基于试验的稻田作物生产水足迹计算方法研究

传统的作物生产水足迹计算通常采用估算的方法,计算精度无法得到保证。基于桶栽试验提出了一种稻田作物生产水足迹计算方法,即利用实测稻田水量平衡要素推算稻田作物蓝绿水足迹,再通过记录每次排水量及测定每次排水水样中氮磷浓度来计算稻田作物生产灰水足迹。试验设置浅水勤灌(Frequent and Shallow Irrigation,FSI)、浅湿灌溉(Wet and Shallow Irrigation,WSI)、控制灌溉(Controlled Irrigation,CI)和蓄水-控灌(Rain-catching and Controlled Irrigation,RC-CI)4种灌溉模式,计算各灌溉模式下的稻田作物生产水足迹。结果表明,稻田生产蓝绿水足迹随生育期呈"增—降—增—降"的趋势,以拔节孕穗期较大;灰水足迹集中在返青期和分蘖前期,这主要与施肥和降雨有关;总水足迹随生育期呈"增-降-增-降"的趋势,以分蘖前期较大,返青期和拔节孕穗期次之。返青期和分蘖前期稻田作物生产水足迹组成以灰水足迹为主,其余生育期以蓝绿水足迹为主。稻田作物生产水足迹计算结果说明灌溉模式对稻田生产水足迹影响显著(P0.05)。基于试验的作物生产水足迹计算方法能够准确计算出各生育阶段作物生产蓝绿水和灰水足迹。

Calculating Water Footprint of Rice Production Based on Experimental Data

Traditional methods for calculating water footprint (WF) of crop production areusually based on esti-mation, giving rise to uncertainties. This paper proposed a direct methodto calculate WF based on the data mea-sured from rice growing in lysimeters in attempts to improve its accuracy. The blue-green water footprint (BG-WF) of the rice was first calculated from water balance and the gray water footprint (GWF) was calculated using the nitrogen and phosphorus concentrationsmeasured fromall drains. We then applied the methods to four scenari-os: frequent and shallow irrigation (FSI), wet irrigation (WI), controlled irrigation (CK) and rain-catching and controlled irrigation (RCCI). The results showed that the BGWF of the paddy field varied with time in increase-decrease-increase-decrease, peaking at jointing-booting stage (J).The BGWF appeared predominantly in the re-turning green stage (R) and the earlytillering stage (Te) due to fertigation and precipitation. The overallwater foot-prints changed with time in increase-decrease-increase-decrease over the growth season, higher at early tillering stage. BGWF was higher than GWF during R and Te stages, while the opposite was true during other stages. Overall, the BGWF and GWF were457.3~548.3 mm and 214.3~511.9 mm respectively, affected significantly by how the rice was irrigated (P<0.05). The proposed method for calculating water footprints based on the data measured from the experiment is more accurate and reliable than other methods.