Master of Agribusiness / Department of Agricultural Economics / Nathan P. Hendricks / Risk and uncertainty are inherent in agriculture especially when lack of precipitation needed for crop production is common. Precipitation in the High Plains is highly variable. To supplement precipitation, the Ogallala Aquifer, a large underground water storage reservoir, was developed for irrigation. However, as the saturated thickness of the aquifer decreases, the rate at which water can be extracted (i.e., well capacities) decreases. Limited well capacities induce risk in agricultural production because producers may not be able to irrigate sufficiently in dry years. This study’s objective was to develop a method to assist producers in comparing alternative irrigation management strategies in the face of risk due to a limited well capacity. The objective was accomplished by simulating average net returns for 172 different irrigation strategies across 30 years (1986-2015) of historical weather (Kansas Mesonet 2016). Management strategies include different combinations of corn and wheat production with full irrigation, moderate irrigation, deficit irrigation and dryland production. The three risk measures were Value at Risk (VaR), expected shortfall, and standard deviation. The risk-return tradeoff is estimated for management strategies for two well capacities, 300 GPM (gallons per minute) and 600 GPM. Estimating these risk measures can help producers better evaluate the optimal management strategy compared to the approach of only equating average net returns.

Poussée par une forte demande et un marché très compétitif, la technologie PPD CIS est en évolution permanente. Du fait de leurs très bonnes performances en terme de bruit, les capteurs d’image CMOS à base de Photodiode Pincée (PPD CIS) peuvent désormais atteindre une sensibilité de l’ordre de quelques photons, ce qui rend cette technologie particulièrement intéressante pour les applications d’imagerie à haute résolution temporelle. Aujourd’hui, la physique des photodiodes pincées n’est pas encore comprise dans sont intégralité et il y a un manque important d’uniformisation des méthodes de caractérisation de ces détecteurs. Ces travaux s’intéressent à la définition, à la modélisation analytique, à la simulation et à l’estimation de paramètres clés des PPD CIS, tels que le temps de transfert, la tension de pincement et la full well capacity (FWC). Comme il a été mis en évidence par cette thèse, il est de première importance de comprendre l’effet des conditions expérimentales sur les performances de ces capteurs. Ceci aussi bien pour l’optimisation de ces paramètres lors de la conception du capteur, que lors de la phase de caractérisions de celui-ci, et enfin pour choisir correctement les conditions de mesures lors de la mise en œuvre du dispositif. / Driven by an aggressive market competition, CMOS Image Sensor technology is in continuous evolution. Thanks to the outstanding noise performances of Pinned Photodiode (PPD) CIS, CMOS sensors can now reach a few photons sensitivity, which makes this technology a particularly interesting candidate for high temporal resolution applications. Despite the incredibly large production volume, today, the PPD physics is not yet fully understood, and there is still a lack of golden standards for the characterization of PPD performances. This thesis focuses on the definition, analytical modeling, simulation and estimation of PPD key design parameters, with a particular focus on charge mechanisms, on the pinning voltage and on the full well capacity. The models developed in this work can help both manufacturers and users understanding the design trade-offs and the dependence of these parameters from the experimental conditions, in order to optimize the sensor design, to correctly characterize the image sensor, and to adjust the operation conditions to reach optimum performances.