OPTIMIZING WATER USE EFFICENCY IN HIGH VALUE CROPS

我的研究项目旨在开发水资源管理系统，在水资源供应有限的情况下提高作物产量，减少水资源污染，减少温室气体排放。在过去的六年里，我们的研究结果表明，作物反射率指数对温室和田间高价值蔬菜作物的水分胁迫最敏感。使用配备多光谱和热像仪的无人机，将结果扩展到更大的领域。然而，这是昂贵的，耗时的，高度依赖天气，并且由于土壤和作物参数的高度空间异质性，难以准确评估作物水分胁迫。为了克服这些限制，我们将利用卫星技术和数值强大的能量平衡算法的最新发展，精确估计大型灌区的作物蒸散（ETc）和作物水分胁迫（CWS）。新的纳米卫星可以提供非常高分辨率的作物反射率数据，每天三次。这使得灌溉应用几乎是实时的，这是ETc卫星制图方面前所未有的发展。此外，当ETc和CWS与来自NASA SMAP平台的土壤湿度相结合时，这将产生另一个前所未有的创新，使用作物和土壤参数来估计灌溉应用，使灌溉调度更加精确和稳健。我们将在魁北克省南部和安大略省的大型灌溉蔬菜产区测试这些创新，使用我们最近开发的算法来划定灌溉管理区（具有几乎相似土壤性质和地形的农田块），从而解释大型农田的空间异质性。通过整合地理空间和作物生长模型的力量，我们将确定每个管理区域的最佳灌溉用水，以最大限度地提高作物产量。这也是迄今为止尚未探索的作物水分生产力建模和评估方面的一项前所未有的创新。通过地下滴灌和调节亏缺灌溉的节水潜力将使用HYDRUS模型进行研究。预期的成果是：利用最近的卫星监测创新技术，采用先进技术测量作物水分胁迫和土壤湿度；支持区域尺度特定地点灌溉管理的算法；使作物产量最大化同时保护稀缺水资源的灌溉管理做法。这项研究的好处具有全球重要性，包括提高蔬菜生产部门的经济竞争力、提高农业用水效率、保护有限的水资源供应，以及用于水土管理的新的遥感产品。研究结果将对联邦和省政府的灌溉顾问和水资源规划者非常有益。

My research program aims to develop water management systems, that increase crop productivity under limited water supplies, reduce contamination of water resources, and mitigate greenhouse gas emissions. Our findings, over the past six years, have indicated crop reflectance indices most sensitive for detecting water stress in high value vegetable crops in the greenhouse and field. The results were scaled up to larger fields, using Unmanned Aerial Vehicles equipped with multispectral and thermal cameras. However, this was costly, time consuming, highly weather dependant, and difficult to accurately assess crop water stress due to the high spatial heterogeneity of soil and crop parameters. To overcome these limitations, we will take advantage of most recent developments in satellite technology and numerically powerful energy balance algorithms, to precisely estimate crop evapotranspiration (ETc) and crop water stress (CWS) over large irrigated regions. New Nano-satellites can provide crop reflectance data at very high resolution, thrice daily. This enables irrigation applications on a near real-time basis, and is an unprecedented development in satellite mapping of ETc. Furthermore, when ETc and CWS are coupled with soil moisture derived from NASA's SMAP platform, this will yield another unprecedented innovation using both crop and soil parameters to estimate irrigation applications, making for more precise and robust irrigation scheduling. We will test these innovations in large, irrigated vegetable producing regions of Southern Quebec and Ontario, using our recently developed algorithms to delineate irrigation management zones (field blocks with nearly similar soil properties and topography), thus accounting for spatial heterogeneity in large fields. By integrating the power of both geospatial and crop growth modelling, we will determine the most optimum irrigation water applications in each management zone, to maximize crop yields. This is also an unprecedented innovation in crop water productivity modelling and assessment that has hitherto not been explored. The potential for additional water savings through buried drip and regulated deficit irrigation will be investigated using the HYDRUS model. Anticipated outcomes are: advanced techniques for measuring crop water stress and soil moisture using recent innovations in satellite monitoring; algorithms to support site-specific irrigation management at regional scales, and; irrigation management practices which maximize crop yields while simultaneously conserving scarce water resources. The research benefits, which are of global importance, include a more economically competitive vegetable production sector, higher water use efficiency in agriculture, conservation of limited water supplies, and new remotely sensed products for soil and water management. The results will be highly beneficial to irrigation advisors and water resource planners in the federal and provincial governments.