Water quality responses to rainfall and surrounding land uses in urban lakes

Urban Lake Health Assessment Based on the Synergistic Perspective of Water Environment and Social Service Functions

Urban lakes serve as vital ecological and recreational anchors within built environments, essential for enhancing urban resilience. Evaluating lake health predominantly focuses on water quality, assessing indicators such as nutrient levels, toxicity, pH balance, and water clarity to monitor changes. This study proposes a comprehensive evaluation framework that systematically describes specific spatiotemporal manifestations and periodic exogenous regulation characteristics across five dimensions: physical structure, water quality, shoreline dynamics, external regulation, and social service. Furthermore, it introduces an urban lake health assessment model based on synergistic development to evaluate the integrated development and interaction between water environments and social services. This model is applied across urban lakes in various developmental stages in China. Key findings include: 1) Urban development often impacts lake health disparately, with varying degrees of synergy observed between water environments and social services across different urban lakes. However, shifts in urban ideologies and improvements in governance, along with protective policies and project implementations, have contributed to improving water quality to some extent. 2) Engineering interventions do not consistently correspond with improvements in water quality, and governance measures sometimes yield mixed outcomes, underscoring the necessity for systematic solutions to lake health. Restoring hydrological processes emerges as crucial for enhancing sustainability.

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.

Seasonal and interannual changes (2005-2021) of lake water quality and the implications for sustainable management in a rapidly growing metropolitan region, central China

A series of restoration measures such as municipal wastewater treatment and aquaculture closures have been implemented in Wuhan City during recent years. In order to explore the impact of restoration measures and climate change on lake water quality, long-term (2005-2021) water quality data of 47 lakes were explored to reveal spatiotemporal changes in lake water quality. Percentages of polluted lakes were calculated according to six water-quality parameters, including total phosphorus (TP), ammonia nitrogen (NH3-N), chemical oxygen demand (COD), biological oxygen demand (BOD), chemical oxygen demand using potassium permanganate as oxidant (CODMn) and petroleum contamination (PET), at interannual and monthly timescales. At the interannual timescale, percentages of COD, BOD, CODMn and PET pollution decreased significantly, suggestive of water quality improvement during recent years. At the monthly timescale, low percentages of NH3-N and BOD pollution in March 2020 probably resulted from the sharp reduction in human activities during the COVID-19 lockdown. At the monthly timescale, temperature was positively correlated with percentage of CODMn pollution, but negatively correlated with percentage of NH3-N pollution; precipitation was negatively correlated with percentage of BOD pollution. The similarity of water-quality parameters generally decreased with an increase in geographical distance between each pair of lakes. However, the regression coefficients between the similarity of lake water quality and the geographical distance decreased with time, probably resulting from enhanced similarity of water quality parameters among all lakes with rapid urbanization. Our results highlight the importance of active restoration measures for sustainable management of lakes in Wuhan City, as well as in similar developing regions.

Analysis of changes in nutrient salts and other water quality indexes in the pond water for largemouth bass (micropterus salmoides) farming

To explore the changes in nitrite nitrogen, ammoniacal nitrogen, nitrate nitrogen, phosphates, pH, dissolved oxygen, salinity, and water temperature over time and the correlations and mutual influences between these indexes in the traditional farming of largemouth bass, this study selected three ponds in Lizigu Farm in Baodi District of Tianjin, China as research objects. From May to October 2021, nutrient salts and other water quality indexes in the ponds were measured, and water samples were collected at different depths for repetition, Water is collected from the ponds using Plexiglas samplers and sent back to the lab for determination of water quality indexes using our national laboratory standards. According to the analysis of the measurement results, in traditional farming, nitrite nitrogen, ammoniacal nitrogen, nitrate nitrogen, phosphates, pH, dissolved oxygen, salinity, and water temperature in the ponds for largemouth bass all change significantly over time, with different changing trends and certain correlations with each other. In particular, nutrient salts indexes in ponds are influenced by other water quality indexes, human activities, and phytoplankton. During the breeding process, strengthening the dynamic monitoring of nutrient salts and other water quality indexes in the ponds and adjusting the nitrogen, phosphorus, and ammonia levels in the ponds artificially play an important role in preventing eutrophication in the water and promoting the green and sustainable production of pond ecosystems, in particular, allowing better quality growth of the largemouth bass, as well as ensuring the production and economic efficiency. This study provides a theoretical basis and data support for further optimization of traditional pond aquaculture in similar regions, in order to provide aquatic products with better quality and achieve higher economic benefits.

Spatiotemporal variation and driving factors of water quality in Yunnan-Guizhou plateau lakes, China

The Yunnan-Guizhou Plateau (YGP) lakes are the typical plateau rift lakes and an important water source in southwest China. However, there is a scarcity of research on its spatiotemporal water quality variations and driving factors, especially on long-term scales. Herein, multiple water quality indicators for 11 natural lakes on the YGP were measured from 2005 to 2020. In this study, the effects of natural lake attributes, human activities, and meteorological conditions on water quality were also analyzed. The results showed that the water quality of the YGP lakes tended to degrade, and was divided into heavy, medium, and light pollution types. Total phosphorus (TP), total nitrogen (TN), permanganate index (COD_Mn), and biochemical oxygen demand (BOD₅) increased by 14.69%, 14.44%, 22.61%, and 11.26%, respectively, from 2005 to 2020. Natural attributes of lakes and land use types were the main reasons for the spatial heterogeneity of water quality in YGP. In contrast, the temporal evolution of lake water quality was mainly related to human activities and climatic conditions. The smaller the water/ terrestrial area ratio, water storage capacity, and water depth, the easier the eutrophication and the worser the water quality of YGP lakes. Land degradation accelerated the deterioration of water quality in plateau lakes, while ecological land played an improving role. This study summarizes the water quality changes and influencing factors in YGP lakes over the past 15 years, which can provide a scientific database reference for water environment protection in YGP.

Watershed health assessment using the coupled integrated multistatistic analyses and PSIR framework

Quantitatively assessing watershed health under anthropogenic activities and management responses is important for the scientific planning and management of watersheds. The current research on watershed health assessments insufficiently reflects watershed scale information from different dimensions, which leads to the incomplete understanding of watersheds and thus the lack of systematic management. This study investigated the health status in the Chaohu Lake watershed (CLW) based on monthly sampling data at 46 river sites in 2018. Watershed health assessment comprehensively considered four dimensions including socioeconomic and natural pressures, nonpoint pollution export, river water quality and management responses with the pressure-state-impact-response (PSIR) framework. Canonical correlation analysis (CCA) and variance partitioning analysis (VPA) were integrated to further quantify the inter-relationships among the variables of each PSIR index. An obstacle degree model was applied to examine the factors of mainly affecting the status of watershed health. The results showed that phosphorus, nitrogen and sediment exports of CLW increased more and river water quality in CLW worsened due to socioeconomic and natural pressures. Water quality improvement effectively responds to increasing woodland and grassland. Compared with natural factors, phosphorus, nitrogen and sediment exports had closer relationships with the pressures from socioeconomic activities. Moreover, socioeconomic pressures explained more changes in phosphorus and nitrogen exports, while natural factors explained relatively more changes in sediment exports. Phosphorus, nitrogen and sediment exports and woodland and grassland coverage explained <35 % of the variation in river water quality. Additionally, the obstacle degrees of pressures and phosphorus, nitrogen and sediment exports were lower, and the obstacle degrees of river water quality and woodland and grassland coverage were higher in urban sub-watersheds, which was the opposite in agricultural sub-watersheds. This research provides a new evaluation framework of watershed health and its obstacle factors, which is crucial to improve watershed health.

Water-Quality Assessment and Pollution-Risk Early-Warning System Based on Web Crawler Technology and LSTM

The openly released and measured data from automatic hydrological and water quality stations in China provide strong data support for water environmental protection management and scientific research. However, current public data on hydrology and water quality only provide real-time data through data tables in a shared page. To excavate the supporting effect of these data on water environmental protection, this paper designs a water-quality-prediction and pollution-risk early-warning system. In this system, crawler technology was used for data collection from public real-time data. Additionally, a modified long short-term memory (LSTM) was adopted to predict the water quality and provide an early warning for pollution risks. According to geographic information technology, this system can show the process of spatial and temporal variations of hydrology and water quality in China. At the same time, the current and future water quality of important monitoring sites can be quickly evaluated and predicted, together with the pollution-risk early warning. The data collected and the water-quality-prediction technique in the system can be shared and used for supporting hydrology and in water quality research and management.

Water Quality Assessment of Urban Ponds and Remediation Proposals

Ponds are a common feature in urban parks to provide aesthetic and recreational functions, but also deliver a wide range of ecosystem services. The objective of this study was to assess the water quality of six urban ponds in the city of Lisbon, Portugal, to determine the factors that influence it and consider remediation measures for them. Besides that, our study aims to deliver data in order to support the best approach for a future monitoring program, toward more strategic and sustainable management. Floating treatment wetlands (FTW) were installed in three of the ponds during the study, where nutrient levels were higher. Water sampling was performed since 2016, with more intensive campaigns in 2020 and 2021. Average pH ranged from 7.9 to 9.0, average Chemical Oxygen Demand ranged from 36 mg/L to 90 mg/L and average Total Suspended Solids ranged from 7 to 93 mg/L. The main factors that contribute to these values were identified as the presence of waterbirds, vegetative debris that falls in ponds, and contamination with sewage. The FTW that were installed in some of the ponds could help to improve the water quality, but additional measures such as removal of bottom sediments and leaves in the fall, may be necessary. It is expected that the assessment of water quality carried out in the urban ponds can contribute to the overall improvement of urban water management.

Prediction and optimization of regional land-use patterns considering nonpoint-source pollution control under conditions of uncertainty

Socioeconomic development, leading to significant changes in land-use patterns, has further influenced the output of regional nonpoint-source (NPS) pollution. Multiple uncertainties exist in the processes of land-use changes and NPS pollution export. These uncertainties can deeply affect the management of regional land-use patterns and control of NPS pollution. In this research, an integrated land-use prediction and optimization (ILUPO) model based on system dynamics, export coefficient, interval linear programming, and fuzzy parameter programming models was proposed. The ILUPO model can provide future land-use patterns and NPS pollution loads, and also help optimize the patterns under multiple pollution reduction scenarios. Interval and fuzzy uncertainties in the processes of land-use changes and NPS pollution output can be effectively addressed. The developed model was applied to a water source area in the central part of northern Guangdong Province in South China. For the prediction period 2020-2030 under the high-speed development scenario, results show that cropland area would decrease, while grassland and waterbody areas would increase. In contrast, these three types of land-use would show opposite variation trends under the low-speed development scenario. Construction land area would decrease, while forestland area would increase under both the low-speed and high-speed development scenarios. Variation of the predicted land-use patterns would lead to an increase of total nitrogen loads under each of the scenario, while the total phosphorus loads would show relatively complex variation trends. Regional land-use patterns should be further optimized to mitigate NPS pollution. However, the pollution loads in the study area cannot be reduced by >5% through land-use adjustment. Because cropland would still be the critical source of NPS pollution after optimization, strictly controlling the areas of cropland would be important for the management of such pollution in the research area. In addition, certain areas of grassland and waterbody would need to be converted into cropland and construction land to balance the economic benefit of the system and NPS pollution control. Multiple results obtained from the model under different scenarios of pollution reduction targets and α-cut levels can provide decision-making supports for the local policy makers. The developed ILUPO model can yield insights useful for the planning and adjustment of regional land-use patterns while considering NPS pollution control under conditions of uncertainty.

The influence of rainfall and catchment characteristics on runoff generation in urban catchments-a case study in Hebi City of China

An in-depth understanding of the rainfall-runoff process is essential for effective stormwater management. However, the understanding of the hierarchy of rainfall characteristics in terms of their importance in influencing runoff generation is limited. This paper investigates the influence of rainfall characteristics and catchment characteristics on runoff generation in urban catchments. The outcomes showed that there are 4 dominant factors affecting runoff generation: total precipitation TP and maximum 60-min rainfall intensity MAX60 are the two top-ranked factors while average rainfall intensity RI and maximum 5-min rainfall intensity MAX5 are ranked second. Additionally, compared to the moderate rainfall regime (MR), the heavy rainfall regime (HR) tends to produce higher peak flow rates, higher total inflow per unit area, and lower runoff control effect. Note that the antecedent precipitation has a more significant effect on runoff generation and is even the dominant factor when rainstorm events with daily rainfall larger than 50 mm are not considered. The results of analyzing the influence of catchment characteristics suggest that only under HR regime conditions do the catchment characteristics have an impact on runoff generation and behave as smaller catchment areas, and higher proportions of green landscapes always lead lower peak flow rates, lower total inflows per unit area, and higher runoff control effects.

Evaluation of the Effectiveness of the SED-BIO System in Reducing the Inflow of Selected Physical, Chemical and Biological Pollutants to a Lake

The aim of this study was to assess the efficiency of the innovative SED-BIO system in limiting the inflow of pollutants to Jelonek Lake. The analyses were conducted in the Gniezno Lake District in Greater Poland (the western part of Poland). Physical and chemical analyses were conducted in the years 2016–2019. The results demonstrate that the system is highly effective in the reduction of such nutrients as nitrogen (NO3−—63%; NH4+—14.9%) and phosphorus (PO43−—19.3%). Although the presence of cyanobacteria was confirmed practically throughout the whole monitoring period of the system (2016), the specimens found in most samples were not toxigenic genotypes with a potential to produce microcystins. Microcystins (3 µg·L−1) were detected only once, immediately after the SED-BIO system had been installed in the river and pond, which demonstrates that this natural toxin was eliminated from the additional pool of contaminants that might be transported to Jelonek Lake.