Response of water quality in major tributaries to the difference of multi-scale landscape indicators in Dongting Lake basin, China.

River water quality has been increasingly deteriorated because of the influence of natural process and anthropogenic activities. Quantifying the influence of landscape metrics, namely topography and land use pattern, which encompass land use composition and landscape configuration, across different spatial and seasonal scales that reflect natural process and anthropogenic activities, is highly beneficial for water quality protection. In this study, we focused on investigating the effects of topography, landscape configuration and land use composition on water quality at different spatial scales, including 1-km buffer and sub-watershed, and seasonal scales, including wet and dry season, based on the monthly water quality data in 2016 of Dongting Lake in China. Multivariate statistical analysis of redundancy analysis and partial redundancy analysis was used to quantify the contributions of these factors under different scales. Our results showed that among the three environmental groups, topography made the greatest pure contribution to water quality, accounting for 11.4 to 30.9% of the variation. This was followed by landscape configuration, which accounted for 9.4 to 23.0%, and land use composition, which accounted for 5.9 to 15.7%. More specifically, water body made the greatest contribution to the water quality variation during dry season at both spatial scales, contributing 16.6 to 17.2% of the variation. In contrast, edge density was the primary interpreter of the variability in water quality during wet season at both spatial scales, accounting for 9.9 to 11.1% of the variation. The spatial variability in the influence of landscape metrics on water quality was not markedly distinct. However, these metrics have a minimal impact difference on water quality at the buffer scale and the sub-watershed scale. Moreover, the contribution of landscape configuration varied the most from the buffer to sub-watershed scales, indicating its importance for the spatial scale difference in water quality. The findings of this study offer useful insights into enhancing water quality through improved handling of landscape metrics.

Parsimonious Random-Forest-Based Land-Use Regression Model Using Particulate Matter Sensors in Berlin, Germany.

Machine learning (ML) methods are widely used in particulate matter prediction modelling, especially through use of air quality sensor data. Despite their advantages, these methods' black-box nature obscures the understanding of how a prediction has been made. Major issues with these types of models include the data quality and computational intensity. In this study, we employed feature selection methods using recursive feature elimination and global sensitivity analysis for a random-forest (RF)-based land-use regression model developed for the city of Berlin, Germany. Land-use-based predictors, including local climate zones, leaf area index, daily traffic volume, population density, building types, building heights, and street types were used to create a baseline RF model. Five additional models, three using recursive feature elimination method and two using a Sobol-based global sensitivity analysis (GSA), were implemented, and their performance was compared against that of the baseline RF model. The predictors that had a large effect on the prediction as determined using both the methods are discussed. Through feature elimination, the number of predictors were reduced from 220 in the baseline model to eight in the parsimonious models without sacrificing model performance. The model metrics were compared, which showed that the parsimonious_GSA-based model performs better than does the baseline model and reduces the mean absolute error (MAE) from 8.69 µg/m3 to 3.6 µg/m3 and the root mean squared error (RMSE) from 9.86 µg/m3 to 4.23 µg/m3 when applying the trained model to reference station data. The better performance of the GSA_parsimonious model is made possible by the curtailment of the uncertainties propagated through the model via the reduction of multicollinear and redundant predictors. The parsimonious model validated against reference stations was able to predict the PM2.5 concentrations with an MAE of less than 5 µg/m3 for 10 out of 12 locations. The GSA_parsimonious performed best in all model metrics and improved the R2 from 3% in the baseline model to 17%. However, the predictions exhibited a degree of uncertainty, making it unreliable for regional scale modelling. The GSA_parsimonious model can nevertheless be adapted to local scales to highlight the land-use parameters that are indicative of PM2.5 concentrations in Berlin. Overall, population density, leaf area index, and traffic volume are the major predictors of PM2.5, while building type and local climate zones are the less significant predictors. Feature selection based on sensitivity analysis has a large impact on the model performance. Optimising models through sensitivity analysis can enhance the interpretability of the model dynamics and potentially reduce computational costs and time when modelling is performed for larger areas.

Ecosystem health assessment of East Kolkata Wetlands, India: Implications for environmental sustainability.

The East Kolkata Wetlands (EKW) in Kolkata, India, span 12,500 ha and are a vital ecological zone providing several benefits, including water purification, flood control, and biodiversity support. This study investigated land use and land cover (LULC) alterations in the EKW from 1991 to 2023, using a random forest (RF) machine learning model. Significant LULC changes were observed over the 32 years, with wetland areas decreasing from 91.2 km2 in 1991 to 33.4 km2 in 2023, reflecting substantial habitat loss and reduced ecosystem services. Conversely, agricultural land expanded from 27.8 km2 to 58.7 km2, driven by economic and food production needs, and built-up areas increased dramatically from 0.2 km2 to 10.5 km2, indicating rapid urbanization. This study evaluated the health, resilience, and ecosystem functionality of EKW by analysing human-induced land use changes and using ecological indicators and landscape metrics. Landscape and class level metrics such as PLAND, largest patch index (LPI), total edge (TE), edge density (ED), number of patches (NP), and patch density (PD) were used to analyse the spatiotemporal dynamics of the wetlands. This study revealed a significant increase in fragmentation, with the number of patches increasing from 2689 in 1991 to 4532 in 2023, despite a consistent decrease in core wetland areas. Ecosystem health indicators, such as the ecosystem structure index (ESI) and landscape deviation degree (LDD), were used to assess landscape metrics and fragmentation changes. The ESI and other metrics revealed significant temporal fluctuations, providing insights into landscape structure, connectivity, and heterogeneity. The ESI improved from 0.87 in 1991 to 1.03 in 2023, indicating enhanced connectivity and diversity. Conversely, the LDD increased from 20.6% to 56.85%, indicating a shift towards impervious surfaces. The vegetation productivity and ecosystem health index (EHI) decreased, indicating biodiversity loss and reduced carbon sequestration. The EHI also dropped from 0.67 to 0.55, signifying ongoing environmental stress. This study emphasizes the need for conservation efforts to maintain the ecological integrity of the EKW amidst urbanization and land use changes and recommends a balanced approach for sustainable urban development and enhanced wetland resilience.

Assessing the impact of three biosphere reserves on the conservation of coastal ecosystems.

Biosphere Reserves (BR) manage large territories with diverse natural covers and land uses to preserve biodiversity, promote local development and preserve ecosystems. This study evaluated how their zoning (buffer and core) and policy timeframes (decree period, management plan period, and land planning period) influence four landscape management outcomes: deforestation, natural cover recovery, and anthropic and natural permanence. For three Mexican BR case studies, land use and cover transitions were calculated and compared to contrafactual sites. Observed rates of land cover change were marginal within all three BR zoning and across their policy timeframe (<0.02 % change rate), suggesting that BR effectively promote the permanence of both natural and anthropic covers. Nevertheless, the predicted probability of uncommon deforestation and recovery outcomes at local levels showed that the effect of a BR over its regulated landscape is not spatiotemporally static, contrasting the effect of individual allocation vs a group or network. Poverty, land tenure, agriculture aptitude and distance to markets adds to this dynamic and is modelled and discussed. This study shows that BR zoning schemes and its regulatory sequence influence the rates of land cover change and the predicted probability of landscape management outcomes across space and time.

Reptile responses to fire across the western Mediterranean Basin.

Effects of anthropogenic activities, including climate change, are modifying fire regimes, and the dynamic nature of these modifications requires identification of general patterns of organisms' responses to fire. This is a challenging task because of the high complexity of factors involved (including climate, geography, land use, and species-specific ecology). We aimed to describe the responses of the reptile community to fire across a range of environmental and fire-history conditions in the western Mediterranean Basin. We sampled 8 sites that spanned 4 Mediterranean countries. We recorded 6064 reptile sightings of 36 species in 1620 transects and modeled 3 community metrics (total number of individuals, species richness, and Shannon diversity) as responses to environmental and fire-history variables. Reptile community composition was also analyzed. Habitat type (natural vs. afforestation), fire age class (time since the last fire), rainfall, and temperature were important factors in explaining these metrics. The total number of individuals varied according to fire age class, reaching a peak at 15-40 years after the last fire. Species richness and Shannon diversity were more stable during postfire years. The 3 community metrics were higher under postfire conditions than in unburned forest plots. This pattern was particularly prevalent in afforested plots, indicating that the negative effect of fire on reptiles was lower than the negative effect of afforestation. Community composition varied by fire age class, indicating the existence of early- and late-successional species (xeric and saxicolous vs. mesic reptiles, respectively). Species richness was 46% higher in areas with a single fire age class relative to those with a mixture of fire age classes, which indicates pyrodiverse landscapes promoted reptile diversity. An expected shift to more frequent fires will bias fire age distribution toward a predominance of early stages, and this will be harmful to reptile communities.

Respuestas de reptiles al fuego en la Cuenca Mediterránea occidental Resumen Los efectos de actividades antropogénicas, incluyendo el cambio climático, están modificando los regímenes de fuego, y la naturaleza dinámica de estas modificaciones requiere la identificación de patrones generales de las respuestas de los organismos al fuego. Esta es una tarea desafiante debido a la gran complejidad de los factores involucrados (incluyendo clima, geografía, uso de suelo y la ecología de cada especie). Nuestro objetivo fue describir las respuestas de la comunidad de reptiles al fuego bajo diversas condiciones ambientales e historias de fuego en la Cuenca Mediterránea occidental. Muestreamos ocho sitios en cuatro países mediterráneos. Registramos 6064 avistamientos de reptiles de 36 especies en 1620 transectos y modelamos tres métricas comunitarias (número total de individuos, riqueza de especies y diversidad de Shannon) como respuestas a las variables ambientales y de historia de fuego. También analizamos la composición de la comunidad de reptiles. El tipo de hábitat (natural versus forestación), la clase de edad del fuego (tiempo transcurrido desde el último incendio), la precipitación pluvial y la temperatura fueron factores importantes en la explicación de estas métricas. El número total de individuos varió de acuerdo con la clase de edad del fuego, alcanzando un pico a los 15­40 años después del último incendio. La riqueza de especies y la diversidad de Shannon fueron más estables durante los años posteriores a incendios. Las tres métricas de la comunidad fueron más altas bajo condiciones post incendio que en las parcelas sin historial de fuego. Este patrón fue particularmente prevalente en parcelas forestadas, lo cual indica que el efecto negativo del fuego sobre los reptiles fue menor que el efecto negativo de la forestación. La composición de la comunidad varió por clase de edad del fuego, indicando la existencia de especies sucesionales tempranas y tardías (reptiles xéricos y saxícolas, respectivamente). La riqueza de especie fue 46% mas alta en áreas con una sola clase de edad del fuego que en aquellas con una mezcla de clases de edad del fuego, lo cual indica que los paisajes pirodiversos promovieron la diversidad de reptiles. Un cambio esperado hacia incendios más frecuentes sesgará la distribución de la edad del fuego hacia una predominancia de etapas tempranas, y esto será perjudicial para las comunidades de reptiles.

Land in limbo: Nearly one third of Indonesia's cleared old-growth forests left idle.

Indonesia has experienced rapid primary forest loss, second only to Brazil in modern history. We examined the fates of Indonesian deforested areas, immediately after clearing and over time, to quantify deforestation drivers in Indonesia. Using time-series satellite data, we tracked degradation and clearing events in intact and degraded natural forests from 1991 to 2020, as well as land use trajectories after forest loss. While an estimated 7.8 Mha (SE = 0.4) of forest cleared during this period had been planted with oil palms by 2020, another 8.8 Mha (SE = 0.4) remained unused. Of the 28.4 Mha (SE = 0.7) deforested, over half were either initially left idle or experienced crop failure before a land use could be detected, and 44% remained unused for 5 y or more. A majority (54%) of these areas were cleared mechanically (not by escaped fires), and in cases where idle lands were eventually converted to productive uses, oil palm plantations were by far the most common outcome. The apparent deliberate creation of idle deforested land in Indonesia and subsequent conversion of idle areas to oil palm plantations indicates that speculation and land banking for palm oil substantially contribute to forest loss, although failed plantations could also contribute to this dynamic. We also found that in Sumatra, few lowland forests remained, suggesting that a lack of remaining forest appropriate for palm oil production, together with an extensive area of banked deforested land, may partially explain slowing forest loss in Indonesia in recent years.

Assessing rural land use in contemporary China: Data compilation and methodology.

In rural areas, land use decisions are not only shaped by economic considerations but also deeply influenced by cultural and social factors. The objective of this research is to examine the complex and diverse aspects of making decisions about how land is used in rural communities, specifically by investigating the influence of cultural and social elements. Using empirical data and rigorous analysis, this research examine how traditional practices, social norms, and community dynamics influence land use patterns. The research topic focuses on the need to have a thorough understanding of the fundamental elements that affect land use choices in rural regions, going beyond only economic incentives. This research objective is to address a significant vacuum in the current literature by examining the cultural and social aspects of land usage. This research provides vital insights for policymakers and stakeholders engaged in land management and rural development projects. This research utilizes a mixed-methods approach, using qualitative interviews, participatory observations, and quantitative surveys to collect comprehensive data on the cultural and socioeconomic elements that impact land use choices. The research sample includes a wide range of rural areas, guaranteeing a thorough representation of various cultural settings and socioeconomic backgrounds. Our study reveals that cultural traditions, social networks, and power structures have a substantial impact on land use practices in rural regions. Traditional land tenure systems, community ownership arrangements, and customary land-use practices play a vital role in influencing land-use choices and resource distribution within communities. The significance of these results is substantial for policymakers, land managers, and rural development practitioners. Policymakers may create land use policies and actions that are more appropriate to the specific cultural and socioeconomic environment by understanding the complex relationship between these aspects. Furthermore, promoting community involvement and allowing local actors to participate in decision-making may result in land management results that are both more sustainable and fair.

Response of changes in lake area to drought and land use change.

The lake area is a crucial parameter that characterizes the state of a lake. Under the dual pressures of climate change and human activity, the magnitude and frequency of changes in lake areas become more pronounced. This process poses a serious threat to the local ecological environment. In this study, we constructed a lake water extraction model (LakeNet) based on a fully convolutional neural network. We extracted and analyzed the spatiotemporal characteristics of the area of nine major lakes from 1987 to 2022, as well as the driving factors behind these changes. Our results indicate that: 1) LakeNet exhibits high extraction accuracy and can remove some clouds. 2) The area of the nine major lakes shows a fluctuating downward trend (-8.11km2/10a), with drought and land use changes identified as significant driving forces behind the changes in lake boundaries, drought events caused the lake area to decrease, and the expansion of cropland further reduced the lake area. 3) Due to variations in lake area, the impact of drought on the area of the nine major lakes exhibits a lag effect, smaller lakes are likely to respond more quickly to drought.

Evaluating the quality of sediments in streams draining contrasting land-use areas in Osogbo metropolis, southwestern Nigeria.

The attendant effects of urbanization on the environment and human health are evaluable by measuring the potentially harmful element (PHE) concentrations in environmental media such as stream sediments. To evaluate the effect of urbanization in Osogbo Metropolis, the quality of stream sediments from a densely-populated area with commercial/industrial activities was contrasted with sediments from a sparsely-populated area with minimal anthropogenic input.Forty samples were obtained: 29 from Okoko stream draining a Residential/Commercial Area (RCA, n = 14) and an Industrial Area (IA, n = 15), and 11 from Omu stream draining a sparsely-populated area (SPA). The samples were air-dried, sieved to < 75 micron fraction, and analysed for PHEs using inductively-coupled plasma atomic emission spectrometry (ICP-AES). Index of geoaccumulation (Igeo), pollution index (PI), ecological risk factor (Er) and index (ERI) were used for assessment. Inter-elemental relationships and source identification were done using Pearson's correlation matrix and principal component analysis (PCA).PHE concentrations in the stream sediments were RCA: Zn > Pb > Cu > Cr > Sr > Ni > Co, IA: Zn > Cr > Ni > Co > Pb > Cu > Sr and SPA: Zn > Co > Cr > Cu > Sr > Ni > Pb. Igeo calculations revealed moderate-heavy contamination of Cu, Pb and Zn in parts of RCA, moderate-heavy contamination of Zn in IA while SPA had moderate contamination of Co and Zn. PI values revealed that stream sediments of RCA are extremely polluted, while those of IA and SPA are moderately and slightly polluted, respectively.The pollution of the stream sediments in RCA and IA is adduced to anthropogenic activities like vehicular traffic, automobile repairs/painting, blacksmithing/welding and metal scraping. In SPA however, the contamination resulted from the application of herbicides/fertilizers for agricultural purposes.

Investigating the impact of urban growth on land use using spatial autocorrelation methods in Konya/Türkiye.

Land use land cover (LULC) change, global environmental change, and sustainable change are frequently discussed topics in research at the moment. It is important to determine the historical LULC change process for effective environmental planning and the most appropriate use of land resources. This study analysed the spatial autocorrelation of the land use structure in Konya between 1990 and 2018. For this, Global and Local Moran's I indices based on land use data from 122 neighbourhoods and hot spot analysis (Getis-Ord Gi*) methods were applied to measure the spatial correlation of changes and to determine statistically significant hot and cold spatial clusters. According to the research results, the growth of urban areas has largely destroyed the most productive agricultural lands in the region. This change showed high spatial clustering both on an area and a proportional basis in the northern and southern parts of the city. On the other hand, the growth in the industrial area suppressed the pasture areas the most in the north-eastern region of the city, and this region showed high spatial clustering on both spatial and proportional scales.

Exposure of water purification deficit network in response to nitrogen application intensity.

Ecosystem services are strongly responsive to changes in land use intensity, especially for the service of water purification, which is highly sensitive to water pollutant emission. Increased nitrogen (N) application to cropland has potential impacts on the supply and demand for water purification through changes in land use intensity. However, there has been a lack of research focusing on the impacts of cropland N application on population exposure to water purification deficit and their cross-regional delivery network. Taking the Dongting Lake (DTL) Basin as an example, this study explored the spatial pattern of N exposure in the DTL Basin from 1990 to 2015 by integrating water purification deficit and population density. Changes in potential N exposure in 2050 were simulated based on population projection data from the Shared Socioeconomic Pathways (SSP1-5). N delivery pathways in the DTL Basin were clarified by constructing the N delivery network. The results showed that N exposure increased significantly with increasing N application in DTL Basin. The DTL surrounding area and lower reaches of the Xiangjiang River Basin had high increases of N exposure (50.2 % and 71.6 %) and high increases in N exposure due to increases in N application per unit (N influence coefficients exceeding 0.5). The lower reaches of the Xiangjiang River Basin with the highest population density had the smallest decrease in N exposure (1.4 %-11.1 %) in the SSP1-5 scenarios. During 1990-2015, the increase of N export to the DTL surrounding area was higher in the lower reach sub-basins of DTL Basin. N application had a stronger impact on N delivery processes in the lower reaches of DTL Basin. Managers should distribute N applications to basins with high N retention and low N export to the DTL surrounding area. This study confirmed the strong response of water purification deficit and its population exposure to N application, and provided decision-making guidelines for water quality enhancement in DTL Basin from a spatial planning perspective.

The future of plant diversity within a Mediterranean endemism centre: Modelling the synergistic effects of climate and land-use change in Peloponnese, Greece.

Climate- and land-use change stand as primary threats to terrestrial biodiversity. Yet, their synergistic impacts on species distributions remain poorly understood. To address this knowledge gap, we conducted the first-ever comprehensive species distribution analysis on an entire regional endemism centre within an eastern Mediterranean country, incorporating dynamic land-use/land-cover change data together with climate change scenarios. Specifically, we apply species distribution modelling and spatial data analysis techniques to compare the individual and synergistic effects of these environmental drivers on the endemic vascular flora of Peloponnese, focusing on potential range contractions, altitudinal shifts, and habitat fragmentation levels. Moreover, we identify fine-scale present and potential future endemism hotspots within our study area, incorporating taxonomic and phylogenetic information. Overall, we aim to enhance our current understanding of endemism patterns and contribute to the development of future-proof conservation strategies for safeguarding Greece's endangered endemic flora. The integration of land-use change projections with climate change yielded less severe impacts compared to the effects anticipated when considering climatic variables alone. Most taxa are expected to undergo significant range declines and nearly half might experience increased habitat fragmentation, due to the synergistic effects of climate- and land-use change. We identified endemism hotspots, which are concentrated in or along the main Peloponnesian mountain massifs. However, our predictions indicate that areas presently recognized as endemism hotspots will undergo a concerning area decline, across all future scenarios considered in this study. Our findings highlight the importance of including dynamic land-use variables alongside climatic predictors when projecting species distributions under global change. Moreover, we showed that endemism hotspots are not static and considering their potential geographic shifts is paramount to delineate effective forward-looking conservation strategies.

Spatial distribution, pollution level and human health risk assessment of heavy metals in urban street dust at neighbourhood scale.

Urban street dust (UStD) is a vital issue for human health and is crucial for urban sustainability. This study aims to enhance the creation of safe, affordable, and resilient cities by examining environmental contamination and health risks in urban residential areas. Specifically, it investigates the concentrations and spatial distribution of chromium (Cr), cadmium (Cd), nickel (Ni), copper (Cu), lead (Pb), and zinc (Zn) in UStD in Yenimahalle, Ankara. The mean concentrations of Zn, Cr, Pb, Cd, Ni, and Cu in UStD were 97.98, 66.88, 55.22, 52.45, 38.37, and 3.81 mg/kg, respectively. The geoaccumulation pollution index (Igeo) values for these elements were: Cd (5.12), Ni (1.61), Cr (1.21), Pb (1.13), Cu (0.78), and Zn (0.24). These indices indicate that the area is moderately polluted with Cr, Pb, and Ni, uncontaminated to moderately contaminated with Cu and Zn, and extremely polluted with Cd. The hazard index (HI) values for Cr, Cd, Ni, Cu, Pb, and Zn were below the non-carcinogenic risk threshold for adults, indicating no significant risk. However, for children, the HI values for Pb, Ni, Cd, and Zn were 3.37, 1.80, 1.25, and 1.25, respectively, suggesting a higher risk. Carcinogenic risk (RI) of Cd, Ni, and Pb was significant for both children and adults, indicating that exposure through ingestion, inhalation, and dermal contact is hazardous. The findings highlight the need for strategic mitigation measures for both natural and anthropogenic activities, providing essential insights for residents, policymakers, stakeholders, and urban planners.

Artificial neural networks in soil quality prediction: Significance for sustainable tea cultivation.

In today's era artificial intelligence is quite popular, one of the most effective algorithms used is Artificial Neural Networks (ANN). In this study, the determination of soil quality using the Soil Management Assessment Framework (SMAF) model in areas where tea cultivation is carried out at the micro-watershed scale and the predictability of soil quality using ANN were evaluated. According to the results, the soil quality indices of tea-growing areas were generally classified as "medium" between 55 and 70 %. Among the evaluated features for determining soil quality, the highest relative importance value was for soil organic carbon content (13 %) and potential mineralizable nitrogen (13 %), whereas the lowest values were for exchangeable potassium (4 %) and sodium adsorption ratio (SAR) (4 %). In addition, when comparing the actual and predicted values for soil quality prediction using ANN, the Lin's concordance correlation coefficient (LCCC), ratio of performance to deviation (RPD), and R2 values were found to be 0.93, 2.95, and 0.89, respectively. Significant properties for the determined values within a 90 % predicted interval were found to be organic matter, microbial biomass carbon, bulk density, and aggregate stability of the soils. Moreover, the uncertainty values (standard deviation) in the model predictions were determined to be within the range of 1.01-4.56 %. Consequently, the Soil Quality Index (SQI) obtained from the SMAF model using 12 soil properties in tea-growing areas could be accurately predicted using ANN. As a result of this study, digital maps showing the spatial distribution of SQI and the predicted uncertainties can help monitor SQI levels in this area.

The spatial overlay effect of urban waterlogging risk and land use value.

Urban waterlogging poses a severe threat to lives and property globally, making it crucial to identify the distribution of urban value and waterlogging risk. Previous research has overlooked the heterogeneity of value and risk in spatial distribution. To identify the overlay effect of urban land value and risk, this study employs the Entropy Weighting Method (EM) to assess urban value, Principal Component Analysis (PCA) to determine waterlogging risk and key areas (RK), local Moran's I (SC) to identify key areas (HK), and finally Bivariate local Moran's I (DC) to comprehensively evaluate urban value and waterlogging risk to delineate key areas (BH). The results indicate that waterlogging risk is primarily influenced by proximity to water systems (PCA coefficient: 0.567), population density (0.550), and rainfall (0.445). There is a positive correlation between urban value and waterlogging risk, with a global Moran's I of 0.536, indicating that areas with higher urban value also face greater waterlogging risk. The DC method improved identification precision, reducing the BH area by 6.42 and 3.51 km2 compared to RK and HK, accounting for 25.50 % and 15.76 % of the RK and HK identified areas, respectively. At present, rescue resources can access less than one-third of the area within 5 min, but with the DC method, during the centennial rainfall scenario, the accessibility rate within 5 min for the BH area reaches 63 %, and all BH key areas can be covered within 15 min. This study provides a new methodology for identifying key areas of waterlogging disasters and can be used to enhance urban rescue efficiency and the precision management of flood disasters.

Natural background levels and driving factors of aluminum in shallow groundwater of an urbanized delta: Insight from eliminating anthropogenic-impacted groundwaters.

Knowledge on natural background levels (NBLs) of aluminum (Al) in groundwater can accurately assess groundwater Al contamination at a regional scale. However, it has received little attention. This study used a combination of preselection and statistic methods consisting of the oxidation capacity and the boxplot iteration methods to evaluate the NBL of shallow groundwater Al in four groundwater units of the Pearl River Delta (PRD) via eliminating anthropogenic-impacted groundwaters and to discuss driving factors controlling high NBLs of Al in groundwater in this area. A total of 280 water samples were collected, and 18 physico-chemical parameters including Redox potential, dissolved oxygen, pH, total dissolved solids, HCO3 -, NH4 +, NO3 -, SO4 2-, Cl-, NO2 -, F-, K+, Na+, Ca2+, Mg2+, Fe, Mn, and Al were analyzed. Results showed that groundwater Al NBLs in groundwater units A-D were 0.11, 0.16, 0.15, and 0.08 mg/L, respectively. The used method in this study is acceptable for the assessment of groundwater Al NBLs in the PRD, because groundwater Al concentrations in various groundwater units in residual datasets were independent of land-use types, but they were opposite in the original datasets. The dissolution of Al-rich minerals in sediments/rocks was the major source for groundwater Al NBLs in the PRD, and the interaction with Al-rich river water was secondary one. The high groundwater Al NBL in groundwater unit B was mainly attributed to the acid precipitation and the organic matter mineralization inducing the release of Al in Quaternary sediments. By contrast, the high groundwater Al NBL in groundwater unit C mainly was ascribed to the release of Al complexes such as fluoroaluminate from rocks/soils into groundwater induced by acid precipitation, but it was limited by the dissolution of Mg minerals (e.g., dolomite) in aquifers. This study provides not only useful groundwater Al NBLs for the evaluation of groundwater Al contamination but also a reference for understanding the natural geochemical factors controlling groundwater Al in urbanized deltas such as the PRD. PRACTITIONER POINTS: The natural background level (NBL) of groundwater aluminum in the Pearl River Delta (PRD) was evaluated. The dissolution of aluminum-rich minerals in sediments/rocks was the major source for groundwater aluminum NBLs in the PRD. The acid precipitation and organic matter mineralization contribute to high groundwater Al NBL in the groundwater unit B. The acid precipitation contributes to high groundwater Al NBL in the groundwater unit C, while dissolution of magnesium minerals limits it.

Combining Google Earth historical imagery and UAV photogrammetry for urban development analysis.

Rural-urban migration often triggers additional demand for housing and infrastructural development to cater for the growing population in urban areas. Consequently, town planners and urban development authorities need to understand the urban development trend to make sustainable urban planning decisions. Yet, methods to analyse changes and trends in urban spatial development are often complex and require costly data collection. This article thus presents a simplified method to analyse the urban development trend in an area. The method integrates Google Earth (GE) historical imagery (baseline data) and unmanned aerial vehicle (UAV) photogrammetry (recent data) to quantify the changes over time. This approach can be applied to study the urban development trends in low-income countries with budget constraints. The method is discussed under four main headings: (1) background, (2) method details, (3) limitations, and (4) conclusion.•Google Earth historical image can be extracted with its associated world file.•The population of an area can be estimated by using average household size data and the number of residential buildings in the area.•The building height ratio can be used to ascertain if the land is being used parsimoniously.

Exploring spatial and temporal symptoms of the freshwater salinization syndrome in a rural to urban watershed.

The freshwater salinization syndrome (FSS), a concomitant watershed-scale increase in salinity, alkalinity, and major-cation, and trace-metal concentrations, over recent decades, has been described for major rivers draining extensive urban areas, yet few studies have evaluated temporal and spatial FSS variations, or causal factors, at the subwatershed scale in mixed-use landscapes. This study examines the potential influence of land-use practices and wastewater treatment plant (WWTP) effluent on the export of major ions and trace metals from the mixed-use East Branch Brandywine Creek watershed in southeastern Pennsylvania, during the 2019 water year. Separate analysis of baseflow and stormflow subsets revealed similar correlations among land-use characteristics and streamwater chemistry. Positive associations between percent impervious surface cover, which ranged from 1.26 % to 21.9 % for the 13 sites sampled, and concentrations of Ca2+, Mg2+, Na+, and Cl- are consistent with road-salt driven reverse cation exchange and weathering of the built environment. The relative volume of upstream WWTP was correlated with Cu and Zn, which may be derived in part from corroded water-conveyance infrastructure; chloride to sulfate ratios (CSMR) ranged from ~6.3 to ~7.7× the 0.5 threshold indicating serious corrosivity potential. Observed exceedances of U.S. Environmental Protection Agency Na+ and Cl- drinking water and aquatic life criteria occurred in winter months. Finally, correlation between percent cultivated cropland and As and Pb concentrations may be explained by the persistence of agricultural pesticides that had been used historically. Study results contribute to the understanding of FSS solute origin, fate, and transport in mixed-use watersheds, particularly those in road salt affected regions. Study results also emphasize the complexity of trace-metal source attribution and explore the potential for FSS solutes to affect human health, aquatic life, and infrastructure.

Woody encroachment: social-ecological impacts and sustainable management.

Woody plants are encroaching across terrestrial ecosystems globally, and this has dramatic effects on how these systems function and the livelihoods of producers who rely on the land to support livestock production. Consequently, the removal of woody plants is promoted widely in the belief that it will reinstate former grasslands or open savanna. Despite this popular management approach to encroachment, we still have a relatively poor understanding of the effects of removal on society, and of alternative management practices that could balance the competing needs of pastoral production, biodiversity conservation and cultural values. This information is essential for maintaining both ecological and societal benefits in encroached systems under predicted future climate changes. In this review, we provide a comprehensive synthesis of the social-ecological perspectives of woody encroachment based on recent studies and global meta-analyses by assessing the ecological impacts of encroachment and its effects on sustainable development goals (SDGs) when woody plants are retained and when they are removed. We propose a working definition of woody encroachment based on species- and community-level characteristics; such a definition is needed to evaluate accurately the effects of encroachment. We show that encroachment is a natural process of succession rather than a sign of degradation, with encroachment resulting in an overall 8% increase in ecosystem multifunctionality. Removing woody plants can increase herbaceous plant richness, biomass and cover, but at the expense of biocrust cover. The effectiveness of woody plant removal depends on plant identity, and where, when and how they are removed. Under current management practices, either removal or retention of woody plants can induce trade-offs among ecosystem services, with no management practice maximising all SDGs [e.g. SDG2 (end hunger), SDG13 (climate change), SDG 15 (combat desertification)]. Given that encroachment of woody plants is likely to increase under future predicted hotter and drier climates, alternative management options such as carbon farming and ecotourism could be effective land uses for areas affected by encroachment.

Quantifying spatiotemporal dynamics in the Kolonnawa marsh of Colombo, Sri Lanka.

Kolonnawa marsh (KM) is an important wetland ecosystem in Colombo district, Sri Lanka that provides essential ecosystem services, and has undergone significant changes over recent decades due to continuous exploitation and reclamation. The values of wetlands are disregarded by decision-makers, despite the fact that they are crucial for improving the quality of water and offer chances for relaxation and amusement in metropolitan areas. Underestimation of the value of wetlands contributes to their continuing deterioration and inevitable loss. Investigating the changes in wetlands can provide crucial information for decision-making. This study aimed to monitor the spatiotemporal land-cover dynamics of KM with the prospect prediction as reduced total extent of KM gradually with time and marsh area being transformed into terrestrial vegetation with time. The collective images from Google Earth (2000 to 2021) and drone data (2022) were analyzed with the GIS application. Subsequently, 50-m2 grid squares with unique cell IDs are designed to link among land cover maps for spatiotemporal land-cover change analysis. Then, we calculate land cover category: surface water, marsh, and terrestrial vegetation proportions for each map in 50-m2 grid cells. Statistical comparison of the land cover changes in grid square cells shows that each land cover category has significant change with the time. The results showed that the reduction of KM marsh resulting in land cover changes has a positive implication on wetland degradation. Thus, interventions should be made for the restoration and sustainable management of KM.