Refinement of predictive reaeration equations for a typical Indian river

Dissolved oxygen mass balance has been computed for different reaches of River Kali in western Uttar Pradesh (India) to obtain the reaeration coefficient (K₂). A total of 270 field data sets have been collected during the period from March 1999 to February 2000. Eleven most popular predictive equations, used for reaeration prediction and utilizing mean stream velocity, bed slope, flow depth, friction velocity and Froude number, have been tested for their applicability in the River Kali using data generated during field survey. The K₂ values computed from these predictive equations have been compared with the K₂ values observed from dissolved oxygen balance measurements in the field. The performance of predictive equations have been evaluated using error estimation, namely standard error (SE), normal mean error (NME), mean multiplicative error (MME) and correlation statistics. The equations developed by Smoot and by Cadwallader and McDonnell showed comparatively better results. Moreover, a refined predictive equation has been developed using a least‐squares algorithm for the River Kali that minimizes error estimates and improves correlation between observed and computed reaeration coefficients. Copyright © 2001 John Wiley & Sons, Ltd.     

A supplementary approach for estimating reaeration rate coefficients

Different commonly used predictive equations for the reaeration rate coefficient (K₂) have been evaluated using 231 data sets obtained from the literature and 576 data sets measured at different reaches of the River Kali in western Uttar Pradesh, India. The data sets include stream/channel velocity, bed slope, flow depth, cross‐sectional area and reaeration rate coefficient (K₂), obtained from the literature and generated during the field survey of River Kali, and were used to test the applicability of the predictive equations. The K₂ values computed from the predictive equations have been compared with the corresponding K₂ values measured in streams/channels. The performance of the predictive equations has been evaluated using different error estimation, namely standard error (SE), normal mean error (NME), mean multiplicative error (MME) and coefficient of determination (r²). The results show that the reaeration rate equation developed by Parkhurst and Pomeroy yielded the best agreement, with the values of SE, NME, MME and r² as 33·387, 4·62, 3·58 and 0·95, respectively, for literature data sets (case 1) and 37·567, 3·57, 2·6 and 0·95, respectively, for all the data sets (literature data sets and River Kali data sets) (case 2). Further, to minimize error estimates and improve correlation between measured and computed reaeration rate coefficients, supplementary predictive equations have been developed based on Froude number criteria and a least‐squares algorithm. The supplementary predictive equations have been verified using different error estimates and by comparing measured and computed reaeration rate coefficients for data sets not used in the development of the equations. Copyright © 2003 John Wiley & Sons, Ltd.     

Effect of land‐use changes on nonpoint source pollution in the Xizhi River watershed,Guangdong, China

The Annualized Agricultural Non‐point Source (AnnAGNPS) pollution model has been widely used to assess and predict runoff, soil erosion, sediment and nutrient loading with a geographic information system. This article presents a case study of the effect of land‐use changes on nonpoint source (NPS) pollution using the AnnAGNPS model in the Xizhi River watershed, eastern Pearl River Delta of Guangdong province, China. The land‐use changes in the Xizhi River watershed between 1998 and 2003 were examined using the multitemporal remote sensing data. The runoff, soil erosion, sediment transport and nutrient loading 1998 and 2003 were assessed using AnnAGNPS. The effects of land‐use changes on NPS were studied by comparing the simulation results of each year. Our results showed that (i) the NPS loadings increased when forest and grass land converted into paddy, orchard and farmland land, and population size and gross domestic product size as well as the usage amounts of fertilizer and pesticide in the entire watershed were firmly correlated with the NPS loadings; (ii) the land‐use change during fast urbanization in particular when other land types were converted into the development land and buildup land led to increasing of NPS pollution; and (iii) urban land expansion showed more important effects on total organic carbon (TOC) loading compared with nitrogen and phosphorus loadings. Copyright © 2012 John Wiley & Sons, Ltd.     

Pollution Source Investigation and Water Quality Management in the Carp Lake Watershed,Taiwan

In this study, a full survey of pollutant sources and water quality was conducted, followed by the application of a water quality model (Water Quality Analysis Simulation Program, WASP) to establish strategies of water quality control in Carp Lake, Taiwan. Results of the field investigation show that both point and non‐point source (NPS) pollutants were responsible for the poor water quality. The contributions of biochemical oxygen demand (BOD) from point source and NPS pollution were 45.9 and 55.1%, respectively. About 80% of total phosphorus (TP) were contributed by NPS. Additionally, point source and NPS pollution discharged 55.5 and 44.5% of NH₃–N load, respectively. The Carlson's Trophic State Index ranged from 61.9 to 69.2 showing serious eutrophic problems in Carp Lake. The calculated BOD, NH₃–N, and TP carrying capacity were approximately 2.8, 0.42, and 0.15 kg per day, respectively. However, the current pollutant loadings are approximately 3.0–5.5 times the calculated carrying capacity. With the help of the calibrated WASP model, remedial strategies for the lake water from short‐term to long‐term were developed. The completion of the small local sewer system to remove 80% of the point source pollution can serve as a short‐term goal while 40–60% of NPS removal by natural treatment systems may serve as a mid‐term goal. Furthermore, 80% of both source point and NPS pollution removal can be considered as a long‐term strategy. Results of heavy metal analysis show that the enriched sediment would be safe for agricultural applications.     

PUBLICATIONS OF THE INTERNATIONAL ASSOCIATION OF HYDROLOGICAL SCIENCES

Abstract

Most commonly used biochemical oxygen demand (BOD) and dissolved oxygen (DO) models have been tested for their applicability in the River Kali, which is one of the most polluted rivers in India. A total of 732 field data sets were generated during field survey from March 1999 to February 2000. The modelling of BOD and DO in the River Kali involves derivation and solution of the governing equations that describe concentration change with time and space brought on by advective, decay, settling and loading functions. However, due to continuous discharges (e.g. from wastewater treatment plants) and steady-state flow conditions in the River Kali, the dispersion effects are found to be insignificant. In the analysis, the model parameters used in BOD-DO models were optimized using the Newton-Raphson technique and the performance of different models was evaluated using correlation statistics (r ²) and error estimation, viz. standard error (SE) and mean multiplicative error (MME). The results indicate that the BOD-DO models developed after Camp (1963) yielded the best agreement with the observed values as compared with several other approaches.     

Modeling of non‐point source nitrogen pollution from 1979 to 2008 in Jiaodong Peninsula,China

Efforts to reduce land‐based non‐point source (NPS) pollutions from watersheds to coastal waters are ongoing all around the world. In this study, annual yield of NPS nitrogen (NPS‐N) pollution in Jiaodong Peninsula, China from 1979 to 2008 was estimated. The results showed that: from 1979 to 2008, NPS‐N yields exhibited significant inter‐annual variations and an increasing trend on decadal scale. High NPS‐N yield was mainly found in east and south parts, as well as the urbanized coastal regions in Jiaodong Peninsula. Among the 32 river basins, the three largest basins yielded more than 41.16% of the NPS‐N. However, some small coastal watersheds along the South Yellow Sea and Jiaozhou Bay had higher per unit area yield. Most of the small watersheds characterized by seasonal runoff had coastal waters pertain to mild and moderate pollution levels. The ratio of watershed area to shoreline length and the up‐stream land use had significant impacts on NPS‐N flux through the shoreline. Among the four adjacent coastal areas of Jiaodong Peninsula, Jiaozhou Bay was the most noteworthy one not only because of high levels of land‐based NPS‐N pollution but also because of its nearly enclosed structure. The combination between integrated coastal zone management and integrated river basin management, land use planning and landscape designing in Jiaodong Peninsula is recommended. Copyright © 2013 John Wiley & Sons, Ltd.     

A GIS‐based variable source area hydrology model

Effective control of nonpoint source pollution from contaminants transported by runoff requires information about the source areas of surface runoff. Variable source hydrology is widely recognized by hydrologists, yet few methods exist for identifying the saturated areas that generate most runoff in humid regions. The Soil Moisture Routing model is a daily water balance model that simulates the hydrology for watersheds with shallow sloping soils. The model combines elevation, soil, and land use data within the geographic information system GRASS, and predicts the spatial distribution of soil moisture, evapotranspiration, saturation‐excess overland flow (i.e., surface runoff), and interflow throughout a watershed. The model was applied to a 170 hectare watershed in the Catskills region of New York State and observed stream flow hydrographs and soil moisture measurements were compared to model predictions. Stream flow prediction during non‐winter periods generally agreed with measured flow resulting in an average r² of 0·73, a standard error of 0·01 m³/s, and an average Nash‐Sutcliffe efficiency R² of 0·62. Soil moisture predictions showed trends similar to observations with errors on the order of the standard error of measurements. The model results were most accurate for non‐winter conditions. The model is currently used for making management decisions for reducing non‐point source pollution from manure spread fields in the Catskill watersheds which supply New York City's drinking water. Copyright © 1999 John Wiley & Sons, Ltd.     

Non‐point source pollution modelling using Soil and Water Assessment Tool and its parameter sensitivity analysis in Xin'anjiang catchment,China

Non‐point source pollution is a key issue in integrated river basin management around the world and has resulted in water contamination, aquatic ecology deterioration and eutrophication. Xin'anjiang catchment is the key drinking water source area for Hangzhou City, China. A promising model (Soil and Water Assessment Tool) was applied to assess the non‐point source pollution and its effect on drinking water. Sensitivity analysis of model parameters was carried out using the Sequential Uncertainty Domain Parameter Fitting 2 sensitivity technique. Water discharge, sediment, total nitrogen and total phosphorus load processes from 2000 to 2010 were simulated, and the spatial distributions of non‐point source pollutants were evaluated at the catchment and administrative country levels. The results show that the hydrological parameters of the Soil and Water Assessment Tool were dominantly sensitive for non‐point source pollution simulation, including CN2, RCHRG_DP, ALPHA_BF, SOL_AWC, ESCO and SOL_K and the characteristic parameters of sub‐basins (viz. HRU_SLP and SLSUBBSN). Also, water quality parameters (viz. CH_EROD, NPERCO, RSDCO and PPERCO, PHOSKD, etc.) have a significant effect on nutrients. The model performance was very satisfactory, especially for runoff, sediment and total phosphorus simulation. The non‐point source pollutant load increased from 2001 to 2010 in the whole catchment. Total nitrogen load increased from 3428 tons (0.59 ton km^?2) to 7315 tons (1.25 ton km^?2), and total phosphorus load increased from 299 tons (0.05 ton km^?2) to 867 tons (0.15 ton km^?2). The contribution of rice land was the largest, accounting for nearly 95%, followed by tea garden (3.56%), winter wheat (1.37%), forest (0.07%) and grassland (0.02%). Moreover, She County and Xiuning County contributed more than half of the non‐point source pollutants. This study was expected to provide a method and reference for non‐point source pollution quantification and to support water quality management implementation in China. Copyright © 2012 John Wiley & Sons, Ltd.     

Analytical and experimental study on dissolved pollutant wash‐off over impervious surfaces

Non‐point source pollution in the impervious surface of city, which including dissolved and particulate pollutants, is a significant source of water pollution. Simple first‐order decay models can generally simulate the cumulative wash‐off process of the particulate pollutants. There is inadequate knowledge as to whether or not they are suitable for dissolved pollutants. This study presents a mathematical wash‐off model for dissolved pollutants, which combines analytical equations for overland flows and the exponential equation for the pollutant wash‐off. A series of laboratory experiments have been conducted to verify this wash‐off model. It shows that the pollutant concentration and pollutant transport rate can be predicted well by the newly developed equations. It is found that the pollutant concentration monotonically decreases to zero as the accumulated pollutants are washed off, whereas the pollutant transport rate first increases to the maximum value and then decreases to zero. The maximum pollutant transport rate is found to increase with the decrease of the arrival time of the maximum value. The difference between the simplified exponential model and the amended wash‐off equation depends on the initial residual percentage (P_c), but the present equation generally provides a more accurate representation of the wash‐off process of dissolved pollutants.     

Non-point source pollution estimation in the Pingqiao River Basin,China, using a spatial hydrograph-separation approach

For efficient and targeted management, this study demonstrates a recently developed non-point source (NPS) pollution model for a year-long estimation in the Pingqiao River Basin (22.3 km²) in China. This simple but physically reasonable model estimates NPS export in terms of land use by reflecting spatial hydrological features and source runoff measurements under different land-use types. The NPS export was separately analysed by a distributed hydrological model, a spatial hydrograph-separation technique, and an empirical water quality sub-model. Simulation results suggest that 57 890 kg of total nitrogen (TN) and 1148 kg of total phosphorus (TP) were delivered. The results, validated with observed stream concentrations, show relative errors of 23.3% for TN and 47.4% for TP. Countermeasures for urban areas (5.3% of total area) were prioritized because of the high contribution rate to TN (14.1%) and TP (26.2%) which is caused by the high degree of runoff (8.5%) and pollution source.     

Application of chemical mass balance approach to determine nutrient loading

Abstract

The River Kali in western Uttar Pradesh, India is a typical water course for untreated municipal and industrial effluents. The river receives considerable amounts of waste every day from the industries and municipal area of Muzaffarnagar town. Agricultural runoff is the other major factor in pollution of the river water. The mass balance calculations conducted on the river reach indicate that nitrate and phosphate from the non-point sources constitute 32.4 and 11.2% of the total load, respectively. The resulting differential loading, if adjusted for uncharacterized non-point contribution to the load, may represent the total point sources load to the river minus any losses due to volatilization, settling, and/or degradation. Indirect monitoring using upstream/downstream sampling locations provides a viable alternative to conventional methods for measuring the changes in the concentration and/or load to the river.     

Nested‐Scale Nutrient Flux in a Mixed‐Land‐Use Urbanizing Watershed

To improve quantitative understanding of mixed‐land‐use impacts on nutrient yields, a nested‐scale experimental watershed study design (n = 5) was applied in a 303(d), clean water act impaired urbanizing watershed of the lower Missouri River Basin, USA. From 2010 to 2013, water samples (n = 858 sample days per site) were analysed for total inorganic nitrogen (TIN‐N), nitrite (NO₂–N) nitrate (NO₃–N), ammonia (NH₃–N), and total phosphorus (TP‐P). Annual, seasonal, and monthly flow‐weighted concentrations (FWCs) and nutrient yields were estimated. Mean nutrient concentrations were highest where agricultural land use comprised 58% of the drainage area (NH₃ = 0.111 mg/l; NO₂ = 0.045 mg/l; NO₃ = 0.684 mg/l, TIN = 0.840 mg/l; TP = 0.127 mg/l). Average TP‐P increased by 15% with 20% increased urban land use area. Highly variable annual precipitation was observed during the study with highest nutrient yields during 2010 (record setting wet year) and lowest nutrient yields during 2012 (extreme drought year). Annual TIN‐N and TP‐P yields exceeded 10.3 and 2.04 kg ha^?1 yr^?1 from the agricultural dominated headwaters. Mean annual NH₃–N, NO₂–N, NO₃–N, TIN‐N, and TP‐P yields were 0.742, 0.400, 4.24, 5.38, and 0.979 kg ha^?1 yr^?1, respectively near the watershed outlet. Precipitation accounted for the majority of the explained variance in nutrient yields (R² values from 0.68 to 0.85). Nutrient yields were also dependent on annual precipitation of the preceding year (R² values from 0.87 to 0.91) thus enforcing the great complexity of variable mixed‐land‐use mediated source‐sink nutrient yield relationships. Study results better inform land managers and best management practices designed to mitigate nutrient pollution issues in mixed‐land‐use freshwater ecosystems. Copyright © 2015 John Wiley & Sons, Ltd.     

Estimation of land surface evapotranspiration over complex terrain based on multi‐spectral remote sensing data

Land surface evapotranspiration (ET) plays an important role in energy and water balances. ET can significantly affect the runoff yield of a basin and the available water resources in mountainous areas. The existing models to estimate ET are typically applicable to plains, and excessive data are required to calculate the surface fluxes accurately. This study established a simple and practical model capable of depicting the surface fluxes, while using relatively less parameters. Considering the complex terrain, solar radiation was corrected by importing a series of topographic factors. The water deficit index, a measure of land surface wetness, was calculated by applying the f_c (vegetation fractional cover)‐T_rad (land surface temperature) framework in the two‐source trapezoid model for evapotranspiration model to mountainous areas after corrections of temperature based on altitude variations. The model was successfully applied to the Kaidu River Basin, a basin with few gauges located in the east Tien Shan Mountains of China. Based on the time scale extensions, ET was analyzed at different time scales from 2000 to 2013. The results demonstrated that the corrected solar radiation and water deficit index were reasonably distributed in space and that this model is applicable to ungauged catchments, such as the Kaidu River Basin.     

Quantifying and modelling urban stream temperature: a central US watershed study

Hydrologic models that rely on site specific linear and non‐linear regression water temperature (T_w) subroutines forced solely with observed air temperature (T_a) may not accurately estimate T_w in mixed‐use urbanizing watersheds where hydrogeological and land use complexity may confound common T_w regime assumptions. A nested‐scale experimental watershed study design was used to test T_w model predictions in a representative mixed‐use urbanizing watershed of the central USA. The linear regression T_w model used in the Soil and Water Assessment Tool (SWAT), a non‐linear regression T_w model, and a process‐based T_w model that accounts for watershed hydrology were evaluated. The non‐linear regression T_w model tested at a daily time step performed significantly (P < 0.01) better than the linear T_w model currently used in SWAT. Both regression T_w models overestimated T_w in lower temperature ranges (T_w < 10.0 °C) with percent bias (PBIAS) values ranging from ?28.2% (non‐linear T_w model) to ?66.1% (linear regression T_w model) and underestimated T_w in the higher temperature range (T_w > 25.0 °C) by 3.2%, and 7.2%, respectively. Conversely, the process‐based T_w model closely estimated T_w in lower temperature ranges (PBIAS = 4.5%) and only slightly underestimated T_w in the higher temperature range (PBIAS = 1.7%). Findings illustrate the benefit of integrating process‐based T_w models with hydrologic models to improve model transferability and T_w predictive confidence in urban mixed‐land use watersheds. The findings in this work are distinct geographically and in terms of mixed‐land use complexity and are therefore of immediate value to land‐use managers in similarly urbanizing watersheds globally. Copyright © 2015 John Wiley & Sons, Ltd.     

Developing an expert group method of data handling system for predicting the geometry of a stable channel with a gravel bed

Predicting the geometry of channels and alluvial rivers is of primary importance in river engineering science. Appropriately designing channels and predicting stable river cross‐sections can decrease costs and prevent the destruction of installations and agricultural land by rivers. Consequently, researchers have applied different empirical and regression methods to achieve relations for predicting stable channel and river geometry. In this study, Group Method of Data Handling ]GMDH) models are used to predict three geometric variables of stable channels, namely width (w), depth (h) and slope (s). The effect of different input parameters, such discharge (Q), median grain size (d₅₀) and the Shields parameter (τ^*) on the GMDH models is assessed with regard to predicting stable channel geometry. The results indicate that the GMDH model with mean absolute percentage error (MAPE) of 5.53%, 4.05% and 4.89% for channel width, depth and slope prediction respectively, exhibits good accuracy. Moreover, a comparison of the GMDH models with previous theoretical equations (based on regression analysis) indicates the superiority of GMDH model performance, with error reductions of one‐fifth, one‐eighth and one‐sixth compared with the regression equations for channel width, depth and slope prediction, respectively. Copyright © 2016 John Wiley & Sons, Ltd.     

Development of a soil moisture‐based distributed hydrologic model for determining hydrologically based critical source areas

A simple grid cell‐based distributed hydrologic model was developed to provide spatial information on hydrologic components for determining hydrologically based critical source areas. The model represents the critical process (soil moisture variation) to run‐off generation accounting for both local and global water balance. In this way, it simulates both infiltration excess run‐off and saturation excess run‐off. The model was tested by multisite and multivariable evaluation on the 50‐km² Little River Experimental Watershed I in Georgia, U.S. and 2 smaller nested subwatersheds. Water balance, hydrograph, and soil moisture were simulated and compared to observed data. For streamflow calibration, the daily Nash‐Sutcliffe coefficient was 0.78 at the watershed outlet and 0.56 and 0.75 at the 2 nested subwatersheds. For the validation period, the Nash‐Sutcliffe coefficients were 0.79 at the watershed outlet and 0.85 and 0.83 at the 2 subwatersheds. The per cent bias was less than 15% for all sites. For soil moisture, the model also predicted the rising and declining trends at 4 of the 5 measurement sites. The spatial distribution of surface run‐off simulated by the model was mainly controlled by local characteristics (precipitation, soil properties, and land cover) on dry days and by global watershed characteristics (relative position within the watershed and hydrologic connectivity) on wet days when saturation excess run‐off was simulated. The spatial details of run‐off generation and travel time along flow paths provided by the model are helpful for watershed managers to further identify critical source areas of non‐point source pollution and develop best management practices.     

Artificial neural network modelling of concentrations of nitrogen,phosphorus and dissolved oxygen in a non‐point source polluted river in Zhejiang Province,southeast China

A back‐propagation algorithm neural network (BPNN) was developed to synchronously simulate concentrations of total nitrogen (TN), total phosphorus (TP) and dissolved oxygen (DO) in response to agricultural non‐point source pollution (AGNPS) for any month and location in the Changle River, southeast China. Monthly river flow, water temperature, flow travel time, rainfall and upstream TN, TP and DO concentrations were selected as initial inputs of the BPNN through coupling correlation analysis and quadratic polynomial stepwise regression analysis for the outputs, i.e. downstream TN, TP and DO concentrations. The input variables and number of hidden nodes of the BPNN were then optimized using a combination of growing and pruning methods. The final structure of the BPNN was determined from simulated data based on experimental data for both the training and validation phases. The predicted values obtained using a BPNN consisting of the seven initial input variables (described above), one hidden layer with four nodes and three output variables matched well with observed values. The model indicated that decreasing upstream input concentrations during the dry season and control of NPS along the reach during average and flood seasons may be an effective way to improve Changle River water quality. If the necessary water quality and hydrology data are available, the methodology developed here can easily be applied to other case studies. The BPNN model is an easy‐to‐use modelling tool for managers to obtain rapid preliminary identification of spatiotemporal water quality variations in response to natural and artificial modifications of an agricultural drainage river. Copyright © 2009 John Wiley & Sons, Ltd.     

The design of visco‐acoustic weighted L1‐error frequency–space wavefield extrapolators

Seismic imaging is an important step for imaging the subsurface structures of the Earth. One of the attractive domains for seismic imaging is explicit frequency–space (f – x) prestack depth migration. So far, this domain focused on migrating seismic data in acoustic media, but very little work assumed visco‐acoustic media. In reality, seismic exploration data amplitudes suffer from attenuation. To tackle the problem of attenuation, new operators are required, which compensates for it. We propose the weighted L ₁ ‐error minimisation technique to design visco‐acoustic f – x wavefield extrapolators. The L ₁ ‐error wavenumber responses provide superior extrapolator designs as compared with the previously designed equiripple L ₄ ‐norm and L_∞‐norm extrapolation wavenumber responses. To verify the new compensating designs, prestack depth migration is performed on the challenging Marmousi model dataset. A reference migrated section is obtained using non‐compensating f – x extrapolators on an acoustic dataset. Then, both compensating and non‐compensating extrapolators are applied to a visco‐acoustic dataset, and both migrated sections are then compared. The final images show that the proposed weighted L ₁ ‐error method enhances the resolution and results in practically stable images.     

Control strategy for variable damping element considering near‐future excitation influence

A control strategy is proposed for variable damping elements (VDEs) used together with auxiliary stiffness elements (ASEs) that compose a time‐varying non‐linear Maxwell (NMW) element, considering near‐future excitation influence. The strategy first composes a state equation for the structural dynamics and the mechanical balance in the NMW elements. Next, it establishes a cost function for estimating future responses by the weighted quadratic norms of the state vector, the controlled force and the VDEs' damping coefficients. Then, the Euler equations for the optimum values are introduced, and also approximated by the first‐order terms under the autoregressive (AR) model of excitation information. Thus, at each moment t_k, the strategy conducts the following steps: (1) identify the obtained seismic excitation information to an AR model, and convert it to a state equation; and (2) determine VDEs' damping coefficients under the initial conditions at t_k and the final state at t_k+L, using the first‐order approximation of the Euler equations. The control effects are examined by numerical experiments. Copyright © 2000 John Wiley & Sons, Ltd.