Total Phosphorus Research Articles

Evaluating the Impacts of Fertilization and Rainfall on Multi-Form Phosphorus Losses from Agricultural Fields: A Case Study on the North China Plain

Excessive fertilizer application increases the risk of eutrophication and agricultural non-point source pollution (ANPS) in rivers near farmland. However, the processes and mechanisms of runoff and phosphorus losses, particularly in the interflow, under various fertilizer treatments and rainfall scenarios are not well understood. This study used orthogonal experimental methods to investigate the combined effects of fertilization schemes and rainfall intensity on multi-form phosphorus runoff losses and to establish statistical relationships and regression models between phosphorus losses and environmental factors in surface runoff and interflow. The results indicated that (1) the optimized fertilization scheme, compared with conventional fertilization, enhanced pak choi (Brassica rapa) growth while reducing phosphorus runoff losses. By reducing phosphorus fertilization by 35.7%, total phosphorus losses decreased by 29.3%, 34.2%, and 29.8% under light, moderate, and heavy rainfall, respectively. (2) Different fertilizer applications and rainfall intensities had varying effects on phosphorus losses through different pathways. Fertilizer application was the primary factor affecting phosphorus losses in surface runoff, while rainfall intensity mainly influenced phosphorus losses through interflow. (3) Surface runoff was the dominant pathway for phosphorus losses from farmland (>92.0%), with particulate phosphorus (>89.4%) being the predominant form. However, under high-intensity and long-duration rainfall, interflow became a significant pathway for phosphorus losses. This study highlights the importance of optimized fertilization in reducing phosphorus losses and improving fertilizer efficiency in agricultural fields. The findings will help develop strategies to mitigate ANPS and soil nutrient losses in the North China Plain.

An Analysis of the Spatiotemporal Variability of Key Water Quality Parameters in China

Intensifying anthropogenic disturbances have caused water pollution in China in recent decades. China has a vast territory with diverse climate conditions, land use types, and human activities, leading to significant water quality variability. However, few studies have investigated nationwide spatiotemporal patterns of key water quality parameters. In this study, we analyze monthly water quality observations from 3647 gauge stations to understand how water quality changes over time and space in China. We group the stations by water resource regions and adopt Python and SPSS to analyze the spatiotemporal variability and intercorrelations of eight water quality parameters. Results indicate that the concentrations of biochemical oxygen demand of 5 days (BOD5), chemical oxygen demand (COD), dissolved oxygen (DO), ammonia nitrogen (NH3-N), total nitrogen (TN), and total phosphorus (TP) show similar spatial patterns, with higher concentrations in the northern parts than the southern regions of China. The concentrations of COD and TP are higher in the rainy season than in the dry season, while DO, NH3-N, and TN show the opposite seasonal patterns. Strong positive correlations were found between BOD and COD, NH3-N and TP. The annual cumulative distribution figures demonstrate that all parameters showed slightly lower concentrations in 2022 and 2023 than in 2021, except for DO and TN. The TN/TP ratios across different water resource regions in China are significantly higher than 16, indicating that phosphorus is the limiting factor of eutrophication. This investigation provides a comprehensive understanding of the spatiotemporal variability of water quality parameters across China. The results of this study are highly valuable for investigating mechanisms regulating water quality across large spatial scales, thus providing valuable implications for improving water quality and mitigating water pollution.

High-altitude aquatic ecosystems offer faster aging rate of plastics

While research on the aging behavior of plastics in aquatic systems is extensive, studies focusing on high-altitude ecosystems, characterized by higher solar radiation and lower temperatures, remain limited. This study investigated the long-term aging behavior of non-biodegradable plastics (non-BPs), namely polyethylene terephthalate (PET) and polypropylene (PP) and biodegradable plastics (BPs), specifically polylactic acid plus polybutylene adipate-co-terephthalate (PLA + PBAT) and starch-based plastic (SBP), in a tributary of the Yarlung Zangbo River on the high-altitude Tibetan Plateau. Over 84 days of field aging, all four types of plastics exhibited initial rapid aging followed by deceleration. This aging process can be divided into two phases: rapid surface oxidation aging and an aging plateau phase. Notably, PP aged at a rate comparable to BPs, contrary to expectations of faster aging for BPs. Compared to low-altitude aquatic ecosystems, plastics in this study showed a faster aging rate. This was primarily due to intense ultraviolet radiation causing severe photoaging. Furthermore, the lower temperatures contributed to the formation of thinner biofilms. These thinner biofilms exhibited a reduced capacity to block light, further exacerbating the photoaging process of plastics. Statistical analysis results indicated that temperature, total nitrogen TN, and total phosphorus TP were likely the main water quality parameters influencing plastic aging. The varying effects of water properties and nutrients underscore the complex interaction of water quality parameters in high-altitude environments. Given the delicate nature of the high-altitude environment, the environmental impact of plastics, especially BPs, warrants careful consideration.

Co-composting of Black Soldier Fly Frass (BSFF) with various organics additives for nutrient enhancement

Black soldier fly frass is the nutrient-rich waste produced by black soldier fly larvae. This study aimed to enhance the frass by co-composting it with fish meal, bone meal, boiler ash, and sawdust. The co-composting process involved blending frass with the selected materials to achieve C:N ratio of 20, 25 and 30. After co-composting, characterization of total carbon, nitrogen, phosphorus and potassium contents and germination test were conducted. Fish meal increased nitrogen from 2.47 % to 3.10 %, bone meal improved phosphorus from 0.024 % to 0.042 %, and boiler ash raised potassium from 0.0023 % to 0.0039 %. Nevertheless, all the NPK source additives are required to balance and enhance all the nutrient level. Additionally, composts BSFF, fish meal, bone meal, and boiler ash, resulted in 100 % seed germination. The study demonstrates that co-composting frass with these materials effectively improves its nutrient content, providing a sustainable alternative for organic waste management and nutrient recycling.

Effect of Nano Urea on Leaf Nutrients and Some Quality Parameters of Tea (Camellia sinensis (L) O. Kuntze)

Some important parameters of tea on mature plants of TV 23 clone were studied after application of Nano-urea as foliar spray at Experimental Garden for Plantation Crops, Assam Agricultural University, Jorhat during the period 2021-2022. The usage of "Nano Urea" (Liquid), a novel product created and patented by Indian Farmers Fertilizer Cooperative Limited (IFFCO), is projected to replace the use of urea granules, one of the most widely used fertilizers in the world. Leaf nutrients i.e., nitrogen, phosphorus, potassium and quality parameters i.e., Caffeine, polyphenol were observed after application of nano urea. Leaf nitrogen, leaf phosphorus and leaf potassium were found to be increased with the application of higher dose of Nano Urea. Leaf nitrogen was observed maximum (4.57%) in the plot where 0.4% Nano-urea applied in three sprays. Total phosphorus content of leaf was found to be the highest in treatment T7(0.423%) the lowest was observed in treatment T0 (0.370%). Total potassium content of leaf was the highest in treatment T7 (2.517%) and lowest K2O content was observed in treatment T0 (2.013%) which was a control. In quality parameters, it was found that application of Nano Urea showed significant impact on the total caffeine content of tea leaf. The highest value of caffeine was found in treatment T7 (3.233%) and lowest was found in treatment T0 (3.10%) (control).

Impact of joint dispatch of reservoir group on water pollution incident in drinking water source area

To reduce the harm of water contamination incidents in drinking water source areas (DWSAs) and explore feasible approaches, the research developed a hydrodynamic water quality model for DWSAs based on two dimensional water quality and quantity equations, Geographic Information System (GIS), and Digital Elevation Model (DEM). The Heshangshan Drinking Water Source Area (HDWSA) in the Three Gorges Reservoir Area (TGRA) was selected as the research area, with total phosphorus (TP) as the representative pollutant in the water. The research investigated the changes in TP content during various hydrological phase under pollution incident, compared the duration and trends of TP concentration exceeding standard value before and after joint reservoir group dispatch. The results showed that the migration speed of TP pollutants varied from slowest to fastest in the following order: dry phase, recession phase, storage phase, and flood phase. Under pollution incident condition, the time demanded for TP content to meet standard value in each water phase was 36 min (dry phase), 33 min (recession phase), 30 min (storage phase), and 27 min (flood phase). The joint dispatch group 1–3 shortened the time required to meet standard value by 6–13 min (dry phase), 5–11 min (recession phase), 4–9 min (storage phase), and 3–7 min (flood phase). The trend of TP concentration before and after joint dispatch showed four stages: significant increase, sharp decrease, rapid decrease, and slow decrease. Joint dispatch of reservoir group can effectively reduced the TP concentration in DWSA under pollution incident.

Trade-Offs in Plant Functional Traits Driven by Soil Changes under Urban Hardened Surfaces

The large-scale surface hardening has changed the urban environment and affected the normal growth of urban plants. However, it is still unclear how the urban hardened surface affects the functional urban plant traits. To explore whether the urban hardened surface affects the ecological strategies of plants by changing the urban soil properties and reflecting them on the plant traits, we studied the physical and chemical properties and plant functional traits of three different types of hardened surface in Shandong Province, China. Our results showed that the physical and chemical properties (soil bulk density, soil total porosity, capillary porosity, non-capillary porosity, soil moisture content, pH, organic carbon, total nitrogen, total phosphorus, total potassium, available phosphorus, and available potassium) of urban soils showed obvious differences with the increase of hardening strength. In this case, the plant functional traits (branch diameter, branch length, leaf thickness, branch weight, internode length, leaf dry weight, leafing intensity, leaf area, specific leaf area, and leaf dry matter content) were also differentiated to varying degrees. Meanwhile, there was a strong correlation among plant functional traits. Nevertheless, hardened surfaces break the quantitative relationship among functional traits of urban trees. They do not affect their stable correlation: as the hardening intensity gradually increases, its correlation weakens. In addition, plant functional traits have a significant response mechanism to soil physicochemical properties. There was a transformation of plant resource utilization strategy by changing plant functional traits to adapt to the hardened environment. Urban trees exhibit strong and rapid resource-allocation strategies. They are mainly reflected in the reduction of branch diameter, branch weight, leaf dry matter content, leaf area, mass ratio of branches and leaves, and the improvement of leafing intensity and leaf thickness. Overall, there were tight connections among urban soil properties, plant branches, and leaves functional properties. This finding reveals that urban trees can change their functional traits and the plasticity of their trait combinations under the background of hardened urban surface expansion, which is conducive to survival and growth.

Source identification of organic C and N in suspended particulate matter and sediments in plateau lakes as influenced by trophic status using stable isotopic signatures

Understanding the relationship between suspended particulate matter (SPM), sediment organic C, N stable isotopes, and lake trophic state index (TSI) is essential for managing lake pollution and eutrophication. According to the δ13C, δ15N, and C/N we found that the organic C in SPM and sediment of Caohai Lake primarily originated from macrophytes, while N was sourced from chemical fertilizers, phytoplankton, and aquatic plants. Total nitrogen, total phosphorus, NO3−-N, oxidation reduction potential, and Chl.a were identified as key factors influencing the sources and variations of SPM and sediment organic C and N stable isotopes in Caohai Lake, with a significant linear correlation observed between C, N stable isotopes, and TSI in sediments. To mitigate eutrophication in Caohai Lake, it is recommended that farmers apply fertilizers judiciously to minimize nutrient loss and that aquatic plants be regularly harvested to reduce N release from plant residues.

Spatial-temporal distribution characteristics of surface water pollutants and their potential sources in Ngari, China.

The Ngari region has many important rivers and is critical to water resource security and water resource continuity in China and even in adjoining Asian countries. However, the spatial distribution and monthly variation in local water quality have been poorly understood until recently. In this study, the spatial-temporal variations of 12 water quality parameters, including pH, dissolved oxygen (DO), permanganate index (IMn), chemical oxygen demand (COD), five-day biochemical oxygen demand (BOD5), ammonia nitrogen (NNH3), total nitrogen (Ntotal), total phosphorus (Ptotal), copper (Cu), fluoride (F), arsenic (As) and cadmium (Cd), were determined from samples collected monthly at 22 water cross-sectional sites in the Ngari region in 2020. The surface water pollution in the southern Ngari region was the most serious, and the water pollution level in winter was higher than that in the other seasons. As (0.0781 ~ 0.6154 mg/L) and F (1.05 ~ 4.64 mg/L) were the main exceedance factors derived from the recharge of high arsenic and fluoride geothermal water and weathering of As and F-bearing minerals. The hazard quotient and carcinogenic risk for As and F at the five contaminated sampling sites indicated potential health risks and even carcinogenicity to local populations. The hydrochemistry types of the lakes and rivers in the Ngari region were mainly chloride water and carbonate water. The results from this study can provide a scientific basis for the prevention and control of surface water pollution in the Ngari region and contribute to subsequent research on the ecology of water bodies.

Causal feedback loops modify lake chlorophyll a–nutrient relationships over two decades of nutrient reductions and climate warming

AbstractUnderstanding how the causal feedback between phytoplankton and environmental drivers controlling the chlorophyll a (Chl a, as a proxy of phytoplankton biomass)–nutrient relationships are modulated under different ecosystem conditions is a major challenge in aquatic ecology. Using an empirical dynamic model (convergent cross mapping) on a 20‐yr dataset on 20 Danish lakes, we quantified hypothesized causal feedback networks for each lake and related them to lake system properties (e.g., mean water depth, nutrient concentrations and extent of reduction, climate warming) vs. the Chl a–nutrient relationship (estimated from generalized least square models). The results showed prevalent causal feedback across the studied lakes, which demonstrated clear patterns for the tested ecosystem variations. Weaker causal feedbacks were found in deeper lakes and lakes with larger warming trends, while stronger causal feedbacks appeared in lakes experiencing greater reductions of TP (total phosphorus) and TN (total nitrogen). Moreover, these causal feedbacks showed a strong and positive coupled pattern. Most of the causal feedbacks worked as enhancement loops, which promote the sensitivity of phytoplankton to TP, not least in shallow lakes with a high TP reduction, and as regulatory loops, which force a shift in the Chl a–TN relationship from a more negative slope in lakes experiencing a high nutrient reduction and weak warming to a positive slope in lakes with low nutrient reduction and stronger warming. Our findings suggest a mechanistic explanation of how internal feedbacks regulate the Chl a–nutrient relationships across a broad gradient of nutrient reductions, climate warming, and lake morphologies.

Elucidating and forecasting the organochlorine pesticides in suspended particulate matter by a two-stage decomposition based interpretable deep learning approach

Accurately predicting the concentration of organochlorine pesticides (OCPs) presents a challenge due to their complex sources and environmental behaviors. In this study, we introduced a novel and advanced model that combined the power of three distinct techniques: Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Variational Mode Decomposition (VMD), and a deep learning network of Long Short-Term Memory (LSTM). The objective is to characterize the variation in OCPs concentrations with high precision. Results show that the hybrid two-stage decomposition coupled models achieved an average symmetric mean absolute percentage error (SMAPE) of 23.24 % in the empirical analysis of typical surface water. It exhibited higher predictive power than the given individual benchmark models, which yielded an average SMAPE of 40.88 %, and single decomposition coupled models with an average SMAPE of 29.80 %. The proposed CEEMDAN-VMD-LSTM model, with an average SMAPE of 13.55 %, consistently outperformed the other models, yielding an average SMAPE of 33.53 %. A comparative analysis with shallow neural network methods demonstrated the advantages of the LSTM algorithm when coupled with secondary decomposition techniques for processing time series datasets. Furthermore, the interpretable analysis derived by the SHAP approach revealed that precipitation followed by the total phosphorus had strong effects on the predicted concentration of OCPs in the given water. The data presented herein shows the effectiveness of decomposition technique-based deep learning algorithms in capturing the dynamic characteristics of pollutants in surface water.

Phosphorus doped hydrogenated silicon oxycarbide: Film formation, properties and its application on silicon heterojunction solar cell

An ultrathin phosphorus doped hydrogenated microcrystalline silicon oxycarbide (n-μc-SiCO:H) layer deposited by plasma enhanced chemical vapor deposition (PECVD) method can be used as a window layer for silicon heterojunction solar cells. The optical and electrical properties of n-μc-SiCO:H films were controlled by PECVD deposition conditions. The interplay effects of H2, CO2 and PH3 to SiH4 gas ratio on the chemical composition, material structure and properties of n-μc-SiCO:H film were systematically determined. O, H, C and P atoms were observed to incorporate into the silicon network of n-μc-SiCO:H layer, while most of the atoms bond directly to Si atoms. Incorporation of oxygen and carbon atoms into n-μc-SiCO:H film, confirmed by XPS as formation of Si-O and Si-C bonds, enlarged the optical absorption band gap (Eg) value. Both film crystallinity and phosphorus concentration in n-μc-SiCO:H layer were observed to be controlled by the H2, CO2 and PH3 to SiH4 gas ratio. The electric performance of HJT solar cell was depended on the optical and electrical properties of n-μc-SiCO:H layer. An average efficiency (across ∼ 120 cells) of 26.32 % was achieved in cells with optimized deposition parameters for the n-μc-SiCO:H layer. The reaction gas ratio was also the dominant factor in determining the number and size of nanoscale Si crystallites embedded in the n-μc-SiCO:H layer. The conductivity of n-μc-SiCO:H layer was determined by the activated phosphorus concentration but independent of the total phosphorus concentration. It was also found that large concentrations of small Si crystallites of size less than 3 nm improved film conductivity.

Bioretention cells filled with epoxy resin-modified loess for stormwater purification

As a filler material in bioretention cells, loess has a good ability to remove nitrogen and phosphorus. However, its low permeability can easily trigger cell blockage. To improve permeability, the modification of loess has become important in the construction of bioretention cells. This study tested water-soluble epoxy resin-modified loess and investigated its feasibility as a filler for bioretention cells. Its purification performance under different rainfall conditions, including intensity and dry periods, was analyzed and compared with traditional sand bioretention cells both with and without a submerged zone. Epoxy-modified loess could be used as a bioretention cell filler, significantly increasing the permeability coefficient of the cell. Although modification with epoxy resin did not affect the crystal composition of the loess, the cross-linking reaction that occurred on its surface increased the C content, decreased the Si content, and made the texture rougher. When the amount of epoxy resin was 2.5 % (SZ25), the resulting loess met the permeability coefficient design requirements; its maximum adsorption capacity for ammonium-nitrogen was at least 1.92 times more than that of sand. For phosphate, the maximum adsorption capacity reached 5.17 mg/g. The average removal efficiencies of ammonium-nitrogen, nitrate-nitrogen, total nitrogen, and total phosphorus in the epoxy-modified loess bioretention cells were 91.67 %, −12.42 %, 39.91 %, and 91.97 %, respectively, 3.14 %, 28.91 %, 20.07 %, and 9.59 % higher than those in the sand bioretention cell. Microbiological analyses revealed that modified loess filler promoted the enrichment of denitrifying bacteria to a relative abundance 14.31 %–26.47 % higher than that in traditional sand filler. Based on the Functional Annotation of Prokaryotic Taxa analysis, the modified loess bioretention cell had stronger C and N cycling than that of the traditional sand bioretention cell, indicating that microbial metabolism and denitrification were stronger and nitrogen removal was improved.

Phosphorus prediction in the middle reaches of the Yangtze river based on GRA-CEEMDAN-CNLSTM-DBO

Accurate and rapid prediction of water quality is crucial for the protection of aquatic ecosystems. This study aims to enhance the prediction of total phosphorus (TP) concentrations in the middle reaches of the Yangtze River by integrating advanced modeling techniques. Using operational and discharge data from the Three Gorges Reservoir (TGR), along with water quality parameters from downstream sections, we used Grey Relational Analysis (GRA) to rank the factors contributing to TP concentrations. The analysis identified turbidity, permanganate index (CODMn), total nitrogen (TN), water temperature, chlorophyll a, upstream water level variation, and discharge from the Three Gorges Dam (TGD) as the top contributors. Subsequently, a coupled neural network model was established, incorporating these key contributors, to predict TP concentrations under the dynamic water level control during flood periods in the TGR. The proposed GRA-CEEMDAN-CN1D-LSTM-DBO model was compared with conventional models, including BP, LSTM, and GRU. The results indicated that the GRA-CEEMDAN-CN1D-LSTM-DBO model significantly outperformed the others, achieving a correlation coefficient (R) of 0.784 and a root mean square error (RMSE) of 0.004, compared to 0.58 (R) and 0.007 (RMSE) for the LSTM model, 0.576 (R) and 0.007 (RMSE) for the BP model, and 0.623 (R) and 0.006 (RMSE) for the GRU model. The model's accuracy and applicability further validated in two sections: YC (Yunchi) in Yichang City and LK (Liukou) in Jingzhou City, where it performed satisfactorily in predicting TP in YC (R = 0.776, RMSE = 0.007) and LK (R = 0.718, RMSE = 0.007). Additionally, deep learning analysis revealed that as the distance away from dam increased, prediction accuracy gradually decreased, indicating a reduced impact of TGR operations on downstream TP concentrations. In conclusion, the GRA-CEEMDAN-CN1D-LSTM-DBO model demonstrates superior performance in predicting TP concentration in the middle reaches of the Yangtze River, offering valuable insights for dynamic water level control during flood seasons and contributing of smart to the advancement of water management in the Yangtze River.

Contribution of Litter and Root to Soil Nutrients in Different Rocky Desertification Grasslands in a Karst Area.

Litter and root decomposition is an important source of soil organic matter and nutrients. To ascertain the contribution of litter and root to natural grassland nutrients in rocky desertification areas, from March 2017 to January 2018, the continuous soil column method, collector method, and litter decomposition method were used to study the soil nutrients, litter and root biomass, decomposition, and nutrient release of potential, moderate, and severe rocky desertification grasslands, as well as their responses to rocky desertification. The results showed that the litter and root decomposition rate showed a trend of being first fast and then slow, and the decomposition rate of litter and root was greater than 50% after 300 days. The annual litter decomposition rates of potential, moderate, and severe rocky desertification grasslands were 69.98%, 62.14%, and 49.79%, respectively, and the annual decomposition rates of root were 73.64%, 67.61%, and 64.09%, respectively. With a deepening degree of rocky desertification, the litter and root decomposition rate decreased. The decomposition coefficients, k, of litter in potential, moderate, and severe rocky desertification grasslands were 1.128, 0.896, and 0.668, respectively, and the decomposition coefficients, k, of root were 1.152, 1.018, and 0.987, respectively. The nutrient release processes of litter and root were different, and the release mode ultimately manifests as "release". In rocky desertification grasslands, the organic carbon (OC), total nitrogen (TN), total phosphorus (TP), and total potassium (TK) released by litter and root decomposition were 18.93-263.03 g·m-2·yr-1, 1.79-5.59 g·m-2·yr-1, 0.18-0.47 g·m-2·yr-1, and 0.66-3.70 g·m-2·yr-1, respectively. The contribution of root to soil nutrients was greater than that of litter. The degree of rocky desertification was negatively correlated with the biomass, decomposition rate, and nutrient return amount of litter and root. The results of this study provide direct field evidence and illustrate the contribution of litter and root decomposition in rocky desertification grasslands to soil nutrients.

Hydrothermal carbonization of combined food waste: A critical evaluation of emergent products

Hydrothermal carbonization (HTC) increasingly appears as an eco-friendly method for managing food waste (FW). In this work, a combination of FW was subjected to HTC, and products were critically evaluated. This involved a lab-scale pressure reactor and optimization of HTC conditions: temperature (220–340 °C) and residence time (90–260 min) via central composite design type of response surface methodology (CCD-RSM). Results showed varying temperatures and residence time to impact the hydrochar (HC) and hydrothermal carbonization aqueous phase (HTC-AP) properties. Although HC produced through HTC exhibited lower ash content (<2%) despite higher fixed carbon (>55 %) with respect to the raw FW, the heating value of HC ranged from 19.2 to 32.5 MJ/kg. Temperature primarily influenced FW conversion, affecting carbonaceous properties. Saturated fatty acids (SFA) were found to be predominant in the HTC-AP under all tested operating conditions (77.3, 48.4, and 37.1 wt% for HTC at 340, 280, and 220 °C in 180 min, respectively). Total phosphorus recovery in HC and HTC-AP respectively peaked at 340 °C and 220 °C in 180 min. The study concludes that HTC holds promise for energy-dense biofuel production, nutrient recovery, and fostering a circular economy.

Advancing non-optical water quality monitoring in Lake Tana, Ethiopia: insights from machine learning and remote sensing techniques

Water quality is deteriorating in the world's freshwater bodies, and Lake Tana in Ethiopia is becoming unpleasant to biodiversity. The objective of this study is to retrieve non-optical water quality data, specifically total nitrogen (TN) and total phosphorus (TP) concentrations, in Lake Tana using Machine Learning (ML) techniques applied to Landsat 8 OLI imagery. The ML methods employed include Artificial Neural Networks (ANN), Support Vector Regression (SVR), Random Forest Regression (RF), XGBoost Regression (XGB), AdaBoost Regression (AB), and Gradient Boosting Regression (GB). The XGB algorithm provided the best result for TN retrieval, with determination coefficient (R2), mean absolute error (MARE), relative mean square error (RMSE) and Nash Sutcliff (NS) values of 0.80, 0.043, 0.52, and 0.81 mg/L, respectively. The RF algorithm was most effective for TP retrieval, with R2 of 0.73, MARE of 0.076, RMSE of 0.17 mg/L, and NS index of 0.74. These methods accurately predicted TN and TP spatial concentrations, identifying hotspots along river inlets and northeasters. The temporal patterns of TN, TP, and their ratios were also accurately represented by combining in-situ, RS and ML-based models. Our findings suggest that this approach can significantly improve the accuracy of water quality retrieval in large inland lakes and lead to the development of potential water quality digital services.

Spatiotemporal and vertical variability of water quality in lentic small water bodies: implications of varying rainfall and land use conditions.

Lentic small water bodies (LSWBs) deteriorate owing to anthropogenic activities, such as untreated domestic and agricultural waste disposal. Moreover, different turnover mechanisms occur during different seasons, contributing to nutrient enrichment and consequent degradation of LSWBs. However, understanding their spatial, temporal, and vertical variations during different seasons is understudied. In addition, studies on the variation in water quality under varying rainfall and land-use conditions are limited. Therefore, in this study, three LSWBs located in Northern India were studied during the pre-monsoon and monsoon seasons (December 2022 to October 2023). Total nitrogen (TN), chlorophyll-a (Chl-a), total phosphorus (TP), temperature, pH, dissolved oxygen (DO), total dissolved solids (TDS), chemical oxygen demand (COD),secchi disk depth (SDD), and water level (WL) were measured monthly. Sentinel-2 and CHIRPS pentad data were used for land use, land cover classification, and rainfall analysis. The spatial analysis indicates that the seasonal shift affects the water quality distribution, especially near the inlets and at the edges. The overall concentrations of TN and TP decreased during the monsoon season; however, they increased significantly at the inlets of the LSWBs. On the other hand, the Chl-a concentration shifted towards the edges due to the inflow during the monsoon. Temporal analysis also suggests that the arrival of the monsoon lowers pH, DO, and TDS. However, the concentrations of TN and TP increased because of agricultural runoff. Chl-a and COD show distinct variations due to the individual LSWBs' local conditions. Vertical variability analysis demonstrated pH, temperature, and TN stratification during the pre-monsoon period. However, during the monsoon, stratification is less significant due to intermixing. Redundancy analysis (RDA) showed that land use and rainfall patterns affected the water quality of LSWB 1, 2, and 3 by 53.49%, 81.62%, and 92.64%, respectively. This shows that land use, land cover, and rainfall changes affect the water quality of LSWBs. This study highlights the negative impact of runoff from agricultural land use as the main factor responsible for increased nutrient levels in the LSWBs.

Effects of Different Tillage Years on Soil Composition and Ground-Dwelling Arthropod Diversity in Gravel-Sand Mulching Watermelon Fields

Arthropods play a crucial role in ecological processes and agricultural productivity. Soil physicochemical properties, indicators of soil health, are closely linked to arthropod communities. Gravel-sand mulching, commonly employed in arid farming, initially enhances water retention and temperature regulation but may contribute to land degradation with prolonged use. This study investigated how varying tillage durations affected soil properties and arthropod diversity under gravel-sand mulching. The analysis employed multiple comparison methods, covariance analysis (ANCOVA), non-metric multidimensional scaling (NMDS), and redundancy analysis (RDA). The results indicated that while soil fertility was better preserved in cultivated fields compared to in the desert grassland, arthropod diversity significantly decreased with longer cultivation periods. A total of 1099 arthropods from 79 species were sampled, by Barber trap. The highest diversity was observed in native grassland (NG), with 305 arthropods from 39 species, while tillage 21 years (GPS-21Y) exhibited the lowest diversity, with only 103 arthropods from 6 species. Dominant species included the carnivores Labidura japonica and Cataglyphis aenes. The analysis revealed low similarity in arthropod communities between GPS-21Y and other fields and high similarity in soil physicochemical properties between NG and the transition zone (STZ). RDA showed available potassium (APP) was negatively correlated with arthropod species diversity and concentration, total Nitrogen (TN) was positively correlated with arthropod species diversity but negatively correlated with species concentration, total phosphorus (TP) was negatively correlated with arthropod species diversity and concentration. This study provides insights into the relationship between maintaining soil fertility and supporting arthropod diversity in grassland agriculture. While soil fertility and arthropod diversity were correlated, continuous cropping practices negatively impacted arthropod diversity, offering valuable information for pest management and sustainable agricultural practices.

Cumulative effects of fish disturbance and vegetative propagules reduce the growth advantage of Vallisneria natans

Benthivorous fish disturbance and density-dependent competition from adjacent macrophytes are two important biotic factors that significantly impact the growth of submerged macrophyte pioneer species, which is crucial for the success of eutrophication lake restoration. We conducted an outdoor mesocosm experiment to explore the individual and combined effects of these two factors on water quality and the growth of Vallisneria natans. The experiment involved two levels of fish (Misgurnus anguillicaudatus) disturbance crossed with two levels of Hydrilla verticillata vegetative propagule (shoot) intensity. The results showed that fish disturbance significantly increased the water column total nitrogen (TN), ammonia nitrogen (N-NH4), total phosphorus (TP), and phosphate‑phosphorus (P-PO4). V. natans exhibited restricted plant height elongation and decreased soluble carbohydrate (SC) and starch concentration in fish treatments. Fish disturbance inhibited the growth advantage of V. natans by increasing the extinction coefficient of the water column. There was no statistical significance in total biomass between the two macrophytes in increased vegetative propagule and fish treatments. H. verticillata exhibited a higher relative growth rate (RGR) and summed dominance ratio (SDR3) than V. natans in four treatments and the treatment with three shoots of H. verticillata and one M anguillicaudatus, respectively. Fish disturbance and vegetative propagules showed cumulative effects that negatively affected the RGR_V.H (V. natans relative to H. verticillata). Our findings indicated that benthivorous fish disturbance and vegetative propagules could individually and cumulatively reduce the growth advantage of the pioneer species, V. natans. Our study sheds light on the accumulated effects of multiple disturbances that simultaneously occur in lakes, which holds theoretical and practical importance for lake restoration efforts.