Water Use Efficiency and Sensitivity Assessment for Agricultural Production System from the Water Footprint Perspective

Abstract

The increasing shortage of water resources and the growing demand for crops make water use efficiency a decisive factor for the sustainable and healthy development of the agricultural system. In order to evaluate agricultural water use efficiency from the water footprint perspective, the current study constructed the comprehensive water efficiency (CWE) index based on eight single agricultural water use efficiency performance parameters. The water resources utilization and efficiency in the wheat production system of China from 2006 to 2015 were analyzed and the sensitivity of single indices for CWE was identified. The results show that the national crop water footprint (CWF) for wheat production was estimated to be, including 46.3% blue, 36.6% green and 17.0% blue components, respectively. The spatial distribution patterns of water use efficiency performance indices were different. CWE of the country was 0.387, showing an upward trend over time and decreased from the southeast to the northwest geographically. Crop water productivity (CWP), productive water ratio (PWR) and rainwater consumption ratio (RCR) turned out to be the first three sensitive parameters for CWE in China. The improvement of China’s overall CWE relied on reducing inefficient blue-green water use and increasing the output capacity for per unit water. Advanced agricultural water-saving technologies were in high need for goal achievement, especially for the Huang-Huai-Hai plain, which held more than 70% of Chinese wheat production and CWF. The results provide support for efficient utilization and sustainable development of water resources in the agricultural system.

Irrigation Scheme Selection Based on Water Footprint Analysis of Winter Wheat Production in Piedmont Plains of Hebei Province under Future Climate Scenarios

“…In the view of the restricted water resource and its storage in the piedmont plain area in Hebei Province, a high yield should not be the top priority of winter wheat production in this area under future climate conditions, and achieving an 'acceptable yield' should be the main objective [31,38,39]. In the production mode of 'irrigation once in spring', the irrigation rate of 95 mm in the jointing period was the optimal irrigation scheme, and this irrigation rate was the lowest to achieve the acceptable yield of 500 km per mu for winter wheat in this area.…”

“…The precipitation exhibited changes in different directions in these two future climate scenarios, with a decrease of 7.52 mm in scenario A2 and an increase of 6.86 mm in scenario B2. [31], the Genotype program was used to prepare the initial variety parameter file for model calibration. In view of the manifestation of growth characteristics of Jimai 583, the manually defined data ranges and the improved Clue program were used to calibrate the variety parameters of the test wheat variety with the trial-and-error method on the basis of the phenophase and yield data of winter wheat.…”

Green Water Resource Utilization Efficiency in Urban Agglomerations: Measurement, Spatiotemporal Variations and Influencing Factors

“…The geographical detector model (GDM) was proposed by Wang et al (2020) based on spatial variance analysis, which is a novel statistical method used to reveal the driving factors of the spatial variation of geographical elements. This method has been widely applied to quantify the influence of potential driving factors on geospatial elements (Wu et al, 2016; Zhou et al, 2018a; Bai, 2019; Luo et al, 2019; Wei et al, 2020; Fang et al, 2021; Song and Wu, 2021).…”

Green water resource utilization efficiency in urban agglomerations: measurement, spatiotemporal variations and influencing factors

“…The geographical detector model (GDM) was proposed by Wang et al (2020) based on spatial variance analysis, which is a novel statistical method used to reveal the driving factors of the spatial variation of geographical elements. This method has been widely applied to quantify the influence of potential driving factors on geospatial elements (Wu et al 2016;Zhou et al 2018a;Luo et al 2019;Bai et al 2019;Wei et al 2020;Song and Wu 2021;Fang et al 2021).…”

“…With the continuous expansion and development of urban agglomerations, the demand for water resources is increasing, and the contradiction between water resource demand and supply is becoming increasingly prominent, which brings serious pressure to the sustainable utilization of water resources in urban agglomerations. However, improving water use efficiency and saving water are regarded as fundamental ways to alleviate the contradiction between the supply and demand of water resources (Wang et al 2020). Therefore, it is important to quantify the water resource utilization efficiency (WRUE) in urban agglomerations and identify potential ways to improve it and thus promote the sustainable development of the society, economy and water resources utilization in a region.…”