Watershed Ecology and the Environment最新文献

Wetland changes are very serious ecosystem problems, which stem from unrestrained human and environmental actions. Despite significant attention in environmental management research, the means to tackle wetland changes are still gaining momentum in science and research within developing countries. With the increasing availability of remote sensing data and flexible solutions, finding the right solution to wetland changes becomes a key research and policy agenda. Herein, we assessed the wetland change prediction of Ogun River (OR) basin, Nigeria, during 1999, 2009, and 2019 by analyzing land cover change (LCC) images using cellular automata-Markov (CA-Markov) chain and remote sensing (RS) techniques. The acquired shuttle radar topographic mapper and Landsat remotely sensed data were applied to create thematic-maps of the normalized difference vegetation index (NDVI), normalized difference salinity index (NDSI), and digital elevation model (DEM) of the study area. The CA-Markov required the supervised classification of the land cover maps of 1999, 2009, and 2019. The results of the elevation, NDVI, and NDSI revealed the qualitative differences in the study area. The LCC analysis indicated that farmlands and built-up areas increased by 54.56 and 33.21 %, respectively. However, waterbodies, wetlands, and vegetation decreased by 0.42, 3.53, and 8.28 % respectively. These findings agree with the CA-Markov with an accuracy exceeding 70 %, and, thus predict the wetland changes for the year 2030. The major attributions to wetland cover variations in the study area are built-up encroachment with extensive, spontaneous, and uncontrolled agricultural activities. This study, through its findings, provides relevant guidelines and information on wetland changes required by stakeholders for environmental policy, planning, and sustainability.

New Zealand’s freshwater resources in coastal regions are under increasing pressure from demands for drinking, irrigation and industrial uses, and climate change effects, particularly sea level rise. The management of water resources needs to balance values associated with (but not limited to) economy, society, ecology, culture, recreation and water quality. To assist the management of water resources in the Motueka-Riwaka Plains, New Zealand, a numerical integrated surface-groundwater model was developed. Calibration of the transient integrated surface-groundwater model was achieved with a root mean square error (RMSE) of 2.6% for groundwater levels. Model verification against groundwater levels not used in the calibration also resulted in an RMSE of 2.6% for groundwater levels. Model outputs, coupled with groundwater trend analyses, were used to identify the impact of groundwater abstractions on rivers, streams and groundwater-fed springs. Trend analyses showed that groundwater levels are lowering in the central area of the plains. Model scenarios predict that additional groundwater abstraction of over 30,000 m³/day from a well field located near the central area of the plains (adjacent to the Motueka River) is unlikely to increase the risk of saltwater intrusion and will result in surface water flow depletion within acceptable limits.

An analytical protocol was developed to quantify six-category pharmaceuticals in surface water under paralleling pHs using a combination of solid phase extraction (SPE) and high-performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS). Of 121 compound standards commercially, 94 compounds were reliably quantified using a paralleling pH combination at 3 and 9 with a sound recovery-rate of 50-150%. The quantified compounds covered 6 categories as 37 antibiotics, 16 central nervous system drugs (CNs), 14 cardiovascular drugs (CVs), 12 endocrine and family planning drugs (EFs), 8 antiparasitic drugs (APs), and 7 non-steroidal anti-inflammatory drugs (NSAIDs). The protocol achieved limits of detection and quantitation in ranges of 0.001–11.9 ng L^–1 and 0.003–39.7 ng L^–1, respectively. Serial field surface water samples from Jiulong River in Fujian, China were testified using the protocol with 41 quantified compounds of the above-mentioned 6 categories from < LODs to 1,389 ng L⁻¹ (caffeine). The key procedure prior to the SPE is to split filtrate of each surface water sample into two portions, adjusted to pH 3 and 9 separately and both spiked with 0.2 g Na₂EDTA.

The contamination of freshwater resource by heavy metals is still a major environmental and human health concern globally. The release of these contaminants into the aquatic environment can lead to the pollution of water resources and generate risks for aquatic living organisms and human health. The sediments can act as reservoir for heavy metals, thereby they are used to assess the pollution status of the rivers. In the present investigation, surface sediments collected from two urban rivers named, N’djili and Lukaya draining through the city of Kinshasa, Democratic Republic of the Congo were characterized for grain size, organic matter (OM) and heavy metals. Additionally, Sediment Quality Guidelines for the protection of aquatic life (SQGs), enrichment factor (EF) and geoaccumulation index (Igeo) were performed to determine the river pollution status. The results highlight high concentrations of heavy metals in sediment samples mainly from N’djili River, reaching the values (mg kg⁻¹) of 180.3 (Cu), 451.5 (Zn), 185.8 (Pb) and 4.1 (Hg). These values exceed the SQGs. Based on EF and Igeo values, the sediments from the two rivers have severe enrichment and polluted with Cu, Zn and Pb, and moderate enrichment of Cr and As. In general, the positive correlation was observed between some heavy metals and OM suggesting that these contaminants could have originated from common sources with a similar transport pathway. Based on the SQGs, EF and Igeo, N’djili River is considered as highly polluted with heavy metals indicating environmental and human health potential risks. The results of this study clearly indicate that the pollution of urban rivers in developing countries can be explained by several anthropogenic activities such as urban runoff, uncontrolled landfills in riverbanks, untreated wastewater from densely populated areas, anarchic commercial and industrial settlements, and heavy road traffic. The approaches used in this study represent a useful tool to assess the river sediment quality of urban river which can be applied to similar environment.

There has long been interest in making inferences about future low-probability natural events that have magnitudes greater than any in the past record. Given a stationary time series, the unbounded Type 1 and Type 2 asymptotic extreme value distributions are often invoked as giving theoretical justification for extrapolating to large magnitudes and long return periods for hydrological variables such as rainfall and river discharge. However, there is a problem in that environmental extremes are bounded above by the bounded nature of their causal variables. Extrapolation using unbounded asymptotic models therefore cannot be justified from extreme value theory and at some point there will be over-prediction of future magnitudes. This creates the apparent contradiction, for example, of annual rainfall maxima being well approximated by Type 2 extreme value distributions despite the bounded nature of rainfall magnitudes. An alternative asymptotic extreme value approach is suggested for further investigation, with the model being the asymptotic distribution of minima (Weibull distribution) applied to block maxima reciprocals. Two examples are presented where data that are well matched by Type 1 or Type 2 extreme value distributions give reciprocals suggestive of lower bounds (upper bound γ to the original data). The asymptotic model here is a 3-parameter Weibull distribution for the reciprocals, with positive location parameter γ⁻¹. When this situation is demonstrated from data, parameter estimation can be carried out with respect to the distribution of reciprocals of 3-parameter Weibull random variables. This distribution is referenced here as the bounded inverse Weibull distribution. A maximum likelihood parameter estimation methodology is presented, together with a parametric bootstrap approach for obtaining one-sided upper confidence limits to γ. When data permits estimation of γ, the bounded inverse Weibull distribution is suggested as an improved alternative to Type 1 or Type 2 extreme value distributions because the upper bound reality is recognised. However, extensive application to many data sets is required to evaluate the practical utility of the bounded approach for extrapolating beyond the largest recorded event.

Interactions between surface water (SW) and groundwater (GW) have been a focus of watershed hydrology research for a long time. A holistic perspective on integrated SW–GW modeling approach is necessary to understand the hydrological and biogeochemical processes of these two interconnected systems within the watershed. This paper reviewed the progress and coupling strategy of one important SW model (Soil and Water Assessment Tool, SWAT) and GW model (Modular Finite Difference Groundwater Flow, MODFLOW) since 1999. Three main stages of development of coupled SWAT–MODFLOW model are reflected by the high citation of publications by three pioneer studies, which are Sophocleous et al. (1999), Kim et al. (2008) and Bailey et al. (2016). Currently, the research scope of coupled SWAT–MODFLOW models is focused on hydrologic processes, solute transport and the effects of climate change and human activity on water resources. Major uncertainties of SWAT–MODFLOW from model structure, database and parameterization are discussed. In an era of big data, the coupled SWAT–MODFLOW model has great potential to improve understanding of hydro-biogeochemical processes and support sustainable water and ecological management in the watershed.

Sulfur (S) uptakes by woody plants might indicate the presence of urban air pollution in the form of sulfur dioxide (SO₂), which is one of the most important pollutants worldwide. The present study detected total carbon (C) and S contents in the leaf and stem (dry mass) of 53 common woody species in representative forest plots in five cities across the Pearl River Delta (PRD), a densely urbanized region in Southern China. Coupling analysis explored whether spatial patterns of S content in woody species were relatively consistent with atmospheric SO₂ concentration in the five PRD cities. Total S content varied in leaves and stems with averages of 2.0 g/kg and 0.8 g/kg, respectively, while air SO₂ concentration ranged from 9.0 to 108.0 g/m³. However, total C content was relatively constant among all the species across the diverse forest plots, with an average of 443.5 g/kg and a median of 448.0 g/kg in leaves and 437.0 g/kg in stems. This suggests that air SO₂ pollution did not influence tree growth, so afforestation may be an effective method of eliminating urban air pollution in the PRD.

The urban agriculture in developing countries plays a huge important socioeconomic role in confronting the challenge of eradicating hunger, improving food security and the social daily life of the population. However, the quality evaluation of water used for urban agriculture irrigation as well as the accumulation of pollutants such as heavy metals in fresh produces are still largely unstudied. The purpose of this study was to investigate the concentration of metals (Cr, Co, Ni, Cu, Zn, As, Cd, Pb and Hg) in irrigation water from rivers, soil and Amaranthus viridis (A. viridis), in order to evaluate the potential human dietary risks. The research was conducted in eight sites characterized by intensive agriculture performed in watersheds in Kinshasa, capital of Democratic Republic of the Congo. The results showed high metal concentrations in A. viridis leaf varying considerably among sampling sites (P < .05), reaching the values (in mg kg⁻¹ wet weight) of 2.97 (Cr), 1.73 (Co), 12.30 (Ni), 16.11 (Cu), 652.91 (Zn), 0.10 (As), 1.62 (Cd), 8.91 (Pb), and 0.1 (Hg). These values exceeded safe limits set by Food and Agriculture Organization/World Health Organization for human consumption (WHO/FAO). The assessment of human health risks using the targeted risk quotient and estimated dietary intake showed potential health hazards to consumers due to the levels of Cd and Pb in leafy vegetables from several studied sites. The vegetable contamination can be explained by chemicals used to combat and prevent A. viridis diseases, and the vehicle and motorcycle emissions around. Thus, given the concentrations of metals in A. viridis leaf, human health implications are likely to occur on heavy continuous consumption.