Hydrological Distance Research Articles

The Critical Role of Hydrological Distance in Shaping Nutrient Dynamics Along the Watershed‐Lake Continuum

AbstractTerrestrial hydrological and nutrient cycles are subjected to major disturbances by agricultural operations and urbanization that profoundly influence freshwater resources. Non‐point source pollution is one of the primary causes for water quality deterioration, and thus an emerging imperative in limnology is establishing empirical models that connect watershed attributes and hydrological drivers with lake nutrient dynamics. Here, we compiled three nation‐wide nutrient, meteorological, and watershed‐landscape data sets, to develop Generalized Linear Models that predict lake phosphorus and nitrogen concentrations as a function of the surrounding watershed characteristics within various hydrological distances across 104 Chinese lakes and reservoirs. Our national‐scale investigation revealed that lake nutrient concentrations can be satisfactorily predicted by proxies of natural drivers and anthropogenic activities, reflecting the properties of the surrounding watershed. Counter to previous studies, we found that China's lake nutrient concentrations strongly depend on watershed characteristics within a hydrological distance of less than 45 km rather than the entire watershed. Furthermore, extensive human activities in watersheds not only compromise our predictive capacity, but also increase the hydrological distance that is relevant to predict lake nutrients. This national‐scale characterization can inform one of the most contentious issues in the context of China's lake management, that is, the determination of the extent of the nearshore area, where nutrient control should be prioritized. As far as we know, our study represents the first attempt to apply the concept of hydrological distance and establish statistical models that can delineate the critical spatial domain primarily responsible for the nutrient conditions along the watershed‐lake continuum.

Marginal Distribution Fitting Method for Modelling Flood Extremes on a River Network

This study utilized a max-stable process (MSP) model with a dependence structure defined via a non-Euclidean distance metric, with the goal of modelling extreme flood data on a river network. The dataset was composed of mean daily discharge observations from 22 United States Geological Survey streamflow gaging stations for river basins in Missouri and Arkansas. The analysis included the application of the elastic-net penalty to automatically build spatially varying trend surfaces to model the marginal distributions. The dependence model accounted for the river distance between hydrologically connected gaging sites and the hydrologic distance, defined as the Euclidean distance between the centers of site’s associated drainage areas, for all stations. Modelling the marginal distributions and spatial dependence among the extremes are two key components for spatially modelling extremes. Among the 16 covariates evaluated for marginal fitting, 7 were selected to spatially model the generalized extreme value (GEV) location parameter (for each gaging station’s contributing drainage basin, its outlet elevation, centroid x coordinate, centroid elevation, area, average basin width, elevation range, and median land surface slope). The three covariates selected for the GEV scale parameter included the area, average basin width, and median land surface slope. The GEV shape parameter was assumed to be constant throughout the entire study area. Comparisons of estimates obtained from the spatial covariate model with their corresponding “at-site” estimates resulted in computed values of 0.95, 0.95, 0.94 and 0.85, 0.84, 0.90 for the coefficient of determination, Nash–Sutcliffe efficiency, and Kling–Gupta efficiency for the GEV location and scale parameters, respectively. Brown–Resnick MSP models were fit to independent multivariate events extracted from a set of common discharge data, transformed to unit Fréchet margins while considering different permutations of the non-Euclidean dependence model. Each of the fitted model’s log-likelihood values indicated improved fits when using hydrologic distance rather than Euclidean distance. They also demonstrated that accounting for flow-connected dependence and anisotropy further improved model fit. In this study, the results from both parts were illustrative; however, further research with larger datasets and more heterogeneous systems is recommended.

Landslide Dynamic Susceptibility Mapping Base on Machine Learning and the PS-InSAR Coupling Model

Complex and fragile geological conditions combined with periodic fluctuations in reservoir water levels have led to frequent landslide disasters in the Three Gorges Reservoir area. With the development of remote sensing technology, many scholars have applied it to landslide susceptibility assessment to improve model accuracy; however, how to couple these two to obtain the optimal susceptibility assessment model remains to be studied. Based on Sentinel-1 data, relevant data, and existing research results, the information value method (IV), random forest (RF), support vector machine (SVM), and convolutional neural network (CNN) models were selected to analyze landslide susceptibility in the urban area of Wanzhou. Models with superior performance will be coupled with PS-InSAR deformation data using two methods: joint training and weighted overlay. The accuracy of different models was assessed and compared with the aim of determining the optimal coupling model and the role of InSAR in the model. The results indicate that the accuracy of different landslide susceptibility prediction models is ranked as RF > SVM > CNN > IV. Among the coupled dynamic models, the performance ranking was as follows: InSAR jointly trained RF (IJRF) > InSAR weighted overlay RF (IWRF) > InSAR jointly trained SVM (IJSVM) > InSAR weighted overlay SVM (IWSVM). Notably, the IJRF model, which combines InSAR deformation data through joint training, exhibited the highest accuracy, with an AUC value of 0.995. In the factor importance analysis within the IJRF model, InSAR deformation data ranked third after hydrological distance (0.210) and elevation (0.163), with a value of 0.154. A comparison between landslide dynamic susceptibility mapping (LDSM) and landslide susceptibility mapping (LSM) revealed that the inclusion of InSAR deformation data effectively reduced false positives around the landslide areas. The results suggest that joint training is the most suitable coupling method, allowing for the optimal expression of InSAR deformation data and enhancing the predictive accuracy of the model. This study serves as a reference for future research and provides a foundation for landslide risk management.

Assessing performance of spatial statistical stream network models in predicting alkalinity: A comparative study of two river basins in Türkiye

Developing and implementing water quality models that utilize sophisticated processes and plenty data in large river basins can be a challenging task. Factors such as sampling design, prediction at unsampled sites, and derivation of new spatial information in monitoring studies can restrict the methodologies applicable to water quality modeling. In recent years, spatial stream network (SSN) models, incorporating hydrologic distance and topological data structures, have emerged as a novel approach for predicting water quality in extensive study areas. These models have integrated conventional geostatistical methodologies and have demonstrated their effectiveness in analyzing water quality within large river basins. In this study, we aimed to investigate the feasibility of using SSN to predict alkalinity through a comparative analysis of two distinct river basins in Türkiye. We evaluated the prediction performance of SSN and the spatial characterization of the basins using spatial data sets as model components. The models are based on moving-average (MA) functions and constructed by evaluating alkalinity observations at 90 locations in Kucuk Menderes River Basin and 224 locations in the Coruh River Basin, using torgegram, correlogram, principal component analysis, and exhaustive search algorithm for covariate selection. In this research, we evaluated the optimal combination of covariates obtained from 20 different variables within the context of five spatial data set classes: topography, geology, climate, land use, and anthropology. The outcomes of the model indicate that impact of anthropogenic activities on autocorrelation based on hydrologic distance, impact of spatial covariates on variance, and root mean square prediction error (RMSPE) values of the predictions in Kucuk Menderes are more effective than those in the Coruh. The findings from the model predictions show that modeling water quality on stream network scale by using topological relationships and autocorrelation based on hydrologic distance can be recommended for rivers affected by complex and detailed processes.

The relative importance of environmental heterogeneity and dispersal limitation on spatial patterns of phytoplankton communities varies across seasons

AbstractEnvironmental heterogeneity and dispersal limitation structure community assembly, but there is limited knowledge on how their effects vary on temporal scale. This study compiled a series of data, including phytoplankton, seawater depth and chemistry from 104 sites, to explore the spatial patterns and their drivers of phytoplankton communities in the Beibu Gulf and adjacent waters, located in the northwestern South China Sea. Our results showed that (1) the beta diversity values ranged from 0.2 to 0.84 (0.5 average), and turnover dominated. (2) The relative contributions of environmental heterogeneity and dispersal limitation to beta diversity varied seasonally, wherein former dominated in summer and winter, latter dominated in spring and autumn. (3) Hydrologic distance, pH, alkalinity, and total nitrogen were the crucial factors shaping the beta diversity pattern. This study detailed the temporal variation of the relative roles of environmental heterogeneity and dispersal limitation in shaping the patterns of phytoplankton communities, which may reflect the dynamical nature of ocean, characterized by seasonal variation in wind and hydrology. It also clarified the intrinsic linkage between these two processes in the ocean, which provides a novel insight to understanding the ocean biogeography and informs decision making for area‐based marine biodiversity conservation.

Spatio-Temporal Model of a Product–Sum Simulation on Stream Network Based on Hydrologic Distance

The modeling of spatio-temporal processes is crucial in many fields such as environmental science, hydrology, and water storage engineering. A basic concept of the spatio-temporal model is an auto-covariance function. The stream network model based on the Euclidean distance as the auto-covariance function for investigating river pollution will potentially face a serious accuracy problem, due to the material or water pollutant movement on the water only occurring within the river network and the distance travelled not following the path of the river network. The use of the hydrologic distance may overcome the problem because, statistically, the Euclidean distance-based auto-covariance function is not valid if it is a negative-definite. Therefore, this study develops a spatio-temporal model of the generalized product–sum based on the hydrologic distance with a positive-definite property. The proposed model is built and, subsequently, it is then verified mathematically to be positive-definite. Furthermore, the relationships between the hydrologic distance, the Euclidean distance, and spatial configurations are also investigated. The simulation study result shows the proposed spatio-temporal model is positive-definite for some semivariogram models. The relationships between spatial configurations in the stream network follow an exponential model.

Landscape spatial configuration influences phosphorus but not nitrate concentrations in agricultural headwater catchments

AbstractLandscape organized (or structured) heterogeneity influences hydrological and biogeochemical patterns across space and time. We developed landscape indices that describe the spatial configuration of nutrient sources and sinks as a function of their hydrological distance to the stream (lateral dimension) or to the outlet (longitudinal dimension) and their intersection with flow‐accumulation areas. Using monthly nitrate, total phosphorus (TP), soluble reactive phosphorus (SRP) and daily discharge (Q) data from 221 rural catchments (1–300 km2) from 2010–2020, we observed higher variability in flow‐weighted mean concentrations in smaller catchments than in larger ones. The variability in landscape configurations also decreased with increasing catchment size. A landscape configuration index, calculated as mean arable land use weighted by spatial data on hydrological distance and flow accumulation, improved prediction of TP and SRP, but not nitrate, compared to the unweighted mean arable land use. We conclude that landscape configuration influences phosphorus transfer more than nitrate transfer, and that flow‐accumulation zones and riparian areas are critical source areas for TP and SRP, respectively. By contrast, landscape spatial configuration in the lateral (upslope–downslope) and longitudinal (upstream–downstream) dimensions did not have an identifiable influence on nutrients temporal dynamics. The indices developed in this study can help design landscapes that minimize diffuse phosphorus losses to streams and show that landscape management is not a first order control for nitrate losses.

Bibliometric analysis of spatio-temporal model using a general product-sum based on a hydrological distance

In the last two decades, the number of model developments in the field of Geostatistics increased rapidly, especially in the Spatio-temporal models. Almost of these models are based on Euclidean distance, only a few which based on non-Euclidean distance. The purpose of this study is to analyze and visualize the types of literatures on stationary Spatio-temporal models that utilize General Product-sum and Hydrological distance through bibliometric analysis methods, by considering a set of bibliometric metrics, including productive and impact measures, methods analysis, and co-authorships analysis. Scientific research works related to Spatio-temporal models using the product-sum field that consider hydrological aspects, published between 2002 and 2022 are reviewed. Some of the most relevant research works in this field and some of the newest trends are collected during September 2022 from Google Scholar, Scopus and Dimensions databases. The literature search method is carried out in two steps. Firstly, literature sources were obtained from Google Scholar, Scopus and Dimensions. Secondly, meta-analysis is performed using Harzing's Publish or Perish and VOSviewer software program. Total of 488 articles related to Spatio-temporal product-sum, and 8 articles related to Spatio-temporal product-sum based on hydrologic distance are selected. The analysis result shows that the proposed topic “Spatio-temporal model using product-sum based on hydrologic distance” has a different significant attribute from the existing research works, i.e., the hydrologic distance. Therefore, the proposed topic can be considered has a novelty.

Flood patterns in a catchment with mixed bedrock geology and a hilly landscape: identification of flashy runoff contributions during storm events

Abstract. With flash flood events having been repeatedly observed in Central and Western Europe in recent years, there is a growing interest in how catchment physiographic properties and hydrological conditions are eventually controlling rapid and concentrated hydrological responses. Here we focus on a set of two nested catchments in Luxembourg (Europe) that have been exposed in 2016 and 2018 to flash flood events and study their seasonal runoff time transfer distributions. Both catchments are of similar size (∼ 30 km2) and have analogous hydrological distance distributions, but their geological bedrock and landscape features are notably different. The upper catchment (KOE) is dominated by a low land area (38 % of the catchment is located less than 30 m above the river network) consisting of variegated marly bedrock (middle Keuper Km3) and moderately steep Luxembourg sandstone outcrops (lower Liassic Li2). The lower catchment (HM) has its drainage network deeply cut into the Luxembourg sandstone, with half of it being covered by marly plateaus (Lower Liassic Li3, located between 80 and 100 m above the river network) featuring heavy clay soil. Based on data generated from a dedicated hydro-meteorological monitoring network, we calculated for 40 rainfall–runoff events observed between August 2019 and July 2021 the corresponding net rainfall transfer time distributions (TTDs) from the hillslopes to the catchment outlet. We then compared the TTD properties and related them to the catchment's hydrological state and rainfall properties. We observed a marked seasonality in TTDs for both catchments. The KOE catchment reacts fastest during the winter period (December–February), while its response time is most delayed and spread out during periods of catchment recharging (October–November) and drying (March–May). The HM catchment exhibits similar TTDs during the mid-October to mid-April period, but they diverge markedly during the remaining part of the year, with opposite variations. During the mid-April to mid-October period, the average response time increases progressively in the KOE catchment. This behavior is in stark contrast to the HM catchment, where response times are significantly shorter (peak discharge delay time decreases by −70 % ± 28 %) and more concentrated (runoff volume occurring in 1 h increases by +48 % ± 87 %) during the mid-April to mid-October, in comparison to the extended winter period. This opposite seasonality leads us to consider different control factors of the runoff transfer processes in relation with the topographic and geological layout of the catchment areas. In the KOE catchment, we found the TTD to be essentially driven by onset and cessation of hydrological connectivity on the flat marly terrain – the latter operating like a variable contributing area in terms of deep soil storage dynamics (except for one summer event). The HM section exhibits contrasted TTDs throughout the year, suggesting threshold-dependent hydrological processes. More specifically, particularly quick runoff transfers seem to dominate under dry conditions (mid-April to mid-October). Correlation analyses compared to the literature on runoff generation on the one hand and our descriptive knowledge of the catchments on the other hand suggest multiple causes for the triggering of these rapid flows. The fractured marly plateaus, but also the hydrophobic forest litter forming during dry conditions on steep slopes, stand as our main hypotheses in this respect. Moreover, the absence of a riparian zone, preventing any dampening of (observed) abrupt and massive flows during extreme precipitation events, also seems to be a key feature of the rapid runoff transfer. For improving our understanding and forecasting capabilities in Luxembourg (and more broadly in the nearby regions of Germany, Belgium, and France with similar physiographic and climate conditions), we recommend further studies focusing on catchments with fractured bedrock and limited riparian zones. Special attention may equally be given to the hypothesized responses of hydrophobic soil surfaces on steep hillslopes and marly soils to heavy precipitation events occurring after extended dry spells.

Patterns of genetic diversity of brown trout in a northern Spanish catchment linked to structural connectivity

The alteration of structural connectivity in fluvial networks is important for the genetic dynamics of aquatic species. Exploring the effects of network fragmentation through genetic analysis is crucial to assess the conservation status of riverine species. In this study, we investigated the genetic consequences of the altered connectivity of brown trout in the Deva–Cares catchment (northern Spain). We investigated (1) genetic diversity, (2) genetic differentiation and genetic structure, (3) migration rates and effective population size and (4) genetic differentiation and riverscape characteristics. Analysis of the genetic variation among 197 individuals from the 13 study sites revealed a high degree of genetic differentiation (FST = 0.181). Below-barrier study sites had higher genetic diversity and lower FST values, while headwater and above-barrier study sites had lower genetic diversity and higher FST values. Most of the genetic groups identified were separated by one or more impermeable barriers. We reported an abrupt decrease in genetic diversity and effective population size in upper course tributaries and isolated reaches. Likewise, a downstream-biased gene flow was found, and it was most likely related to the fragmentation caused by barriers, since the results from migration indicated that gene flow between groups without impermeable barriers was higher bidirectionally. Isolation by impermeable barriers played a more important role than hydrological distance in determining the genetic structure. Most of the genetic groups showed small effective population sizes. Genetic analysis at the river network scale provides evidence for the role of barriers in determining genetic diversity patterns, highlighting the importance of maintaining and restoring river longitudinal connectivity.

Phytoplankton Species Diversity Patterns and Associated Driving Factors in China’s Jiulong River Estuary: Roles That Nutrients and Nutrient Ratios Play

Understanding diversity patterns and associated driving factors are the critical topics in macroecology and conservation biology. Phytoplankton are highly susceptible to environmental changes in estuaries, particularly eutrophication. This study examined phytoplankton alpha and beta diversity using investigation data in May (springtime), August (summer) and November (autumn) 2009 in China’s Jiulong River estuary, where it was easily polluted because of considerable discharge from a highly dense human population and low self-purification capacity with its limited river basin area, potentially resulting in eutrophication and then influencing phytoplankton diversity. Potential influencing factors were also explored, including dissolved oxygen, salinity, nutrients, nutrient ratios, geographic and hydrologic distance, and so on. The results indicated that Shannon’s index (H’) and Pielou’s index (J) decreased from the estuary’s upper to middle and then increased from middle to lower reaches, Simpson’s (D) observed the opposite trend and species number (S) gradually increased from the estuary’s upper to lower reaches. For beta diversity, all the indices showed a gradual decrease trend from the estuary’s upper to lower reaches, where also, turnover dominated beta diversity for all seasons. It is noteworthy that the significant roles that nutrients and nutrient ratios played in shaping phytoplankton diversity patterns and the nutrient balance were characterized by excess nitrogen (N) and silicon (Si) and limited phosphorus (P), which could potentially cause diatom blooms. Findings also showed that decreasing Si concentrations can help to reduce overall pollution levels as well as the restoration of the estuary’s ecosystem better than just reducing N alone. Accordingly, this study advocates for the protection of the entire estuary system with particular emphasis on its upper reaches. Moreover, greater attention should also be paid to impacts associated with N input and nutrient ratio trade-offs to the prospective watershed management of this estuary. This study provides a practical approach to explore estuarine diversity in a comprehensive way, which can inform effective biodiversity conservation and also be applied to other marine ecosystems to better guide sustainable management and conservation practices.

Vegetation characteristics control local sediment and nutrient retention on but not underneath vegetation in floodplain meadows.

Sediment and nutrient retention are essential ecosystem functions that floodplains provide and that improve river water quality. During floods, the floodplain vegetation retains sediment, which settles on plant surfaces and the soil underneath plants. Both sedimentation processes require that flow velocity is reduced, which may be caused by the topographic features and the vegetation structure of the floodplain. However, the relative importance of these two drivers and their key components have rarely been both quantified. In addition to topographic factors, we expect vegetation height and density, mean leaf size and pubescence, as well as species diversity of the floodplain vegetation to increase the floodplain’s capacity for sedimentation. To test this, we measured sediment and nutrients (carbon, nitrogen and phosphorus) both on the vegetation itself and on sediment traps underneath the vegetation after a flood at 24 sites along the River Mulde (Germany). Additionally, we measured biotic and topographic predictor variables. Sedimentation on the vegetation surface was positively driven by plant biomass and the height variation of the vegetation, and decreased with the hydrological distance (total R2 = 0.56). Sedimentation underneath the vegetation was not driven by any vegetation characteristics but decreased with hydrological distance (total R2 = 0.42). Carbon, nitrogen and phosphorus content in the sediment on the traps increased with the total amount of sediment (total R2 = 0.64, 0.62 and 0.84, respectively), while C, N and P on the vegetation additionally increased with hydrological distance (total R2 = 0.80, 0.79 and 0.92, respectively). This offers the potential to promote sediment and especially nutrient retention via vegetation management, such as adapted mowing. The pronounced signal of the hydrological distance to the river emphasises the importance of a laterally connected floodplain with abandoned meanders and morphological depressions. Our study improves our understanding of the locations where floodplain management has its most significant impact on sediment and nutrient retention to increase water purification processes.

Topographical factors related to flooding frequency promote ecosystem multifunctionality of riparian floodplains

Various ecosystem functions provided by floodplains depend on a natural river activity and floodplain morphology. Therefore, anthropogenic alterations of rivers modify their flooding regimes and may affect the provisioning of numerous ecosystem functions. Restoration projects, which aim at reestablishing natural processes of floodplains, require a better understanding of the ecosystem’s ability to simultaneously provide multiple functions (multifunctionality) and how this relates to the environmental template.Here we investigate the relationship between environmental drivers and ecosystem multifunctionality. We focus on 24 ecosystem functions, representing five ecosystem services provided by floodplains of the Mulde River: plant productivity, biodiversity provisioning, retention of sediments, nutrients and pollutants. These functions were measured on 74 plots located on three well preserved floodplain sites of the Mulde River. We described synergies and trade-offs between single functions using correlations and calculated quantitative measures of ecosystem multifunctionality, quantified as the number of functions provided above either 50% of maximal functioning, or 75% of maximal functioning. We then explored relations of multifunctionality with two environmental factors, which also affect the probability of flooding i.e., the hydrological distance and the distance to the water table.Although numerous functions related to sedimentation processes were positively correlated to each other, they traded off with functions related to biodiversity provisioning. This advocates the application of a holistic measure of ecosystem functioning. Multifunctionality indices decreased with an increase of both distance to the water table and hydrological distance, with effects of the distance to the water table being most strongly negative. These findings imply that ecosystem multifunctionality is highest at sites which are flooded regularly. We conclude that restoration attempts which shorten hydrological distance and distance to the water table, like removal of artificial embankments or reconstruction of side channels, may have a positive effect not only on single functions, but also on overall ecosystem multifunctionality. We also advocate the application of a multifunctionality measure to facilitate management and restoration of floodplains.

The influence of landscape spatial configuration on nitrogen and phosphorus exports in agricultural catchments

ContextNitrogen (N) and phosphorus (P) exports from rural landscapes can cause eutrophication of inland and coastal waters. Few studies have investigated the influence of the spatial configuration of nutrient sources—i.e. the spatial arrangement of agricultural fields in headwater catchments—on N and P exports.ObjectivesThis study aimed to (1) assess the influence of the spatial configuration of nutrient sources on nitrate (NO3−) and total phosphorus (TP) exports at the catchment scale, and (2) investigate how relationships between landscape composition (% agricultural land-use) and landscape configuration vary depending on catchment size.MethodsWe analysed NO3− and TP in 19 headwaters (1–14 km², Western France) every two weeks for 17 months. The headwater catchments had similar soil types, climate, and farming systems but differed in landscape composition and spatial configuration. We developed a landscape configuration index (LCI) describing the spatial organisation of nutrient sources as a function of their hydrological distance to streams and flow accumulation zones. We calibrated the LCI’s two parameters to maximise the rank correlation with median concentrations of TP and NO3−.ResultsWe found that landscape composition controlled NO3− exports, whereas landscape configuration controlled TP exports. For a given landscape composition, landscape spatial configuration was highly heterogeneous at small scales (< 10 km2) but became homogeneous at larger scales (> 50 km2).ConclusionsThe spatial configuration of nutrient sources influences TP but not NO3− exports. An ideal placement of mitigation measures to limit diffuse TP export should consider both the hydrological distance to streams and flow accumulation zones.

云南省把边江流域不同土地利用方式对大型底栖动物群落的影响

研究土地利用对大型底栖动物群落的影响，对流域土地利用规划修编和河流生态修复等有重要意义。以红河上游的把边江流域为研究区，调查大型底栖动物群落现状，计算37个样点上游集水区土地利用组分、配置、多样性和水文距离4个方面20个土地利用指标，分析不同土地利用方式对大型底栖动物群落的影响。本次调查共鉴定出25个大型底栖动物分类单元，其中水生昆虫最多，占分类单元总数的72%；摄食功能群以捕食者（PR）、刮食者（SC）和直接收集者（GC）为主。把边江流域城镇用地和林地对大型底栖动物群落的影响占主导地位，而耕地对大型底栖动物群落的影响较小。影响把边江流域大型底栖动物群落的关键土地利用指标为城镇用地面积比（3PLA）、城镇用地最大斑块指数（3LPI）、城镇用地聚合指数（3AI）、城镇用地水流长度（3FLOW）、林地最大斑块指数（1LPI）和林地形状指数（1LSI）。土地利用组分、配置和水文距离是影响把边江流域大型底栖动物群落的主要方面，而土地利用多样性对大型底栖动物群落的影响较小。大型底栖动物物种密度和物种多样性与3PLA、3LPI、3AI、3FLOW和1LSI呈负相关，与1LPI呈正相关。1LPI与浮游目（如小蜉科、扁蜉科）为代表的清洁物种呈现较明显的正相关关系。城镇用地指标与SC和SH（撕食者）密度具有显著的负相关关系，与GC密度有较弱的正相关关系，而与其他功能群没有明显的相关关系。SC和SH对水质和环境条件敏感，而GC对人类干扰耐受性较强。1LPI与SC和FC（滤食收集者密度）正相关，而与PR和GC密度负相关。SC和FC对生境的完整性要求较高，而GC和PR对人为干扰和较为破碎的生境更为适应。一方面，随着城镇用地的规模、边界复杂性和聚集程度增加，研究区大型底栖动物密度和多样性降低；另一方面，随着林地完整性降低，大型底栖动物物种均匀度降低。土地利用与大型底栖动物物种多样性和功能群多样性的关系不完全一致，1LSI和3FLOW与物种多样性负相关，而与功能群多样性呈正相关关系，土地利用对物种-功能群-群落不同尺度上的影响差异还需要更深入的研究。;It is of great significance to study the impact of land use on macrobenthic communities for watershed land use planning revision and river ecological restoration. Taking the Babian River Basin in the upper reaches of the Red River as research area, the status of macrobenthic communities was investigated. Twenty land use indicators in 4 aspects including composition, allocation, diversity and hydrological distance based on upper catchment area of 37 sampling points were calculated to analyze the impacts of different land use patterns on macrobenthic communities. A total of 25 macrobenthic taxa were identified in this survey, of which aquatic insects accounted for 72% of the total. The main feeding functional groups were predators (PR), scrapers (SC), and gather collectors (GC). The impacts of urban land and woodland on macrobenthic communities were dominant, while the impact of agricultural land was relatively small in the Babian River Basin. The key land use indicators affecting the macrobenthic communities were the percentage of urban land (3PLA), the largest patch index of urban land (3LPI), the aggregation index of urban land (3AI), the flow length of urban land (3FLOW), the largest patch index of woodland (1LPI), and the landscape shape index of woodland (1LSI). Land use composition, allocation and hydrological distance were the main factors affecting macrobenthic communities in the Baibian River Basin, while land use diversity had little effect on macrobenthic community. The species density and diversity of macrobenthos showed negative correlations with 3PLA, 3LPI, 3AI, 3FLOW and 1LSI, while positive correlations with 1LPI. The clean species, such as Ephemeridae and Heptaglidae, increased with increasing of 1LPI. There were significantly negative correlations between the urban indexes and the density of SC and SH (Shredders), but no significant correlations between the urban indexes with other functional groups. SC and SH were sensitive to water quality and environmental conditions, however, GC were more tolerant of human interference. 1LPI was positively correlated with the density of SC and FC (Filter Collectors), but negatively correlated with the density of PR and GC. SC and FC had higher demands on habitat integrity, while GC and PR were more adaptive to human disturbance and fragmented habitat. On the one hand, with the increase of urban land use, the complexity of boundaries, and the degree of aggregation, the density and species diversity of macrobenthos in the study area decreased. On the other hand, as the integrity of woodland decreased, the species evenness of macrobenthos also decreased. The relationship between land use and macrobenthic species diversity and functional group diversity is not completely consistent, such as 1LSI and 3FLOW are negatively correlated with species diversity, but are positively correlated with functional group diversity. More in-depth researches are needed to investigate the impacts of land use on species, functional groups and communities at different scales.

Quantifying plankto-environmental interactions in a tropical river Narmada, India: An alternative model-based approach

Plankton is one of the key elements for biological monitoring of riverine ecosystem. It is of paramount importance to understand plankto-environmental interaction for river ecological assessment. This article has presented an alternative model-based analytical framework to quantify plankto-environmental interactions and prediction thereof for a tropical river system. Analysis of secondary data on the Narmada River in India has made it possible to accomplish this. Hierarchical cluster analysis, based on water quality similarity, has been applied for grouping of sites. The resulted clusters slightly deviate from subjective division of the river, but their formation have been coherently ordered downstream-wise. Generalized additive modeling (GAM) with Poisson error assumption of plankton abundance has been the key modeling approach. The GAM, which has explained 66% and 88% deviance of phytoplankton and zooplankton density, respectively, has identified four (transparency, nitrate, temperature, alkalinity) out of thirteen water quality attributes in order of their relative influence on the phytoplankton and zooplankton abundance. The study has established that, in riverine system, application of GAM model under Poisson error assumption has been very effective; and the model has provided reasonably accurate prediction of plankton abundance along hydrologic distance—with noise reduction due to water quality parameters.

Using Remote Sensing Based Metrics to Quantify the Hydrological Response in a City

We propose a remote-sensing based metric approach to evaluate the hydrological response of highly urbanized areas and apply it to the city of Brussels. The model is set-up using 2 m resolution hyperspectral data. Next, it is upscaled to the city level, using multi-spectral Sentinel-2 data with 20 m resolution. We identify the total impervious area, the vegetation cover and the leaf area index as important metrics to derive a timeseries of spatially distributed net rainfall, runoff and infiltration from rainfall data. For the estimation of the actual evapotranspiration we use the potential evapotranspiration and the available water storage based on the interception, the depression storage and the infiltration. Additionally, we route the runoff to the outlet of selected sub-catchments. An important metric for the routing is the timing to the outlet which is approximated using the total impervious area and the hydrological distance to the outlet. We compare our approach to WetSpa model simulations and reach R 2 values of 98% for net rainfall, 95% for surface runoff, 99% for infiltration and 97% for cumulative evapotranspiration. The routing in the Watermaelbeek catchment is evaluated with discharge observations and reaches NSE values of 0.89 at a 2 m resolution and 0.88 at a 20 m resolution using an hourly timestep. At the timestep of 10 min and a 20 m resolution the NSE is reduced to 0.76. For the Roodebeek catchment we reach an NSE of 0.73 at a spatial resolution of 20 m and an hourly timestep. The results presented in this paper are optimistic for using spatial and temporal metrics retrieved from remote sensing data to quantify the water balance of urban catchments.

Genetic diversity and structure of striped snakehead (Channa striata) in the Lower Mekong Basin: Implications for aquaculture and fisheries management

Striped snakehead (Channa striata) has been cultured for several decades in Viet Nam while only recently cultured in Cambodia. A cross-country comparison of genetic diversity in wild and cultured striped snakehead populations provided novel insights for improved genetic resource management and cultivation in Lower Mekong region. We collected striped snakehead samples from three wild and three cultured populations in the Vietnamese Mekong Delta for comparison to samples from eight wild populations in Cambodia (n = 5 and 3 from Tonle Sap Lake and Mekong River floodplain, respectively). Sequencing of cytochrome b (585 bp) and D-loop (874 bp) from 270 individuals yielded 28 and 128 haplotypes, respectively, resulting in 150 concatenated haplotypes. Mean genetic diversity indices of concatenated sequences were highest in wild Tonle Sap Lake populations (haplotype diversity Hd = 0.994 ± 0.004, nucleotide diversity pi = 0.0077 ± 0.0009), intermediate in wild Cambodian Mekong River populations (Hd = 0.925 ± 0.097, pi = 0.0076 ± 0.0005) and wild Vietnamese Mekong River populations (Hd = 0.832 ± 0.152, pi = 0.0061 ± 0.0018), and lowest in cultured Vietnamese populations (Hd = 0.451 ± 0.198, pi = 0.0021 ± 0.0002). The wild Tonle Sap Lake and cultured Vietnamese populations differed significantly in all genetic diversity indices (P < 0.05). The unique haplotypes and significant genetic divergence (P < 0.01) among striped snakehead populations from each habitat (e.g., lake or floodplain, wild or cultured) suggests habitat-specific genetic structure. Genetic differences among all wild populations were also positively correlated with hydrological distance in the range of 600 km (P < 0.01), suggesting isolation by distance. These findings have important implications for appropriate management of wild and cultured C. striata in Viet Nam and Cambodia.

Relationship between water quality and macro-scale parameters (land use, erosion, geology, and population density) in the Siminehrood River Basin

To date, few studies have investigated the simultaneous effects of macro-scale parameters (MSPs) such as land use, population density, geology, and erosion layers on micro-scale water quality variables (MSWQVs). This research focused on an evaluation of the relationship between MSPs and MSWQVs in the Siminehrood River Basin, Iran. In addition, we investigated the importance of water particle travel time (hydrological distance) on this relationship. The MSWQVs included 13 physicochemical and biochemical parameters observed at 15 stations during three seasons. Primary screening was performed by utilizing three multivariate statistical analyses (Pearson's correlation, cluster and discriminant analyses) in seven series of observed data. These series included three separate seasonal data, three two-season data, and aggregated three-season data for investigation of relationships between MSPs and MSWQVs. Coupled data (pairs of MSWQVs and MSPs) repeated in at least two out of three statistical analyses were selected for final screening. The primary screening results demonstrated significant relationships between land use and phosphorus, total solids and turbidity, erosion levels and electrical conductivity, and erosion and total solids. Furthermore, water particle travel time effects were considered through three geographical pattern definitions of distance for each MSP by using two weighting methods. To find effective MSP factors on MSWQVs, a multivariate linear regression analysis was employed. Then, preliminary equations that estimated MSWQVs were developed. The preliminary equations were modified to adaptive equations to obtain the final models. The final models indicated that a new metric, referred to as hydrological distance, provided better MSWQV estimation and water quality prediction compared to the National Sanitation Foundation Water Quality Index.

Are zooplankton communities structured by taxa ecological niches or by hydrological features?

AbstractThis study aimed to clarify the mechanisms that structure zooplankton communities in a lowland river network. Fourteen stations on the Scheldt upper river basin (France/Belgium) were sampled during 4 campaigns in 2014–2015.Firstly, a niche analysis of zooplankton taxa was conducted for April and September 2014 using the outlying mean index (OMI) ordination technique. Then, application of Hutchinson's niche and of Hubbell's neutral theories to zooplankton community of the river network was tested for April and June 2015. We subsequently tested whether the taxa ecological preferences revealed were reflected in the April and June 2015 zooplankton spatial distributions.In April 2015, zooplankton community dissimilarity (Bray–Curtis distance) was more influenced by environmental conditions than by hydrological distance, in accordance with niche theory. In June 2015, a stronger influence of neutral processes was suggested by an important role of hydrology. In 2014 samples, 17 over 32 taxa presented significant marginality relying on the considered environmental parameters. This specialization was reflected in the 2015 community patterns, particularly in April. During this month, local environmental parameters were more influencing than hydrology, probably related to a higher environmental heterogeneity than in June 2015.Although zooplankters are often considered to be generalists and opportunists, mainly dependent of river hydrology, these results showed that even for passive dispersers in highly connected systems, niche processes contribute to community structuring by local filtering. Determination of species niche parameters is thus important to understand observed community patterns but also changes in species distribution relative to environmental and hydrological changes.