Identifying the relationships between water quality and land cover changes in the Tseng-Wen reservoir watershed of Taiwan

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.

Analysis of water quality indexes and their relationships with vegetation using self-organizing map and geographically and temporally weighted regression

Natural vegetation has been proved to promote water purification in previous studies, while the relevant laws has not been excavated systematically. This research explored the relationships between vegetation cover and water quality indexes in Liaohe River Basin in China combined with self-organizing map (SOM) and geographically and temporally weighted regression (GTWR) innovatively and systematically based on the distributing heterogeneity of water quality conditions. Results showed that the central and northeast regions of the study area had serious organic and nutrient pollution, which needed targeted treatment. And SOM verified that high vegetation coverage with retention potential of organic and inorganic pollutants as well as nutrients improved water quality to some degree, while the excessive discharges of pollutants still had serious threats to nearby water environment despite the purification function of vegetation. GTWR indicated that the waterside vegetation was beneficial for dissolved oxygen increasing and contributed to the decreasing of organic pollutants and inorganic pollutants with reducibility. Natural vegetation also obsorbed nutrients like TN and TP to some degree. However, the retential potential of nitrogen and organic pollutants became not obvious when there were heavy pollution, which demonstrated that pollution sources should be controlled despite the purification function of vegetation. This study implied that natural vegetation purified water quality to some degree, while this function could not be revealed when there was too heavy pollution. These findings underscore that the pollutant discharge should be controlled though the natural vegetation in ecosystem promoted the purification of water bodies.

Analysis of indicators of surface water pollution in Atlantic Forest preservation areas

Managing water resources in regions with scarce data, like most developing countries, is still one of the major challenges around the world. Analysis of water quality parameters can provide important information for understanding the current status of water resources and their surroundings, including the changes that have occurred over time. This study aims to evaluate the influence of preservation areas on surface water quality in the Atlantic Forest biome. For this purpose, water quality monitoring sites with a greater number of parameters and longer monitoring time, located in six basins in the Atlantic Forest region of Brazil near preservation areas, were selected. This study employs seven statistical methods, such as cluster and principal component analysis (PCA), and promotes a robust analysis of the pollution of water resources in the Atlantic Forest. The most preserved basins, with more than 87% preservation area, have lower levels of pollution. The second most degraded basin, with 56% preservation area, presents intermediate pollution levels. The most degraded basin has the highest level of pollution. The basin with the lowest area of native vegetation is considered a degraded basin. Finally, non-point sources of pollution from agricultural activities were identified as the main sources of pollution in the region. The cophenetic correlation of 0.97 indicates a good performance of the cluster analysis. In addition, the pre-tests of PCA showed the suitability of the data for performing the test (Bartlett test, < 2.2e^-16 and KMO, P= 0.7). The first principal component in the PCA, which accounts for 31.4% of the total variation, is associated with strong ammonia nitrogen and total Kjeldahl nitrogen loads, and moderate biological oxygen demand and nitrite loads. The second component, representing 13.6% of the total variation, indicates periods of self-cleaning of water resources after contamination. The results indicate the importance of maintaining preservation areas in the watershed contribution areas for the improvement of surface water quality in the Atlantic Forest.

Save reservoirs of humid subtropical cities from eutrophication threat

Reservoir water is the most important freshwater resource for many cities, especially in densely populated humid subtropical areas. Economic growth, population increase, and urbanization have been putting reservoir water of Shenzhen (China), a humid subtropical city, under severe threat of eutrophication and water supply shortage. In this study, we focused on an upstream reservoir of Shenzhen and established a 3-dimensional hydrodynamic-ecological model to investigate the water dynamics and nutrient budget. Tributaries to the reservoir were identified as the greatest contributors to nitrogen and phosphorus loads. Zones with weak flows and high nutrient concentration have high risks of causing blooms. Several mitigation measures were proposed, including improving flow by adding additional water exit locations in the reservoir, reducing nutrients in tributaries, and enhancing algal predation, and were evaluated with the established model. The strategies combining hydrodynamic improvement and phosphorus reduction were suggested to decision makers and government managers for short-term management. However, for future water safety, excessive nitrogen is a potential danger. This study provides a modeling framework that can be applied to anthropogenic-influenced reservoirs elsewhere.

Scenario-Based Hydrological Modeling for Designing Climate-Resilient Coastal Water Resource Management Measures: Lessons from Brahmani River, Odisha, Eastern India

Widespread urban expansion around the world, combined with rapid demographic and climatic changes, has resulted in serious pollution issues in many coastal water bodies. To help formulate coastal management strategies to mitigate the impacts of these extreme changes (e.g., local land-use or climate change adaptation policies), research methodologies that incorporate participatory approaches alongside with computer simulation modeling tools have potential to be particularly effective. One such research methodology, called the “Participatory Coastal Land-Use Management” (PCLM) approach, consists of three major steps: (a) participatory approach to find key drivers responsible for the water quality deterioration, (b) scenario analysis using different computer simulation modeling tools for impact assessment, and (c) using these scientific evidences for developing adaptation and mitigation measures. In this study, we have applied PCLM approach in the Kendrapara district of India (focusing on the Brahmani River basin), a rapidly urbanizing area on the country’s east coast to evaluate current status and predict its future conditions. The participatory approach involved key informant interviews to determine key drivers of water quality degradation, which served as an input for scenario analysis and hydrological simulation in the next step. Future river water quality (BOD and Total coliform (Tot. coli) as important parameters) was simulated using the Water Evaluation and Planning (WEAP) tool, considering a different plausible future scenario (to 2050) incorporating diverse drivers and pressures (i.e., population growth, land-use change, and climate change). Water samples (collected in 2018) indicated that the Brahmani River in this district was already moderately-to-extremely polluted in comparison to the desirable water quality (Class B), and modeling results indicated that the river water quality is likely to further deteriorate by 2050 under all of the considered scenarios. Demographic changes emerged as the major driver affecting the future water quality deterioration (68% and 69% for BOD and Tot. coli respectively), whereas climate change had the lowest impact on river water quality (12% and 13% for BOD and Tot. coli respectively), although the impact was not negligible. Scientific evidence to understand the impacts of future changes can help in developing diverse plausible coastal zone management approaches for ensuring sustainable management of water resources in the region. The PCLM approach, by having active stakeholder involvement, can help in co-generation of the coastal management options followed by open access free software, and models can play a relevant cost-effective approach to enhance science-policy interface for conservation of natural resources.

Compound-specific isotope analysis with nested sampling approach detects spatial and temporal variability in the sources of suspended sediments in a Scottish mesoscale catchment

Intensification of land use is a primary cause of increased suspended sediment load in freshwater systems, hence land-use-specific sediment source tracing is necessary to inform sustainable land and water management. Here we tested the application of compound-specific isotope analysis (CSIA) of vegetation biomarkers to fingerprint suspended sediment sources from the mesoscale agricultural Tarland catchment (74 km²) in NE Scotland. Our aim was to test a parsimonious nested sampling approach from a headwater sub-catchment to apportion suspended sediment sources across headwater to catchment-wide scales. Compound-specific carbon isotopic signatures (δ¹³C) of long-chain fatty acids (LCFAs) from source soils were able to successfully distinguish between forest, heather moorland, permanent grassland, and arable land cover. Permanent grassland was a prominent source of sediment at both headwater and catchment scales, with an annual average contribution of 79% and 56%, respectively, indicating grazing pressure and runoff via preferential pathways. Increased sediment input from arable land at the catchment scale (40%) compared to the headwater sub-catchment (18%) indicated land use intensification in lowland areas. Forest and heather moorland contributed marginally to suspended sediments (~2%), despite covering 43% area of the catchment area. Temporal variability of sediment sources observed over fourteen months (May 2017 - June 2018) showed a higher relative contribution from arable land during summer and autumn and a higher contribution from permanent grassland during winter and spring, likely linked to seasonality of rainfall and agronomic activities. These results demonstrate a successful use of δ¹³C values of LCFAs to quantify land-use-specific suspended sediment sources. Comparison of two suspended sediment techniques showed usefulness of time-integrated mass samplers for representative and cost-effective sampling. We recommend that future nested sampling designs should include spatially distributed source soil tracer characterization covering the whole catchment area to reduce the uncertainty in sediment source attribution from headwaters to the catchment outlet.

Assessment of intensive agriculture on water quality in the Culiacan River basin, Sinaloa, Mexico

The percentage of agricultural land cover effect on water quality in Culiacan River basin is studied in this research. The basin contains only intensive cropland as primary economic activity with 60% of the total area. Mathematical relationships between percentages of cropland and total phosphorus (TP) and total nitrogen (TN) concentrations were established. Sampling sites in middle and lower basin and water quality information during 2013-2018 were considered, and percentages of cropland were obtained by geospatial methods including variable area buffers. During rainy season, coefficients of determination were less than 0.2, although quantified nutrient concentration was higher, related to point sources of pollution in the basin. During dry season, coefficients of determination were higher than 0.76 and 0.90 for TN and TP, respectively, with an exponential mathematical trend. Results suggest that intensive agriculture practices generate accelerated loss of soil consolidation, which is transported to water bodies. These soils are in continuous contact with fertilizers and pesticides, mostly organophosphates which have been transported by runoff and underground flows. Using the information generated will help to establish environmental management plans, and to improve environmental diagnosis and effect in countries where there is not enough historical cartographic information and/or water quality data.

Land Use/Land Cover Changes Impact on Groundwater Level and Quality in the Northern Part of the United Arab Emirates

This study aims to develop an integrated approach for mapping and monitoring land use/land cover (LULC) changes and to investigate the impacts of LULC changes and population growth on groundwater level and quality using Landsat images and hydrological information in a Geographic information system (GIS) environment. All Landsat images (1990, 2000, 2010, and 2018) were classified using a support vector machine (SVM) and spectral analysis mapper (SAM) classifiers. The result of validation metrics, including precision, recall, and F1, indicated that the SVM classier has a better performance than SAM. The obtained LULC maps have an overall accuracy of more than 90%. Each pair of enhanced LULC maps (1990–2000, 2000–2010, 2010–2018, and 1990–2018) were used as input data for an image difference algorithm to monitor LULC changes. Maps of change detection were then imported into a GIS environment and spatially correlated against the spatiotemporal maps of groundwater level and groundwater quality. The results also show that the approximate built-up area increased from 227.26 km2 (1.39%) to 869.77 km2 (7.41%), while vegetated areas (farmlands, parks and gardens) increased from about 76.70 km2 (0.65%) to 290.70 km2 (2.47%). The observed changes in LULC are highly linked to the depletion in groundwater level and quality across the study area from the Oman Mountains to the coastal areas.

Spatial and Temporal Variations in Water Quality and Land Use in a Semi-Arid Catchment in Bolivia

Increasing pressures caused by human activities pose a major threat to water availability and quality worldwide. Water resources have been declining in many catchments during recent decades. This study investigated patterns of river water quality status in a peri-urban/rural catchment in Bolivia in relation to land use during a 26 year period. Satellite images were used to determine changes in land use. To assess water quality, data in the dry season from former studies (1991–2014), complemented with newly collected data (2017), were analysed using the National Sanitation Foundation-Water Quality Index method and the Implicit Pollution Index method. The highest rates of relative increase in land use area were observed for forest, urban, and peri-urban areas, whereas relative decreases were observed for water infiltration zones, bare soil, shrubland, and grassland areas. The water quality indices revealed clear water quality deterioration over time, and from catchment headwaters to outlet. Statistical analyses revealed a significant relationship between decreasing water quality and urban expansion. These results demonstrate the need for an effective control programme, preferably based on water quality index approaches as in the present study and including continuous monitoring of runoff water, mitigation of pollution, and water quality restoration, in order to achieve proper water management and quality.

Effect of Land Use Changes on Water Quality in an Ephemeral Coastal Plain: Khambhat City, Gujarat, India

Rapid changes in land use and land cover pattern have exerted an irreversible change on different natural resources, and water resources in particular, throughout the world. Khambhat City, located in the Western coastal plain of India, is witnessing a rapid expansion of human settlements, as well as agricultural and industrial activities. This development has led to a massive increase in groundwater use (the only source of potable water in the area), brought about significant changes to land management practices (e.g., increased fertilizer use), and resulted in much greater amounts of household and industrial waste. To better understand the impacts of this development on the local groundwater, this study investigated the relationship between groundwater quality change and land use change over the 2001–2011 period; a time during which rapid development occurred. Water quality measurements from 66 groundwater sampling wells were analyzed for the years 2001 and 2011, and two water quality indicators (NO3− and Cl− concentration) were mapped and correlated against the changes in land use. Our results indicated that the groundwater quality has deteriorated, with both nitrate (NO3−) and chloride (Cl−) levels being elevated significantly. Contour maps of NO3− and Cl− were compared with the land use maps for 2001 and 2011, respectively, to identify the impact of land use changes on water quality. Zonal statistics suggested that conversion from barren land to agricultural land had the most significant negative impact on water quality, demonstrating a positive correlation with accelerated levels of both NO3− and Cl−. The amount of influence of the different land use categories on NO3− increase was, in order, agriculture > bare land > lake > marshland > built-up > river. Whereas, for higher concentration of Cl− in the groundwater, the order of influence of the different land use categories was marshland > built-up > agriculture > bare land > lake > river. This study will help policy planners and decision makers to understand the trend of groundwater development and hence to take timely mitigation measures for its sustainable management.

Effect of watershed land use on tributaries' water quality in the east African Highland

A study was carried out on four tributaries of Gilgel Gibe Reservoir to identify water physicochemical characteristics in different land use categories (farmland, naturally vegetated land, and settlement). Water samples were collected from 12 sampling sites along four permanent streams flowing into Gilgel Gibe Reservoir. Data sets were evaluated using nonparametric statistical techniques. Dissolved oxygen (DO), temperature, biochemical oxygen demand (BOD₅), total phosphorus (TP), soluble reactive phosphorus (SRP), total nitrogen (TN), turbidity, total dissolved solids (TDS), and total suspended solids (TSS) spatially showed significant differences in the wet season and DO, temperature, and BOD₅ varied significantly during the dry season. When excluding DO, electrical conductivity (EC), and TP during the wet and dry seasons, the remaining variables showed significant differences. During the wet season, concentrations of most water quality parameters were greatest in influents from agricultural land. Pollution and eutrophication risk is closely associated with drainage from agricultural land, requiring that emphasis and priorities be given to land use management and conservation.

The Effects of Storm Runoff on Water Quality and the Coping Strategy of a Deep Canyon-Shaped Source Water Reservoir in China

Storm runoff events in the flooding season affect the water quality of reservoirs and increase risks to the water supply, but coping strategies have seldom been reported. The phenomenon of turbid current intrusion resulting in water turbidity and anoxic conditions reappearing after storm runoff, resulting in the deterioration of water quality, was observed in the flooding season in the deep canyon-shaped Heihe Reservoir. The objective of this work was to elucidate the effects of storm runoff on the Heihe Reservoir water quality and find a coping strategy. In this study, an intensive sampling campaign measuring water temperature, dissolved oxygen, turbidity, nutrients, and metals were conducted in the reservoir over a period of two years, and the water-lifting aerators were improved to achieve single aeration and a full layer of mixing and oxygenation functions using different volumes of gas. The operation of the improved water-lifting aerators mixed the reservoir three months ahead of the natural mixing time, and good water quality was maintained during the induced mixing period, thereby extending the good water quality period. The results can provide an effective coping strategy to improve the water quality of a source water reservoir and ensure the safety of drinking water.