Agricultural Water Research Articles

Extreme Precipitation Events During the Wet Season of the South America Monsoon: A Historical Analysis over Three Major Brazilian Watersheds

Most of South America, particularly the region between the southern Amazon and southeastern Brazil, as well as a large part of the La Plata Basin, has its climate regulated by the South American Monsoon System. Extreme weather and climate events in these areas have significant socioeconomic impacts. The Madeira, São Francisco, and Paraná river basins, three major watersheds in Brazil, are especially vulnerable to wet and drought periods due to their importance as freshwater ecosystems and sources of water for consumption, energy generation, and agriculture. The scarcity of surface meteorological stations in these basins makes meteorological studies challenging, often using reanalysis and satellite data. This study aims to identify extreme weather (wet) and climate (wet and drought) events during the extended wet season (October to March) from 1980 to 2022 and evaluate the performance of two gridded datasets (CPC and ERA5) to determine which best captures the observed patterns in the Madeira, São Francisco, and Paraná river basins. Wet weather events were identified using the 95th percentile, and wet and drought periods were identified using the Standardized Precipitation Index (SPI) on a 6-month scale. In general, CPC data showed slightly superior performance compared to ERA5 in reproducing statistical measures. For extreme day precipitation, both datasets captured the time series pattern, but CPC better reproduced extreme values and trends. The results also indicate a decrease in wet periods and an increase in drought events. Both datasets performed well, showing they can be used in the absence of station data.

A comparative analysis of deep-learning models for dam discharge forecasting for disaster management

ABSTRACT This paper represents a comprehensive study of dam water discharge prediction using various deep-learning models. The main aim of this paper is to provide a data-driven solution for effective water resource management and thereby controlling the effects of floods and droughts. The Malampuzha dam, which has a spillway, a right bank canal (RBC), and a left bank canal (LBC), is considered for the study. While the spillway helps to control the water level in the reservoir by allowing extra water to flow downstream during times of severe rainfall or high inflow, hence reducing the risk of floods, the LBC and RBC are intended to divert water for agriculture. Altogether, 10 years of consecutive meteorological and dam-related data are utilized for training and testing the models in forecasting water discharge through LBC, RBC, and the spillway. Different deep-learning models, namely, long short-term memory, Bi-directional long-short term memory, recurrent neural network, gated recurrent unit, one-dimensional convolutional neural network (1D-CNN), deep neural network, autoencoder, and residual networks are explored in predicting the accuracy of dam water discharge. After testing eight deep-learning models, it was discovered that 1D-CNN performed well in predicting the discharge of water.

Precision Agriculture and Water Conservation Strategies for Sustainable Crop Production in Arid Regions

The intensifying challenges posed by global climate change and water scarcity necessitate enhancements in agricultural productivity and sustainability within arid regions. This review synthesizes recent advancements in genetic engineering, molecular breeding, precision agriculture, and innovative water management techniques aimed at improving crop drought resistance, soil health, and overall agricultural efficiency. By examining cutting-edge methodologies, such as CRISPR/Cas9 gene editing, marker-assisted selection (MAS), and omics technologies, we highlight efforts to manipulate drought-responsive genes and consolidate favorable agronomic traits through interdisciplinary innovations. Furthermore, we explore the potential of precision farming technologies, including the Internet of Things (IoT), remote sensing, and smart irrigation systems, to optimize water utilization and facilitate real-time environmental monitoring. The integration of genetic, biotechnological, and agronomic approaches demonstrates a significant potential to enhance crop resilience against abiotic and biotic stressors while improving resource efficiency. Additionally, advanced irrigation systems, along with soil conservation techniques, show promise for maximizing water efficiency and sustaining soil fertility under saline–alkali conditions. This review concludes with recommendations for a further multidisciplinary exploration of genomics, sustainable water management practices, and precision agriculture to ensure long-term food security and sustainable agricultural development in water-limited environments. By providing a comprehensive framework for addressing agricultural challenges in arid regions, we emphasize the urgent need for continued innovation in response to escalating global environmental pressures.

Nuclear abnormalities and DNA damage indicate different genotoxic stress responses of marsh frogs (Pelophylax ridibundus, Pallas 1771) to industrial and agricultural water pollution in South Bulgaria.

Amphibians are continuously exposed to pollutants and anthropogenic stressors in their natural habitats, representing a significant challenge to their survival. This study aimed to quantify the extent of DNA damage caused by chronic industrial and agrochemical surface water pollution in wild populations of the marsh frog (Pelophylax ridibundus). The observed genotoxic effects on the marsh frog DNA, manifesting as abnormalities in erythrocyte nuclei, micronuclei, and DNA strand breaks, demonstrate a clear cause-and-effect relationship with surface water parameters, heavy metals, metalloids, and pesticides. The most prevalent nuclear abnormalities observed were notched and blebbed nuclei and nuclear buds, indicative of chromosomal instability. The significant correlation between cadmium, lead, and copper contamination and the increased frequency of DNA breakage in the marsh frogs from the industrial site indicates that heavy metal contamination has a higher genotoxic potential than pesticide contamination. These findings underscore the vulnerability of amphibians inhabiting heavy metal-contaminated wetlands to genotoxic stress due to their lower tolerance to environmental genotoxins. Therefore, using in situ assays to detect erythrocyte nuclear abnormalities and DNA damage in P. ridibundus could serve as a reliable indicator of environmental quality and provide early detection of anthropogenic pollution.

Multi-Dimensional Assessment, Regional Differences, and Influencing Factors of Agricultural Water Pollution from the Perspective of Grey Water Footprint in Zhejiang Province, China

The implementation of differentiated governance for agricultural water pollution (AWP) plays a significant role in alleviating the pressure on agricultural water resources. However, research that comprehensively assesses AWP and its influencing factors from a multidimensional perspective remains relatively limited. This study utilized the grey water footprint (GWF) model to quantify the agricultural grey water footprint (AGWF), agricultural grey water footprint efficiency (AGWFE), agricultural grey water footprint intensity (AGWFI), and agricultural water pollution level (AWPL) in Zhejiang from 2010 to 2020. Subsequently, we applied the standard deviational ellipse (SDE), the kernel density estimation (KDE), and the Dagum Gini coefficient to delve into the dynamic evolution and regional disparities of these indicators. Ultimately, we leveraged both the random forest model and the panel regression model to identify and examine the key factors shaping AGWF-related indicators. The results show that: (1) From 2010 to 2020, in Zhejiang, both AGWF and AGWFI exhibit a trend of first increasing and then decreasing, peaking in 2012. In contrast, AGWFE has consistently increased over the years, reaching an increase of 54.56 CNY/m3 by 2020. Meanwhile, despite fluctuations, AWPL in Zhejiang shows an overall gradual decline. (2) The centroids of relevant indicators for AWP in Zhejiang are primarily located in Jinhua (for AGWF and AGWFI), Shaoxing (for AWPL), and in the area where AGWFE converge. (3) Compared to 2010, the regional disparities in AGWF and AWPL have shrunk significantly in 2020, whereas the regional differences in AGWFE and AGWFI have increased to some extent. In most years, the regional disparities in AGWF, AGWFI, and AWPL are more pronounced in Northeastern Zhejiang compared to the southwestern part. (4) The influencing factors of AGWF, AGWFE, and AGWFI exhibit significant regional heterogeneity. In Northeastern Zhejiang, the primary factors influencing them are technological innovation, resource endowment, and crop-cultivation methods. Conversely, in the southwestern region, the primary factors exerting the same influence are the application intensities of fertilizers, pesticides, and agricultural film application. The primary drivers of AWPL in Zhejiang are grain yield, water resource availability, and crop-planting structure. Notably, these factors do not exhibit regional heterogeneity. The paper proposes AWP control policies from both a comprehensive and multi-dimensional perspective.

Agricultural Water Conservation Methods: Application, Difficulties, and Innovation

The largest growth in water usage among water-using industries has been in agriculture due to the growing need for agricultural goods to feed the world's expanding population. Presently, agricultural water conservation encompasses a range of technologies that are mostly grounded in human understanding, but also include a number of complex strategies that significantly rely on cutting-edge mechanical and electrical techniques. Modern agronomic practices like precision agriculture may conserve water. Precision agriculture is a modern agronomic strategy that may preserve water.Modern agricultural investments, land transfers, and urbanisation have left these irregular and traditionally built villages with an ambiguous and ever-changing land use pattern. This may hinder water-saving adoption. In addition to taking into account the growth of the agricultural sector, the agricultural water management policy prioritises the long-term ecological economy and the sustainability of the water resource supply network. Water needs are predicted to rise significantly by the end of the twenty-first century, particularly for irrigation. Reducing the amount of water used in agriculture is crucial. With temperatures rising and droughts occurring more frequently in many nations, water is a vital component of agricultural output. Certain technology-based practices coupled with efficient farmers and humans management of water resources will be the key features for improving water conservation.

Assessing the impact of agriculture value chains on food and water environments in Meerut District, India

AbstractWater and food are interconnected elements crucial for agricultural production and food security. While sufficient water resources have facilitated significant food production, intensive agricultural practices have contributed to the degradation of water resources. Agriculture value chains play a pivotal role in shaping food systems and can lead to virtual water movement through the production and trade of water-intensive crops. These chains affect both water and food environments, with water being a driver and food determining factors like availability and accessibility. Despite the economic benefits, agriculture value chains pose non-economic challenges, including environmental and social impacts. The focus on profitability often overlooks sustainability and equity concerns, leading to mono cropping and exclusion of small farmers from markets. This trend is evident in Meerut district, situated in the fertile Indo Gangetic plain and a top farming state in India. Despite its agricultural potential, the district has shifted towards sugarcane monoculture, impacting water and food environments. This study aims to explore the complex relationship between agriculture value chains, water sustainability, food availability and accessibility. The objectives include understanding these interlinkages, analyzing baseline scenarios, and assessing the implications of value chains on food and water environments. The analysis reveals the adverse effects of sugarcane monoculture on water environment, food environment and agricultural sustainability. To address these challenges, the study puts a way forward to adopt value chains approach for the strategical promotion of crop diversification, emphasizing resilience and sustainability.

Influence of Farmer’s Income Level on Adoption of Agricultural Water Management Practices among Smallholder Farmers in Rongai Sub-county, Kenya

Water is a resource that cannot be replaced and can only be renewed if it is well managed. It is basic for all forms of life, for every aspects of socio-economic development, and for the maintenance of a healthy ecosystem. Agriculture is the biggest water user globally, accounting for 70 percent of total water withdrawals on average. There are different practices that can aid in managing water used for agriculture. Some of these agricultural water management practices are; rainwater harvesting, irrigation, organic farming, and use of drought resistant crops. Farmer’s decision to either adopt or reject these practices can be affected by several factors, some of which are socio-economic. Some of the socio-economic factors that may influence adoption of these practices include farmer’s educational level, income level and farm size. This study examined the influence of farmer’s income level on adoption of agricultural water management practices (Rainwater harvesting, Irrigation Drought resistant crops). Cross-sectional survey design was adopted, while proportionate and simple random sampling technique was used to obtain the respondents. The accessible population was 6,230 smallholder farmers from the target population of 26,804 smallholder farmers in Rongai sub county Kenya. The study was done in August 2023 to November 2023.The study included 120 smallholder farmers in Rongai Sub County. The study used questionnaire to collect data while binary logistic regression was used to analyze the data. The results indicated that adoption of agricultural water management practices is low, only 36% of smallholder farmers had adopted agricultural water management practices. The P value calculated for the 120 smallholder farmers was P=.033 which is < than .05 and therefore the null hypothesis was rejected concluding that in this study income level had statistically significant influence on adoption of agricultural water management practices among smallholder farmers in Rongai sub-county in Nakuru ,Kenya. The findings may help in emphasizing the necessity of assisting farmers in removing financial obstacles that may hinder adoption of agricultural water management practices.

Interannual variations of normalized difference vegetation index and potential evapotranspiration and their relationship in the Baghdad area

Abstract A monthly correlation between urban vegetation growth and potential evapotranspiration (PET) is needed for better knowledge of controlling water resources and organized irrigation processes. This study aims to explore their relationship within an urban area like Baghdad, using a linear regression model to derive a best-fit line drawn in a scatterplot on a monthly time scale. Based on two different monthly data sources: weather variables (e.g., air temperature, solar radiation, and relative humidity) and Sentinel-2 satellite imagery of 2 years, 2018 and 2021, this study presented the interannual variations of PET and normalized difference vegetation index (NDVI). The choice of these years has a significant feature of climatic differences, which are arid and semi-arid, respectively. PET values were estimated by the Truc method, while the areas of vegetation (represented by NDVI) were calculated using the Geographic Information Sensing program. The results show that the maximum PET in both years was found in the summer months (June and July) with mean values of about 8.8 mm/day, while their minimum mean values of about 1.5 mm/day occurred in winter months (January and December). From the spatial distribution of NDVI, it was found that at positive pixels when NDVI >0.2, vegetation cover in March, April, and December 2018 had large areas with more than 200 km2 in 2018, while they were largest only in May 2021 with 197.8 km2. There was a linear correlation with slope (0.03) and intercept (= 1.8) and a strong correlation, R 2 = 0.72. The practical implications of the findings contribute to enhancing a solid scientific basis for improving agricultural water management, especially under dry conditions.

Persistence of Microcystin in Three Agricultural Ponds in Georgia, USA

Cyanobacteria and their toxins can have multiple effects on agricultural productivity and water bodies. Cyanotoxins can be transported to nearby crops and fields during irrigation and may pose a risk to animal health through water sources. Spatial and temporal variations in cyanotoxin concentrations have been reported for large freshwater sources such as lakes and reservoirs, but there are fewer studies on smaller agricultural surface water bodies. To determine whether spatiotemporal patterns of the cyanotoxin microcystin occurred in agricultural waters used for crop irrigation and livestock watering, three agricultural ponds on working farms in Georgia, USA, were sampled monthly within a fixed spatial grid over a 17-month period. Microcystin concentrations, which ranged between 0.04 and 743.75 ppb, were determined using microcystin–ADDA ELISA kits. Temporal stability was assessed using mean relative differences between microcystin concentrations at each location and averaged concentrations across ponds on each sampling date. There were locations or zones in all three ponds that were consistently higher or lower than the average daily microcystin concentrations throughout the year, with the highest microcystin concentrations occurring in winter. Additionally, microcystin patterns were strongly correlated with the patterns of chlorophyll, phycocyanin, and turbidity. The results of this work showed that consistent spatiotemporal patterns in cyanotoxins can occur in produce irrigation and livestock watering ponds, and this should be accounted for when developing agricultural water monitoring programs.

Stereo bathymetry to monitor small seasonal agriculture water ponds in ungauged areas

Abstract. Small reservoirs represent a critical water supply to farmers across semi-arid regions, but their hydrological modelling suffers from data scarcity and highly variable and localised rainfall intensities. Over 200,000 ancient rainwater harvesting reservoirs (“tanks”) exist across South India, but with their complex history, considerable size variation, and widespread distribution, understanding the hydrological role of these tanks has been difficult. Fortunately, the last decade has seen improvements in sensors and technologies that enhance our ability to assess the hydrological role of these tanks. In particular, high-resolution Digital Elevation Model (DEMs), now much easier to produce, can be used to improve the characterization of tanks and their surrounding watersheds. Here, a high-resolution DEM is created during the lowest reservoir conditions using Pléiades stereoscopy, and along with two global DEMs, compared with volume estimates from a field-derived UAV reference DEM for a set of tanks in South India. This study demonstrates that a Pléiades-derived DEM can capture accurate reservoir geometry and, when simulating water volume, achieves volumetric differences of 2–8% compared to our UAV reference data. The Pléiades-derived-DEM produced an equivalent height bias less than the expected bias for the recently launched Surface Water and Ocean Topography (SWOT) mission. Deriving high-resolution tank bathymetry from space during low-water conditions provides an opportunity to systematically and repeatably measure tank volume. These results are encouraging in efforts to utilize very high resolution DEMs chosen at an appropriate hydrological time, particularly in regions where water management and security is paramount.

An integrated approach to evaluating water contaminants and evaporation in agricultural water distribution systems

This study presents an innovative approach for assessing water quality in agricultural irrigation networks, integrating stable isotope analysis, in vivo zebrafish screening, and comprehensive chemical profiling to investigate the occurrence, transformation, and potential toxicity of organic contaminants. Stable isotope analysis was used to measure evaporation as a proxy for water residence time in the canal, while liquid chromatography-high resolution mass spectrometry (LC-HRMS) identified a range of organic compounds in water samples collected from both the irrigation canal and its source river. Results indicated a reduction in contaminant levels in the canal compared to the river, with the most significant evaporation and concentration changes occurring at a holding reservoir, suggesting that managing residence time could help reduce water loss in arid irrigation networks. The data also highlighted how evaporation, particularly during the dry, hot season, influences contaminant dynamics. Hierarchical clustering of LC-HRMS results showed notable differences between the chemical profiles of canal and river samples, indicating that irrigation systems may contribute to the degradation or removal of certain compounds. Over 60 % of detected compounds were naturally derived, with anthropogenic contaminants like pesticides and personal care products further highlighting human impacts. Priority contaminants, including DEET and 2-naphthalene sulfonic acid, likely originated from urban activities upstream. Initial screening using zebrafish embryos showed bioactivity across sites, confirming the presence of contaminants needing further examination. Correlation analysis linked natural compounds to evaporation rates, suggesting that flora and fauna play significant roles in the chemical makeup of canal water. Overall, this approach provides a comprehensive framework for monitoring irrigation water, offering insights into contaminant behavior and supporting the development of standardized methods for assessing chemical fate and ecological risks in agricultural irrigation systems.

A Copula Function–Monte Carlo Method-Based Assessment of the Risk of Agricultural Water Demand in Xinjiang, China

A Copula Function–Monte Carlo Method-Based Assessment of the Risk of Agricultural Water Demand in Xinjiang, China

Exploring the Interactions of Climate Change, Freshwater Supply, and Environmental Balance

Climate change has far-reaching implications for global freshwater availability and environmental balance. The increase in greenhouse gases from the burning of fossil fuels has triggered global climate change, affecting precipitation patterns, glacier melt and sea level rise. Parts of the United States are experiencing significant changes in precipitation patterns, with some areas experiencing frequent storms and others experiencing more prolonged droughts. Accelerated glacier melt is leading to fewer water sources during the dry season, and sea level rise is threatening coastal freshwater resources, triggering saltwater intrusion and a decline in freshwater quality. Wildfires in California are an important consequence of climate change, severely affecting freshwater resources and environmental balance. Wildfires lead to reduced water resources, impacting agricultural water use and irrigation infrastructure, and affecting water quality through increased sediment and pollutant loads. The 2018 Camp Hill Fire contaminated local water sources, and the rebuilding process has increased demand for water resources, exacerbating resource constraints. Global warming has lengthened wildfire seasons and increased fire intensity, leading to increased pressure on freshwater resources. By analyzing the impacts of climate change on freshwater resources, this paper hopes to draw public attention to environmental protection and provide a reference for gradually optimizing ecosystems and creating a healthy living environment.

Combined Effects of Magnetized Irrigation and Water Source on Italian Lettuce (Lactuca sativa L. var. ramosa Hort.) Growth and Gene Expression

Agricultural water scarcity has become a global issue. Optimizing irrigation water quality and effectively utilizing non-conventional water resources are essential strategies to alleviate pressure on agricultural water use and achieve sustainable development. This study employed Italian lettuce as the test crop to explore the effects of magnetization treatment (M) at a magnetic field strength of 0.2 T and various irrigation water sources (T) on its growth. The following six treatments were established: fresh water irrigation (M0T1), recycled water irrigation (M0T2), saline water irrigation (M0T3), magnetized fresh water irrigation (M1T1), magnetized recycled water irrigation (M1T2), and magnetized saline water irrigation (M1T3). The results showed that the magnetization treatment increased the electrical conductivity (EC), power of hydrogen (pH), and dissolved oxygen (DO) of the three water sources compared to the non-magnetized treatment. Furthermore, magnetized irrigation with fresh water, recycled water, and saline water increased the contents of nitrogen (N), potassium (K), calcium (Ca), and magnesium (Mg) in lettuce. It also led to increases in the contents of soluble proteins (by 9.27% to 22.25%), soluble sugars (by 13.45% to 20.50%), and vitamin C (VitC) (by 4.18% to 19.33%) in lettuce. Additionally, it enhanced the above-ground fresh weight of lettuce (by 9.36% to 8.81%) and water productivity (WPc) (by 5.85% to 10.40%), while reducing water consumption. Among these treatments, magnetized fresh water irrigation was the most effective in improving quality, fresh weight, and WPc, followed by magnetized recycled water. Gene expression analysis revealed that differentially expressed genes (DEGs) were primarily enriched in metabolic pathways such as the MAPK signaling pathway—plant, phytohormone signaling, and cysteine and methionine metabolism. In summary, magnetized irrigation significantly enhanced DO levels in irrigation water, along with the fresh weight, quality, and WPc of lettuce, demonstrating its effectiveness as an efficient method for agricultural irrigation.

Spatiotemporal variation in grain production performance and efficiency of the cultivated landscapes in Upper Blue Nile Basin of Ethiopia: the impact of residual moisture-based farming on water and food security

Analysis of grain production performance can provide reference information to explore multiple cropping options and further improve the resource use efficiency of farming methods. This study investigated the spatiotemporal dynamics of grain production performance and efficiency of major crop production systems (CPS) in the Ethiopia’s Blue Nile Basin. The results show that only 39% of the basin is currently cultivated, although a significant cropland expansion (10%) was recorded between 1985 and 2020. The study identified 11 major CPS, mostly practiced in the basin. Of these, single cropping based on the main rainy season (Meher-Only) covers the largest area (26%), followed by Meher-Residual-Intermittent (12%) and Meher-Belg-Dependable (11%). Extended-Meher, Meher-Residual-Dependable, Meher-Residual-Intermittent, and Meher-Belg-Dependable are the four more powerful CPS with higher efficiency. Comparatively, CPS practiced in Wet-Woyna-Dega and Wet-Dega have better overall performance. Findings confirm that agricultural space management (land) and green-water (rainfall) utilization are the most influential factors, followed by land use planning and land use systems (CPS) invention. As landscape suitability for grain production governs future performance, in the low elevation and flood plains parts of the basin, the possibility of creating additional space into the food system is very high. In mountainous and high-altitude regions, the efficiency of grain production will decrease because incorporating additional arable land into the food system is trivial. In the last three decades, in BNB, only 10% of arable land (equivalent to 30 million quintals of food) has been added to the good system, which can support approximately 6 million people. Compared to the population growth of the basin (12 million 1985–2020), its contribution to the food system was less than 50%. This confirms that multiple cropping systems, such as Residual moisture-based CPS, have played a significant role in boosting the food system in the basin. Therefore, improving grain production performance/efficiency requires targeted investments, including the invention of more adaptable crop varieties, efficient cropping practices, and the introduction of advanced agricultural space and water management technologies. The results of the study will help identify important policy gaps and suggest possible options to enhance residual farming and other multiple cropping systems.

Study on optimization of maize irrigation scheduling in Shaanxi Province

With the impact of climate change in recent years, the instability of precipitation and the increase of evaporation have made water resources in Shaanxi Province more and more stressed. How to maintain stable economic development while ensuring the sustainable development of agriculture within the limited water resources has become an important issue facing Shaanxi Province. This paper analyzes the temporal and spatial distribution characteristics of maize irrigation water requirement in Shaanxi Province based on meteorological data and obtains the ideal irrigation water requirement. However, considering the agricultural water scarcity issue in this region, this paper establishes different water scarcity scenarios, adopts the Jensen model to construct an objective function aimed at minimizing crop yield reduction, and solves it using a genetic algorithm to obtain the optimized maize irrigation scheduling under different water scarcity scenarios. The results analysis indicates the following: (1) The effective rainfall in Shaanxi Province from 1960 to 2019 shows a slight upward trend, while the maize water requirement and maize irrigation water requirement shows a downward trend. (2) The spatial distribution of maize irrigation water requirement in Shaanxi Province decreases gradually from north to south. High-value areas are mainly distributed in the northern regions of Yulin City and Yan’an City in Shanbei. Low-value areas are distributed in Ankang City in Shannan. (3) In the face of water scarcity, spring maize should ensure water use during the middle growth period, fast development period, and initial growth periods. Under the same water scarcity conditions, the yield reduction rate is the highest in Guanzhong, followed by the Shannan, and the lowest in Shanbei. This paper aims to provide a scientific and reasonable optimization plan for maize irrigation in Shaanxi Province by calculating and analyzing the maize irrigation water requirement in Shaanxi Province, combined with optimization tools such as genetic algorithms, to address the challenges brought by water resource constraints.

Simulating Agricultural Water Recycling Using the APEX Model

Irrigation plays a vital role in many agricultural crop production regions. Drainage water recycling (DWR) is a popular irrigation water management system that collects excess water drained from cropland fields and stores it in on-site reservoirs for reuse. The efficacy of these systems varies by location, climate, irrigation frequency, and crop demands. Simulating this system would be beneficial for assessing the impact of water and land management practices on agriculture and natural resources. This study presents the development of computational algorithms for DWR simulation with the Agricultural Policy Environmental eXtender (APEX) model, along with the results for 39 testing sites where both reservoir and drainage systems are adopted. Simulating a DWR system with the revised reservoir module, the APEX model simulates irrigation water reuse ranging between 29% and 93%; sediment reduction of around 66%; nitrogen loss reduction of 23% and 73% for the mineral and organic forms, respectively; and phosphorus loss reduction of 22% and 79% for the soluble and sediment-transported forms, respectively. In conclusion, the results provided by the APEX model for sediment loss reduction align with field data, but discrepancies for nitrogen and phosphorus losses emerged from this test.

Single Laboratory Evaluation of the Q20+ Nanopore Sequencing Kit for Bacterial Outbreak Investigations

Leafy greens are a significant source of produce-related Shiga toxin-producing Escherichia coli (STEC) outbreaks in the United States, with agricultural water often implicated as a potential source. Current FDA outbreak detection protocols are time-consuming and rely on sequencing methods performed in costly equipment. This study evaluated the potential of Oxford Nanopore Technologies (ONT) with Q20+ chemistry as a cost-effective, rapid, and accurate method for identifying and clustering foodborne pathogens. The study focuses on assessing whether ONT Q20+ technology could facilitate near real-time pathogen identification, including SNP differences, serotypes, and antimicrobial resistance genes. This pilot study evaluated different combinations of two DNA extraction methods (Maxwell RSC Cultured Cell DNA kit and Monarch high molecular weight extraction kits) and two ONT library preparation protocols (ligation and the rapid barcoding sequencing kit) using five well-characterized strains representing diverse foodborne pathogens. High-quality, closed bacterial genomes were obtained from all combinations of extraction and sequencing kits. However, variations in assembly length and genome completeness were observed, indicating the need for further optimization. In silico analyses demonstrated that Q20+ nanopore sequencing chemistry accurately identified species, genotype, and virulence factors, with comparable results to Illumina sequencing. Phylogenomic clustering showed that ONT assemblies clustered with reference genomes, though some indels and SNP differences were observed, likely due to sequencing and analysis methodologies rather than inherent genetic variation. Additionally, the study evaluated the impact of a change in the sampling rates from 4 kHz (260 bases pair second) to 5 kHz (400 bases pair second), finding no significant difference in sequencing accuracy. This evaluation workflow offers a framework for evaluating novel technologies for use in surveillance and foodborne outbreak investigations. Overall, the evaluation demonstrated the potential of ONT Q20+ nanopore sequencing chemistry to assist in identifying the correct strain during outbreak investigations. However, further research, validation studies, and optimization efforts are needed to address the observed limitations and fully realize the technology’s potential for improving public health outcomes and enabling more efficient responses to foodborne disease threats.

The functions and factors governing fungal communities and diversity in agricultural waters: insights into the ecosystem services aquatic mycobiota provide

IntroductionFungi are essential to the aquatic food web, nutrient cycling, energy flow, and ecosystem regulation. Fungal community structures in water can be influenced by adjacent terrestrial environments, which drive and control some ecosystem services they provide. However, the roles of freshwater fungal communities remain underexplored compared to bacterial communities in this context.MethodsWe assessed the impact of anthropological and environmental factors on freshwater mycobiota in an agriculturally dominated water basin in eastern Ontario, Canada. We undertook bi-weekly surface water sampling from 2016 to 2021 and conducted fungal internal transcribed spacer 2 (ITS2) metabarcoding on the samples, complemented by ancillary data, including water physicochemical properties, upstream land use, hydrology, and weather conditions.ResultsOur study yielded 6,571 OTUs from 503 water samples, spanning 15 fungal phyla, dominated by Ascomycota, Basidiomycota, and Chytridiomycota. Agricultural land use was associated with decreased mycobiota alpha diversity and distinct fungal communities were observed at agricultural drainage ditch and mixed-land use sites compared to a forested site that had minimal anthropogenic activities in catchment. Notably, river discharge emerged as a predominant influencer of both community diversity and composition, likely amplified by precipitation-induced erosion and drainage from adjacent terrestrial environments.DiscussionWater physicochemical properties, including stream fungicide levels, explained a small proportion of the variation in mycobiota communities, underscoring the significance of unmeasured factors, alongside stochastic community assembly processes. Nevertheless, stream mycobiota demonstrated functional resilience for critical ecological processes under different environmental conditions. Altogether, these results highlight the complex interplay of factors influencing the freshwater mycobiota, which is essential for elevated understanding of the ecosystem services these fungi provide.