Effects of change in streamflow patterns on water quality

New insight into the spatiotemporal distribution and ecological risk assessment of endocrine-disrupting chemicals in the Minjiang and Tuojiang rivers: perspective of watershed landscape patterns

This study evaluated the pollution characteristics, spatiotemporal distribution, and ecological risks of eight endocrine-disrupting chemicals (EDCs) in the Minjiang and Tuojiang rivers. Utilizing 3S technology (ArcGIS, remote sensing, GPS) and Fragstats, the research calculated eight landscape pattern indices related to land use types along the Minjiang river and established correlations between landscape factors and EDC distribution through stepwise multiple regression. The results indicated that bisphenol A (BPA) and nonylphenol (NP) were the most concerning EDCs, with detection frequencies of 97-100% and peak concentrations up to 63.35 ng L-1, primarily located in the middle and lower reaches of the Minjiang river and the upper reaches of the Tuojiang river. There was a significant correlation between the spatial distribution of pollutants and landscape patterns, where increased fragmentation, a higher number of patches, and complex patch shapes within a 10-kilometer buffer zone were associated with elevated levels of river pollution. By integrating four classical mathematical models to fit curves for acute and chronic toxicity data of BPA and NP, the findings suggested that BPA posed a higher ecological risk. This interdisciplinary research provided essential theoretical insights for investigating river pollution and its influencing factors, offering a new perspective on simultaneous river pollution control, urban functional zoning, and adjustment of watershed landscape spatial patterns from an urban planning standpoint.

Effect of varying hydrologic regime on seasonal total maximum daily loads (TDML) in an agricultural watershed

Rising hypoxia due to the eutrophication of riverine ecosystems is primarily caused by the transport of nutrients. The majority of existing TMDL models cannot be efficienty applied to represent nutrient concentrations in riverine ecosystems having varying flow regimes due to seasonal differences. Accurate TMDL assessment requires nutrient loads and suspended matter estimation under varying flow regimes with minimal uncertainty. Though a large database can enhance accuracy, it can be resource intensive. This study presents the design of an innovative modeling strategy to optimize the use of existing datasets to effectively represent streamflow-load dynamics while minimizing uncertainty. The study developed an approach to assess TMDLs using six different flux models and kriging techniques (i) to enhance the accuracy of nutrient load estimation under different hydrologic regimes (flow stratifications) and (ii) to derive an optimal modeling strategy and sampling scheme for minimizing uncertainty. The flux models account for uncertainty in load prediction across varying flow strata, and the deployment of multiple load calculation procedures. Further, the proposed flux approach allows the determination of load exceedance under different TMDL scenarios aimed at minimizing uncertainty to achieve reliable load predictions. The study employed a 10-year dataset (2009-2018) consisting of daily flow data (m3/sec) and weekly data (mg/L) for nitrogen (N), phosphorus (P) and total suspended solids (TSS) concentrations in three distinct agricultural sites in+ the Minnesota River Watershed. The outcomes were analyzed geospatially in a Geographic Information System (GIS) environment using the kriging interpolation technique. The study recommends (i) triple stratification of flows to obtain accurate load estimates, and (ii) an optimal sampling scheme for nitrogen and phosphorous with 30.6 % and 49.8 % datapoints from high flow strata. The study outcomes are expected to contribute to the planning of economically and technically sound combinations of best management practices (BMPs) required for achieving total maximum daily loads (TMDL) in a watershed.

Impacts of longleaf pine (Pinus palustris Mill.) on long-term hydrology at the watershed scale

Threats from climate change and growing populations require innovative solutions for restoring streamflow in many regions. In the arid western U.S., attempts to increase streamflow (Q) through forest management have had mixed results, but these approaches may be more successful in the eastern U.S. where greater precipitation (P) and lower evapotranspiration (ET) offer greater potential to increase Q by reducing ET. Longleaf pine (Pinus palustris Mill.) (LLP) woodlands, once the dominant land cover in the southeastern United States, often have lower ET than other forest types but it is unclear how longleaf pine cover impacts watershed-scale hydrology. To address this question, we analyzed 21 gaged rural watersheds. We estimated annual water balance ET (ETwb) as the difference between precipitation (P) and streamflow (Q) between 1989 and 2021 and quantified low flow rates (7Q10) among watersheds with high and low LLP cover. To control for climate variability among watersheds, we compared variation in hydrology metrics with biotic and abiotic variables using the Budyko equation (ETBudyko) to understand the differences between the two ET estimates (∆ET). Watersheds with 15-72 % LLP cover had 17 % greater mean annual Q, 7 % lower annual ETwb, and 92 % greater 7Q10 low flow rates than watersheds with <3 % LLP. LLP cover decreased ET and increased Q by 2.4 mm or 0.15 % Q/P per 1 % of watershed area, but only when LLP was managed as open woodlands. Our results demonstrate that ecological forest restoration in these systems, which entails mechanical thinning and re-introduction of low-intensity prescribed fire to maintain open woodlands, and enhance understory diversity, can contribute to decreases in ET and increases in Q in eastern forests.

Spatiotemporal variations of river water turbidity in responding to rainstorm-streamflow processes and farming activities in a mountainous catchment, Lai Chi Wo, Hong Kong, China

River turbidity is an important factor in evaluating environmental water quality, and turbidity dynamics can reflect water sediment changes. During rainfall periods, specifically in mountainous areas, river turbidity varies dramatically, and knowledge of spatiotemporal turbidity variations in association with rainfall features and farming activities is valuable for soil erosion prevention and catchment management. However, due to the difficulties in collecting reliable field turbidity data during rainstorms at a fine temporal scale, our understanding of the features of turbidity variations in mountainous rivers is still vague. This study conducted field measurements of hydrological and environmental variables in a mountainous river, the Lai Chi Wo river, in Hong Kong, China. The study results revealed that variations of turbidity graphs during rainstorms closely match variations of streamflow hydrographs, and the occurrence of the turbidity peaks and water level peaks are almost at the same time. Moreover, the study disclosed that the increasing rates of the turbidity values are closely related to the rainfall intensity at temporal scales of 15 and 20 min, and the impact of farming activities on river turbidity changes is largely dependent on rainfall intensity. In the study area, when the rainfall intensity is larger than 35 mm/hr at a time interval of 15 min, the surface runoff over the farmland would result in higher river water turbidity downstream than that upstream. The study results would enrich our understanding of river water turbidity dynamics at minute scales and be valuable for further exploration of the river water environment in association with turbidity.

Short-term variations and correlations in water quality after dam removal in the Chishui river basin

Dam damming has an adverse effect on river connectivity, leading to downstream nutrient transport and ecosystem fragmentation. Dam demolition has already been used as an effective measurement to promote the ecological restoration of rivers. Few studies have analyzed the short-term variations of water quality following dam removal. This study investigated the response of multi-element and multi-form water quality parameters, such as water temperature (TEM), dissolved oxygen (DO), pH, biochemical oxygen demand (BOD₅), chemical oxygen demand (COD), ammonia nitrogen (NH₃-N), total nitrogen (TN) and total phosphorus (TP), to the demolition of 4 dams in Chishui River Basin in short term. The study employed Spearman correlation analysis and Generalized Additive Models to identify the critical variables and examine the inter-relationship between these water quality parameters. Our results show that COD, BOD_5, and TP increased after two weeks of dam removal, while NH₃-N and TN decreased. Dams with larger volumes and higher heights led to more obvious deterioration for DO, COD, and BOD₅. We also found that denitrification and resuspension dominantly affect the water quality indicators following dam removal. Denitrification is responsible for downstream TN increase, and resuspension and related sediment transport contribute to downstream TP increase. Our study provides an opportunity to explore the transformation and migration of N and P in reservoirs following dam removal in the short term and presents a scientific basis and new thought for the short-term protection and management following the clean-up and rectification of multiple small hydropower plants.

Autochthonous sources and drought conditions drive anomalous oxygen-consuming pollution increase in a sluice-controlled reservoir in eastern China

Freshwater reservoirs are an important type of inland waterbody. However, they can suffer from oxygen-consuming pollution, which can seriously threaten drinking water safety and negatively impact the health of aquatic ecosystems. Oxygen-consuming pollutants originate from both allochthonous and autochthonous sources, and have temporally and spatially heterogeneous drivers. Datanggang Reservoir, China, is located in a small agricultural watershed; it is controlled by multiple sluice gates. Anomalously high oxygen consumption indicators were observed in this reservoir in March 2021. Here, it was hypothesized that autochthonous sources were the primary drivers of oxygen-consuming pollution in the reservoir under drought conditions. Datasets of water quality, precipitation, primary productivity, and sediment were used to analyze water quality trends in the reservoir and inflow rivers, demonstrating the effects of allochthonous inputs and autochthonous pollution. No correlation was found between reservoir oxygen consumption indicators and allochthonous inputs; reservoir oxygen consumption indicators and chlorophyll-a concentration were significantly positively correlated (p < 0.05). Substantially lower precipitation and higher water temperature and pH (compared to historical levels) were also observed before the pollution event. Therefore, during this period the hydrological conditions, water temperature, pH, and other variables caused by short-term drought conditions may have facilitated phytoplankton growth in the reservoir. This contributed to a large increase in autochthonous oxygen-consuming pollutants, as reflected by the abnormally high indicators. Sediments contaminated with organic matter may also have been an important contributor. As the effects of environmental management and pollution control continue to emerge, exogenous pollutants imported from the land to reservoirs are currently effectively controlled. However, endogenous pollutants driven by a variety of factors, such as meteorology and hydrology, will likely become the main drivers of short-term changes in oxygen-consuming pollution in freshwater reservoirs in the foreseeable future.

Sensitivity of streamflow patterns to river regulation and climate change and its implications for ecological and environmental management

Streamflow patterns support complex ecosystem functions and services. However, the direct impacts of flow regulation and climate change on patterns of streamflow are less studied. This study aims to analyse the sensitivity of streamflow patterns to the effects of flow regulation and climate change in the Goulburn-Broken catchment in Victoria, Australia. Daily streamflow was classified into low, medium, high, and overbank flow metrics using a statistical quantile-based approach. Trends and percent changes in streamflow metrics during the 1977-2018 period were analysed, and effects of change in rainfall, regulation, and flow diversion on streamflow patterns were predicted using a generalized additive model and path analysis. Low flows and medium flows increased by 26%, and high flows and overbank flows decreased by 31% during the period between 1977 and 2018. While current river regulation and flow diversion practices would dominate future change in magnitude, duration, and frequency of the streamflow, the timing of flow metrics would be dominated by variation in rainfall. These could bring a new ecological and environmental risk to the riverine ecosystem. It is recommended to increase the duration of high flows (90-120 days) and overbank flows (10-30 days) and the frequency of overbank flows to at least once every 1-2 years during wet periods to mitigate ecological and environmental risks of climate change and flow regulation in the Goulburn-Broken catchment.