of nodules than the low nodulating ones, which is the variation contained in soybean genotypes. Furthermore, this was not due to bacterial promiscuity, since the re-sponse was independent of the bradyrhizobia strain inoculated. The ability of cultivars to develop a larger number and biomass of nodules was unrelated with the maturity group they belong to and also was not a response to quorum sensing effects. Our results suggest that breeding programs can be aimed at improving the nodulation capacity of soybean and that cultivars from different maturity groups can be a source of nodulation QTLs