Nonparametric Rank Regression for Analyzing Water Quality Concentration Data with Multiple Detection Limits

2011 ◽  
Vol 45 (4) ◽  
pp. 1481-1489 ◽  
Author(s):  
Liya Fu ◽  
You-Gan Wang
Keyword(s):  
Water Quality ◽  
Detection Limits ◽  
Concentration Data ◽  
Rank Regression ◽  
Multiple Detection

scholarly journals Amines in boreal forest air at SMEAR II station in Finland

2018 ◽  
Vol 18 (9) ◽  
pp. 6367-6380 ◽  
Author(s):  
Marja Hemmilä ◽  
Heidi Hellén ◽  
Aki Virkkula ◽  
Ulla Makkonen ◽  
Arnaud P. Praplan ◽  
...  
Keyword(s):  
Boreal Forest ◽  
Gas Phase ◽  
Particle Number ◽  
Detection Limits ◽  
Ambient Air ◽  
Monthly Means ◽  
Ammonium Ions ◽  
Quadrupole Mass ◽  
Concentration Data ◽  
Diurnal Variability

Abstract. We measured amines in boreal forest air in Finland both in gas and particle phases with 1 h time resolution using an online ion chromatograph (instrument for Measuring AeRosols and Gases in Ambient Air – MARGA) connected to an electrospray ionization quadrupole mass spectrometer (MS). The developed MARGA-MS method was able to separate and detect seven different amines: monomethylamine (MMA), dimethylamine (DMA), trimethylamine (TMA), ethylamine (EA), diethylamine (DEA), propylamine (PA), and butylamine (BA). The detection limits of the method for amines were low (0.2–3.1 ng m−3), the accuracy of IC-MS analysis was 11–37 %, and the precision 10–15 %. The proper measurements in the boreal forest covered about 8 weeks between March and December 2015. The amines were found to be an inhomogeneous group of compounds, showing different seasonal and diurnal variability. Total MMA (MMA(tot)) peaked together with the sum of ammonia and ammonium ions already in March. In March, monthly means for MMA were < 2.4 and 6.8 ± 9.1 ng m−3 in gas and aerosol phases, respectively, and for NH3 and NH4+ these were 52 ± 16 and 425 ± 371 ng m−3, respectively. Monthly medians in March for MMA(tot), NH3, and NH4+ were < 2.4, 19 and 90 ng m−3, respectively. DMA(tot) and TMA(tot) had summer maxima indicating biogenic sources. We observed diurnal variation for DMA(tot) but not for TMA(tot). The highest concentrations of these compounds were measured in July. Then, monthly means for DMA were < 3.1 and 8.4 ± 3.1 ng m−3 in gas and aerosol phases, respectively, and for TMA these were 0.4 ± 0.1 and 1.8 ± 0.5 ng m−3. Monthly medians in July for DMA were below the detection limit (DL) and 4.9 ng m−3 in gas and aerosol phases, respectively, and for TMA these were 0.4 and 1.4 ng m−3. When relative humidity of air was > 90 %, gas-phase DMA correlated well with 1.1–2 nm particle number concentration (R2=0.63) suggesting that it participates in atmospheric clustering. EA concentrations were low all the time. Its July means were < 0.36 and 0.4 ± 0.4 ng m−3 in gas and aerosol phases, respectively, but individual concentration data correlated well with monoterpene concentrations in July. Monthly means of PA and BA were below detection limits at all times.

Large discrepancies on nitrate loading estimates from sparse measurements by SWAT and statistical models at catchment scale

2021 ◽  
Author(s):  
Kang Liang ◽  
Yefang Jiang ◽  
Fan-Rui Meng
Keyword(s):  
Water Quality ◽  
Agricultural Watershed ◽  
Data Availability ◽  
Accurate Estimation ◽  
Observation Data ◽  
Load Estimation ◽  
Concentration Data ◽  
Regression Methods ◽  
Nitrate Load ◽  
Sparse Measurements

&lt;p&gt;Nitrogen (N) is one of the major pollutants to aquatic ecosystems. One of the key steps for efficient N reduction management at watershed scale is accurate quantification of N load. High frequency monitoring of stream water N concentration has not been common, and this has largely been the limiting factor for accurate estimation of N loading worldwide. N loads have often been estimated from sparse measurements. The objective of this study was to investigate the performance of the physical-based SWAT (Soil and Water Assessment Tool) model and three commonly used regression methods, namely LI (linear interpolation), WRTDS (Weighted Regression on Time, Discharge, and Season), and the LOADEST (LOAD ESTimator) on estimating nitrate load from sparse measurements through a case study in an agricultural watershed in eastern Canada. The range of daily nitrate load of SWAT and LOADEST was 0.05-1.29 and 0.14 - 1.35 t day&lt;sup&gt;-1&lt;/sup&gt;, compared with 0.13 - 13.08 t day&lt;sup&gt;-1&amp;#160; &lt;/sup&gt;and 0.15 - 16.75 t day&lt;sup&gt;-1 &lt;/sup&gt;for LI and WRTDS, respectively. Mean daily nitrate load estimated by the four methods followed the order: WRTDS &gt; LI &gt; LOADEST &gt; SWAT. The large discrepancies were mainly occurred during the non-growing season during which there was observation data available. As regression methods use concentration data from dry seasons to estimate the concentrations of wet seasons, there is a strong likelihood of overestimation of nitrate load for wet seasons. The results of this study shed new light on nitrate load estimation under conditions of different data availability. Under situations of limited water quality measurement, policy makers or researchers are likely to benefit from using hydrological models such as SWAT for constituent load estimation. However, the selection of the most appropriate method for load estimation should be seen as a dynamic process, and case by case evaluation is required especially when only sparsely measured data is available. As agri-environmental water quality issues become more pressing, it is critical that data collection strategies that encompass seasonal variation in streamflow and nitrate concentration be employed in regions like Atlantic Canada in the future.&lt;/p&gt;

scholarly journals Operational Forest Stream Crossings Effects on Water Quality in the Virginia Piedmont

2011 ◽  
Vol 35 (3) ◽  
pp. 123-130 ◽  
Author(s):  
Wallace M. Aust ◽  
Mathew B. Carroll ◽  
M. Chad Bolding ◽  
C. Andrew Dolloff
Keyword(s):  
Water Quality ◽  
Best Management Practices ◽  
Management Practices ◽  
Quality Parameters ◽  
Site Factors ◽  
Concentration Data ◽  
Individual Site ◽  
Forest Stream ◽  
Randomized Design ◽  
Portable Bridges

Abstract Water quality indices were examined for paired upstream and downstream samples for 23 operational stream crossings and approaches during four periods. Stream crossings were (1) portable bridges (BRIDGE), (2) culverts backfilled with poles (POLE), (3) culverts with earth backfill (CULVERT), and (4) reinforced fords (FORD). The four operational periods were (1) prior to crossing installation (INITIAL), (2) after installation (INSTALL), (3) during harvest (HARVEST), and (4) after road closure (CLOSURE). Differences (Δ) in water samples collected above and below stream crossings were analyzed for Δtotal dissolved solids (ΔTDS), ΔpH, Δconductivity, Δtemperature, and Δsediment concentration. Data were analyzed as a completely randomized design with unequal replication (four to seven replications). Significant differences were observed (α < 0.10) among crossing types for Δtemperature, ΔTDS, ΔpH, and Δconductivity. Overall, the least disruptive crossing type for water quality was BRIDGE, but road standards and approach characteristics were also important. Modeled estimates of erosion demonstrated that CULVERT approaches had higher potential erosion than other crossings. Water quality parameters were most negatively affected during INSTALL and HARVEST and were apparently improving during CLOSURE. Permanent crossings were associated with significantly greater temperatures than temporary crossings, likely because of increased width of streamside management zone removal. Water quality effects could be minimized by installing appropriate best management practices during all harvest periods rather than waiting until CLOSURE. Findings should be used cautiously because individual site factors such as climate, site, soil, and operational variability will alter effects.

Improved dynamic simulation technique for hydrodynamics and water quality of river-connected lakes

2020 ◽  
Vol 20 (8) ◽  
pp. 3752-3767
Author(s):  
Bojun Liu ◽  
Jun Xia ◽  
Libin Yang ◽  
Changyong Cui ◽  
Linwei Wang ◽  
...  
Keyword(s):  
Water Quality ◽  
Latin Hypercube Sampling ◽  
Resistance Coefficient ◽  
Water Quality Model ◽  
Roughness Coefficient ◽  
Model Parameters ◽  
State Variables ◽  
Quality Model ◽  
Rank Regression ◽  
Hongze Lake

Abstract In this study, a two-dimensional hydrodynamic water-quality model is proposed for river-connected lakes in an effort to improve calibration accuracy and reduce computational burden. To achieve this, the sensitivity of parameters involved in the hydrodynamic model is analyzed using stepwise rank regression and Latin hypercube sampling (LHS), and the roughness coefficient, wind drag coefficient and wind resistance coefficient are identified as the most important parameters affecting the hydrodynamics of the Hongze Lake. Then, the ensemble Kalman filter (EnKF) is used to assimilate observations to the proposed hydrodynamic and water quality model. It is found that assimilation of both state variables and model parameters results in a significant improvement of the simulation of the water level, flow velocity and pollutant concentration in the Hongze Lake.

scholarly journals Tracer test modeling for local scale residence time distribution characterization in an artificial recharge site

2016 ◽  
Author(s):  
Cristina Valhondo ◽  
Lurdes Martínez-Landa ◽  
Jesús Carrera ◽  
Juan J. Hidalgo ◽  
Isabel Tubau ◽  
...  
Keyword(s):  
Water Quality ◽  
Artificial Recharge ◽  
Groundwater Resources ◽  
Homogeneous Model ◽  
Tracer Test ◽  
Flow Conditions ◽  
Transport Parameters ◽  
Complex Flow ◽  
Concentration Data ◽  
Heterogeneous Model

Abstract. Artificial recharge of aquifers is a technique for improving water quality and increasing groundwater resources. Understanding the fate of a potential contaminant requires knowledge of the residence times distribution (RTD) of the water beneath the artificial recharge infrastructure. A simple way to obtain the RTDs is to perform a tracer test. We performed a pulse injection tracer test in an artificial recharge system through an infiltration basin to obtain the breakthrough curves, which yield directly the RTDs. These were very broad and we used a numerical model to interpret them, and to extend the characterization to other flow conditions. The model comprised nine layers at the site scaled to emulate the layering of aquifer deposits. Two types of hypotheses were considered: homogeneous (all flow and transport parameters identical for every layer) and heterogeneous (diverse parameters for each layer). The parameters were calibrated against the head and concentration data in both model types, which were validated quite satisfactory against 1,1,2-Trichloroethane and electrical conductivity data collected over a long period of time with highly varying flow conditions. We found that the broad RTDs were caused by both the complex flow structure generated under the basin (the homogeneous model produced broad RTDs) and the heterogeneity of the media (the heterogeneous model yielded much better fits). We conclude that acknowledging heterogeneity is required to properly assess mixing and broad RTDs, which are required to explain the water quality improvement of artificial recharge basins.

scholarly journals Deterministic and Stochastic Principles to Convert Discrete Water Quality Data into Continuous Time Series

2021 ◽  
Author(s):  
Danieli Mara Ferreira ◽  
Marcelo Coelho ◽  
Cristovão Vicente Scapulatempo Fernandes ◽  
Eloy Kaviski ◽  
Daniel Henrique Marco Detzel
Keyword(s):  
Water Quality ◽  
Water Resources ◽  
Statistical Characteristics ◽  
Quality Data ◽  
Model Description ◽  
Water Resources Planning ◽  
Concentration Data ◽  
Water Quality Data ◽  
Planning And Management ◽  
Resources Planning

Abstract Limited water quality data is often responsible for incorrect model description and misleading interpretation in water resources planning and management scenarios. This study compares two hybrid strategies to convert discrete concentration data into continuous daily values for one year in different river sections. Model A is based on an autoregressive process, accounting for serial correlation, water quality historical characteristics (mean and standard deviation) and random variability; the second approach (model B) is a regression model, based on the relationship between monitoring flow and concentrations, plus an error term. The generated series (here referred to as synthetic series) are propagated in time and space by a full deterministic model (SihQual), that solves the Saint-Venant and advection-dispersion-reaction equations. Results reveal that both approaches are appropriate to reproduce the variability of biochemical oxygen demand and organic nitrogen concentrations, leading to the conclusion that the combination of deterministic/empirical and stochastic components are compatible. A second outcome arises from the comparison of results in different time scales, supporting the need for further assessment of statistical characteristics of water quality data - which relies on monitoring plans. Nonetheless, the proposed methods are suitable to estimate multiple scenarios of interest in water resources planning and management.

scholarly journals PENGARUH EKOENZIM TERHADAP KUALITAS AIR DALAM PEMBESARAN IKAN LELE (Clarias gariepinus)

2018 ◽  
Vol 7 (4) ◽  
pp. 307-314
Author(s):  
Arnita Ayu Kusumawati ◽  
Djoko Suprapto ◽  
Haeruddin Haeruddin
Keyword(s):  
Water Quality ◽  
Data Analysis ◽  
Descriptive Analysis ◽  
Clarias Gariepinus ◽  
Ammonia Concentration ◽  
Concentration Data ◽  
Randomized Design ◽  
Poor Water Quality ◽  
Temperature And Growth ◽  
One Way Anova

Kualitas air merupakan salah satu faktor penting dalam budidaya, walaupun ikan lele mampu bertahan hidup dalam kondisi kualitas air yang buruk namun keadaan itu akan berpengaruh pada pertumbuhannya. Pada penelitian ini bertujuan untuk mengetahui pengaruh ekoenzim terhadap kualitas air pada pembesaran ikan lele. Penelitian dilakukan pada bulan April - Mei 2018 di Laboratorium Pengelolaan Sumberdaya Ikan dan Lingkungan, Fakultas Perikanan dan Ilmu Kelautan, Universitas Diponegoro,Semarang. Metode yang digunakan pada penelitian ini adalah metode eksperimen di laboratorium dengan menggunakan desain penelitian yaitu rancangan acak lengkap (RAL). Penelitian ini dilakukan dengan menggunakan 4 perlakuan yaitu kontrol, 0,1 ml/L, 0,5 ml/L, dan 1 ml/L dengan 3 pengulangan. Pada penelitian ini menggunakan analisis data one way Anova dengan menggunakan data konsentrasi amoniak dan nitrit sedangkan konsentrasi DO, pH, temperature , dan Pertubuhan menggunakan analisis deskriptif. Hasil analisis data yang telah dilakukan menunjukan bahwa tidak ada perbedaan rata-rata hasil konsentrasi amoniak dan nitrit dengan konsentrasi ekoenzim yang berbeda. Jadi pemberian ekoenzim di media pemeliharaan ikan lele menunjukan hasil yang baik untuk proses budidaya namun masih kurang baik untuk pertumbuhan ikan lele tersebut, karena didapatkan hasil pertumbuhan ikan lele cenderung lambat. Water quality is an important factor in cultivation, although catfish are able to survive under poor water quality conditions but the situation will affect its growth. In this study aims to determine the effect of eczymes on water quality in the enlargement of catfish. The study was conducted in April - May 2018 at the Fish and Environmental Resource Management Laboratory, Faculty of Fisheries and Marine Sciences, Diponegoro University, Semarang. The method used in this study is an experimental method in the laboratory using a research design that is a completely randomized design (CRD). This research was conducted by using 4 treatments, namely control, 0.1 ml / L, 0.5 ml / L, and 1 ml / L with 3 repetitions. In this study used one way Anova data analysis using ammonia concentration data and nitrite concentration while DO, pH, temperature, and Growth using descriptive analysis. The results of the data analysis that has been carried out show that there is no difference in the average yield of the concentration of ammonia and nitrite with different eczene concentrations. So ekoenzim peberian in catfish breeding media showed good results for the cultivation process but still not good for the growth of catfish, because the results obtained growth of catfish tend not slow.

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