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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

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.

Providing historical data on riparian plant biodiversity and physico-chemical parameters of stream water in Mediterranean mountains helps to assess the effects of climate change and other human stressors on these sensitive and critical ecosystems. This database collects data from the main natural headwater streams of the Sierra Nevada (southeastern Spain), a high mountain (up to 3479 m above sea level [m asl]) recognized as a biodiversity super hotspot in the Mediterranean basin. On this mountain, rivers and landscapes depend on snowmelt water, representing an excellent scenario for evaluating global change’s impacts. This dataset covers firstto third-order headwater streams at 41 sites from 832 to 1997 m asl, collected from December 2006 to July 2007. Our goal is to supply information on the vegetation associated with streambanks, the essential physico-chemical parameters of stream water, and the physiographic features of the subwatersheds. Riparian vegetation data correspond to six plots sampled at each site, including total canopy, individual number, height and DBH (diameter at breast height) in woody species, and cover percentage for herbs. Physico-chemical parameters were measured in situ (electric conductivity, pH, dissolved O₂ concentration, stream discharge) and determined in the laboratory (alkalinity, soluble reactive phosphate-phosphorus [SRP], total phosphorus [TP], nitrate-nitrogen [NO⁻ ₃ –N], ammonium-nitrogen [NH⁺ ₄ –N], total nitrogen [TN]). Watershed physiographic variables comprise drainage area, minimum altitude, maximum altitude, mean slope, orientation, stream order, stream length, and land cover surface percentage. We recorded 197 plant taxa (67 species, 28 subspecies, and 2 hybrids), representing 8.4% of the Sierra Nevada vascular flora. Due to the botanical nomenclature used, the database can be linked to FloraSNevada database, contributing to Sierra Nevada (Spain) as a laboratory of global processes. This data set can be freely used for non-commercial purposes. Users of these data should cite this data paper in any publications resulting from its use.

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.

The morphometric attributes of a drainage basin reveal the hydrological and morphological dynamics of the area. Current work emphasizes the hydro-geomorphic characterization of the Kunhar river basin using remote sensing and GIS tools. Basin dynamics are demarcated by hypsometry and the allied areal, linear, and relief parameters. Current work involves the evaluation of Shuttle Radar Topography Mission (SRTM) 1 Arc-Second DEM of 30 m for virtual extraction of hydrological parameters of Kunhar basin. Seven sub-basins (Barasi, Bas Katna, Gitidas, Kalah- da- Katha, Kunhar, Manur, and Nill) are demarcated using hydrological inference from the drainage patterns extracted. Studies revealed that the basin comprises of area about 2434 km2 and its perimeter stretches up to 456 km. Linear morphometric parameters, e.g., stream network, stream order, mean stream length, mean bifurcation ratio, stream length ratio, length of overland flow, basin perimeter, and basin length are calculated by DEM processing. The areal morphometric parameters, e.g., basin area, drainage density, Infiltration number, form factor ratio, drainage frequency, circularity ratio, and elongation ratio are assessed algorithm and Arc GIS. The significant relief parameters determined are basin relief, relief ratio, basin slope, relative relief, hypsometric integral, ruggedness number, lowest elevation, and highest elevation. The ruggedness and basin slope of the study area suggest a moderate flood potential, which is moderate to high in the northeastern sub-basins as for basin maturity is concerned, the basin is young to mature in nature. Sub-basin analysis reflects Nill Sub-basin is younger than the rest of all. The modeled Kunhar river sub-basin portrays a deep coherence to the morphometric and hydrological models that suggest it as a medium flood potential basin. Kunhar watershed can be prioritized for water resource management by considering the inferences from the geo-morphometric outcome and the channel flow parameters assessed by the hydrological model.