Spatio-seasonal variation of water quality influenced by land use and land cover in Lake Muhazi

Modelling relationships between land use and water quality using statistical methods: A critical and applied review

Land use/land cover (LULC) can have significant impacts on water quality and the health of aquatic ecosystems. Consequently, understanding and quantifying the nature of these impacts is essential for the development of effective catchment management strategies. This article provides a critical review of the literature in which the use of statistical methods to model the impacts of LULC on water quality is demonstrated. A survey of these publications, which included hundreds of original research and review articles, revealed several common themes and findings. However, there are also several persistent knowledge gaps, areas of methodological uncertainty, and questions of application that require further study and clarification. These relate primarily to appropriate analytical scales, the significance of landscape configuration, the estimation and application of thresholds, as well as the potentially confounding influence of extraneous variables. Moreover, geographical bias in the published literature means that there is a need for further research in ecologically and climatically disparate regions, including in less developed countries of the Global South. The focus of this article is not to provide a technical review of statistical techniques themselves, but to examine important practical and methodological considerations in their application in modelling the impacts of LULC on water quality.

The multiscale nexus among land use-land cover changes and water quality in the Suquía River Basin, a semi-arid region of Argentina

Agricultural intensification and urban sprawl have led to significant alterations in riverscapes, and one of the critical consequences is the deterioration of water quality with significant implications for public health. Therefore, the objectives of this study were the assessment of the water quality of the Suquía River, the assessment of LULC change at different spatial scales, and the analysis of the potential seasonal correlation among LULC change and Water Quality Index (WQI). The Sample Sites (SS) 1 and 2 before Cordoba city had the highest WQI values while from SS3 the WQI decreased, with the lowest WQI close to the wastewater treatment plant (SS7) after Cordoba city. From SS8 in a agricultural context, the WQI increases but does not reach the original values. In light of analysis carried out, the correlation between water quality variables and the different LULC classes at the local and regional scales demonstrated that WQI is negatively affected by agricultural and urban activities, while natural classes impacted positively. The spatialization of the results can help strongly in assessing and managing the diffusion of point and non-point pollution along the riverscape. The knowledge gained from this research can play a crucial role in water resources management, which supports the provision of river ecosystem services essential for the well-being of local populations.

Interactions between water quality and microbes in epiphytic biofilm and superficial sediment of lake in trophic agriculture area

Epiphytic and superficial sediment biofilm-dwelling microbial communities play a pivotal role in water quality regulation and biogeochemical cycling in shallow lakes. However, the interactions are far from clear between water physicochemical parameters and microbial community on aquatic plants and in surface sediments of lake in trophic agriculture area. This study employed Illumina sequencing, Partial Least Squares Path Modeling (PLS-PM), and physico-chemical analytical methods to explore the interactions between water quality and microbes (bacteria and eukaryotes) in three substrates of trophic shallow Lake Cyohoha North, Rwanda. The Lake Cyohoha was significantly polluted with total phosphorus (TP), total nitrogen (TN), nitrate nitrogen (NO3-N), and ammonia nitrogen (NH3-N) in the wet season compared to the dry season. PLS-PM revealed a strong positive correlation (+0.9301) between land use types and physico-chemical variables in the rainy season. In three substrates of the trophic lake, Proteobacteria, Cyanobacteria, Firmicutes, and Actinobacteria were dominant phyla in the bacterial communities, and Rotifers, Platyhelminthes, Gastrotricha, and Ascomycota dominated in microeukaryotic communities. As revealed by null and neutral models, stochastic processes predominantly governed the assembly of bacterial and microeukaryotic communities in biofilms and surface sediments. Network analysis revealed that the microbial interconnections in Ceratophyllum demersum were more stable and complex compared to those in Eichhornia crassipes and sediments. Co-occurrence network analysis (|r| > 0.7, p < 0.05) revealed that there were complex interactions among physicochemical parameters and microbes in epiphytic and sediment biofilms, and many keystone microbes on three substrates played important role in nutrients removal, food web and microbial community stable. These findings emphasize that eutrophic water influence the structure, composition, and interactions of microbes in epiphytic and surface sediment biofilms, and provided new insights into the interconnections between water quality and microbial community in presentative substrates in tropical lacustrine ecosystems in agriculturally polluted areas. The study provides useful information for water quality protection and aquatic plants restoration for policy making and catchment management.

Quality assessment and evaluation of irrigation water and soil used for maize (Zea mays L.) production in Boloso Sore district, southern Ethiopia

Poor quality of irrigation water and soil are among the major factors determining maize productivity in Ethiopia. This study assessed and evaluated the quality of irrigation water and soil under maize production in Soke and Woybo irrigation schemes in Boloso Sore district, Ethiopia. Four water samples per site per season were collected from the first point of the irrigation schemes and farm gate for dry and rainy seasons in 2019/2020. Soil samples of 108 were collected from 36 points, from which 18 composited samples were taken for laboratory analysis. Results show that irrigation water of the two schemes is non-saline (electrical conductivity <0.2 dS m^-1) and in the normal pH range (6.5-7.5). Maximum concentration of cations in irrigation water was in the order of sodium (22.3 mg l^-1) > potassium (7.3 mg l^-1) > calcium (6.2 mg l^-1) > magnesium (3.1 mg l^-1). Moderate to severe sodicity (sodium adsorption ratio of 10.9) was also recorded. Sulfate, nitrate, and phosphate contents in water were trace, and increased during rainy seasons in downstream. Textural classes of soils are clay loam to clay, and less compact to restrict root penetration (bulk density ≤1.4 g cm^-3), have slow infiltration rate (≤0.13 cm h^-1), and medium level of total available water (≤178 mm m^-1). Soils are strongly acidic to neutral (pH: 5-6.5), salt-free, and have low soil organic carbon (≤2.1%), low total nitrogen (≤0.1%), low available phosphorus and sulfur, and low Ca²⁺: Mg²⁺ ratio. It can be concluded that the irrigation water in the study area has cation imbalance (poor quality) which affects soil quality and maize productivity. Likewise, soils of the study area have poor quality. Lime application, efficient fertilizer use, and organic matter applications can be suggested. Further study on optimizing fertilizer rates and irrigation levels has to be conducted to improve maize productivity.

Effects of land use and slope on water quality at multi-spatial scales: a case study of the Weihe River Basin

Exploring the impact of land use and slope on basin water quality can effectively contribute to the protection of the latter at the landscape level. This research concentrates on the Weihe River Basin (WRB). Water samples were collected from 40 sites within the WRB in April and October 2021. A quantitative analysis of the relationship between integrated landscape pattern (land use type, landscape configuration, slope) and basin water quality at the sub-basin, riparian zone, and river scales was conducted based on multiple linear regression analysis (MLR) and redundancy analysis (RDA). The correlation between water quality variables and land use was higher in the dry season than in the wet season. The riparian scale was the best spatial scale model to explain the relationship between land use and water quality. Agricultural and urban lands had a strong correlation with water quality, which was most affected by land use area and morphological indicators. In addition, the greater the area and aggregation of forest land and grassland, the better the water quality, while urban land presented larger areas with poorer water quality. The influence of steeper slopes on water quality was more remarkable than that of plains at the sub-basin scale, while the impact of flatter areas was greater at the riparian zone scale. The results indicated the importance of multiple time-space scales to reveal the complex relationship between land use and water quality. We suggest that watershed water quality management should focus on multi-scale landscape planning measures.

How anthropogenic factors influence the dissolved oxygen in surface water over three decades in eastern China?

The aquatic environment, linked to the sustainable development of human existence and ecological environment, is influenced comprehensively by anthropogenic and natural activities. In light of the continuously low concentration of dissolved oxygen (DO) in surface water in plain river networks and the phenomenon of delay in the improvement of surface water quality, this research aims to introduce a method that may be utilized in identifying the critical driving forces of DO in surface water and their lagging characteristics, which will contribute to the assessment and adjustment of water quality drivers and/or policies. The research analyzes a typical small watershed in a river network region of the Yangtze River Delta plain as the study area, collecting 35-year (1986-2020) data on several water quality parameters, decades of anthropogenic activities, and two natural factors. The time series methods of vector autoregressive model, Granger causality tests, forecast error variance decompositions, and impulse response functions (hereinafter referred to as VAR+), which are rarely applied in related research, were employed in this study and proved helpful for screening out pivotal drivers and capturing the lagging responses of DO level to driving forces at each lagged time. Results show that there exists a fluctuating drop in DO level in surface water from 1986 to 2008 and a steady climb from 2008 to 2020, with the lowest DO level being present in 2008. The impulsive perturbations of phosphate fertilizer consumption (PFC), motor vessel number, and precipitation minimally increase DO concentration, while the impulsive perturbation of gross domestic product (GDP) causes the sharpest drop in DO level. With these perturbations, the driving force of PFC persists for approximately seven years, and the driving forces of water temperature, permanent population, and GDP persist for only five years. Future research could be conducted with spatial hysteresis, selection of lag order and variable quantity within the model, as well as intermediate variables between drivers and DO level for exploring driving pathways and mechanisms.