Source Of Water For Agriculture Research Articles

Understanding the Spatiotemporal Dynamics and Influencing Factors of the Rice–Crayfish Field in Jianghan Plain, China

The rice–crayfish co-culture system, a representative of Agri-aqua food systems, has emerged worldwide as an effective strategy for enhancing agricultural land use efficiency and boosting sustainability, particularly in China and Southeast Asia. Despite its widespread adoption in China’s Jianghan Plain, the exact spatiotemporal dynamics and factors influencing this practice in this region are yet to be clarified. Therefore, understanding the spatiotemporal dynamics and influencing factors of the rice–crayfish fields (RCFs) is crucial for promoting the rice–crayfish co-culture system, and optimizing land use policies. In this study, we identified the spatial distribution of RCF using Sentinel-2 images and land use spatiotemporal data to analyze its spatiotemporal dynamics during the period of 2016–2020. Additionally, we used the Multiscale Geographically Weighted Regression model to explore the key factors influencing RCF’s spatiotemporal changes. Our findings reveal that (1). the RCF area in Jianghan Plain expanded from 1216.04 km2 to 2429.76 km2 between 2016 and 2020, marking a 99.81% increase. (2). RCF in Jianghan Plain evolved toward a more contiguous and clustered spatial pattern, suggesting a clear industrial agglomeration in this area. (3). The expansion of the RCFs was majorly influenced by its landscape and local agricultural conditions. Significantly, the Aggregation and Landscape Shape Indexes positively impacted this expansion, whereas proximity to rural areas and towns had a negative impact. This study provides a solid foundation for promoting the rice–crayfish co-culture system and sustainably developing related industries. To ensure the sustainable development of rice–crayfish co-culture industries in Jianghan Plain, we recommend that local governments optimize the spatial layout of rural settlements, improve transportation infrastructure, and enhance regional agricultural water sources and irrigation system construction, all in line with the national strategy of rural revitalization and village planning. Additionally, promoting the concentration and contiguity of RCF through land consolidation can achieve efficient development of these industries.

Shiga toxin-producing Escherichia coli isolated from hunted wild boar (Sus scrofa) in Switzerland.

Shiga toxin-producing Escherichia (E.) coli (STEC) are zoonotic foodborne pathogens of significant public health importance. While ruminants are considered the main reservoir, wild animals are increasingly acknowledged as carriers and potential reservoirs of STEC. The aim of this study was to determine the occurrence of STEC in a total of 59 faecal samples of hunted wild boars (Sus scrofa) from two different regions in Switzerland (canton Thurgau in northern Switzerland and canton Ticino in southern Switzerland), and to characterise the isolates using a whole genome sequencing approach. After an enrichment step, Shiga-toxin encoding genes (stx) were detected by real-time PCR in 41 % (95 % confidence interval (95 %CI) 0,29 - 0,53) of the samples, and STEC were subsequently recovered from 22 % (95 %CI 0,13 - 0,34) of the same samples. Seven different serotypes and six different sequence types (STs) were found, with O146:H28 ST738 (n = 4) and O100:H20 ST2514 (n = 4) predominating. Subtyping of stx identified isolates with stx1c/stx2b (n = 1), stx2a (n = 1), stx2b (n = 6), and stx2e (n = 6). No isolate contained the eae gene, but all harboured additional virulence genes, most commonly astA (n = 10), hlyE (n = 9), and hra (n = 9). STEC O11:H5, O21:H21, and O146:H28 harboured virulence factors associated with extra-intestinal pathogenic E. coli (ExPEC), and STEC O100:H20 and O155:H26 possessed sta1 and/or stb and were STEC/enterotoxigenic E. coli (ETEC) hybrid pathotypes. Our results show that wild boars are carriers of STEC which may be distributed in the environment, possibly leading to the contamination of agricultural crops and water sources. The serogroups included STEC O146 which belongs to the most common non-O157 serogroups associated with human illness in Europe, with implications for public health. Since Stx2e-producing STEC have frequently been reported in swine and pork, STEC O100:H20 harbouring stx2e in faeces of wild boars may be relevant to free-range systems of pig farming because of the potential risk of transmission events at thewildlife-livestock interface.

WATER EROSION RISK AND FOOD SECURITY: A CASE STUDY

Water erosion reduces soil fertility and productivity, negatively impacting crop yields. The transported material not only affects water quality but also significantly shortens the lifespan of water infrastructure. The Catamayo-Chira transboundary basin, spanning an area of 17,199 km2, serves as the primary water source for agriculture in the Ecuador-Peru border. Ongoing sediment production within the basin has drastically decreased the volume of the Poechos reservoir, northern Peru's largest irrigation system, raising concerns about its potential complete filling in the near future. To identify vulnerable areas to water erosion, the Revised Universal Soil Loss Equation (RUSLE) was utilized. By integrating meteorological, topographic, land use, and soil type data, a GIS-based model was developed to map the spatial variation of soil loss. This approach facilitated the identification of critical areas necessitating soil conservation actions. Within the basin, approximately 65% of the land exhibits high to critical erosion due to a combination of intense rainfall, steep slopes, limited vegetation cover, and erodible soils. Soil losses of around 200 tons per year have been observed. In the absence of effective soil loss management practices, sediment production, and transportation continue to pose significant challenges for the expansive agricultural lands in northern Peru, thereby jeopardizing regional food security.

Comparative analysis of indices in capturing the onset and withdrawal of the South Asian Summer Monsoon

The South Asian summer monsoon (SASM) exerts a profound influence on South Asia and the southern Tibetan Plateau. The timing of its onset and withdrawal significantly impacts regional rainfall, a critical water source for agriculture and the economy. Various SASM indices, employing different variables, have been employed to gauge monsoon onset and withdrawal, each demonstrating distinct characteristics. This study provides a comprehensive comparison of prominent SASM indices related to onset and withdrawal, revealing similar timing but varying magnitudes. Across nearly all indices, a consistent pattern emerges, indicating a trend towards earlier onset and delayed retreat during 1979–2018, marked by pronounced interdecadal variability, with a notable turning point around 1997. The earlier onset and later retreat are likely to enhance rainfall and potential water resources for South Asia and the Tibetan Plateau. Delving into the mechanisms revealed a delayed connection between the SASM onset to the large-scale sea surface temperature (SST) anomalies characterized by the Oceanic Niño Index (ONI) in the preceding spring, but a simultaneous connection between SASM withdrawl and ONI in autumn. Current index definitions, relying on single or dual variables, may fall short in accurately depicting monsoon onset and withdrawal. To address this, we introduce a novel monsoon index derived from multiple large-scale circulation variables, offering improved trend capture and enhanced representation of interannual variability in SASM onset and withdrawal. This study advances our understanding of SASM indices and their correlation with monsoon rainfall, providing insights into the dynamics of SASM onset and withdrawal.

Disinfection byproduct formation from chlorination of agricultural reuse water sources

Treatment of reuse water sources is critical for achieving proper water quality for the desired end-use. Disinfection is often achieved through chlorination, but this leads to the formation of toxic disinfection byproducts (DBPs). During reuse for agricultural purposes, it is important to reduce the potential for contamination of food crops and thereby minimize DBP production from treatment processes. This study evaluates the DBP formation potential from various reuse water sources under different reaction conditions to determine the implications of chlorination-derived DBPs for agricultural water reuse. Chlorination experiments were conducted on wastewater, stormwater, and farm lagoon water at pH 5, 6, 7, and with Br− addition. DBP concentrations were then evaluated in conjunction with initial concentrations of dissolved organic carbon (DOC), total nitrogen (TN), initial bromide, and specific UV-absorbance (SUVA). The most abundantly formed DBP class for nearly all sources was trihalomethanes (THMs), followed by nitrogenous DBPs (N-DBPs). Despite a high DOC concentration of 37.8 mg/L, lagoon source 2 only formed a total of 4.15 µg/L DBPs, likely due to oxidation of the inorganic nitrogen (54.8 mg/L TN) inhibiting DBP formation. Stormwater sources (DOC range 3.0-15.3 mg/L) had the highest DBP formation potential, with chloroform concentrations reaching up to 92 µg/L. Waters with lower DOC, TN and bromide and at lower pH ranges had less DBP formation potential for the compounds evaluated in this study. While SUVA did not prove to be a strong indicator of DBP formation, with increasing Br/UVA, there was an exponential increase in bromine substitution factor for THMs (R2=0.927, p < 0.0001) across all reuse sources. Toxicity-weighted DBP concentrations were also evaluated for all sources. Waters with higher TN and bromide content produced more toxic N-DBPs, mainly dichloroacetonitrile and dibromoacetonitrile.

Assistance in Designing Citarum River Cliff Protection to Control River Erosion in Atirompe Village, Majalaya District, Bandung Regency

Rivers are often used as a water source for agriculture, transportation, and water supply needs. One of the causes of riverbanks' damage is scouring the cliff's foot, which cannot withstand scouring currents. If not addressed immediately, it will cause more severe damage. Citarum River is one river that passes through Atirompe Village, Majalaya District. The riverbanks in the area have a risk of cliff failure. The study objective was to analyze the problem, design the protection, and calculate the budget. The hydrology and riverbank analysis of the Majalaya River has been performed. The steps are important to analyze the depth and width of the scour caused by the flow of the Citarum River water. Sediment data were collected at three locations, namely the upstream, middle, and downstream of the river segment that will be reviewed. In data processing, to obtain a sediment rating curve, it is necessary to measure the flow velocity, which will later be calculated and used as the flow rate that flows during TSS data collection. Using the HEC – RAS 6.2 software, the calculations with the Ripley Equation were compared to obtain the scour depth. For the design alternative, constructing a steel sheet pile-type cliff protection structure is one form of planning to protect riverbanks. This study also analyzes the recapitulation of the budgeting for protecting the Citarum riverbanks in Atirompe Village, Majalaya District. Using standardized unit price, the total price for the protection is 1,8 billion rupiahs.

Treated water from oil and gas extraction as an unconventional water resource for agriculture in the Anadarko Basin

The energy industry generates large volumes of produced water (PW) as a byproduct of oil and gas extraction. In the central United States, PW disposal occurs through deep well injection, which can increase seismic activity. The treatment of PW for use in agriculture is an alternative to current disposal practices that can also provide supplemental water in regions where limited freshwater sources can affect agricultural production. This paper assesses the potential for developing PW as a water source for agriculture in the Anadarko basin, a major oil and gas field spanning parts of Kansas, Oklahoma, Colorado, and Texas. From 2011 to 2019, assessment of state oil and gas databases indicated that PW generation in the Anadarko Basin averaged 428 million m3/yr. A techno-economic analysis of PW treatment was combined with geographical information on PW availability and composition to assess the costs and energy requirements to recover this PW as a non-conventional water resource for agriculture. The volume of freshwater economically extractable from PW was estimated to be between 58 million m3 per year using reverse osmosis (RO) treatment only and 82 million m3 per year using a combination of RO and mechanical vapor compression to treat higher salinity waters. These volumes could meet 1–2 % and 49–70 % of the irrigation and livestock water demands in the basin, respectively. PW recovery could also modestly contribute to mitigating the decline of the Ogallala aquifer by ~2 %. RO treatment costs and energy requirements, 0.3–1.5 $/m3 and 1.01–2.65 kWh/m3, respectively, are similar to those for deep well injection. Treatment of higher salinity waters increases costs and energy requirements substantially and is likely not economically feasible in most cases. The approach presented here provides a valuable framework for assessing PW as a supplemental water source in regions facing similar challenges.

Evaluation of Treated Wastewater Quality for Reuse in the Northern Region of Minas Gerais

Objective: This study aims to analyze the quality of effluents treated at three Wastewater Treatment Plants (WWTPs) in the northern region of Minas Gerais, evaluating reuse potential and proposals. Theoretical framework: The practice of reusing sanitary effluents holds significant economic and environmental importance. It conserves water resources allocated for higher priority uses. When assessed and compliant with regulations, effluents become potential water sources for agriculture and urban squares. The trend towards reusing treated effluents presents an alternative to meet water demands that could be satisfied with lower-quality water. Method: The study conducted laboratory analyses of three COPASA MG sewage treatment plants, referred to as WWTPs I, II, and III, between January 2021 and September 2022. Parameters crucial for effluent reuse, including Biochemical Oxygen Demand (BOD), Electrical Conductivity (EC), Hydrogen Potential (pH), Escherichia coli, Sodium Adsorption Ratio (SAR), and viable helminth eggs, were monitored and evaluated. The feasibility of proposed water reuse methods was assessed by analyzing the quality of treated effluents from the three WWTPs, considering that the treatments adhered to the conditions and effluent discharge standards outlined in Joint Normative Decision COPAM and CERH-MG No. 01 of May 5, 2008 (Minas Gerais, 2008), as well as the reuse parameters defined in Normative Decision CERH-MG No. 65/2020 of June 18, 2020 (CERH-MG, 2020). Results and Conclusion: The findings indicate that the effluents treated in the studied WWTPs are suitable for reuse, with potential corrective measures for non-compliant parameters. This allows for irrigation of urban squares, subject to approval by local authorities, and internal irrigation within interested businesses. Research Implications: This approach is highly relevant for fostering discussions on expanding reuse practices and shaping regulations through legislation, norms, and deliberations. Originality: This study stands out due to its in-depth investigation, ensuring a viable water reuse source for localities facing water scarcity, particularly in the northern region of Minas Gerais. This innovative topic, though less explored in literature, is gaining momentum in environmental discourse, thanks to the potential of effluents for agricultural purposes.

Assessing the performance of the Gaussian Process Regression algorithm to fill gaps in the time-series of daily actual evapotranspiration of different crops in temperate and continental zones using ground and remotely sensed data

The knowledge of crop evapotranspiration is crucial for several hydrological processes, including those related to the management of agricultural water sources. In particular, the estimations of actual evapotranspiration fluxes within fields are essential to managing irrigation strategies to save water and preserve water resources. Among the indirect methods to estimate actual evapotranspiration, ETa, the eddy covariance (EC) method allows to acquire continuous measurement of latent heat flux (LE). However, the time series of EC measurements are sometimes characterized by a lack of data due to the sensors' malfunctions. At this aim, Machine Learning (ML) techniques could represent a powerful tool to fill possible gaps in the time series. In this paper, the ML technique was applied using the Gaussian Process Regression (GPR) algorithm to fill gaps in daily actual evapotranspiration. The technique was tested in six different plots, two in Italy, three in the United States of America, and one in Canada, with different crops and climatic conditions in order to consider the suitability of the ML model in various contexts. For each site, the climate variables were not the same, therefore, the performance of the method was investigated on the basis of the available information. Initially, a comparison of ground and reanalysis data, where both databases were available, and between two different satellite products, when both databases were available, have been conducted. Then, the GPR model was tested. The mean and the covariance functions were set by considering a database of climate variables, soil water status measurements, and remotely sensed vegetation indices. Then, five different combinations of variables were analyzed to verify the suitability of the ML approach when limited input data are available or when the weather variables are replaced with reanalysis data. Cross-validation was used to assess the performance of the procedure. The model performances were assessed based on the statistical indicators: Root Mean Square Error (RMSE), coefficient of determination (R2), Mean Absolute Error (MAE), regression coefficient (b), and Nash-Sutcliffe efficiency coefficient (NSE). The quite high Nash Sutcliffe Efficiency (NSE) coefficient, and the root mean square error (RMSE) low values confirm the suitability of the proposed algorithm.

Pemberdayaan Petani dalam Memanfaatkan Air Hujan untuk Sistem Budidaya Tanaman dengan Metode Water Harvesting

Rainwater harvesting is one municipal initiative that uses rainwater for everyday needs. Rainwater is very useful in meeting water sources for agriculture, homes and industries, but unmanaged rainwater can also cause disasters such as flooding and flooding. The rainwater that falls on the earth is clean water for living things. However, during the rainy season, when the catchment area decreases, rainwater cannot penetrate into the ground and often causes flooding. For this reason, this service activity is essential to help farmers meet their crops' water needs during periods of drought. This activity was conducted from November to December 2022 in Husok Village, Hubikiak District, Jayawijaya District, Papua Mountains. The implementation of this service activity will be implemented through the pilot project phase of the Kosabangsa program. This stage is divided into his three phases: the preparation phase, the activity phase, and the evaluation and monitoring phase. The results of the implementation of this community service activity were achieved based on the plans set and the tools made to function properly because they can accommodate and drain water to each holding tank in the middle of the land for watering the plants as well as being an alternative in providing clean water for farmer groups so they no longer have to walk far to take clean water. This is supported by community participation in accepting the technology made by the implementing team.

Change in groundwater table depth caused by natural change and human activities during the past 40 years in the Shiyang River Basin, northwest China

Groundwater is the primary water source for agriculture, social economy, and ecosystem in the Shiyang River Basin (SRB), northwest China. Research on its variation and attribution is of great importance for the sustainable development of local economy, water resources, and the environment. In this study, the changes in the groundwater table depth (GTD) during 1980–2017 in different sub-basins and different periods were analyzed using the linear trend and moving t-test methods. The contribution of natural and human activity to GTD in the before and after periods of the Comprehensive Treatment Program of the SRB (CTSRB) were quantified using a multiple general linear model. The results showed that (1) the GTD in SRB showed a significant increasing trend during 1980–2017, and it could be divided into three stages: slow increase (1980–1987), rapid increase (1987–2008), and spatially different trends (2009–2017). In sub-basins, the increasing rates in the three stages in Wuwei were 1.05 m/10a, 2.86 m/10a, and 4.50 m/10a, respectively, while those in Minqin were 3.89 m/10a, 6.24 m/10a, and 0.85 m/10a, respectively. (2) The contribution of human irrigation activity to GTD in Minqin decreased from 77.3 % during the pre-CTSRB period to 38.0 % during the post-CTSRB period, while that in Wuwei increased from 67.3 % to 83.8 %. This was due to the CTSRB focusing on the groundwater and ecological restoration in the lower reaches of SRB. (3) The dominant attributing factor to the increase in GTD was groundwater exploitation driven by expanded irrigated-farmland during the pre-CTSRB period. However, the implementation of CTSRB has achieved remarkable results, and the groundwater level in Minqin virtually reached a stable state, especially in the Lake irrigation district. This study provides a reference and basis for sustainable utilization and management of groundwater resources in similar arid and semi-arid regions.

A Meta-Heuristic Algorithm-Based Feature Selection Approach to Improve Prediction Success for Salmonella Occurrence in Agricultural Waters

The presence of Salmonella in agricultural waters may be a source of produce contamination. Recently, the performance of various algorithms has been tested for the prediction of indicator bacteria population and pathogen occurrence in agricultural water sources. The purpose of this study was to evaluate the effect of meta-heuristic optimization algorithms for feature selection to increase the Salmonella occurrence prediction performance of commonly used algorithms in agricultural waters. Previously collected dataset from six agricultural ponds in Central Florida included the population of indicator microorganisms, physicochemical water attributes, and weather station measurements. Salmonella presence was also reported with PCR-confirmed method in data set. Features were selected by binary meta-heuristic optimization methods including differential evolution optimization (DEO), grey wolf optimization (GWO), Harris hawks optimization (HHO) and particle swarm optimization (PSO). Each meta-heuristic method was run for 100 times for the extraction of features before classification analysis. Selected features after optimization were used in the K-nearest neighbor algorithm (kNN), support vector machine (SVM) and decision tree (DT) classification methods. Microbiological indicators were ranked as the first or second features by all optimization algorithms. Generic Escherichia coli was selected as the first feature 81 and 91 times out of 100 by GWO and DEO, respectively. The meta-heuristic optimization algorithms for the feature selection process followed by machine learning classification methods yielded the prediction accuracy between 93.57 and 95.55%. Meta-heuristic optimization algorithms had a positive effect to improve Salmonella prediction success in agricultural waters despite spatio-temporal variations in agricultural water quality.

A Hydrogeological Conceptual Model Refines the Behavior of a Mediterranean Coastal Aquifer System: A Key to Sustainable Groundwater Management (Grombalia, NE Tunisia)

The Mediterranean coastal aquifer system of the Grombalia basin (NE Tunisia) offers immense potential as a source of fresh water for agriculture, industry, and drinking water supply. Nonetheless, due to its intricate hydrogeological characteristics and the prevailing issue of groundwater salinity, comprehending its groundwater system behavior becomes crucial for the effective and sustainable management of this aquifer system. Based on the hydrogeological characterization of the Grombalia basin, a novel 3D hydrogeological conceptual model was developed to enhance the understanding of its complex aquifer system. The integration of insights from geological, hydrogeological, hydrodynamic, and hydrochemical components facilitated the construction of the hydrogeological conceptual model. Although the model’s validity faced initial uncertainties due to spatial interpolation of lithological sequences, this study’s thorough and encompassing hydrogeological investigation overcame these limitations. As a result, a more informed comprehension of the aquifer system complexities was achieved. This study reveals that the basin is underlain by an extensive, cohesive Mio–Plio–Quaternary aquifer system. The model demonstrates vertical and lateral hydrogeological continuity between the Quaternary and underlying Mio–Pliocene deposits, enabling groundwater flow and exchange between these layers. Over-abstraction of the Mio–Plio–Quaternary aquifer system has led to a significant drop in piezometric levels and raised the risk of seawater intrusion. These findings emphasize the critical necessity of taking into account the interconnections among hydrogeological units to ensure sustainable groundwater management. The developed conceptual model offers a key tool for understanding the hydrodynamic functioning of the Grombalia aquifer system with a view toward guiding future groundwater management strategies. The application of this approach in the Grombalia basin suggests its potential applicability to other regional aquifers facing comparable challenges.

Groundwater contamination apportionment in Beida-Bordj rural territory, northeast Algeria, using the nitrate pollution index (NPI) and groundwater pollution index (GPI)

Most of the time, too much use of artificial fertilizers in rural areas, especially nitrogen fertilizers used to make crops grow faster, causes nitrate levels in groundwater to rise. In the Beida-Bordj area in northeast Algeria, groundwater is the main source of water for agriculture and drinking. Because of this, the quality of groundwater is very important. Therefore, nitrogen pollution in groundwater, which is one of the most important environmental problems, needs to be looked into. Therefore, evaluating groundwater contamination to protect human health was the primary focus of this investigation. As a result, 111 samples were taken in May 2022 from wells in different parts of the study area for physical and chemical research. Therefore, the nitrogen pollution index (NPI) and the groundwater pollution index (GPI) have been used to measure how clean groundwater is. The results show that the groundwater in the area that was tested is alkaline. Based on their average values, the abundance of cations and anions is as follows: Ca2+ > Na+ > Mg2+ > K+; and SO42− > Cl− > HCO3− > NO3−, in that order. The estimated NPIs ranged from – 1 to 4.5, with 0.92 being the average. Overall, the NPI data showed that only 25% of groundwater samples were clean, and the other 75% were dirty. The GPI readings ranged from 6.3 to 0.4, with an average of 1.2. This means that only 54% of the samples of groundwater from the study area were safe to drink. According to analyses of water quality parameters like SAR, SSP, RSC, PI, MH, and KR, the majority of groundwater samples from the research region are suitable for irrigation, because they fall into the "good" or "suitable" quality classes. This study's findings offer some intriguing suggestions for lowering pollution levels and bolstering groundwater management strategies for the future.

Developing a Decision-making Tool for Agricultural Surface Water Decontamination Using Ultraviolet-C Light

Ultraviolet-C (UV-C) light-assisted water treatment systems are an increasingly investigated alternative to chemical sanitizers for agricultural surface water decontamination. However, the relatively high concentration of particulate matter in surface water is a major challenge to expanding its application in the production of fresh produce. The objective of this project was to test the efficacy of two commercial UV-C devices to reduce the microbial risk of agricultural water in order to develop a web application to assist growers in decision-making related to the on-farm implementation of UV-C technologies for agricultural water treatment. An on-farm study using three agricultural water sources was performed to determine the microbial reduction efficacy of a low power, low flow (LP/LF; 1–9 gallons per minute (GPM), 1.34-gallon capacity) and a high powered, high flow (HP/HF; 1–110 GPM, 4.75-gallon capacity) device at flow rates of 6, 7, and 9 GPM. A threshold of 30% UVT for the HP/HF device was observed, wherein lower water transmissibility significantly impacted microbial inactivation. Although less effective at lower %UVT, the LP/LF device costs less to install, maintain, and operate. The observations were used to design an online tool for growers to calculate the predicted reduction of generic Escherichia coli using either device based on the %UVT of their water source. However, because this study utilized an exploratory and proof-of-concept approach, the experimental flow rates were limited to reflect the capacities of the smaller unit (9 GPM) for direct comparison to the larger unit. Thus, the preliminary model and tool are largely limited to the experimental conditions. Yet, these results of this study demonstrate the utility of UV-C light in reducing the microbial risk of agricultural water, and future studies using different UV-C devices and higher flow rates will expand the use of the decision-making tool.

Fuzzy Inference System in Assessing the Improved Wastewater Quality for Irrigation through Sedimentation, Dilution, and Biochar Filtration in Sulaymaniyah City, Iraq

The study aims to improve the quality of wastewater in Sulaymaniyah city, Iraq, which has been facing drought problems, by using sedimentation, dilution (1:1), and biochar filtration. It provides an alternative source of water for agriculture, addressing the water shortage problem in the region. The irrigation water quality is evaluated based on the Water Quality Index (WQI) using a fuzzy inference system, a mathematical tool that converts complex statements into mathematical terms and simplifies them into outputs. The centroid defuzzification technique is applied to convert the fuzzy results into crisp numbers. The output of the FIS score is used to determine the suitability of water for irrigation. The study utilized six different samples: groundwater (GW), wastewater (WW), sedimented wastewater (SW), filtered sedimented wastewater (FSW), diluted sedimented wastewater (DSW), and filtered diluted sedimented wastewater (FDSW). The samples were analyzed for their physical and chemical properties, including pH, electrical conductivity (EC), total suspended solids (TSS), turbidity (TUR), total nitrogen (TN), total phosphate (TP), cations (Ca, Na), anions (Cl and SO4), and heavy metals (Mn, Fe, Co, Ni, Zn, Cu). The study found that the WQI FIS-I values for wastewater increased with each treatment step, with the final step of passing the DSW through a biochar filter resulting in an FIS WQI-I value of 61.59, indicating good water quality. The deterministic method also showed improved levels for TP, TN, TSS, and turbidity. Mean TN and TP values decreased to 8.9 mg L-1 and 3.62 mg L-1, respectively, in the FDSW, with turbidity and TSS also decreasing to 0.37 NTU and 21 mg L-1. The resulting FDSW was of the best quality among the treated waters, making it suitable for drip irrigation.

Investigation on Water Pollution Control of Drinking Water Source in China

Drinking water source is an important guarantee of domestic water for urban residents, which has been affected mainly by non-point pollution and aroused widespread concern in various countries. However, with the change of underlying surface types, there are significant differences in pollution control strategies. In this study, two pollution control strategies were proposed for two typical underlying surface conditions with high-density built-up water source and agricultural water source, respectively. It is considered that the high-density built-up area can be divided into ecological area and built-up area. The stormwater runoff from ecological area is intercepted and transferred to reservoir directly. But the stormwater runoff from built-up area are treated in three situations: rainfall less than 7 mm, rainfall greater than 7 mm and less than 50-year return period and rainfall greater than 50-year return period. Correspondingly, the intercepting ditch, embedded ecological reservoir, constructed wetland and deep tunnel are applied. Differently, for agricultural water source, the strategy of land right circulation can be taken to reduce domestic pollution and pesticide pollution. Further, the pollution load entering the reservoir is reduced by near-natural wetland, ecological isolation zone and floating debris interception. At the same time, with the help of superior natural resources, ecological industry can be developed to achieve balance of protection and development based on EOD. The research results can provide valuable reference for the treatment of non-point source pollution reservoirs.

Assessment of Hexavalent Chromium Accumulation of Beta Vulgaris L. Var. Cicla and the Change of Its Antibacterial Activity

ABSTRACT Hexavalent chromium (Cr(VI)) is a frequently encountered heavy metal contaminant in agricultural soil and water sources resulting from industrial and agricultural applications, traffic, and urbanization. It is the most toxic form of chromium (Cr), which causes severe health problems. The accumulation capacity of Swiss chard (Beta vulgaris L. var. cicla) for hexavalent chromium and the effect of heavy metal accumulation on the antibacterial activity of plant extracts were evaluated in a pot experiment. The soil was treated with 10 mg kg−1 hexavalent chromium, 30 days prior to planting Swiss chard seedlings. After the harvest, macro- and micronutrient elements and Cr were measured using Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP-OES). Moreover, plant extracts were obtained by maceration in methanol and the extracts were tested against Gram-positive and Gram-negative bacteria. Cr was found to be uptaken and accumulated with a high concentration (54.7 ± 0.23 mg kg−1) in the aerial parts (transfer factor = 74.95). Cr toxicity reduced plant development and the macronutrient elements phosphorus and potassium in Swiss chard. The micronutrient elements iron and boron were found to be significantly increased in plant upon chromium in a synergistic manner with Cr. Additionally, the antibacterial activity of the extract of Swiss chard decreased against Staphylococcus aureus and Enterococcus faecalis around 50%. Moreover, the number of culturable bacteria decreased about 40% in soil after chromium treatment. The results suggested that this plant can accumulate a high amount of Cr in its aerial parts, which may decrease the health effects of the extracts.

Identifying the impact of land use land cover change on streamflow and nitrate load following modeling approach: a case study in the upstream Dong Nai River basin, Vietnam.

Tri An Reservoir is a vital source of water for agriculture, industry, hydropower, and public usage in Southern Vietnam. Due to human activities, water eutrophication has become a serious problem in recent decades. This study investigated for the first time the impact of land use and land cover (LULC) change on streamflow and nitrate load from the upstream Dong Nai River basin, which is the largest watershed of the reservoir. The study utilized several LULC scenarios, including LULC 2000, 2010, and 2020. The SWAT model was applied to model the watershed during the period 1997-2009. Results showed that the hydrological model performed satisfactorily based on the Nash-Sutcliffe efficiency (NSE) coefficient, the root mean square error observations standard deviation ratio (RSR), and the percent bias (PBIAS). The average simulated values of monthly streamflow and nitrate load were 453.7, 450.0, 446.7 m3/s and 17,699.43, 17,869.13, 17,590.81 tonnes for the LULC 2000, 2010, and 2020 scenarios, respectively. There were no significant differences in streamflow and nitrate load at the basin level under the different LULC scenarios. However, when looking at the subbasin level, there were differences in nitrate load among the scenarios. This suggests that the impacts of LULC on nitrate load may be more pronounced at smaller scales. Overall, our finding underscores the importance of modeling techniques in predicting the impacts of LULC change on streamflow and water quality, which can ultimately aid in the sustainable management of water resources.

Hydrogeochemical Characterization and Appraisal of Groundwater Quality in Yisr River Catchment, Blue Nile River Basin, Ethiopia, by Using the GIS, WQI, and Statistical Techniques

Groundwater is a primary drinking, agricultural, domestic, and nondomestic water source in Ethiopia’s Yisr River watershed of the Blue Nile River basin. There has been no systematic investigation of the hydrogeochemical properties of groundwater in the research area. The study investigated the hydrogeochemical parameters of groundwater in the catchment to find out if it is fit for drinking and irrigation. A total of 26 samples of groundwater were collected and analyzed for seventeen parameters, including pH, temperature, EC, TDS, TH, K+, Na+, Ca2+, Mg2+, Fe2+, Cl−, HCO 3 − , CO 3 2 − , SO 4 2 − , F−, PO 4 2 − , and NO 3 − . The data were processed and evaluated using integrated hydrogeochemical techniques, including individual ionic signatures, interionic ratios, and multivariate statistical methods, such as multiple correlation analysis, principal component analysis, and hierarchical cluster analysis. The water quality index (WQI) and Na%, PI, RSC, SAR, EC, TDS, and MH were used to judge the quality of water for drinking and irrigation, respectively. The box plot diagram shows the dominant ions in descending order of Ca2+ &gt; Mg2+ &gt; Na+ &gt; K+ and HCO 3 2 − &gt; Cl- &gt; SO 4 2 − &gt; NO 3 − &gt; F− for cations and anions, respectively. The chemical composition of shallow wells and springs indicates freshwater. At the same time, the deep groundwater wells are brackish. The two-factor loadings (principal component analysis) were used to explain the existence of anthropogenic and geogenic sources. Three clusters are identified in the dendrogram. The third cluster has the most significant linkage distance among all the clusters. This means that the groundwater sample in this cluster is geochemically different from the other two clusters, and that this cluster is made up of only deep wells. Water quality indices showed that water quality ranged from excellent to very poor, with the majority (53.85%) being excellent and 26.9% being good. The results of the calculated indices for agricultural water quality indicated that the water quality in most collected samples was in the good and excellent categories; however, the EC, RSC, MH, and TDS indices in deep groundwater wells were found to be hazardous. The findings of this study are useful for understanding groundwater sustainability for various reasons. However, they are also helpful in supporting water management and protection in the future.