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Monitoring Irrigation Using Landsat Observations and Climate Data over Regional Scales in the Murray-Darling Basin
Journal of Hydrology ( IF 5.9 ) Pub Date : 2020-11-01 , DOI: 10.1016/j.jhydrol.2020.125356
David Bretreger , In-Young Yeo , Greg Hancock , Garry Willgoose

Abstract Irrigated agriculture has been identified as using approximately 72% of water globally. Australia, like many places in the world, is subject to water sharing plans that cross government boarders and are subject to a mixture of management policies. There is a pressing need to develop a method to monitor irrigation water use to aid in water resource assessments and monitoring. This paper aims to test a method previously developed which monitors irrigation water use using remotely sensed observations over the catchment scale, without the need for in-situ observations, ground data or in-depth knowledge of crops and their planting dates. Using conservative assumptions about agricultural land management practice, irrigation is calculated as I r r = A E T - P . The method uses three vegetation indices derived from Landsat images to calculate crop coefficients ( K c ) based on multiple published relationships. These are combined through the FAO56 methodology using gridded rainfall and two reference evapotranspiration ( E T o ) products to find actual evapotranspiration as A E T = E T o × K c , providing six E T o - K c combinations. Results indicate this study method can effectively assess irrigation water use over a range of catchment sizes from ~6000 to ~600,000 ha, although issues arise when regions have a designated low allocation volume for that season (less than40%). Comparisons with the Standardised Precipitation Index (SPI) and Evaporative Stress Index (ESI) show that the proposed method is robust to the rapid onset and short-term droughts, However, its performance was poor during the long term droughts with low water allocation years. The study results during these years has been predominately attributed to water stress in certain crops being undetected, agricultural managers skipping annual crop commodities as well as stock and domestic water use making up larger portions of total water use. This is a limitation of this approach, although when only comparing results in years with greater than 40% allocations, the results improved significantly showing it can monitor water use effectively. When adequate water is available, this approach is able to accurately predict irrigation water use for the sites examined.

中文翻译:

在墨累-达令盆地使用区域尺度上的陆地卫星观测和气候数据监测灌溉

摘要 灌溉农业已被确定为使用全球约 72% 的水。与世界上许多地方一样,澳大利亚受制于跨政府边界的水资源共享计划,并受制于多种管理政策。迫切需要开发一种监测灌溉用水的方法,以帮助进行水资源评估和监测。本文旨在测试先前开发的方法,该方法使用流域范围内的遥感观测监测灌溉用水的使用,而无需现场观测、地面数据或对作物及其种植日期的深入了解。使用关于农业土地管理实践的保守假设,灌溉计算为 I rr = AET - P。该方法使用源自 Landsat 图像的三个植被指数,根据多个已发布的关系计算作物系数 (K c )。通过FAO56 方法,使用网格降雨量和两个参考蒸发蒸腾(ET o ) 产品将这些组合起来,以找到实际蒸散量,即AET = ET o × K c ,提供六种ET o - K c 组合。结果表明,该研究方法可以有效地评估从约 6000 到约 600,000 公顷的流域规模范围内的灌溉用水,尽管当区域指定的该季节分配量较低(低于 40%)时会出现问题。与标准化降水指数 (SPI) 和蒸发应力指数 (ESI) 的比较表明,该方法对快速发作和短期干旱具有鲁棒性,但是,在长期干旱和水资源分配不足的年份,它的表现很差。这些年来的研究结果主要归因于某些作物的缺水压力未被发现,农业管理者跳过一年生作物商品以及库存和生活用水占总用水量的较大部分。这是这种方法的局限性,尽管仅比较分配超过 40% 的年份的结果时,结果显着改善,表明它可以有效地监测用水量。当有足够的水可用时,这种方法能够准确预测所检查地点的灌溉用水。农业管理者跳过一年生作物商品以及库存和生活用水占总用水量的较大部分。这是这种方法的局限性,尽管仅比较分配超过 40% 的年份的结果时,结果显着改善,表明它可以有效地监测用水量。当有足够的水可用时,这种方法能够准确预测所检查地点的灌溉用水。农业管理者跳过一年生作物商品以及库存和生活用水占总用水量的较大部分。这是这种方法的局限性,尽管仅比较分配超过 40% 的年份的结果时,结果显着改善,表明它可以有效地监测用水量。当有足够的水可用时,这种方法能够准确预测所检查地点的灌溉用水。
更新日期:2020-11-01
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