scholarly journals A method for predicting hydrogen and oxygen isotope distributions across a region's river network using reach-scale environmental attributes

2021 ◽  
Author(s):  
Bruce Dudley ◽  
Jing Yang ◽  
Ude Shankar ◽  
Scott Graham
Keyword(s):  
New Zealand ◽  
Surface Water ◽  
River Water ◽  
Stable Isotope Ratio ◽  
Surface Flow ◽  
River Network ◽  
River Networks ◽  
Environmental Characteristics ◽  
Validation Data ◽  
Water Isotope

Abstract. Stable isotope ratio measurements (isotope values) of surface water provide information on hydrological processes and can be used to determine provenance of hydrogen and oxygen stored in animal and plant tissues. Development of maps of the distribution of isotope values (isoscapes) for river networks is limited by methods to interpolate point measures to values for the entire network. Isotope values of precipitation and environmental characteristics that drive fractionation processes within the catchment also affect downstream reaches via flow. Many environmental characteristics, such as man-made dams, are no more likely to affect nearby unconnected reaches than distant ones. Hence, distance-based geospatial and statistical interpolation methods used to develop isoscapes for precipitation and terrestrial systems are less appropriate for river networks. We used a water balance-based method, which represents patterns of surface flow and mixing, and added a regression-based correction step using catchment environmental predictors. We applied this method across the river network of New Zealand, comprising over 600,000 reaches and over 400,000 kilometres of rivers. Inputs to the model are national rainfall precipitation isoscapes, a digital elevation layer, a national river water isotope monitoring dataset (3 years of monthly sampling at 58 sites) and reach scale river environmental databases across the New Zealand river network. δ2H and δ18O isoscapes produced using this regression-based kriging method showed improved fit to validation data, compared to a model for which residuals were applied as a correction factor across the river network using ordinary kriging. The resulting river water isoscapes have potential applications in ecology, hydrology and provenance studies for which understanding of spatial variation between precipitation and surface water isotope values are required.

A method for predicting hydrogen and oxygen isotope distributions across a region’s river network using reach-scale environmental attributes

2021 ◽  
Author(s):  
Bruce Dudley ◽  
Jing Yang ◽  
Ude Shankar ◽  
Scott Graham
Keyword(s):  
New Zealand ◽  
Water Balance ◽  
River Water ◽  
River Network ◽  
River Networks ◽  
Environmental Characteristics ◽  
Validation Data ◽  
Environmental Attributes ◽  
Water Isotope

<p>Long-term isotope values of river water provide information on hydrological flow pathways and atmospheric exchange and can be used to determine the origins of hydrogen and oxygen stored in animal and plant tissues. However, development of isotope maps for rivers is currently limited by methods to spatially interpolate point measurements to values for entire river networks. Catchment environmental characteristics and structures that affect river water isotope values also affect downstream reaches via flow, but many (such as man-made dams) are no more likely to affect nearby unconnected catchments than distant ones. Hence, distance-based geospatial and statistical interpolation methods used to develop isoscapes for precipitation and terrestrial systems may be less appropriate for river networks. We developed a modified ‘water balance’ river isotope mapping method to consider the effects of reach-scale catchment environmental characteristics and applied it across the entire stream network of New Zealand. This network comprises over 600,000 reaches and over 400,000 kilometres of rivers. The method uses national rainfall precipitation isoscapes, a digital elevation layer, a national river water isotope monitoring dataset (currently over 3 years of monthly sampling at 58 sites) and reach scale environmental attribute databases that cover New Zealand’s river network. δ<sup>2</sup>H and δ<sup>18</sup>O isoscapes produced showed an improved fit to validation data, compared to a model for which residuals between observed and simulated isotope values were applied as a correction factor across the river network using the ordinary kriging method. Hence, we show how a water balance modelling approach can provide an improved representation of long-term river water δ<sup>2</sup>H and δ<sup>18</sup>O values when combined with a correction for catchment environmental attributes.</p>

A method for predicting hydrogen and oxygen isotope distributions across a region’s river network using reach-scale environmental attributes

2020 ◽  
Author(s):  
Bruce Dudley ◽  
Jing Yang ◽  
Ude Shankar ◽  
Scott Graham
Keyword(s):  
New Zealand ◽  
Water Balance ◽  
River Water ◽  
River Network ◽  
Environmental Data ◽  
River Networks ◽  
Environmental Characteristics ◽  
Validation Data ◽  
Water Isotope

<p><span>Long-term isotope values of river water provide information on hydrological flow pathways and atmospheric exchange. However, current development of isotope maps for rivers is limited by methodology that spatially interpolates point measures to entire river networks. Catchment environmental characteristics and structures that affect river water isotope values also affect downstream reaches via flow, but many (such as man-made dams) are no more likely to affect nearby unconnected catchments than distant ones. Hence, geospatial and statistical interpolation methods used to develop isoscapes for precipitation and terrestrial systems may be less appropriate for river networks. We developed a modified ‘water balance’ river isotope mapping method to consider the effects of reach-scale catchment environmental characteristics and applied it across the entire stream network of New Zealand. This network comprises over 600,000 reaches and over 400,000 kilometres of rivers. The method uses national rainfall precipitation isoscapes, a digital elevation layer, a national river water isotope monitoring dataset (currently over 3 years of monthly sampling at 58 sites) and reach scale river environmental databases across the New Zealand river network. δ<sup>2</sup>H and δ<sup>18</sup>O isoscapes produced using our method showed improved fit to validation data, compared to a model for which residuals were applied as a correction factor across the river network using ordinary kriging. Hence, we show that a water balance modelling approach can provide a good representation of long-term river water δ<sup>2</sup>H and δ<sup>18</sup>O values when combined with a regression-based correction using catchment environmental data. </span></p>

Experimental investigation on water quality standard of Yangtze River water source heat pump

2012 ◽  
Vol 66 (5) ◽  
pp. 1103-1109 ◽  
Author(s):  
Zenghu Qin ◽  
Mingwei Tong ◽  
Lin Kun
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
River Water ◽  
Heat Pump ◽  
Yangtze River ◽  
Water Source ◽  
Quality Standard ◽  
Heat Pumps ◽  
The Yangtze River ◽  
Water Conditions

Due to the surface water in the upper reaches of Yangtze River in China containing large amounts of silt and algae, high content of microorganisms and suspended solids, the water in Yangtze River cannot be used for cooling a heat pump directly. In this paper, the possibility of using Yangtze River, which goes through Chongqing, a city in southwest China, as a heat source–sink was investigated. Water temperature and quality of the Yangtze River in the Chongqing area were analyzed and the performance of water source heat pump units in different sediment concentrations, turbidity and algae material conditions were tested experimentally, and the water quality standards, in particular surface water conditions, in the Yangtze River region that adapt to energy-efficient heat pumps were also proposed. The experimental results show that the coefficient of performance heat pump falls by 3.73% to the greatest extent, and the fouling resistance of cooling water in the heat exchanger increases up to 25.6% in different water conditions. When the sediment concentration and the turbidity in the river water are no more than 100 g/m3 and 50 NTU respectively, the performance of the heat pump is better, which can be used as a suitable river water quality standard for river water source heat pumps.

scholarly journals Setting the Flow Accumulation Threshold Based on Environmental and Morphologic Features to Extract River Networks from Digital Elevation Models

2021 ◽  
Vol 10 (3) ◽  
pp. 186
Author(s):  
HuiHui Zhang ◽  
Hugo A. Loáiciga ◽  
LuWei Feng ◽  
Jing He ◽  
QingYun Du
Keyword(s):  
Spatial Scales ◽  
Digital Elevation Models ◽  
Regional Scale ◽  
Drainage Density ◽  
River Network ◽  
Landscape Patterns ◽  
Estimation Methods ◽  
River Networks ◽  
Flow Accumulation ◽  
Digital Elevation

Determining the flow accumulation threshold (FAT) is a key task in the extraction of river networks from digital elevation models (DEMs). Several methods have been developed to extract river networks from Digital Elevation Models. However, few studies have considered the geomorphologic complexity in the FAT estimation and river network extraction. Recent studies estimated influencing factors’ impacts on the river length or drainage density without considering anthropogenic impacts and landscape patterns. This study contributes two FAT estimation methods. The first method explores the statistical association between FAT and 47 tentative explanatory factors. Specifically, multi-source data, including meteorologic, vegetation, anthropogenic, landscape, lithology, and topologic characteristics are incorporated into a drainage density-FAT model in basins with complex topographic and environmental characteristics. Non-negative matrix factorization (NMF) was employed to evaluate the factors’ predictive performance. The second method exploits fractal geometry theory to estimate the FAT at the regional scale, that is, in basins whose large areal extent precludes the use of basin-wide representative regression predictors. This paper’s methodology is applied to data acquired for Hubei and Qinghai Provinces, China, from 2001 through 2018 and systematically tested with visual and statistical criteria. Our results reveal key local features useful for river network extraction within the context of complex geomorphologic characteristics at relatively small spatial scales and establish the importance of properly choosing explanatory geomorphologic characteristics in river network extraction. The multifractal method exhibits more accurate extracting results than the box-counting method at the regional scale.

scholarly journals A new vector-based global river network dataset accounting for variable drainage density

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Peirong Lin ◽  
Ming Pan ◽  
Eric F. Wood ◽  
Dai Yamazaki ◽  
George H. Allen
Keyword(s):  
Spatial Variability ◽  
Flow Direction ◽  
River System ◽  
Drainage Density ◽  
River Network ◽  
River Networks ◽  
Digital Elevation ◽  
Machine Learning Approach ◽  
Elevation Model ◽  
National Hydrography Dataset

AbstractSpatial variability of river network drainage density (Dd) is a key feature of river systems, yet few existing global hydrography datasets have properly accounted for it. Here, we present a new vector-based global hydrography that reasonably estimates the spatial variability of Dd worldwide. It is built by delineating channels from the latest 90-m Multi-Error-Removed Improved Terrain (MERIT) digital elevation model and flow direction/accumulation. A machine learning approach is developed to estimate Dd based on the global watershed-level climatic, topographic, hydrologic, and geologic conditions, where relationships between hydroclimate factors and Dd are trained using the high-quality National Hydrography Dataset Plus (NHDPlusV2) data. By benchmarking our dataset against HydroSHEDS and several regional hydrography datasets, we show the new river flowlines are in much better agreement with Landsat-derived centerlines, and improved Dd patterns of river networks (totaling ~75 million kilometers in length) are obtained. Basins and estimates of intermittent stream fraction are also delineated to support water resources management. This new dataset (MERIT Hydro–Vector) should enable full global modeling of river system processes at fine spatial resolutions.

Taking the pulse of Mother Ganga - Revealing the visible and invisible water pollution crisis along the Ganges River

2021 ◽  
Author(s):  
Stefan Krause ◽  
Keyword(s):  
Water Pollution ◽  
Water Quality ◽  
Land Use ◽  
Surface Water ◽  
River Network ◽  
Ganges River ◽  
Sediment Samples ◽  
Water And Sediment ◽  
The Ganges ◽  
Water And Sediment Samples

<p>It is probably hard to overestimate the significance of the River Ganges for its spiritual, cultural and religious importance. As the worlds’ most populated river basin and a major water resource for the 400 million people inhabiting its catchment, the Ganges represents one of the most complex and stressed river systems globally. This makes the understanding and management of its water quality an act of humanitarian and geopolitical relevance. Water quality along the Ganges is critically impacted by multiple stressors, including agricultural, industrial and domestic pollution inputs, a lack and failure of water and sanitation infrastructure, increasing water demands in areas of intense population growth and migration, as well as the severe implications of land use and climate change. Some aspects of water pollution are readily visualised as the river network evolves, whilst others contribute to an invisible water crisis (Worldbank, 2019) that affects the life and health of hundreds of millions of people.</p><p>We report the findings of a large collaborative study to monitor the evolution of water pollution along the 2500 km length of the Ganges river and its major tributaries that was carried out over a six-week period in Nov/Dec 2019 by three teams of more than 30 international researchers from 10 institutions. Surface water and sediment were sampled from more than 80 locations along the river and analysed for organic contaminants, nutrients, metals, pathogen indicators, microbial activity and diversity as well as microplastics, integrating in-situ fluorescence and UV absorbance optical sensor technologies with laboratory sample preparation and analyses. Water and sediment samples were analysed to identify the co-existence of pollution hotspots, quantify their spatial footprint and identify potential source areas, dilution, connectivity and thus, derive understanding of the interactions between proximal and distal of sources solute and particulate pollutants.</p><p>Our results reveal the co-existence of distinct pollution hotspots for several contaminants that can be linked to population density and land use in the proximity of sampling sites as well as the contributing catchment area. While some pollution hotspots were characterised by increased concentrations of most contaminant groups, several hotspots of specific pollutants (e.g., microplastics) were identified that could be linked to specific cultural and religious activities. Interestingly, the downstream footprint of specific pollution hotspots from contamination sources along the main stem of the Ganges or through major tributaries varied between contaminants, with generally no significant downstream accumulation emerging in water pollution levels, bearing significant implications for the spatial reach and legacy of pollution hotspots. Furthermore, the comparison of the downstream evolution of multi-pollution profiles between surface water and sediment samples support interpretations of the role of in-stream fate and transport processes in comparison to patterns of pollution source zone activations across the channel. In reporting the development of this multi-dimensional pollution dataset, we intend to stimulate a discussion on the usefulness of large river network surveys to better understand the relative contributions, footprints and impacts of variable pollution sources and how this information can be used for integrated approaches in water resources and pollution management.</p>

The Surface Water and Ocean Topography (SWOT) Mission River Database (SWORD): A global river network for satellite data products

2021 ◽  
Author(s):  
Elizabeth H. Altenau ◽  
Tamlin M. Pavelsky ◽  
Michael T. Durand ◽  
Xiao Yang ◽  
Renato Prata de Moraes Frasson ◽  
...  
Keyword(s):  
Surface Water ◽  
Satellite Data ◽  
River Network ◽  
Data Products ◽  
Ocean Topography

Survival of cryptosporidium parvum, escherichia coli, faecal enterococci and clostridium perfringens in river water: influence of temperature and autochthonous microorganisms

1997 ◽  
Vol 35 (11-12) ◽  
pp. 249-252 ◽  
Author(s):  
G. J. Medema ◽  
M. Bahar ◽  
F. M. Schets
Keyword(s):  
Surface Water ◽  
River Water ◽  
Cryptosporidium Parvum ◽  
Health Hazard ◽  
Influence Of Temperature ◽  
E Coli ◽  
Untreated Water ◽  
Time Required ◽  
Micro Organisms

Oocysts of Cryptosporidium parvum can survive for several months in surface water, one of the main factors determining their success in environmental transmission and thus their health hazard via water. Several factors in the environment, e.g. temperature, presence of predators and exo-enzymes will probably influence oocyst survival. The high persistence of oocysts may also limit the value of traditional faecal indicator bacteria. The aim of this study was to determine the rate at which C parvum oocysts, E coli, faecal enterococci and C perfringens spores die in surface water and the influence of temperature and the presence of autochthonous (micro)organisms on the die-off rate. Microcosms with autoclaved river water were inoculated with the organisms. Microcosms with untreated river water were inoculated with concentrated primary effluent containing the bacteria and with C parvum oocysts. Microcosms were incubated at 5°C or 15°C at 100rpm. Viability of oocysts was monitored by in vitro excystation and dye-exclusion; viability of the bacteria was determined on appropriate selective media. When pseudo first-order die-off kinetics were assumed, the die-off rate of oocysts at 5°C was 0.010 log10/d and at 15°C, 0.006–0.024 log10/d. These rates underestimate die-off since oocyst disintegration was not accounted for. Incubation in autoclaved or untreated water did influence the die-off rate of oocysts at 15°C but not at 5°C. The die-off rate of E coli and enterococci was faster in the non-sterile river water than in autoclaved water at both temperatures. At 15°C, E coli (and possibly E faecium) even multiplied in autoclaved water. In untreated river water, the die-off of E coli and enterococci was approximately 10x faster than die-off of oocysts but die-off rates of C perfringens were lower than those of oocysts. As for oocysts, die-off of the bacteria and spores was faster at 15°C than at 5°C. Oocysts are very persistent in river water: the time required for a 10x reduction in viability being 40–160d at 15°C and 100d at 5°C. Biological/biochemical activity influenced oocyst survival at 15°C and survival of both vegetative bacteria at 5 and 15°C. The rapid die-off of E coli and enterococci makes them less suitable as indicators of oocyst presence in water. As C perfringens survived longer in untreated river water than oocysts, it may prove useful as an indicator of the presence of C parvum.

scholarly journals An Innovative Framework for Real Time Monitoring of Pollutant Point Sources in River Networks

2021 ◽  
Author(s):  
Mehdi Mazaheri ◽  
J. M. V. Samani ◽  
Fulvio Boano
Keyword(s):  
Real Time ◽  
Transport Model ◽  
River Network ◽  
Point Sources ◽  
Release Time ◽  
River Networks ◽  
Observation Data ◽  
Geostatistical Approach ◽  
Pollutant Sources ◽  
Simultaneous Identification

Abstract The simultaneous identification of location and source release history in complex river networks is a very complicated ill-posed problem, particularly in a case of multiple unknown pollutant sources with time-varying release pattern. This study presents an innovative method for simultaneous identification of the number, locations and release histories of multiple pollutant point sources in a river network using minimum observation data. Considering two different type of monitoring stations with an adaptive arrangement as well as real-time data collection at those stations and using a reliable numerical flow and transport model, at first the number and suspected reach of presence of pollutant sources are determined. Then the source location and its intensity function is calculated by solving inverse source problem using a geostatistical approach. A case study with three different scenarios in terms of the number, release time and location of pollutant sources are discussed, concerning a river network with unsteady and non-uniform flow. Results showed the capability of the proposed method in identifying of sought source characteristics even in complicated cases with simultaneous activity of multiple pollutant sources.

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