The prevalence and proliferation of antibiotic resistance genes (ARGs) has been identified as an emerging contaminant of concern and a crucial threat to public health worldwide. To determine the occurrence and distribution of ARGs in artificial agricultural irrigation systems, we designed eight sample sites of farmland drainage in the Hetao Irrigation District, Inner Mongolia, China. Results indicated that the distribution of ARGs in sub-drainage canals is influenced by the local urban area, agriculture, and animal husbandry structure. The blaTEM gene was predominant in the water samples (up to 8.98 ARG copies/16S rRNA genes). The average ARG abundance in drainage channel sampling sites was significantly higher than the influent water from the Yellow River, which means that the artificial agricultural irrigation system enhances the abundance of resistance genes in the study area. Moreover, the effluent water of the whole irrigation system presented a lower abundance of ARGs than the influent water. This demonstrates that the Wuliangsuhai watershed ecosystem plays an important role in regulating the abundance of ARGs in the area. In our study, the mobile gene elements correlated with trB, emrD, mexF, and vanC (P < 0.001) in the irrigation system. Additionally, different correlations exist between other special subtypes of ARGs. These findings provided deeper insights into mitigating the propagation of ARGs and the associated risks to public health.

This study investigates the impacts of climate change on yield of selected cereal crops (wheat and maize) in the northern climatic region of Khyber Pakhtunkhwa (KP) province of Pakistan for the period 1986–2015. The first-generation unit root tests such as the Levin, Lin, and Chu (LLC), augmented Dickey-Fuller (ADF)–Fisher, and the second-generation unit root tests such as cross-sectional augmented Im-Pesaran-Shin (CIPS) and cross-sectional ADF (CADF) are used to check stationarity of the series. The cointegration among the variables is discovered via Pedroni test and Westerlund method. The long- and short-run impacts of climatic variables (average precipitation, maximum temperature, and minimum temperature) on yield of wheat and maize crops are assessed through the autoregressive distributed lag (ARDL) model. The empirical findings reveal that average precipitation has a significantly positive impact on yield of both crops in long- as well as short-run. The results further reveal that the effect of average minimum temperature on both crops is insignificant in long-run. However, the short-run effect of average minimum temperature is significantly positive on yield of maize crop but insignificant on yield of wheat crop. In long-run, an increase in average maximum temperature negatively affects crop yield. In short-run, however, it positively affects the yield of wheat and maize crops. The study recommends that increase in area under cultivation, development of advanced irrigation system, and farmers’ access to metrological information will help in lowering the drastic impacts of climate change on crop productivity.

One of the strategies for agricultural development is the optimal use of irrigation and drainage networks, which leads to higher productivity and economic benefits. In this regard, quantitative and qualitative studies of drainage water from networks are essential for efficient water management. In the present study, we develop a model using a system dynamics approach to simulate the cropping pattern of an irrigation and drainage network as well as the discharge and salinity of drainage water from network farms. We apply the Powell algorithm to optimize the economic profitability of cultivated crops by considering the salinity and discharge of drainage water from the fields. With three aims, i.e., (1) maximizing benefit–cost ratio, (2) minimizing drainage water salinity and discharge of network, and (3) economic and environmental considerations simultaneously, the optimization of cropping pattern within the Kosar irrigation and drainage network is performed. Results based on five consecutive years under different scenarios showed that some crops, such as watermelon, are not economically recommened for production due to high costs, water consumption, and low selling price causes environmental pollution. On the other hand, wheat, grain maize, silage maize, sorghum, and alfalfa have different conditions, and their production is suitable by considering all scenarios. By comparing with experimental data, we find that the proposed model is accurate to simulate and optimize the irrigation network and to detect its cropping pattern.

Two field experiments were conducted to evaluate six Salicornia species (Salicornia bigelovii Torr., S. europaea L., S. persica Gorgan ecotype, S. persica Urmia ecotype, S. sinus persica Bushehr ecotype, and S. persica Central Plateau ecotype) at different planting dates and densities under irrigation with Persian Gulf water. Evaluated planting dates were 14 November and 18 December 2016 and 16 January, 8 February, 8 March, and 28 March 2017. Examined planting densities included 13, 20, and 40 plant m⁻². Only S. bigelovii and S. europaea produced measurable yield in all planting dates. The highest dry weight (651.1 gm⁻²) was obtained in S. sinus persica (Bu) planted on 8 February. Dry weight of S. bigelovii, S. europaea, S. sinus persica Bushehr, S. persica Central Plateau, S. persica Gorgan, and S. persica Urmia planted on 8 March were 174.2, 220.7, 542.5, 240.9, 158.0, and 147.5 g m⁻², respectively. The ash contents of S. bigelovii, S. europaea, S. sinus persica Bushehr, S. persica Central Plateau, S. persica Gorgan, and S. persica Urmia were 46.3%, 45.0%, 49.6%, 49.6%, 50.0%, and 53.1%, respectively. Sodium and chloride contents of different Salicornia species varied from 13–15% and 16–17%, respectively. The oilseed content of S. bigelovii and S. sinus persica Bushehr was about 24.0% for both species. The highest and lowest dry weight, from the second experiment, were for S. sinus persica Bushehr and S. persica Central Plateau, respectively, in all planting density. The highest dry weight equal to 1336.2 gm⁻² was obtained for S. sinus persica Bushehr in 40 plant m⁻² density. Under such conditions, forage production potential of Salicornia is more achievable rather than seed production. Nevertheless, high ash content is a serious constraint to direct consumption by livestock; therefore, determining the nutritional value of Salicornia fodder requires further evaluations.

The objective of this study is to evaluate the water quality of the Lien Son irrigation system in Vietnam and identify the critical pollutants that affect the system’s water quality. Firstly, the water quality at fifteen locations distributed along the main Lien Son drainage and irrigation canals was monitored in the dry season (from January to March) for 3 consecutive years (2018, 2019, and 2020) to collect nine physical, chemical, and microbiological parameters. And then, principal component analysis (PCA) and factor analysis (FA) were applied to extract and identify the critical pollutants which helps to preliminarily detect the potential pollution sources to the irrigation system. Results of PCA and FA showed the principal groups of pollutants which had a significant influence on the water quality of the system. Sampling locations LS7 and LS8 had the heaviest pollution. The primary factors that influenced the pollution of the system were organic matter (COD and BOD₅), nutrients (N-NH[Formula: see text] and P-PO[Formula: see text]), sediment transport (turbidity and TSS), and coliform. These factors are usually associated with the sources of domestic wastewaters and agricultural runoff from the vicinity. This suggested that urgent actions should be taken to control domestic wastewaters and agricultural runoff from the vicinity so that they could not deteriorate the water quality of the system.

The arsenic contamination of Bangladesh groundwater involves heavy arsenic inputs to irrigated rice fields. Beside adsorption on soil colloids, iron-arsenic co-precipitation phenomena can affect arsenic retention in soils. In paddy fields of Satkhira District, Bangladesh, the study of the arsenic and iron forms in the irrigation waters and in soils at different times and distances from the irrigation well evidenced that a higher Fe/As ratio in the well water was related to a faster oxidation of Fe(II) and As(III) in water and to a close Fe-As association in soils, together with a greater accumulation of arsenic and poorly ordered iron oxides. The concentration of arsenic and of labile iron forms decreased with the distance from the well and with the depth, as well as the reversibility of arsenic binding. The fate of the arsenic added to the soils by irrigation hence resulted strongly influenced by iron-arsenic co-precipitation, depending on the Fe/As ratio in water. Irrigation systems favouring the sedimentation of the Fe-As flocks could help in protecting the rice from the adverse effects of dissolved arsenic.

Climate change, conventional agricultural management practices, and increasing water scarcity pose a major threat to agricultural production and biodiversity as well as environmental sustainability. Climate-smart agriculture (CSA) is recognized as an efficient, sustainable, and feasible agricultural system that plays a vital role in addressing the potential impacts of climate change in Pakistan. First-hand information was collected from 450 farm households in 24 villages from Okara, Sahiwal, and Khanewal irrigation divisions, having various wheat-based cropping systems of Pakistan. This includes rice–wheat (RW), maize-wheat (MW), and cotton-wheat (CW) cropping systems in the Lower Bari Doab Canal (LBDC) irrigation system. This study estimated and compared the sustainability and efficiency analysis of CSA and conventional agricultural practices. This study also estimated the impact of water-smart practices of the CSA, technical training, and groundwater quality on agricultural production by using production function and bootstrap truncated regression. The findings of this study revealed that adopters of CSA of the wheat-based cropping systems have higher economic benefits and improved resource use efficiencies compared to the conventional farmers. The findings of the study also revealed the increased efficiency of CSA adopters over other two systems in CW cropping system. The water-smart practices of CSA, access to credit, technical training, use of groundwater of varying quality, and other inputs also showed variations in the agricultural production and resource use efficiency. It has been concluded that farmers can earn more profit, save inputs (such as water), and increase their production by adopting water-smart practices of CSA. Hence, the government and other relevant institutions should devise and implement policies that adequately addressed the importance and enhance the use of water-smart practices of CSA in Punjab and beyond.

Water is the most fundamental need for better yield in agriculture. Worldwide, diesel and electricity are typically used to pump water which contributes to atmospheric pollution. Besides, a power outage affects the irrigation process badly. Without water, the crop may wither away, causing a substantial economic loss. This paper discusses the resilience of a solar PV system during a power outage. HOMER Pro software was used to perform the techno-economic analysis of solar-based irrigation for four major divisions of Bangladesh, while 1-hour power outage was assigned in REopt lite to model the survivability of the system against the grid outage. The simulation outcomes showed that the energy cost is $0.1496/kWh, $0.1502/kWh, $0.1557/kWh, and $0.1576/kWh for Rajshahi, Sylhet, Dhaka, and Chattogram, respectively. About 45% of excess electricity can be stored after fulfilling all requirements. The system is more economical than a microgrid-based water pumping system and a diesel-based system, and the photovoltaic system is technically and economically suitable to pump water if the nearest grid connection is impossible. When connected to the main utility grid, the system can survive without grid power for several hours, subject to daytime outages.

Enhancement of water use efficiency (WUE) is considered highly important to cope with the water scarcity challenges in dry regions. Therefore, this study evaluated spatiotemporal characteristics of WUE and its related drivers in the Ω-shaped Region along the Yellow River aiming to provide decision support information for alleviating water shortages in this region. We employed the SBM-DEA (slacks-based measure-data envelopment analysis) model to calculate the WUE considering undesired outputs, analyze temporal and spatial variation based on GIS and statistical methods, and investigate the various factors that influence WUE based on the generalized method of moment (GMM) model. The results are as follows. (1) The WUE followed an increasing–decreasing-increasing trend, suggesting that the expanding agricultural and the second industrial structures are largely dominated by water-intensive activities which add further pressure on the water resources. (2) The spatial discrepancy of WUE among the cities is significant; however, the spatial pattern changes were stable during 2010 to 2019. (3) Analysis of influencing factors provides solutions for improving WUE in the Ω-shaped Region. Irrigation system and water conservancy infrastructure development and the acceleration of industrial transformation are necessary for improving the WUE in the Ω-shaped Region.