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A structural and morphometric analysis of small rivers of the middle reaches of the Nizhnyaya Tunguska River, draining the Ilimpeya-Nidym high trap plateau located within the Central Siberian Plateau, has been carried out using nine drainage basins as an example. To determine the morphometric characteristics of the streams, we use scenes from the FABDEM V1-2 global digital elevation model (DEM). The standard method of processing a DEM in ArcGIS Desktop 10.1 was applied as an algorithm for constructing hydrological networks, based on the morphometric analysis of river basins (Horton analysis, implemented in A. Strahler’s stream order system). Using the simplest structure of the basin organization of the Ganalchik River as an example, the article considers in detail the erosion network of streams of the third-order subbasins, which is characterized by significant variability of the main structural and morphometric indicators. For the study area, in general, a wide variation in the values of structural indices and morphometric characteristics is revealed. The deviations of the structural basin indices from modal values reflect the regional specifics of the geological and geomophrological structure of the territory and result from the layering of relief characteristic of the Ilimpeya-Nidym trap plateau, high tectonic fragmentation at elevations of 600–800 m, and the presence of traces of mountain–valley glaciation. In particular, it is found that the rivers under study have weak dissection of the river network in the middle and upper reaches, and the study area is dominated by basins with the uneven distribution of sediments along the main channel due to the middle and lower reaches, with the most stable proportion of the third-order channels. The most predominant among all third-order basins of the studied rivers are transit basins with a tendency to accumulate and accumulative basins, which account for 37 and 29%, respectively.

Over the last decades, treatment of domestic wastewater promoted by environmental regulations have reduced human health risks and improved water quality. However, ecological risks caused by effluents of wastewater treatment plants (WWTPs) discharged into rivers still persist. Moreover, the evolution of these ecological risks in the future is intimately related to effects of changing climate, especially regarding streamflow in receiving rivers. Here, we present an analytical and transferable framework for assessing the ecological risks posed by WWTP‐effluents at the catchment scale. The framework combines the size‐class k of WWTPs, which is a load‐proxy, with their outflows' location in river networks, represented by stream‐order ω. We identify ecological risks by using three proxy indicators: the urban discharge fraction and the local‐scale concentrations of each total phosphorous and ammonium‐nitrogen discharged from WWTPs. About 3,200 WWTPs over three large catchments (Rhine, Elbe, and Weser) in Central Europe were analyzed by incorporating simulated streamflow for the most extreme projected climate change scenario. We found that WWTPs causing ecological risks in the future prevail in lower ω, across almost all k. Distinct patterns of ecological risks are identified in the k‐ω framework for different indicators and catchments. We show, as climate changes, intensified risks are especially expected in lower ω receiving effluents of intermediate‐k WWTPs. We discuss the implications of our findings for prioritizing WWTPs upgrading and urging updates on environmental regulations. Further discussions underline the feasibility of applying the framework to any geographical regions and highlight its potentials to help in achieving global long‐term commitments on freshwater security. Key Points An analytical, generic framework was developed to assess wastewater treatment plants causing ecological risks in rivers under climate change Smaller streams will face higher ecological risks for almost all load classes of wastewater treatment plants in future climate Of the legally regulated effluent parameters for treated wastewater, ammonium‐nitrogen concentration will pose the greatest ecological risk

Hydrologic response of two fourth-order hilly watersheds of the Ramganga river basin in the central Himalayan region of India has been predicted in this study. Geomorphologic Instantaneous Unit Hydrograph (GIUH) was derived using two models: (i) Horton’s stream-order ratios based model (GIUH-I); and (ii) Nash’s two-parameter gamma distribution based conceptual model (GIUH-II). The travel times for the overland-flow and the stream-flow in Horton-Strahler stream ordering system of the watersheds were determined analytically and probabilistically for GIUH-I model; while a dynamic component (mean velocity of flow) was estimated for the GIUH-II model using two approaches: (a) as a function of effective rainfall intensity (GIUH-IIa); and (b) on the basis of time of concentration concept (GIUH-IIb). Based on eight single-peaked isolated storm events for each watershed, the statistical analysis and coefficient of efficiency showed better overall correlation between predicted and observed direct runoff hydrographs, particularly in terms of the magnitude and time of occurrence of peak runoff rate, by GIUH-IIb as compared to GIUH-I and -IIa models. Moreover, the GIUH-IIb has additional advantage (compared to GIUH-IIa) for being independent of the measured velocity of flow corresponding to the peak flow rate at the watershed outlet. Since, these models require no historical data of rainfall and runoff, they can be effectively used to predict direct runoff from ungauged hilly watersheds for water resources planning and management in the region.

Inland waters are large sources of methane to the atmosphere. However, considerable uncertainty exists in estimating the emissions of this potent greenhouse gas from global streams and rivers due, in part, to a lack of direct measurements in the high-altitude cryosphere and poor accounting for ebullition. Here we present methane concentrations and fluxes over three years in four basins on the East Qinghai–Tibet Plateau. Methane ebullition rates decrease exponentially whereas diffusion declines linearly with increasing stream order. Nonetheless, the average ebullition rate (11.9 mmolCH4 m−2 d−1) from these streams and rivers—which have large organic stocks in surrounding permafrost, abundant cold-tolerant methanogens, shallow water depths, and experience low air pressure—were six times greater than the global average and reached a maximum of 374.4 mmolCH4 m−2 d−1. Upscaled total emissions from sampled third- to seventh-order waterways of the East Qinghai–Tibet Plateau are estimated to be 0.20 TgCH4 yr−1, 79% of which was attributed to ebullition. These methane emissions are approximately 20% of CO2 emissions (2.70 TgCO2 yr−1) in terms of carbon release and two times greater in terms of CO2-equivalent emissions. When upscaled to first- to seventh-order waterways, we estimate emissions of 0.37–1.23 TgCH4 yr−1. Our findings demonstrate that high-elevation rivers on the Qinghai–Tibet Plateau are hotspots of methane delivery to the atmosphere. The large ebullitive fluxes, which constitute a substantial fraction of global fluvial methane emissions, reveal a positive feedback between climate warming, permafrost thaw and methane emissions.High-elevation rivers in permafrost of the East Qinghai–Tibet Plateau are hotspots of methane emissions, according to measurements of methane fluxes in the region.

The geographic distribution of streams and rivers drives a multitude of patterns and processes in hydrology, geomorphology, geography, and ecology. Therefore, a hydrographic network that accurately delineates both small streams and large rivers, along with their topographic and topological properties, with equal precision would be indispensable in the earth sciences. Currently, available global hydrographies do not feature small headwater streams in great detail. However, these headwaters are vital because they are estimated to contribute to more than 70 % of overall stream length. We aimed to fill this gap by using the MERIT Hydro digital elevation model at 3 arcsec (∼90 m at the Equator) to derive a globally seamless, standardised hydrographic network, the “Hydrography90m”, with corresponding stream topographic and topological information. A central feature of the network is the minimal upstream contributing area, i.e. flow accumulation, of 0.05 km2 (or 5 ha) to initiate a stream channel, which allowed us to extract headwater stream channels in great detail. By employing a suite of GRASS GIS hydrological modules, we calculated the range-wide upstream flow accumulation and flow direction to delineate a total of 1.6 million drainage basins and extracted globally a total of 726 million unique stream segments with their corresponding sub-catchments. In addition, we computed stream topographic variables comprising stream slope, gradient, length, and curvature attributes as well as stream topological variables to allow for network routing and various stream order classifications. We validated the spatial accuracy and flow accumulation of Hydrography90m against NHDPlus HR, an independent, national high-resolution hydrographic network dataset of the United States. Our validation shows that the newly developed Hydrography90m has the highest spatial precision and contains more headwater stream channels compared to three other global hydrographic datasets. This comprehensive approach provides a vital and long-overdue baseline for assessing actual streamflow in headwaters and opens new research avenues for high-resolution studies of surface water worldwide. Hydrography90m thus offers significant potential to facilitate the assessment of freshwater quantity and quality, inundation risk, biodiversity, conservation, and resource management objectives in a globally comprehensive and standardised manner. The Hydrography90m layers are available at https://doi.org/10.18728/igb-fred-762.1 (Amatulli et al., 2022a), and while they can be used directly in standard GIS applications, we recommend the seamless integration with hydrological modules in open-source QGIS and GRASS GIS software to further customise the data and derive optimal utility from it.

N₂O is an important greenhouse gas and the primary stratospheric ozone depleting substance. Its deleterious effects on the environment have prompted appeals to regulate emissions from agriculture, which represents the primary anthropogenic source in the global N₂O budget. Successful implementation of mitigation strategies requires robust bottom-up inventories that are based on emission factors (EFs), simulation models, or a combination of the two. Top-down emission estimates, based on tall-tower and aircraft observations, indicate that bottom-up inventories severely underestimate regional and continental scale N₂O emissions, implying that EFs may be biased low. Here, we measured N₂O emissions from streams within the US Corn Belt using a chamber-based approach and analyzed the data as a function of Strahler stream order (S). N₂O fluxes from headwater streams often exceeded 29 nmol N₂O-N m⁻²·s⁻¹ and decreased exponentially as a function of S. This relation was used to scale up riverine emissions and to assess the differences between bottom-up and top-down emission inventories at the local to regional scale. We found that the Intergovernmental Panel on Climate Change (IPCC) indirect EF for rivers (EF5r) is underestimated up to ninefold in southern Minnesota, which translates to a total tier 1 agricultural underestimation of N₂O emissions by 40%. We show that accounting for zero-order streams as potential N₂O hotspots can more than double the agricultural budget. Applying the same analysis to the US Corn Belt demonstrates that the IPCC EF5runderestimation explains the large differences observed between top-down and bottom-up emission estimates.

Understanding the spatial variation of streambed sediment median grain size (d50) is essential for understanding hydrological, geomorphological, and ecological processes, yet network‐scale patterns remain poorly characterized. Here we combined extensive field sampling (249 locations) with Digital Grain Size analysis and laboratory sieving to build a high‐precision d50 database across the 3056 km Xin'anjiang (XAJ) stream network in southeastern China. Using a Spatial Stream Network (SSN) geostatistical model, we produced 1 km resolution predictions of d50 (R2 = 0.92) that explicitly incorporate hydrologic connectivity and spatial autocorrelation. Results reveal high spatial heterogeneity (0.22–100.28 mm), with systematic downstream fining punctuated by stepwise anomalies at tributary confluences. d50 decreases with stream order but increases with flow distance to the outlet, indicating the combined roles of geomorphic scaling and sediment supply contrasts. Sensitivity analysis shows that prediction uncertainty grows as sampling density decreases; a ∼15 km interval provides reliable estimates, while denser sampling is needed near confluences and morphologically complex reaches. This study establishes a transferable framework for network‐scale sediment analysis, advancing understanding of spatial grain‐size dynamics and guiding efficient sampling strategies in diverse stream networks.

This paper presents a mathematical model developed using Horton–Strahler’s stream order to describe basin-wide distributions of human activities, i.e., land use and human population, across several river basins with different geomorphologic features. We assume that for successive stream orders, the mean area of each land use type—paddy field, forest, city, village, etc.—and the human population form a geometric sequence, which is the same mathematical relationship as stated in Horton’s laws of river geomorphology. This geometric sequence modeling implies fractal nature of human activity distributions within a river basin. GIS datasets for the land use and human population in 109 large river basins in Japan were used to verify the model. Herein, we examine the relationships between the Horton ratios and the common ratios obtained from the model to explore links between basin geomorphology and human activities. Furthermore, we quantitatively compare the human activity distributions across the 109 river basins on the basis of results obtained from the model with descriptive statistics. Further, we attempt to classify the river basins into several categories through multivariate statistical analysis.

While the role of citizen science in engaging the public and providing large-scale datasets has been demonstrated, the nature of and potential for this science to supplement environmental monitoring efforts by government agencies has not yet been fully explored. To this end, the present study investigates the complementarity of a citizen science programme to agency monitoring of water quality. The Environment Agency (EA) is the governmental public body responsible for, among other duties, managing and monitoring water quality and water resources in England. FreshWater Watch (FWW) is a global citizen science project that supports community monitoring of freshwater quality. FWW and EA data were assessed for their spatio-temporal complementarity by comparing the geographical and seasonal coverage of nitrate (N-NO3) sampling across the River Thames catchment by the respective campaigns between spring 2013 and winter 2015. The analysis reveals that FWW citizen science-collected data complements EA data by filling in both gaps in the spatial and temporal coverage as well as gaps in waterbody type and size. In addition, partial spatio-temporal overlap in sampling efforts by the two actors is discovered, but EA sampling is found to be more consistent than FWW sampling. Statistical analyses indicate that regardless of broader geographical overlap in sampling effort, FWW sampling sites are associated with a lower stream order and water bodies of smaller surface areas than EA sampling sites. FWW also samples more still-water body sites than the EA. As a possible result of such differences in sampling tendencies, nitrate concentrations, a measure of water quality, are lower for FWW sites than EA sites. These findings strongly indicate that citizen science has clear potential to complement agency monitoring efforts by generating information on freshwater ecosystems that would otherwise be under reported.

ABSTRACT Aim Freshwater mussels are considered among the most at‐risk taxa in the world. As such, comprehensive monitoring assessments of what abiotic and biotic factors influence mussel occupancy will be vital for guiding effective conservation. Here, we analysed vertebrate and mussel environmental DNA (eDNA) metabarcoding data to explore the influence of biotic (i.e., host fish diversity, predator presence, and community composition) and abiotic (i.e., drainage size, forest cover, and stream order) factors on freshwater mussel populations. Location This study utilised water samples and tactile survey data collected from streams throughout Fort Johnson, Louisiana. Methods We first evaluated the effectiveness of eDNA metabarcoding for characterising freshwater communities based on previous conventional tactile surveys. Next, we used eDNA metabarcoding analysis for freshwater mussels and vertebrate species alongside GIS‐derived satellite remote sensing data to assess how various biotic and abiotic variables impact freshwater mussel eDNA occupancy. Results Our eDNA metabarcoding survey largely agreed with both historical and contemporary surveys on Fort Johnson, while uniquely detecting Louisiana pigtoe (Pleurobema riddellii), a proposed threatened species under the US Endangered Species Act. We also found that eDNA detections and occupancy had strong seasonal variation, with increased read abundance and diversity in the spring. Vertebrate, fish, and predator diversity (as a function of habitat quality) were strongly predictive of mussel occupancy, supporting the concept of land managers focusing on the entire ecosystem for mussel conservation. Lastly, we found that percent forest cover and drainage basin size influenced mussel eDNA occupancy, informing habitat associations for mussel species of interest (i.e., the mussels occupied larger drainage sizes and perennial streams). Conclusions Our results demonstrate that combining eDNA metabarcoding of target and non‐target species with occupancy modelling can provide insights into the ecology of freshwater mussels and is a useful tool to improve their conservation and management.