Effects of Land Cover Changes on Sediment and Nutrient Balance in the Catchment with Cascade-Dammed Waters

Examining chlorophyll-a concentrations in tropical reservoirs under various land use changes using Sentinel - 2 and Google Earth engine - Bhadra and Tungabhadra, India

The understanding of spatio-temporal variation in land use and land cover (LULC) patterns is crucial for managing catchment land use planning, as it directly influences of tropical reservoir water quality and the subsequent Nutrient Contamination (NC) of unmonitored water bodies. The current research attempts to accurately measure the influence of LULC and its associated determinants on the quantities of NC loads by using Chl-a as a proxy, within tropical reservoirs, i.e. Bhadra and Tungabhadra, located in same river catchment. This Chl-a spread calculated by the Maximum Chlorophyll Index (MCI) derived from Sentinel 2 satellite data products covering the period from July 2016 to June 2021 were done using Google Earth Engine (GEE) platform. The validation analysis confirms the robustness of the methodology with a strong correlation between MCI-calculated values and EOMAP (Earth Observation and Environmental Services Mapping) Chl-a (μg/L) data points for both reservoirs, Bhadra (R2 = 0.64) and Tungabhadra (R2 = 0.68). The findings reveal that, Tungabhadra reservoir consistently exhibits an excessive spatial distribution of Chl-a spread area (17 km2 to 335 km2), reflecting nutrient-rich water inflows, particularly evident during the post-monsoon period. This notable rise could be linked to harvesting the Kharif crop, resulting in elevated nutrient concentrations. In contrast Bhadra reservoir, dominated by forested areas, maintains relatively lower Chl-a spread areas (<20 km2), highlighting its pivotal role in maintaining water cleanliness and serves as a riparian boundary. In addition, the changes in LULC classes show a strong relationship with variation in Chl-a during the studied period, for the Bhadra Reservoir R2 = 0.51 (F- statistics = 3.983, p = 0.021), and the Tungabhadra Reservoir R2 = 0.802 (F- statistics = 7.489, p = 0.0143). This highlights how changes in land use significantly shape contamination dynamics, deepening our understanding of nutrient inputs and contamination drivers in tropical reservoirs.

Sustainable Development versus Extractivist Deforestation in Tropical, Subtropical, and Boreal Forest Ecosystems: Repercussions and Controversies about the Mother Tree and the Mycorrhizal Network Hypothesis

This research reviews the phenomenon of extractive deforestation as a possible trigger for cascade reactions that could affect part of the forest ecosystem and its biodiversity (surface, aerial, and underground) in tropical, subtropical, and boreal forests. The controversy and disparities in criteria generated in the international scientific community around the hypothesis of a possible link between "mother trees" and mycorrhizal networks in coopetition for nutrients, nitrogen, and carbon are analyzed. The objective is to promote awareness to generate more scientific knowledge about the eventual impacts of forest extraction. Public policies are emphasized as crucial mediators for balanced sustainable development. Currently, the effects of extractive deforestation on forest ecosystems are poorly understood, which requires caution and forest protection. Continued research to increase our knowledge in molecular biology is advocated to understand the adaptation of biological organisms to the new conditions of the ecosystem both in the face of extractive deforestation and reforestation. The environmental impacts of extractive deforestation, such as the loss of biodiversity, soil degradation, altered water cycles, and the contribution of climate change, remain largely unknown. Long-term and high-quality research is essential to ensure forest sustainability and the preservation of biodiversity for future generations.

Effects of rainfall and land use on nutrient responses in rivers in the Brazilian semiarid region

This paper investigated whether rainfall promotes dilution or increase in nutrient concentrations and which land use indicators are the main predictors of nutrients in intermittent rivers in a large Brazilian semiarid region. The total phosphorus (TP) and total inorganic nitrogen (TIN) were monitored between 2013 and 2018 at 92 river water quality monitoring sites. The monthly rainfall (Rn) was obtained from 575 rain gauges. Pearson's correlation (R) between Rn and nutrient concentration was performed. The correlation patterns were also analysed based on land use data: urban area (%), agricultural field area (%), demographic density (inhabitants/km2), sewer system coverage (%), and reservoir density (reservoir/km2). Backward stepwise regression was performed to identify predictors of nutrient concentrations. The results revealed a marginal effect of rainfall on nutrients when the effects of urbanisation outweigh all other aspects. However, in regions with greater accumulated rainfall and lower reservoir density, the rainfall was related to a linear increase in nutrient concentrations (R > 0.8). Contrastingly, in the basins with less accumulated rainfall and greater inter-basin hydrological disconnection, there was a linear reduction in nutrient concentration (R < - 0.5). In the backward stepwise regression, sewer system coverage and Rn had the greatest influence for TP, and the urban area was the strongest predictor for TIN. Importantly, our results demonstrated that in semiarid rivers in densely populated regions, there is no single pattern of variability in nutrient concentration, on a wide scale of assessment. Therefore, adaptative and decentralised management can be more effective in improving water quality in these regions.

Zinc transport and partitioning of a mine-impacted watershed: An evaluation of water and sediment quality

Watershed systems influenced by mining waste products can persist for many years after operations are ceased, leading to negative impacts on the health of the surrounding environment. While geochemical behaviors of these trace metals have been studied extensively at the benchtop-scale, much fewer studies have looked at controls on their distributions at the watershed-level. In this study, trace metals (As, Cd, Cr, Cu, Ni, and Zn) were reported from water and stream bed sediments at eight sites between the years 2014-2018 along a watershed undergoing active remediation efforts. Zn was determined to be the only trace metal analyzed with concentrations above EPA and Kansas Department of Health guidelines for both water and sediment in the watershed, and thus was the primary focus for determining the health of the watershed system. Controls on trace metal pollution distribution over the watershed were investigated to determine where remediation efforts should be focused. Surface cover seemed to have the highest effectivity with pasture lands having a strong positive correlation to Zn concentrations. Initial remediation efforts were assessed by calculating the geoaccumulation index (I_geo) and the contamination factor (C_f-sediment) from sediments and contamination factor from water (C_f-water) after decades of chat pile removal efforts. Most of the sites showed significant reduction in metal concentration values compared to previous studies in the watershed for water and sediment, with four sites still reporting concentrations that reveal potential health risks. Results from this study will inform management and policy makers for areas to focus their remediation efforts on the Spring River Watershed as well as providing a framework for assessing pollution at a watershed scale.

Hydromorphological Inventory and Evaluation of the Upland Stream: Case Study of a Small Ungauged Catchment in Western Carpathians, Poland

The hydromorphological conditions of watercourses depend on numerous natural and anthropogenic factors such as buffer zones or human infrastructure near their banks. We hypothesised that, even in a small stream, there can be substantial differences in the hydromorphological forms associated with naturalness and human impact. The paper aims at the field inventory and evaluation of the hydromorphological conditions of a small upland stream in the conditions of contemporary human activity, against the background of meteorological and hydrological conditions. The study concerned a left-bank tributary of the Stradomka River located in the Wiśnicz Foothills (Western Carpathians). The analyses were conducted with the use of the Polish method, the Hydromorphological Index for Rivers (HIR), which conforms to the EU Water Framework Directive (WFD). The hydromorphological condition and quality of habitats were evaluated based on the Hydromorphological Diversity Score (HDS) and Habitat Modification Score (HMS). The study shows that the largest changes in stream hydomorphology and habitat conditions took place in the downstream, urbanised stream catchment area with an intensive development of construction and technical infrastructure. The hydromorphological condition of the examined stream sections was evaluated as good or poor. The best hydromorphological conditions were found in the section located in the semi-natural area, and the worst in the urbanised area. As our research shows, the strong influence of human activity, including weather extremes, and the risks and hydrological hazards of the hydromorphological conditions of the small, ungauged catchment, highlight the necessity to search for other research methods to support the decision-making cycle in the transformation of riverbeds and catchments.

Prediction of Erosion-Prone Areas in the Catchments of Big Lowland Rivers: Implementation of Maximum Entropy Modelling—Using the Example of the Lower Vistula River (Poland)

It is common knowledge that erosion depends on environmental factors modified by human activity. Erosion within a catchment area can be defined by local lithological, morphometric, hydrological features, etc., and land cover, with spatial distribution described by means of remote sensing tools. The study relied on spatial data for the catchment of the Lower Vistula—the biggest river in Poland. GIS (SAGA, QGIS) tools were used to designate the spatial distribution of independent environmental variables that determined the process of erosion according to land cover types within the Lower Vistula catchment (Corine Land Cover). In addition, soil loss in the catchment area was calculated using the USLE model (Universal Soil Loss Equation). The spatial data was used to determine the predictive power of variables for the process of erosion by applying the maximum entropy model (MaxEnt) commonly used in fields of science unrelated to fluvial hydrology. The results of the study pointed directly to environmental features strongly connected with the process of erosion, identifying areas susceptible to intensified erosion, and in addition positively verified by USLE. This testifies to the correct selection of the proposed method, which is a strong point of the presented study. The proposed interdisciplinary approach to predict erosion within the catchment area (MaxEnt), widely supported by GIS tools, will allow the identification of environmental pressures to support the decision-making process in erosion-prone areas.

Assessment of the impact of land use in an agricultural catchment area on water quality of lowland rivers

In several countries around the world, agricultural land area exceeds 70% (Uruguay 82.6%, Kazakhstan 80.4%, Turkmenistan 72.0%, Great Britain 71.7%, Ukraine 71.6% and others). This poses a serious risk of dissipating nitrates into the aquatic environment in agricultural catchments. The aim of this study was to assess the impact of land use on water quality parameters in an agricultural catchment area. It was decided to select for analysis the catchment of the Orla River (river length of 88 km, catchment area of 1,546 km²). The catchment area is predominantly agricultural in character and its entire area has been declared as an agricultural nitrate vulnerable zone (NVZ). A total of 27 survey sites were selected on the main watercourse and its tributaries. Analyses were conducted in the years 2010-2012 to determine physical and chemical parameters of water (pH reaction, conductivity, dissolved oxygen, total nitrogen, organic nitrogen, ammonia nitrogen, nitrates, total and reactive phosphorus) as well as six macrophyte metrics of ecological status assessment (MIR, IBMR, RMNI, MTR, TIM, RI). The average values of most physico-chemical parameters of water quality repeatedly exceeded limits of good ecological status, both in the Orla River and its tributaries. As many as 18 survey sites were classified as moderate ecological status, five sites as poor and only four as good ecological status. The results indicate the impact of land use in the catchment on water conductivity. Differences were observed in the concentrations of biotic components in the main watercourse and its tributaries, and in water quality in the southern part of the catchment in relation to the rest of the study area. This is probably connected with a greater share of forests and surface waters in that area.

Analysis of Spatial and Temporal Characteristics and Spatial Flow Process of Soil Conservation Service in Jinghe Basin of China

The supply and demand of ecosystem services and their mutual feedback are important for the formulation of basin ecological environmental policies. Simulation of the spatial flow of ecosystem services can clarify the division of areas and can support policy development. This paper takes the Jinghe Basin in the Loess Plateau of China as the case-study area to simulate the spatial flow of soil conservation service on different scales. The results showed that (1) soil erosion situations in Jinghe Basin improved overall, with a trend of first aggravating and then recovering between 2005 and 2015; (2) the amount of annual soil conservation in the basin accounted for more than 75% of the potential soil erosion and showed a trend of first increasing and then decreasing; and (3) using digital elevation model (DEM) data and ArcGIS software, the experiment divided the basin into sub-basins (58 in total) and hydrological response units (HRUs) (e.g., 2181 HRUs in sub-basin #1), which were used to quantify the spatial flow direction and the corresponding amount of soil conservation service on the “HRU—river-sub-basin” scale. The divided supply and demand helped quantify the spatial flow pattern of soil conservation services from HRU to the sub-basin.

Application of High-Resolution Radar Rain Data to the Predictive Analysis of Landslide Susceptibility under Climate Change in the Laonong Watershed, Taiwan

Extreme rainfall has caused severe road damage and landslide disasters in mountainous areas. Rainfall forecasting derived from remote sensing data has been widely adopted for disaster prevention and early warning as a trend in recent years. By integrating high-resolution radar rain data, for example, the QPESUMS (quantitative precipitation estimation and segregation using multiple sensors) system provides a great opportunity to establish the extreme climate-based landslide susceptibility model, which would be helpful in the prevention of hillslope disasters under climate change. QPESUMS was adopted to obtain spatio-temporal rainfall patterns, and further, multi-temporal landslide inventories (2003–2018) would integrate with other explanatory factors and therefore, we can establish the logistic regression method for prediction of landslide susceptibility sites in the Laonong River watershed, which was devastated by Typhoon Morakot in 2009. Simulations of landslide susceptibility under the critical rainfall (300, 600, and 900 mm) were designed to verify the model’s sensitivity. Due to the orographic effect, rainfall was concentrated at the low mountainous and middle elevation areas in the southern Laonong River watershed. Landslide change analysis indicates that the landslide ratio increased from 1.5% to 7.0% after Typhoon Morakot in 2009. Subsequently, the landslide ratio fluctuated between 3.5% and 4.5% after 2012, which indicates that the recovery of landslide areas is still in progress. The validation results showed that the calibrated model of 2005 is preferred in the general period, with an accuracy of 78%. For extreme rainfall typhoons, the calibrated model of 2009 would perform better (72%). This study presented that the integration of multi-temporal landslide inventories in a logistic regression model is capable of predicting rainfall-triggered landslide risk under climate change.