CSIRO Land and Water, GPO Box 1666, Canberra ACT 2601, Australia.
CSIRO Land and Water, GPO Box 1666, Canberra ACT 2601, Australia.
Sci Total Environ. 2016 Jan 15;542(Pt A):372-82. doi: 10.1016/j.scitotenv.2015.10.086. Epub 2015 Nov 3.
Globally, irrigation accounts for more than two thirds of freshwater demand. Recent regional and global assessments indicate that groundwater extraction (GWE) for irrigation has increased more rapidly than surface water extraction (SWE), potentially resulting in groundwater depletion. Irrigated agriculture in semi-arid and arid regions is usually from a combination of stored surface water and groundwater. This paper assesses the usefulness of remotely-sensed (RS) derived information on both irrigation dynamics and rates of actual evapotranspiration which are both input to a river-reach water balance model in order to quantify irrigation water use and water provenance (either surface water or groundwater). The assessment is implemented for the water-years 2004/05-2010/11 in five reaches of the Murray-Darling Basin (Australia); a heavily regulated basin with large irrigated areas and periodic droughts and floods. Irrigated area and water use are identified each water-year (from July to June) through a Random Forest model which uses RS vegetation phenology and actual evapotranspiration as predicting variables. Both irrigated areas and actual evapotranspiration from irrigated areas were compared against published estimates of irrigated areas and total water extraction (SWE+GWE).The river-reach model determines the irrigated area that can be serviced with stored surface water (SWE), and the remainder area (as determined by the Random Forest Model) is assumed to be supplemented by groundwater (GWE). Model results were evaluated against observed SWE and GWE. The modelled SWE generally captures the observed interannual patterns and to some extent the magnitudes, with Pearson's correlation coefficients >0.8 and normalised root-mean-square-error<30%. In terms of magnitude, the results were as accurate as or better than those of more traditional (i.e., using areas that fluctuate based on water resource availability and prescribed crop factors) irrigation modelling. The RS irrigated areas and actual evapotranspiration can be used to: (i) understand irrigation dynamics, (ii) constrain irrigation models in data scarce regions, as well as (iii) pinpointing areas that require better ground-based monitoring.
在全球范围内，灌溉用水量占淡水总需求量的三分之二以上。最近的区域和全球评估表明，地下水开采（GWE）用于灌溉的速度比地表水开采（SWE）更快，这可能导致地下水枯竭。半干旱和干旱地区的灌溉农业通常是由储存的地表水和地下水的组合。本文评估了利用遥感（RS）获得的关于灌溉动态和实际蒸散率的信息的有用性，这两个信息都是河川流域水量平衡模型的输入，以量化灌溉用水量和水的来源（地表水或地下水）。该评估针对澳大利亚墨累-达令流域（澳大利亚）的五个河段在 2004/05 年至 2010/11 年水年期间实施；这是一个受到严格调控的流域，拥有大面积的灌溉区，且经常发生干旱和洪水。每个水年（从 7 月到 6 月），通过使用 RS 植被物候和实际蒸散作为预测变量的随机森林模型来识别灌溉区和用水量。将灌溉区和灌溉区的实际蒸散量与公布的灌溉区和总取水量（SWE+GWE）的估计值进行比较。河川流域模型确定了可以用储存地表水（SWE）服务的灌溉区，而剩余的面积（由随机森林模型确定）则假定由地下水（GWE）补充。模型结果与观测到的 SWE 和 GWE 进行了评估。模拟的 SWE 通常可以捕获观测到的年际变化模式，在某种程度上也可以捕获观测到的规模，皮尔逊相关系数>0.8，归一化均方根误差<30%。在规模方面，结果与更传统的（即，使用基于水资源可用性和规定作物系数波动的区域）灌溉建模一样准确或更好。RS 灌溉区和实际蒸散量可用于：（i）了解灌溉动态，（ii）在数据稀缺地区约束灌溉模型，以及（iii）查明需要更好的地面监测的区域。
