As the global population increases and the climate changes, ensuring a secure food supply is increasingly important. One strategy is irrigation, which allows for crops to be grown outside their optimal climate growing regions and which buffers against climate variability. Although irrigation is a positive climate adaptation mechanism for agriculture, it has a potentially negative effect on water resources as it can lead to groundwater depletion and diminished surface water supplies. This study quantifies how crop yields are affected by climate variability and extremes and the impact of irrigation on crop yield increases under various growing-season climate conditions. To do this, we use historical climate data and county-level rainfed and irrigated crop yields for maize, soybean, winter and spring wheat over the US to analyze the relationship between climate, crop yields, and irrigation. We find that there are optimal climates, specific to each crop, where irrigation provides a benefit and other conditions where irrigation proves to have marginal, if any, benefits. Furthermore, the relationship between crop yields and climate has changed over the last decades, with a changing sensitivity in the relationship of soybean and winter wheat yields to certain climate variables, like crop reference evapotranspiration. These two conclusions have important implications for agricultural and water resource system planning, as it implies there are more optimal climate conditions where irrigation is particularly productive and regions where irrigation should be reconsidered as there is not a significant agricultural benefit and the water could be used more productively.

A B S T R A C T Analytical study of piezoelectric paint, which provides insight about its key material behaviour in ultrasonic sensing, is the focus of this paper. Piezoelectric paint is a composite piezoelectric material that comprises tiny piezoelectric particles randomly dispersed within a polymer matrix phase. Acoustic emission (AE) technique has been used for non-destructive evaluation (NDE) such as fracture monitoring in metal, concrete and composite structures. The feasibility of using piezoelectric paint for AE sensing has been demonstrated. In the context of piezoelectric paint-based AE sensor, models for the key material properties of piezoelectric paint are reviewed first. The effect of piezoelectric ceramic volume fraction on paint sensor response is examined. A coupled field finite element model was established to carry out the electro-mechanical analysis of piezoelectric paint sensor subjected to AE excitation. The simulation model for piezoelectric paint sensor is calibrated with experimental data. While more extensive research needs to be done to characterize piezoelectric paint sensor for fracture monitoring, such an analytical study proves to be very useful to the optimization of piezoelectric paint formulation and sensor geometry for AE sensor.

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There has been a rapid advancement in wireless sensor network (WSN) technology in the past decade and its application in structural monitoring has been the focus of several research projects. The evaluation of the newly developed hardware platform and software system is an important aspect of such research efforts. Although much of this evaluation is done in the laboratories and using generic signal processing techniques, it is important to validate the system for its intended application as well. In this paper the performance of a newly developed accelerometer sensor board is evaluated by using the data from a beam-column connection specimen with a local damage detection algorithm. The sensor board is a part of a wireless node that consists of the Imote2 control/communication unit and an advanced antenna for improved connectivity. A scaled specimen of a steel beam-column connection is constructed in ATLSS center at Lehigh University and densely instrumented by synchronized networked systems of both traditional piezoelectric and wireless sensors. The column ends of the test specimen have fixed connections, and the beam cantilevers from the centerline of the column. The specimen is subjected to harmonic excitations in several test runs and its acceleration response is collected by both systems. The collected data is then used to estimate two sets of system influence coefficients with the wired one as the reference baseline. The performance of the WSN is evaluated by comparing the quality of the influence coefficients and the rate of convergence of the estimated parameters.

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