Gebremariam Filmon Tquabo, Habtu Solomon, Yazew Eyasu, Teklu Berhane
Department of Land Resources Management and Environmental Protection, Mekelle University, Tigray, Ethiopia.
Institute of Water and Environment, Mekelle University, Tigray, Ethiopia.
Heliyon. 2021 Apr 22;7(4):e06822. doi: 10.1016/j.heliyon.2021.e06822. eCollection 2021 Apr.
Global freshwater resources are getting scarcer and scarcer due to the ever-increasing population, climate change, and other human activities. Hence, assessing the consumption of freshwater by different consumers is a key to efficiently utilize the resource. In this study, the Water Footprint Assessment (WFA) tool was used to determine the water footprint (WF) of Center Pivot (CP) irrigated cotton and mung-bean production using two approaches, namely, CROPWAT and field-data based methods. Based on the CROPWAT-based estimates, the average total WF of cotton was found to be 2745 m/ton. Out of this, the green and blue WF contributed to an average of 35% and 65 %, respectively. For mung-bean, the total WF was 6561m/ton, of which blue WF covered around 93 %. Comparison of the blue WF from CROPWAT and field-data based estimates showed a good agreement (nRMSE = 4.5 %, nMBE = 10.7 % and relative error/RE/ranging from 0.8 to 17% for cotton and 12.6% for mung-bean) and no significant difference (p = 0.456) was obtained between the two estimates. The effect of planting date on the WF estimation also showed a small variation of 0.7%-6.6 % for cotton and up to 12% for mung-bean. However, major reductions were obtained on the blue WF of cotton and mung-bean as a result of changing planting dates by about two months prior to the baseline planting dates. In this study, it is concluded that WF assessment could be satisfactorily estimated using CROPWAT model if supported with field obtained information such as soil, crop, and weather data. Another finding of the present study was that, changing planting dates close to the major rainy months could substantially contribute to reducing the blue WF in similar climates.
由于人口不断增长、气候变化和其他人类活动，全球淡水资源日益稀缺。因此，评估不同消费者的淡水消耗量是有效利用该资源的关键。在本研究中，采用水足迹评估（WFA）工具，通过CROPWAT和基于田间数据的两种方法，确定中心支轴（CP）灌溉棉花和绿豆生产的水足迹（WF）。基于CROPWAT估算，棉花的平均总水足迹为2745立方米/吨。其中，绿水足迹和蓝水足迹分别平均占35%和65%。对于绿豆，总水足迹为6561立方米/吨，其中蓝水足迹约占93%。CROPWAT估算的蓝水足迹与基于田间数据的估算结果比较显示出良好的一致性（棉花的标准化均方根误差/nRMSE = 4.5%，标准化平均偏差/nMBE = 10.7%，相对误差/RE/范围为0.8%至17%，绿豆为12.6%），两种估算之间未获得显著差异（p = 0.456）。种植日期对水足迹估算的影响也显示，棉花的变化幅度较小，为0.7% - 6.6%，绿豆高达12%。然而，由于种植日期比基线种植日期提前约两个月，棉花和绿豆的蓝水足迹大幅减少。本研究得出结论，如果有土壤、作物和天气数据等田间获取的信息支持，使用CROPWAT模型可以令人满意地估算水足迹。本研究的另一个发现是，在类似气候条件下，将种植日期接近主要雨季可大幅有助于减少蓝水足迹。
