Water Use Characteristics of Weeds: A Global Review, Best Practices, and Future Directions

Weeds usually penalize crop yields by competing for resources, such as water, light, nutrients, and space. Most of the studies on the crop-weed competition domain are limited to assessing crop-yield losses due to weed pressure and other crop-weed interactions, overlooking the significant uptake of soil-water by weeds that exacerbates global water constraints and threatens the productivity and profitability. The objective of this review was to synthesize globally available quantitative data on weed water use (WU) sourced from 23 peer-reviewed publications (filtered from 233 publications via a multi-step protocol of inclusion criteria) with experimental investigations across space (3 continents), time (1927–2018), weed species (27 broadleaf and 7 grasses) and characteristics, cropping systems (5), soil types (ranging from coarse-textured sand to fine-textured clay soils), determination techniques, experimental factors (environment, management, resource availability, and competition), and aridity regimes (ranging from semi-arid to humid climate). Distributions of weed WU data reported via eight different metrics were assessed for variability and mean WU. A lack of the best experimental and reporting practices in weed WU research was identified that undermined the robustness, transferability, and application of the WU data. Mandatory protocols and the best practices typically followed in the agricultural water management research were described and recommended for weed scientists to avoid pitfalls in quantifying and presenting weed WU. A model of mixed plant community evapotranspiration (ET) was adapted to model weed-crop-soil system evaporation and transpiration in a crop canopy infested with multiple (n) weed species. Finally, potential cross-disciplinary questions across the domains of crop science, weed science, agricultural water management, irrigation science and engineering, and environmental changes were proposed to direct and prioritize future research efforts in the crop-weed-water arena.

Comparison of Crop Evapotranspiration and Water Productivity of Typical Delta Irrigation Areas in Aral Sea Basin

The intensity of agricultural activities and the characteristics of water consumption affect the hydrological processes of inland river basins in Central Asia. The crop water requirements and water productivity are different between the Amu Darya and Syr Darya river basins due to the different water resource development and utilization policies of Uzbekistan and Kazakhstan, which have resulted in more severe agricultural water consumption of the Amu Darya delta than the Syr Darya delta, and the differences in the surface runoff are injected into the Aral Sea. To reveal the difference in water resource dissipation, water productivity, and its influencing factors between the two basins, this study selected the irrigation areas of Amu Darya delta (IAAD) and Syr Darya delta (IASD) as typical examples; the actual evapotranspiration (ETa) was retrieved by using the modified surface energy balance algorithm for land model (SEBAL) based on high spatial resolution Landsat images from 2000 to 2020. Land use and cover change (LUCC) and streamflow data were obtained to analyze the reasons for the spatio-temporal heterogeneity of regional ETa. The water productivity of typical crops in two irrigation areas was compared and combined with statistical data. The results indicate that: (1) the ETa simulated by the SEBAL model matched the crop evapotranspiration (ETc) calculated by the Penman–Monteith method and ground-measured data well, with all the correlation coefficients higher than 0.7. (2) In IAAD, the average ETa was 1150 mm, and the ETa had shown a decreasing trend; for the IASD, the average ETa was 800 mm. The ETa showed an increasing trend with low stability due to a large amount of developable cultivated land. The change of cultivated land dominated the spatio-temporal characteristics of ETa in the two irrigation areas (3). Combined with high spatial resolution ETa inversion results, the water productivity of cotton and rice in IAAD was significantly lower than in IASD, and wheat was not significantly different, but all were far lower than the international average. This study can provide useful information for agricultural water management in the Aral Sea region.

Agricultural Water Use Efficiency: Is There Any Spatial Correlation between Different Regions?

Affected by global climate change and water shortages, food security continues to be challenged. Improving agricultural water use efficiency is essential to guarantee food security. China has been suffering from water scarcity for a long time, and insufficient water supply in the agricultural sector has seriously threatened regional food security and sustainable development. This study adopted the super-efficiency slack-based model (SBM) to measure the provincial agricultural water use efficiency (AWUE). Then, we applied the vector autoregression (VAR) Granger causality test and social network analysis (SNA) method to explore the spatial correlation of AWUE between different provinces and reveal the interprovincial transmission mechanism of spillover effects in AWUE. The results show the following: (1) In China, the provincial AWUE was significantly enhanced, and the gaps in provincial AWUE have widened in the past 20 years. (2) There were apparent spatial heterogeneity and correlations of provincial AWUE. The provinces with higher AWUE were mainly located in economically developed and coastal areas. (3) The correlation of AWUE between provinces showed significant network structure characteristics. Fujian, Hebei, Jiangsu, Shandong, and Hubei Qinghai were central to the network, with high centrality. (4) The AWUE spatial correlation network could be divided into four blocks. Each block played a different role in the cross-provincial transmission of spillover effects. Therefore, it is necessary to manage the agricultural water resources and improve water use efficiency from the perspective of the network.