Uncertainty in acquiring elemental fluxes from subtropical mountainous rivers

Abstract. Mountainous watersheds in high standing islands of the western tropical and subtropical Pacific have received great international attention regarding its high physical and chemical weathering rates caused by cyclone invasion, friable lithology and high tectonic activity. Since mountainous region is usually difficult to assess, particularly, during severe weather conditions, hydrological responses of elements against full-scale of water discharge (often >2 orders of magnitude) are rarely reported. In this study, we conducted discrete sampling (~3 day interval) throughout four seasons and intensive sampling (hourly) during typhoon floods from three upstream watersheds in Taiwan during 2002–2005. These observations revealing various elemental responses are taken as complete dataset (i.e. reference flux) to evaluate flux uncertainty among constituents caused by different sampling frequency, sample size and estimators. Five constituents are analyzed, including nitrate (NO3), sulfate (SO4), dissolved organic carbon (DOC), calcium (Ca), and silicate (Si). Each has specific environmental and geological implications. Direct average, flow-weighted and rating curve methods were applied. Basing on statistical analyses, flow-weighted method is the most conservative method, and is recommended to use for all constituents if few samples are available. The rating curve method is suggested, only when water samples in high-flows are available. Direct average method is only appropriate for stable constituents, such as Si. These findings, such as concentration-discharge variation, sampling frequency effect, and flux estimator assessment, offer fundamental knowledge while estimating geochemical fluxes from small mountainous rivers in Oceania region.

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Water discharge estimates from large radar altimetry datasets in the Amazon basin

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-9-7591-2012 ◽

2012 ◽

Vol 9 (6) ◽

pp. 7591-7611 ◽

Cited By ~ 8

Author(s):

A. C. V. Getirana ◽

C. Peters-Lidard

Keyword(s):

Data Assimilation ◽

Amazon Basin ◽

Water Discharge ◽

Rating Curve ◽

Radar Altimetry ◽

Discharge Data ◽

Modeling Uncertainties ◽

The Mean ◽

Relative Errors ◽

The Impact

Abstract. In this study, we evaluate the use of a large radar altimetry dataset as a complementary gauging network capable of providing water discharge in ungauged regions within the Amazon basin. A rating-curve-based methodology is adopted to derive water discharge from altimetric data provided by Envisat at 444 virtual stations (VS). The stage-discharge relations at VS are built based on radar altimetry and outputs from a global flow routing scheme. In order to quantify the impact of modeling uncertainties on rating-curve based discharges, another experiment is performed using simulated discharges derived from a simplified data assimilation procedure. Discharge estimates at 90 VS are evaluated against observations during the curve fitting calibration (2002–2005) and evaluation (2006–2008) periods, resulting in mean relative RMS errors as high as 52% and 12% for experiments without and with assimilation, respectively. Without data assimilation, uncertainty of discharge estimates can be mostly attributed to forcing errors at smaller scales, generating a positive correlation between performance and drainage area. Mean relative errors (RE) of altimetry-based discharges varied from 15% to 92% for large and small drainage areas, respectively. Rating curves produced a mean RE of 54% versus 68% from model outputs. Assimilating discharge data decreases the mean RE from 68% to 12%. These results demonstrate the feasibility of applying the proposed methodology to the regional or global scales. Also, it is shown the potential of satellite altimetry for predicting water discharge in poorly-gauged and ungauged river basins.

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Atmospheric deposition versus rock weathering in the control of streamwater chemistry in a tropical rain-forest catchment in Malaysian Borneo

Journal of Tropical Ecology ◽

10.1017/s0266467414000303 ◽

2014 ◽

Vol 30 (5) ◽

pp. 481-492 ◽

Cited By ~ 3

Author(s):

Naoyuki Yamashita ◽

Hiroyuki Sase ◽

Ryo Kobayashi ◽

Kok-Peng Leong ◽

Jamil Mohd Hanapi ◽

...

Keyword(s):

Rain Forest ◽

Tropical Rain Forest ◽

Chemical Weathering ◽

Major Ions ◽

Water Discharge ◽

Base Cations ◽

Base Cation ◽

Ion Fluxes ◽

Small Catchment ◽

Streamwater Chemistry

Abstract:Uncertainty about the H+ buffering capacity in tropical rain forest limits our ability to predict the future effect of anthropogenic deposition on the streamwater chemistry. Export of major ions to the stream and the ion-fluxes via rainfall, throughfall, litter-leachate and soil-water pathways were observed to examine the source of streamwater nutrients in a small catchment in Sabah, Malaysia. The streamwater and the ion-fluxes were measured for 3.75 and 2 y, respectively, by collecting water twice a month and setting ion-exchange-resin columns. Streamwater pH ranged from 6.5 to 7.6 and was not sensitive to water discharge controlling base cations. The NO3−-N, Ca2+ and Mg2+ fluxes were low in atmospheric depositions (0.6, 0.5 and 0.3 kg ha−1 y−1, respectively) and markedly increased in the litter layer. The NO3−-N flux decreased drastically from subsoil (70 kg ha−1 y−1) to the stream (1.4 kg ha−1 y−1) whereas the Ca2+ and Mg2+ fluxes were not different between subsoil (38 and 18 kg ha−1 y−1) and stream (30 and 15 kg ha−1 y−1). Neutral pH in tropical streams was mainly due to the base cation leaching with deep chemical weathering in deeper strata, and a rapid decrease in NO3− leaching from the subsoil to the stream.

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Carbon dynamics and full carbon balance of a Northern mire ecosystem

10.5194/egusphere-egu2020-9842 ◽

2020 ◽

Author(s):

Patrik Vestin ◽

Per Weslien ◽

Marcus Wallin ◽

David Bastviken ◽

Natascha Kljun ◽

...

Keyword(s):

Carbon Balance ◽

Dissolved Inorganic Carbon ◽

Water Discharge ◽

Weather Conditions ◽

Carbon Dynamics ◽

Severe Drought ◽

Ecosystem Carbon ◽

Strong Source ◽

Net Ecosystem Carbon Balance ◽

Mire Ecosystem

We present the Net Ecosystem Carbon Balance (NECB) of a Northern mire ecosystem for the period 2016-2019. The Mycklemossen peatland is located in the hemi-boreal region in the Southwestern part of Sweden and is classified as a fen with bog-like vegetation. The NECB was determined from eddy covariance (EC) measurements of carbon dioxide (CO2) and methane (CH4) and continuous water discharge measurements with biweekly measurements of dissolved organic carbon (DOC), dissolved inorganic carbon (DIC) and dissolved CH4. We focus on the carbon dynamics of the Mycklemossen ecosystem during summer droughts and on its recovery during normal years. During 2016-2018, the annual precipitation was lower than the 30-year average while 2019 was a normal year in terms of weather conditions. 2018 sticks out as an extreme year with a severe drought and unusually high air temperature at Mycklemossen, as was the case in much of Northern and Central Europe. The EC results indicate that Mycklemossen lost carbon during 2016-2018. While CH4 emissions decreased, the mire became a strong source of CO2 these years, especially 2018. There were also large losses of DOC during this period, which were further enhanced during 2019.

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Monthly Suspended Sediment Load Estimation using Artificial Neural Network and Traditional Models in Krishna River Basin, India

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.b7743.019320 ◽

2020 ◽

Vol 9 (3) ◽

pp. 613-618

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Suspended Sediment ◽

River Basin ◽

Sediment Yield ◽

Sediment Load ◽

Water Discharge ◽

Tectonic Activity ◽

Precipitation Seasonality ◽

Artificial Neural

The measurement of sediment yield is essential for getting the information of the mass balance between sea and land. It is difficult to directly measure the suspended sediment because it takes more time and money. One of the most common pollutants in the aquatic environment is suspended sediments. The sediment loads in rivers are controlled by variables like canal slope, basin volume, precipitation seasonality and tectonic activity. Water discharge and water level are the major controlling factor for estimate the sediment load in the Krishna River. Artificial neural network (ANN) is used for sediment yield modeling in the Krishna River basin, India. The comparative results show that the ANN is the easiest model for the suspended sediment yield estimates and provides a satisfactory prediction for very high, medium and low values. It is also noted that the Multiple Linear Regressions (MLR) model predicted an many number of negative sediment outputs at lower values. This is entirely unreality because the suspended sediment result can not be negative in nature. The ANN is provided better results than traditional models. The proposed ANN model will be helpful where the sediment measures are not available.

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Comparison of Sediment Rating Curves Developed on Load and on Concentration

Hydrology Research ◽

10.2166/nh.1997.0011 ◽

1997 ◽

Vol 28 (3) ◽

pp. 189-200 ◽

Cited By ~ 18

Author(s):

Margareta B. Jansson

Keyword(s):

Linear Regression ◽

Bias Correction ◽

Water Discharge ◽

Regression Equations ◽

Rating Curve ◽

Weighted Mean ◽

Data Set ◽

Sediment Rating Curve ◽

Rating Curves ◽

Linear Regressions

A sediment rating curve developed as a linear regression on logged values which is back-transformed must be corrected for the bias introduced by the log transformation. This article shows that the variances are identical for linear regressions based on values of logged load and logged concentration from the same data set. This means that the bias correction factoss 101.1513σ2 for the back-transformed regressions are equivalent. Therefore a back-tranoformed log regression based on loads corrected for bias gives identical sedimett discharges to a back-transformed log regression on concentrations corrected for bias. Regression equations from gauging stations in two neighbouring basins in Costa Rica confirm this conclusion. Mean loads for individual discharge classes were plotted on diagrams in log scales to find the points where the sedimett rating curve changes direction. When sediment rating curves were developed on logged mean concentrations, water discharge weighted mean concentrations had to be determined in order to produce equations comparable to those on logged mean loads. Consequently, discharge weighted mean concentrations must be used in a plot to determine the change in direction of a sedimett rating curve and to check the goodnsss of fit of a regression developed by any model employing concentration as the dependent variabe.

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METHOD OF SPATIAL PREDICTION THE DATES OF STARTING AND PASSING THE MAXIMUM WATER DISCHARGE OF SPRING FLOODS

Hydrology, hydrochemistry and hydroecology ◽

10.17721/2306-5680.2019.4.1 ◽

2019 ◽

pp. 8-22

Author(s):

A.A. Dokus ◽

Zh.R. Shakirzanova ◽

N.N. Shvets

Keyword(s):

Water Discharge ◽

Geographical Location ◽

Weather Conditions ◽

Spatial Prediction ◽

Spring Flood ◽

Prognostic Assessment ◽

Maximum Water ◽

Meteorological Observations

Introduction. The problem of long-term and prognostic assessment of the terms of spring floods on rivers is relevant in hydrological investigations. Due to climate warming, the flood tides shifted to early dates or the beginning of the calendar year. The purpose is to analyze the long-term passage of spring floods and to carry out their spatial mapping forecasting on the Dnieper (within Ukraine). Methods. Investigation of the dynamics of long-term changes in the timing of spring floods and the use of the forecast method based on the meteorological forecast of ten-day air temperature in the winter-spring season in the Dnieper basin. Results. The method of forecasting the dates of starting and passing the maximum water discharge (levels) is based on the regional equations of the forecast scheme and allows to make a preliminary estimation of flood terms each year, regardless of the availability of meteorological observations. Assessment of the forecasting methodology allows to recommend it as a consultation, and the earliness of forecast varies depending on the geographical location of the catchments and the current weather conditions of a particular spring. Conclusion. The methodology was implemented on the example of spring floods 2017-2018. The overall forecasts were satisfactory, but the quality of the forecasts was affected by the non-simultaneous terms of the spring flood formation in the Dnieper basin. The prognostic probabilities of the dates of spring flood allow characterizing the frequency of their occurrence over many years. On the example of the 2017-2018 spring flood, the rivers of the Dnieper basin found that, in a changing climate, floods can be shifted to earlier and later ones.

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Bedload transport in two creeks at the ice-free area of the Baranowski Glacier, King George Island, West Antarctica

Polish Polar Research ◽

10.1515/popore-2017-0003 ◽

2017 ◽

Vol 38 (1) ◽

pp. 21-39 ◽

Cited By ~ 11

Author(s):

Joanna Sziło ◽

Robert J. Bialik

Keyword(s):

Water Discharge ◽

Weather Conditions ◽

Arithmetic Mean ◽

Bedload Transport ◽

Water Levels ◽

West Antarctica ◽

Weighted Arithmetic ◽

Granulometric Analysis ◽

First Time

Abstract This paper presents a unique case study and methodology for measurements of the bedload transport in the two, newly created troughs at the forefield of the Baranowski Glacier: Fosa and Siodło creeks. The weather conditions and the granulometric analysis are presented and discussed briefly. Rating curves for the Fosa and Siodło creeks are presented for the first time for this region. Changes of the bedload transport as well as water discharge and water velocity at both creeks are investigated. The hysteresis for the relationships between rate of bedload transport and water discharges were identified showing that for both creeks for the higher water levels a figure of eight loop may be easily recognized. Moreover, a new method for the calculation of bedload transport rate, based on the weighted arithmetic mean instead of the arithmetic mean, is proposed.

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1-D versus 2-D Entropy Velocity Law for Water Discharge Assessment in a Rough Ditch

Entropy ◽

10.3390/e20090638 ◽

2018 ◽

Vol 20 (9) ◽

pp. 638 ◽

Cited By ~ 1

Author(s):

Michele Greco ◽

Giovanni Martino

Keyword(s):

Water Resource Management ◽

Water Discharge ◽

Mathematical Formulation ◽

Structure Design ◽

Rating Curve ◽

One Dimensional ◽

Operational Application ◽

Regular Roughness ◽

The One ◽

Discharge Estimation

Water discharge assessment in open channel flow is one of the most crucial issues for hydraulic engineers in the fields of water resource management, river dynamics, ecohydraulics, irrigation, and hydraulic structure design, among others. Recent studies state that the entropy velocity law allows expeditive methodology for discharge estimation and rating curve development due to the simple mathematical formulation and implementation. Many works have been developed based on the one-dimensional (1-D) formulation of the entropy velocity profile, supporting measurements in the lab and the field for rating curve assessment, but in recent years, the two-dimensional (2-D) formulation was proposed and applied in studies of regular ditch flow, showing good performance. The present work deals with a comparison between the 1-D and 2-D approaches in order to give a general framework of threats and opportunities related to the robust operational application of such laws. The analysis was carried out on a laboratory ditch with regular roughness, under controlled boundary conditions, and in different stages, generating an exhaustive dashboard for better appraisal of the approaches.

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Comparative analysis of rating curve and ADP estimates of instantaneous water discharge through estuaries in two contrasting Brazilian rivers

Hydrological Processes ◽

10.1002/hyp.7972 ◽

2011 ◽

Vol 25 (14) ◽

pp. 2188-2201 ◽

Cited By ~ 9

Author(s):

Francisco José da Silva Dias ◽

Luiz Drude Lacerda ◽

Rozane Valente Marins ◽

Francisco Carlos Fernandes de Paula

Keyword(s):

Comparative Analysis ◽

Water Discharge ◽

Rating Curve

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Streamflow and weather conditions of seven small coastal watersheds, British Columbia, Canada, 2013–2019

10.5194/essd-2021-423 ◽

2021 ◽

Author(s):

Maartje C. Korver ◽

Emily Haughton ◽

William C. Floyd ◽

Ian J. W. Giesbrecht

Keyword(s):

Spatial Data ◽

Weather Conditions ◽

Scientific Basis ◽

Weather Data ◽

Storm Events ◽

Small Watersheds ◽

Coastal Watersheds ◽

Complete Dataset ◽

Data Gap

Abstract. Hydrometeorological observations of small watersheds of the northeast Pacific coastal temperate rainforest (NPCTR) of North America are important to understand land to ocean ecological connections and to provide the scientific basis for regional environmental management decisions. The Hakai Institute operates a densely networked and long-term hydrometeorological monitoring observatory, that fills a spatial data gap in the remote and sparsely gauged outer coast of the NPCTR. Here we present the first five water years (October 2013–October 2019) of hourly streamflow and weather data from seven small (< 13 km2), coastal watersheds. Average yearly rainfall was 3267 mm, resulting in 2317 mm of runoff and 0.1087 km3 of freshwater exports from all seven watersheds per year. However, rainfall and runoff were highly variable depending on location and elevation. The seven watersheds have rainfall-dominated (pluvial) streamflow regimes, streamflow responses are rapid and most water exports are driven by high-intensity fall and winter storm events. Measuring rainfall and streamflow in remote and topographically complex rainforest environments is challenging, hence advanced and novel automated measurement methods were used. These methods, specifically for stream flow measurement allowed us to quantify uncertainty and identify key sources of error, which varied by gauging location. Links to the complete dataset, watershed delineations with metrics, and calculation scripts can be found in Sect. 6 and 7.

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