Establishment of reference conditions for nutrients in an intensive agricultural watershed, Eastern China

Aquatic ecosystem health assessment of a typical sub-basin of the Liao River based on entropy weights and a fuzzy comprehensive evaluation method

River ecosystem health assessments provide the foundation for river ecological protection and integrated management. To evaluate the aquatic ecosystem health of the Fan River basin, benthic macroinvertebrate indices (the Multimeric Macroinvertebrates Index Flanders (MMIF) and Family Biotic Index (FBI)), a habitat index (the river habitat quality Index (RHQI)) and a water quality index (the Improved Water Pollution Index (IWPI)) were selected. The entropy weighting method was used to calculate the RHQI and IWPI. A fuzzy comprehensive evaluation method was used to evaluate the aquatic ecosystem health. The evaluation results indicated that the aquatic ecosystem health of the Fan River basin was better in 2018 than in 2011, which respectively belonged to the ends of the 11th and 12th Five-Year Plans of the Major Science and Technology Programs for Water Pollution Control and Treatment in China. The proportions of sampling stations with good, moderate and poor grades in 2011 were 50.0%, 40.0% and 10.0%, respectively, and in 2018, the proportions of stations with excellent, good and moderate grades were 20.0%, 50.0% and 30.0%, respectively. A correlation analysis showed that the RHQI was significantly correlated with the MMIF, FBI and IWPI. The riparian land use pattern was an important factor that influenced changes in the aquatic ecosystem health grade. Of the water quality parameters, total phosphorous (TP) and potassium bichromate index (COD) were the main factors that affected the characteristics of benthic macroinvertebrates and the aquatic ecosystem health.

Landscape patterns regulate non-point source nutrient pollution in an agricultural watershed

Landscape pattern critically affects hydrological cycling and the processes of non-point source nutrients pollution. However, little is known about the quantitative relationship between landscape characteristics and the river water quality, and very few studies have addressed the abrupt changes in river water quality with the gradient of landscape metrics. The present study was conducted in a typically intensive agriculture watershed of eastern China including 13 sub-watersheds with different landscape pattern metrics. We adopted redundancy analysis, nonparametric deviance reduction approach, bootstrap sampling and other statistical methods to reveal the quantitative relationship between landscape pattern metrics and water quality variables; then, the phenomenon of an abrupt change in river water quality was explored with different landscape pattern gradients. The results show that landscape pattern significantly affects river water quality, and this effect was quite different in dry and rainy seasons. In the studied watershed, landscape pattern metrics could respectively explain 71.1% and 55.3% of the total variance in the river water quality in dry and rainy seasons. The configuration metrics of landscape pattern had a stronger ability than their composition metrics to explain the variance in water quality. In the dry season, largest patch index of forestland (LPI_for), the most important landscape index, explained 37.9% of the total variance in water quality. While, in the rainy season, the most important landscape index was the largest patch index of farmland (LPI_far), and it could explain 32.4% of that variance. In the studied watershed, when the LPI_for was <35% or LPI_far was over than 50%, water quality would typically change abruptly, at which the probability of a change in river water would suddenly rise substantially.

Effect of irrigation amount and fertilization on agriculture non-point source pollution in the paddy field

It is the key point to reveal the effect of irrigation water and fertilization conditions on the agriculture non-point pollution in the paddy field. In this study, the estimation model of agricultural non-point source pollution loads at field scale was established on the basis of agricultural drainage irrigation model and combined with pollutant concentration predication model. Based on the estimation model of agricultural non-point source pollution in the field and experimental data, the load of agricultural non-point source pollution in different irrigate amount and fertilization schedule in paddy field was calculated. The results showed that the variation of field drainage varies greatly under different irrigation conditions, and there is an "inflection point" between the irrigation water amount and field drainage amount. The non-point pollution load increased with the increase of irrigation water and showed a significant power correlation. Under the different irrigation condition, the increase amplitude of non-point pollution load with the increase of irrigation water was different. When the irrigation water is smaller, the non-point pollution load increase relatively less, and when the irrigation water increased to inflection point, the non-point pollution load will increase considerably. In addition, there was a positive correlation between the fertilization and non-point pollution load. The non-point pollution load had obvious difference in different fertilization schedule even with same fertilization level, in which the fertilizer pollution load increased the most in the period of turning green to tillering. The results provide some basis for the field control and management of agricultural non-point source pollution.

Determining Soil Nutrients Reference Condition in Alpine Region Grassland, China: A Case Study of Hulun Buir Grassland

Grasslands represent a source of nutrient cycling, ecosystem stabilization, and services for human use. Grassland soil quality is commonly used as an indicator of ecosystem health and sustainability due to its strong correlation with overall grassland quality and ecosystem health. Although direct and indirect effects of human activities or disturbances on soil can be taken into account, a benchmark (i.e., the reference condition (RC)) should be used and is needed to describe the baseline of an area without significant anthropogenic disturbance. Therefore, determination of the soil reference condition and suitable selection methods have become a key focal point in grassland protection and ecological assessments. In this study, several methods were selected to determine soil nutrient concentrations of Hulun Buir Grassland in northern China based on the proposed criteria. The concentrations of total organic matter, N, P, and K; 112 samples were analyzed using the population distribution method, trisection method, and regression model method. The reference concentrations of total organic matter, N, P, and K in soil were recommended to be 52.12 g/kg, 2.94 g/kg, 2.08 mg/kg, and 305.76 mg/kg, respectively. In the alpine region grassland, the major factors that impact nutrient concentration were agricultural activity and vegetation coverage. Sampling methods should be used preferentially in determining grassland soil reference condition and historical data; experts’ judgment could be used in substitution.

Estimating the nutrient thresholds of a typical tributary in the Liao River basin, Northeast China

Estimating regional nutrient criteria for streams and rivers is a key step toward protecting river water quality and restoring the health of aquatic ecosystems. Using a multivariable statistical analysis technique, nutrients were identified as the main factor influencing the degradation of the benthic macroinvertebrate community. Three chemical methods (the reference stream distribution approach, all-streams distribution approach and Y-intercept approach) and one biological method (the stress-response approach) were applied to evaluate the nutrient thresholds in the Qing River basin. The reference stream distribution approach and all-streams distribution approach were based on calculating a predetermined percentile of reference streams and all-streams water quality data set, respectively. The Y-intercept approach was based on determining the influence of human activity on water quality by linear regression models. The biological method was based on the response of the benthic macroinvertebrate community structure to changes in water quality. The chemical thresholds were 0.750–1.288 mg/L for total nitrogen (TN) and 0.035–0.046 mg/L for total phosphorus (TP); the biological thresholds were 1.050–1.655 for TN and 0.052–0.101 for TP. The results from the chemical approaches were verified using the biological method, resulting in preliminarily recommended thresholds of 1.000 mg/L TN and 0.040 mg/L TP in the Qing River system.

Establishment of stream nutrient criteria by comparing reference conditions with ecological thresholds in a typical eutrophic lake basin

The establishment of numeric nutrient criteria is essential to aid the control of nutrient pollution and for protecting and restoring healthy ecological conditions. However, it's necessary to determine whether regional nutrient criteria can be defined in stream ecosystems with a poor ecological status. A database of periphytic diatom samples was collected in July and August 2011 and 2012. In total 172 samples were included in the database with matching environmental variables. Here, percentile estimates, nonparametric change-point analysis (nCPA) and Threshold Indicator Taxa ANalysis (TITAN) were conducted to detect the reference conditions and ecological thresholds along a total nitrogen (TN) and total phosphorus (TP) gradient and ammonia nitrogen (NH₃-N) for the development of nutrient criteria in the streams of the Lake Dianchi basin. The results highlighted the possibility of establishing regional criteria for nutrient concentrations, which we recommended to be no more than 1.39 mg L^-1 for TN, 0.04 mg L^-1 for TP and 0.17 mg L^-1 for NH₃-N to prevent nuisance growths of tolerant taxa, and 0.38 mg L^-1 for TN, 0.02 mg L^-1 for TP and 0.02 mg L^-1 for NH₃-N to maintain high quality waters in streams. Additionally, the influence of excessive background nutrient enrichment on the threshold response, and the ecological interaction with other stressors (HQI, etc.) in the nutrient dynamic process need to be considered to establish the eventual nutrient criteria, regardless of which technique is applied.

Integrated Application of Multivariate Statistical Methods to Source Apportionment of Watercourses in the Liao River Basin, Northeast China

Source apportionment of river water pollution is critical in water resource management and aquatic conservation. Comprehensive application of various GIS-based multivariate statistical methods was performed to analyze datasets (2009–2011) on water quality in the Liao River system (China). Cluster analysis (CA) classified the 12 months of the year into three groups (May–October, February–April and November–January) and the 66 sampling sites into three groups (groups A, B and C) based on similarities in water quality characteristics. Discriminant analysis (DA) determined that temperature, dissolved oxygen (DO), pH, chemical oxygen demand (COD_Mn)_, 5-day biochemical oxygen demand (BOD₅), NH₄⁺–N, total phosphorus (TP) and volatile phenols were significant variables affecting temporal variations, with 81.2% correct assignments. Principal component analysis (PCA) and positive matrix factorization (PMF) identified eight potential pollution factors for each part of the data structure, explaining more than 61% of the total variance. Oxygen-consuming organics from cropland and woodland runoff were the main latent pollution factor for group A. For group B, the main pollutants were oxygen-consuming organics, oil, nutrients and fecal matter. For group C, the evaluated pollutants primarily included oxygen-consuming organics, oil and toxic organics.

Water and nonpoint source pollution estimation in the watershed with limited data availability based on hydrological simulation and regression model

Nonpoint source (NPS) pollution is considered as the main reason for water quality deterioration; thus, to quantify the NPS loads reliably is the key to implement watershed management practices. In this study, water quality and NPS loads from a watershed with limited data availability were studied in a mountainous area in China. Instantaneous water discharge was measured through the velocity-area method, and samples were taken for water quality analysis in both flood and nonflood days in 2010. The streamflow simulated by Hydrological Simulation Program-Fortran (HSPF) from 1995 to 2013 and a regression model were used to estimate total annual loads of various water quality parameters. The concentrations of total phosphorus (TP) and total nitrogen (TN) were much higher during the flood seasons, but the concentrations of ammonia nitrogen (NH3-N) and nitrate nitrogen (NO3-N) were lower during the flood seasons. Nevertheless, only TP concentration was positively correlated with the flow rate. The fluctuation of annual load from this watershed was significant. Statistical results indicated the significant contribution of pollutant fluxes during flood seasons to annual fluxes. The loads of TP, TN, NH3-N, and NO3-N in the flood seasons were accounted for 58-85, 60-82, 63-88, 64-81% of the total annual loads, respectively. This study presented a new method for estimation of the water and NPS loads in the watershed with limited data availability, which simplified data collection to watershed model and overcame the scale problem of field experiment method.

The Frequency Component of Water Quality Criterion Compliance Assessment Should be Data Driven

A numerical water quality criterion in the U.S. consists of three components representing magnitude, duration, and frequency. While magnitude and duration are well defined and conceptually unambiguous, the meaning of the frequency component is often debatable. We interpret the frequency component as a tool for accounting for uncertainty in estimating the mean concentration of a water quality constituent, after revisiting early works on environmental standards and criteria. Based on this interpretation, we illustrate management-related issues when using the default frequency of one exceedance in 3 years in compliance assessment. We propose a data-driven approach for estimating an appropriate frequency to ensure a consistent level of confidence in a water's compliance of a water quality criterion. The data-driven frequency is determined by water quality constituent concentration distribution characteristics and sample size. The method is illustrated using two examples.

Effects of land use, topography and socio-economic factors on river water quality in a mountainous watershed with intensive agricultural production in East china

Understanding the primary effects of anthropogenic activities and natural factors on river water quality is important in the study and efficient management of water resources. In this study, analysis of Variance (ANOVA), Principal component analysis (PCA), Pearson correlations, Multiple regression analysis (MRA) and Redundancy analysis (RDA) were applied as an integrated approach in a GIS environment to explore the temporal and spatial variations in river water quality and to estimate the influence of watershed land use, topography and socio-economic factors on river water quality based on 3 years of water quality monitoring data for the Cao-E River system. The statistical analysis revealed that TN, pH and temperature were generally higher in the rainy season, whereas BOD₅, DO and turbidity were higher in the dry season. Spatial variations in river water quality were related to numerous anthropogenic and natural factors. Urban land use was found to be the most important explanatory variable for BOD₅, COD_Mn, TN, DN, NH₄⁺-N, NO₃⁻-N, DO, pH and TP. The animal husbandry output per capita was an important predictor of TP and turbidity, and the gross domestic product per capita largely determined spatial variations in EC. The remaining unexplained variance was related to other factors, such as topography. Our results suggested that pollution control of animal waste discharge in rural settlements, agricultural runoff in cropland, industrial production pollution and domestic pollution in urban and industrial areas were important within the Cao-E River basin. Moreover, the percentage of the total overall river water quality variance explained by an individual variable and/or all environmental variables (according to RDA) can assist in quantitatively identifying the primary factors that control pollution at the watershed scale.