Climate change impacts on water demand and salinity in California\u27s irrigated agriculture

This paper examines potential regional-scale impacts of climate change on sustainability of irrigated agriculture, focusing on the western San Joaquin Valley in California. We consider potential changes in irrigation water demand and supply, and quantify impacts on the hydrologic system, soil and groundwater salinity with associated crop yield reductions. Our analysis is based on archived output from General Circulation Model (GCM) climate projections through 2100, which were downscaled to the 1,400 km2 study area. We account for uncertainty in GCM climate projections by considering two different GCM\u27s, each using three greenhouse gas emission scenarios. Significant uncertainty in projected precipitation creates large uncertainty in surface water supply, ranging from a decrease of 26% to an increase of 14% in 2080-2099. Changes in projected irrigation water demand ranged from a decrease of 13% to an increase of 3% at the end of the 21st century. Greatest demand reductions were computed for the dry and warm scenarios, because of increased land fallowing with corresponding decreased total crop water requirements. A decrease in seasonal crop ET by climate warming, despite an increase in evaporative demand, was attributed to faster crop development with increasing temperatures. Simulations of hydrologic response to climate-induced changes suggest that the salt-affected area will be slightly expanded. However, irrespective of climate change, salinity is expected to increase in downslope areas, thereby limiting crop production to mostly upslope areas of the simulation domain. Results show that increasing irrigation efficiency may be effective in controlling salinization, by reducing groundwater recharge and improving soil drainage, and in mitigating climate warming effects, by reducing the need for groundwater pumping to satisfy crop water requirements

Improving visual functions in adult amblyopia with combined perceptual training and transcranial random noise stimulation (tRNS): a pilot study

Amblyopia is a visual disorder due to an abnormal pattern of functional connectivity of the visual cortex and characterized by several visual deficits of spatial vision including impairments of visual acuity (VA) and of the contrast sensitivity function (CSF). Despite being a developmental disorder caused by reduced visual stimulation during early life (critical period), several studies have shown that extensive visual perceptual training can improve VA and CSF in people with amblyopia even in adulthood. With the present study we assessed whether a much shorter perceptual training regime, in association with high-frequency transcranial electrical stimulation (hf-tRNS), was able to improve visual functions in a group of adult participants with amblyopia. Results show that, in comparison with previous studies where a large number sessions with a similar training regime were used (Polat et al., 2004), here just eight sessions of training in contrast detection under lateral masking conditions combined with hf-tRNS, were able to substantially improve VA and CSF in adults with amblyopia

Stable water isotopes and tritium tracers tell the same tale: no evidence for underestimation of catchment transit times inferred by stable isotopes in StorAge Selection (SAS)-function models

Stable isotopes (δ18O) and tritium (3H) are frequently used as tracers in environmental sciences to estimate age distributions of water. However, it has previously been argued that seasonally variable tracers, such as δ18O, generally and systematically fail to detect the tails of water age distributions and therefore substantially underestimate water ages as compared to radioactive tracers such as 3H. In this study for the Neckar River basin in central Europe and based on a &gt;20-year record of hydrological, δ18O and 3H data, we systematically scrutinized the above postulate together with the potential role of spatial aggregation effects in exacerbating the underestimation of water ages. This was done by comparing water age distributions inferred from δ18O and 3H with a total of 21 different model implementations, including time-invariant, lumped-parameter sine-wave (SW) and convolution integral (CO) models as well as StorAge Selection (SAS)-function models (P-SAS) and integrated hydrological models in combination with SAS functions (IM-SAS). We found that, indeed, water ages inferred from δ18O with commonly used SW and CO models are with mean transit times (MTTs) of ∼ 1–2 years substantially lower than those obtained from 3H with the same models, reaching MTTs of ∼10 years. In contrast, several implementations of P-SAS and IM-SAS models not only allowed simultaneous representations of storage variations and streamflow as well as δ18O and 3H stream signals, but water ages inferred from δ18O with these models were, with MTTs of ∼ 11–17 years, also much higher and similar to those inferred from 3H, which suggested MTTs of ∼ 11–13 years. Characterized by similar parameter posterior distributions, in particular for parameters that control water age, P-SAS and IM-SAS model implementations individually constrained with δ18O or 3H observations exhibited only limited differences in the magnitudes of water ages in different parts of the models and in the temporal variability of transit time distributions (TTDs) in response to changing wetness conditions. This suggests that both tracers lead to comparable descriptions of how water is routed through the system. These findings provide evidence that allowed us to reject the hypothesis that δ18O as a tracer generally and systematically “cannot see water older than about 4 years” and that it truncates the corresponding tails in water age distributions, leading to underestimations of water ages. Instead, our results provide evidence for a broad equivalence of δ18O and 3H as age tracers for systems characterized by MTTs of at least 15–20 years. The question to which degree aggregation of spatial heterogeneity can further adversely affect estimates of water ages remains unresolved as the lumped and distributed implementations of the IM-SAS model provided inconclusive results. Overall, this study demonstrates that previously reported underestimations of water ages are most likely not a result of the use of δ18O or other seasonally variable tracers per se. Rather, these underestimations can largely be attributed to choices of model approaches and complexity not considering transient hydrological conditions next to tracer aspects. Given the additional vulnerability of time-invariant, lumped SW and CO model approaches in combination with δ18O to substantially underestimate water ages due to spatial aggregation and potentially other still unknown effects, we therefore advocate avoiding the use of this model type in combination with seasonally variable tracers if possible and instead adopting SAS-based models or time-variant formulations of CO models.</p

Multi-objective calibration of a surface water-groundwater flow model in an irrigated agricultural region: Yaqui Valley, Sonora, Mexico

Multi-objective optimization was used to calibrate a regional surface water-groundwater model of the Yaqui Valley, a 6800 km² irrigated agricultural region located along the Sea of Cortez in Sonora, Mexico. The model simulates three-dimensional groundwater flow coupled to one-dimensional surface water flow in the irrigation canals. It accounts for the spatial distribution of annual recharge from irrigation, subsurface drainage, agricultural pumping, and irrigation canal seepage. The main advantage of the calibration method is that it accounts for both parameter and model structural uncertainty. In this case, results show that the effect of including the process of bare soil evaporation is significantly greater than the effects of parameter uncertainty. Furthermore, by treating the different objectives independently, a better identification of the model parameters is achieved compared to a single-objective approach, since the various objectives are sensitive to different parameters. The simulated water balance shows that 15&ndash;20% of the water that enters the irrigation canals is lost by seepage to groundwater. The main discharge mechanisms in the Valley are crop evapotranspiration (53%), non-agricultural evapotranspiration and bare soil evaporation (19%), surface drainage to the Sea of Cortez (15%), and groundwater pumping (9%). In comparison, groundwater discharge to the estuary was relatively insignificant (less than 1%). The model was further refined by identifying zonal <i>K_v</i> and <i>K_h</i> values based on a spatial analysis of the model residuals

Crossing the border in visual arts and literature : a transmedial analysis between an outline of Don't Cross the Bridge Before You Get to the River by Francis Alys and Senales que precederan al fin del mundo by Yuri Herrera

In the huge production of border arts, we propose a transmedial comparison between an outline of Francis Alys' project Don't Cross the Bridge Before You Get to the River (2008) and Yuri Herrera's novel Sings Preceding the End of the World (2009). Based on Deleuzian concepts of re-/deterritorialization, we argue that both artists question the traditional version of the fixed border as well as the more utopian vision of the fluid border. The destabilization of spatial, ontological and linguistic levels presents borders as imaginary constructions that try to impose fixed structures on a dynamic reality

An inverse oblique effect in human vision

AbstractIn the classic oblique effect contrast detection thresholds, orientation discrimination thresholds, and other psychophysical measures are found to be smallest for vertical or horizontal stimuli and significantly higher for stimuli near the ±45° obliques. Here we report a novel inverse oblique effect in which thresholds for detecting translational structure in random dot patterns [Glass, L. (1969). Moiré effect from random dots. Nature, 223, 578–580] are lowest for obliquely oriented structure and higher for either horizontal or vertical structure. Area summation experiments provide evidence that this results from larger pooling areas for oblique orientations in these patterns. The results can be explained quantitatively by a model for complex cells in which the final filtering stage in a filter–rectify–filter sequence is of significantly larger area for oblique orientations