OPTIMIZING WATER USE EFFICENCY IN HIGH VALUE CROPS

我的研究计划旨在开发水管理系统，在有限的供水条件下提高作物产量，减少水资源污染，减少温室气体排放。我们的研究结果，在过去的六年中，表明作物反射率指数最敏感的高价值蔬菜作物在温室和田间检测水分胁迫。使用配备多光谱和热成像仪的无人驾驶飞行器，将结果扩大到更大的领域。然而，这是昂贵的，耗时的，高度依赖于天气，并难以准确地评估作物水分胁迫由于土壤和作物参数的高度空间异质性。 为了克服这些局限性，我们将利用卫星技术的最新发展和数值强大的能量平衡算法，精确估计作物蒸散量（ETc）和作物水分胁迫（CWS）在大型灌溉区。新的纳米卫星可以每天三次提供非常高分辨率的作物反射率数据。这使得灌溉应用在近实时的基础上，是一个前所未有的发展，卫星地图的ETc。此外，当ETc和CWS与土壤水分来自美国宇航局的SMAP平台相结合，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，使更精确和强大的灌溉调度。 我们将在魁北克南部和安大略的大型灌溉蔬菜生产区测试这些创新，使用我们最近开发的算法来划定灌溉管理区（具有几乎相似的土壤特性和地形的田地块），从而解释大田地的空间异质性。通过整合地理空间和作物生长建模的力量，我们将确定每个管理区最佳的灌溉用水应用，以最大限度地提高作物产量。这也是作物水分生产力建模和评估方面前所未有的创新，迄今尚未探索。将使用HYDRUS模型研究通过埋地滴灌和调亏灌溉进一步节水的潜力。 预期成果如下：利用卫星监测方面的最新创新技术测量作物水分胁迫和土壤湿度的先进技术;支持区域范围特定地点灌溉管理的算法;以及在最大限度地提高作物产量的同时保护稀缺水资源的灌溉管理做法。 具有全球重要意义的研究惠益包括：蔬菜生产部门在经济上更具竞争力，农业用水效率更高，保护有限的水供应，以及用于土壤和水管理的新遥感产品。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.