Irrigation water productivity is more influenced by agronomic practice factors than by climatic factors in Hexi Corridor, Northwest China

Abstract

Quantifying the influence of driving factors on irrigation water productivity (IWP) is vital for efficient agricultural water use. This study analyzed contributions of agronomic practice and climatic factors to the changes of IWP, based on the data from 1981 to 2012 in Hexi Corridor, Northwest China. Cobb-Douglas production functions were developed by the partial least squares method and contribution rates of the driving factors were calculated. Results showed that IWP and its driving factors increased during the study period, with different changing patterns. IWP was significantly correlated with the agronomic practice factors, daily mean temperature and solar radiation of the crop growing period. The agronomic practice factors including irrigation, fertilization, agricultural film, and agricultural pesticide contributed 20.6%, 32.8%, 42.3% and 11.1% respectively to the increase of IWP; and the contribution rates of the climatic factors, i.e. daily mean temperature and solar radiation, are −0.9% and 0.9%. And the contributions of these factors changed in different sub-periods. It is concluded that agronomic practice factors influenced IWP much more than climatic factors. The improvement of IWP should rely on advanced water-saving technology and application of optimum (need-based) fertilizer, agricultural film and pesticide, ensuring efficient use of agronomic inputs in the study area.

An Integrated Water-Saving and Quality-Guarantee Uncertain Programming Approach for the Optimal Irrigation Scheduling of Seed Maize in Arid Regions

“…Although the yield may increase to some extent, the seed quality could not be guaranteed and the corresponding irrigation scheduling would not be acceptable by decision-makers. The results from model (9) showed that the obtained yield was within the bounds of models (7) and (8); therefore, the results of model (7) were reasonable. However, there was only one strategy from model (9) that corresponded to one group value of ET m and EP.…”

“…The local climate features typical arid characteristics including low precipitation (50-150 mm/year) and high evaporation (1500-2500 mm/year) [9,33,34]. The seed maize has five growth stages, including establishment, vegetative, flowering, yield-formation, and ripening.…”

“…Finally, a certain optimization model without consideration of seed quality or any uncertainty was compared. The two latter models can be described by the following models (8) and (9). The parameters of model (9) are listed in Table 6.…”

Effects of irrigation scheduling and different irrigation methods on onion and water productivity in Tigray, northern Ethiopia

“…This has been drawing the attention of researchers for increasing the productivity of onion crop in the region via introducing efficient irrigation water management strategies. Several studies [27][28][29][30] showed that among the different irrigation methods, drip and sprinkler irrigation methods increases the yield of onion and water productivity. However, due to lack of technical knowledge, high labour demand, and poor extension services, these irrigation methods are not well adapted and farmers are distrustful to their acceptance [14].…”

Water Use Efficiency of Rice and Soybean Under Drip Irrigation With Mulch in the South-East of Kazakhstan

“…Irrigated agriculture, the major contributor of agricultural production, faces the challenge of improving irrigation water use efficiency and meanwhile ensuring food security (Li et al, 2016a). The global water consumption for irrigation has been steadily growing over the last 50 years and today it makes 70% of all water consumption (Tian et al, 2016).…”