Nonpoint Source Pollution - IngentaConnect

2 downloads 0 Views 154KB Size Report
phosphorus are two important nonpoint source pollutants. .... TN, NH3-N of the Bahe River in the year of 2009 were. 8.735×103 t ... exceed the regulatory criteria in their study area. .... identify sub-watersheds within the US portion of the Rio.
Nonpoint Source Pollution Jing Nie1, Daniel Dianchen Gang1*, Barbara C. Benson2, Mark E. Zappi3

ABSTRACT:

3

Department of Chemical Engineering, University of Louisiana

The article presents a comprehensive

at Lafayette, Lafayette, LA 70504; Tel. 337-482–6685; Fax. 337-

review of research advancing in 2011 on nonpoint source

482-6688; e-mail: [email protected]

pollution (NPS). Progresses on modeling and estimation of

In recent years, nonpoint source pollution has diminished

NPS pollution, impacts of climate and land tenure changes

water quality on a large scale in China. Zhang and Xu

on pollutants loads, and NPS pollution management are reviewed.

(2011) found that 80% of urban rivers in China were

In addition, major nonpoint pollutants are also

significantly polluted, and poor water quality was a key

summarized.

contributor to poverty in rural China. The Web of Science KEYWORDS:

watershed,

climate

change,

database indicated that the amount of papers concentrated

best

on environmental science increased dramatically in the past

management practice, stormwater, modeling, nonpoint

decade. Gao et al. (2011a) monitored nitrogen data in Luan

source pollutants, nonpoint source pollution

River Channel, Yuqiao Reservoir, and 14 major surface rivers of Tianjin, China. The results showed that dissolved

doi: 10.2175/106143012X13407275695634

inorganic nitrogen which mainly came from the Luan River water during the non-flood season was the major

Major Nonpoint Source Pollutants Nitrogen

and

Phosphorus:

Nitrogen

contaminant in the main water bodies. In the other 14

and

major rivers, the annual average content of total nitrogen

phosphorus are two important nonpoint source pollutants.

(TN) is in the range of 1.45 to 11.7 mg/L, with an average

————————— Department of Civil Engineering, University of Louisiana at

of 4.16 mg/L; the annual average concentration of NH4+-N

Lafayette, Lafayette, LA 70504; Tel. 337-482–5184; Fax. 337-

is in the range of 0.057 to 8.54 mg/L, with an average of

482-6688; e-mail: [email protected]

2.48 mg/L; and the annual average concentration of NO3- -

1*

2

Department of Environmental Science, University of Louisiana

N is in the range of 0.04 to 3.56 mg/L, with an average of

at Lafayette, Lafayette, LA 70504; Tel.337-482-5239; email:

0.908 mg/L. The annual average value of TN in the Yuqiao

[email protected]

Reservoir is 1.90 mg/L, showing a significant upward trend year by year.

1642 Water Environment Research, Volume 84, Number 10—Copyright © 2012 Water Environment Federation

From the research directed by Ding (2011), the

organic nitrogen concentrations and increased in nitrate

total NPS-N loading of Yongding River in Hebei, China

(NO3−) concentrations over the last 30 years. For these

was 5.68×104 t in 2008. The loading from agricultural land

results, a good strategy could be developed to improve

use was 4.38×104 t, and that from rural life and livestock

regional downstream NO3− pollution by reducing the NO3−

feeding was 0.90×104 t and 0.40×104 t respectively. The

exports from N-saturated upland forests.

large amount of N loading suggested that assessment of N was necessary.

In order to track nonpoint source nitrogen (N)

Xia et al. (2011) analyzed the

pollution in Baltimore, U.S., Kaushal et al. (2011) analyzed 15

N-NO3-, and δ

18

O-NO3- to investigate fate and

spatiotemporal characteristics of diffuse source N pollution

δ

in the Lean River catchment. Different water samples in

transport of nonpoint N in forest, agricultural, and

the wet season, dry season, normal season and the

urbanized

agricultural busy season were analyzed.

The data

Ecological Research site. Annual N retention was 55%,

confirmed that due to the fertilizer application, rainfall and

68%, and 82% for agricultural, suburban, and forest

runoff were the main factors causing non-point source N

watersheds, respectively. The results demonstrated that N

exported from the catchment.

source contributions changed with storm magnitude

The universal soil loss equation (USLE) and

watersheds

at

the

Baltimore

Long-Term

(atmospheric sources contributed similar to 50% at peak

simple method were used by Zhang et al. (2011a) to

storm N loads).

calculate and estimate the non-point source pollution from

system and agriculturally derived N, but N from

Nanchang University campus separately.

The results

belowground leaking sewers was less susceptible to

designated that the amount of soil erosion was 1.352× 103

denitrification. In response to climate and storms, there

t/yr, the quantity of silt entering the lake was 270 t/yr, and

were large changes in nitrate sources and other sources as a

the chemical loads of total suspended solids (TSS), total

function of runoff, and storms will be critical for managing

phosphorus (TP), and total nitrogen (TN) were 115.17 t/yr,

nonpoint N pollution.

0.27 t/yr, 1.25 t/yr for roads, and 61.36 t/yr, 0.64 t/yr, 4.55

Denitrification was removing septic

To evaluate the nitrogen loss potential at the

t/yr for grassed land separately.

basin level, Zhang and Huang (2011) developed a spatial

Chiwa et al. (2011) analyzed downstream water

multi-criteria method to generate maps that can be easily

quality in the Tatara River Basin, northern Kyushu, and

interpreted

western Japan. The results revealed that atmospherically

Geographic Information System (GIS). The results were

deposited N to N-saturated forests could be a large enough

validated based on the correlation between the nitrogen loss

non-point source of N leaving the upper watershed to

potential of sub-basin and the water quality class of river.

impact downstream water quality. In downstream water,

Li et al. (2011a) asserted contributions of N and P from

to

provide

decision

support

these sources resulted in reductions in total phosphorus and

1643 Water Environment Research, Volume 84, Number 10—Copyright © 2012 Water Environment Federation

based

on

agricultural pollution around the Lake area. The load of N

orthophosphate and TN in the raw samples decreased

and P were 1.25×104 t and 507.0 t, respectively, accounting

gradually and then increased. Ren

for 48.1% and 46.9% of total loads all over the watershed.

et

al.

(2011)

analyzed

the

spatial

The transportation capacity of N and P from agricultural

characteristics of non-point pollution, and the results

pollution around the Lake area were greater than the others

suggested that due to the complex surface condition and

sub-watersheds, which were 2.33 kg/ha and 0.11 kg/ha,

other point source pollution, the values of TSS, TN, and TP

respectively.

exceed the regulatory criteria in their study area. These

In a study on water quality of the Bahe River,

parameters varied greatly among the three land use types

Qin et al. (2011) found that with flow change, the load

(cropland, woodland and grassland). Zhang et al. (2011b)

transport rate of each pollutant and the concentrations of

reported that the land use relation approach, with simple

Chemical Oxygen Demand (COD), NO3-N, TP, and TN

structure and program, was feasible and practical to predict

increased initially and then decreased, as well as the

NPS pollution load of changed land use.

concentrations of NH3-N and NO2-N decreased initially and then increased.

Wen et al. (2011) concluded that farmland runoff

Using mean concentration method,

was the most significant source for the agricultural NPS

they concluded that the NPS pollution load of COD, TP,

pollution in the Liaoning province of China.

TN, NH3-N of the Bahe River in the year of 2009 were

composition and spatial pattern of agricultural NPS

8.735×103 t, 44.59t, 726.48t and 246.54t respectively. The

pollution, the pollution intensities were greater in the

NPS pollution load proportions of COD, TP, TN NH3-N of

Hunhe River and Liaohe River sub-basins in Central-

the Bahe River in the year of 2009 were 31.92%, 35.47%,

Western Liaoning province than in the upstream Hunhe

46.15% and 42.31%.

River and Taizihe hilly sub-basins in eastern Liaoning

To investigate the effect of the pollution on the

Due to

province.

water quality of the Weihe River, China, Li et al. (2011b)

Shan et al. (2011) developed a method based on

monitored five flood events and three normal discharge

Remote Sensing (RS) and Geographic Information System

events during the non-flood period from July to December

(GIS) to evaluate the NPS pollution.

in 2006, at the Lin-tong section.

They found that the

remote sensing images were used to analyze the variety of

proportions of the NPS pollution load to the total load for

long-term land use change. The results exposed that there

COD, TP, TN and inorganic nitrogen were more than 30%

was a strong relationship between slope, land cover,

in 2006.

The concentrations of suspended solids (SS),

distance to the stream channel and NPS pollution.

NH3-N, NO2-N, NO3-N, COD, and TP increased initially

Anthropic activities on the landscape were intensive to NPS

and then decreased, while the concentration of dissolved

pollution.

Multi-temporal

1644 Water Environment Research, Volume 84, Number 10—Copyright © 2012 Water Environment Federation

Li et al. (2011c) proposed a new method in

sources during higher flows. A method was being applied

nitrate and phosphorus measurements. This method could

which is remediating point mine water discharges to

provide a more accurate dataset, whilst minimizing the

improve water quality at lower flows, but contributions

sampling cost and simplifying the collecting procedure.

from diffuse sources would continue to elevate zinc flux at

The pattern recognition technique was first used in this

higher flows.

method to find out the variable boundary in the region of interest.

Impacts of Climate and Land Tenure Changes on

Liu et al. (2011a) developed slow-release

Pollutant Loads

materials for N & P fertilizers application. Results showed that slow releasing fertilizer application can significantly

Zhang et al. (2011c) combined a general

reduce non-point pollution emission. Mercury:

circulation model (HadCM3) with the Soil and Water

Due to the importance of mercury

Assessment Tool (SWAT) hydrological model to predict

(Hg) impacts to water quality, advances in modeling

the impacts of climate change on streamflow and non-point

watershed Hg processes are needed in diverse regions,

source pollutant loads in the Shitoukoumen reservoir

spatial scales and land cover types. A study conducted by

catchment. The annual stream flow showed a fluctuating

Schelker et al. (2011) concentrated on the role of

upward trend from 2010 to 2099, with an increase rate of

hydrological

and

1.1 m3/s per decade, and a significant upward trend in

upland/wetland transition zones to surface waters in

summer, with an increase rate of 1.32 m3/s per decade. The

Fishing Brook, New York.

The results indicated that

annual NH4+-N load into Shitoukoumen reservoir showed a

stream water total mercury (HgT) concentrations varied

significant downward trend with a decrease rate of 40.6 t

(mean = 2.25 ± 0.5 ng/L), and the two snowmelt seasons

per decade. The annual TP load disclosed an insignificant

contributed 40% (2007) and 48% (2008) of the annual load.

increasing trend, and its change rate was 3.77 t per decade.

Methyl mercury (Me-Hg) concentrations ranged up to a

Gao et al. (2011b) used the proportion of P to indicate the

high level of 0.26 ng/L and showed an inverse log

impact of climate change.

relationship with discharge. The mobilization of HgT is

bioavailable P (BAP) loads (over 90%) was observed to

primarily controlled by the saturation state of the

have been exported between June and September.

connectivity of

riparian

wetlands

The majority mass of total

catchment. Zinc: In order to assess point and diffuse

Modeling and Estimation of NPS Pollution

components of zinc pollution within the River West Allen

Assessment and Application of NPS Pollution

catchment, Gozzard et al. (2011) examined zinc levels in

Models:

The U.S. Department of Agriculture has

the river under various flow regimes. The results revealed

developed two proven models of stream and riparian processes to guide restoration design and to evaluate

that 90% of the in stream zinc load was attributed to diffuse

1645 Water Environment Research, Volume 84, Number 10—Copyright © 2012 Water Environment Federation

indicators of ecological integrity (Langendoen, 2011).

nutrition resources from 2002 to 2007 and using the export

These models have been integrated to evaluate the impact

coefficient model, the average non-point source load of

of in-stream, edge-of-field, and riparian conservation

total nitrogen above Zhangjiashan for many years was

measures on stream morphology and water quality

6.014× 103 t, and in 2003 and 2007, the amounts were

respectively.

The first one was the channel evolution

2.117× 104 t and 5.163× 103 t respectively and for other

computer model CONCEPTS and the second one was the

years, the average amount was 2.432× 103 t. The amounts

riparian ecosystem model REMM. CONCEPTS was a

of precipitation and runoff were large in wet years of 2003

robust computational model for simulating the long-term

and 2007, and the non-point source pollution loads were

evolution of incised and restored or rehabilitated stream

less because of less rainfall in normal-water years.

corridors while REMM was a computational model for

Aprígio et al. (2011) concluded that the land use

evaluating management decisions to control nonpoint

changes in the Mineirinho watershed could result in

source pollution in the riparian zone.

moderate increase in nutrient loading by using the long-

The export coefficient model (ECM) was used by

Term Hydrologic Impact Assessment (L-THIA) model for

Ma et al. (2011a) to assess the influence of NPS on N and P

assessment of the long-term impacts in the Mineirinho

loading to the Three Gorges Reservoir Area (TGRA) of

watershed. In the future, 68% of the annual runoff would

Hubei Province, People's Republic of China. The results

be generated by residential land use. In 2009, this use

indicated that the potential total nitrogen (TN) load was

accounted for 36% of the total water that flowed over the

much higher than the potential total phosphorus (TP) load.

surface. The nutrients increase between the two scenarios

The calculated TN load was 2.83 × 104 t, while the TP load

was 4.47% and 10.86% for nitrogen and phosphorus,

was 2.14 × 103 t in 2007, with a ratio of TN/TP of 13.23.

respectively.

Records specified that “algae blooms” occurred 8 times in

As indicated from the research conducted by

TGRA that year, therefore, there might be a correlation

Moltz et al. (2011), sediment represented a major non-point

between the eutrophication potential in the inlet water of

source pollutant throughout the world. The erosion index

TGRA and the TN/TP ratio of potential NPS loads.

which is an adaptation of the Universal Soil Loss Equation

In order to estimate non-point source pollution

(USLE), correlated well with measurements of sediment

load in watersheds with a consideration of the influences of

yields from runoff plots.

rainfall and the reduction of pollutant in the process of

identify sub-watersheds within the US portion of the Rio

transport, Wang et al. (2011a) conducted a study with an

Grande Basin that merit further investigation for non-point

improved export coefficient method. Taking the Jinghe

source pollution prevention and control via the use of

River in Shaanxi province as an example, by combination

hydrologic modeling techniques.

These indices were used to

with the statistical data information of total nitrogen

1646 Water Environment Research, Volume 84, Number 10—Copyright © 2012 Water Environment Federation

Chen et al. (2011) applied the Soil & Water

Generally, the water quality pollution and

Assessment Tool model (SWAT) to study the space

ecological deterioration in peri-urban rivers are usually

distribution of non-point source pollution in Dafeng city,

serious under rapid urbanization and economic growth. In

China. Based on GIS technology, the spatial and attribute

the study, Jia et al. (2011) selected a typical peri-urban

database of the three river basins were established. In order

river, Nansha River in China, as a case study to investigate

to make the SWAT model applicable in this area, they

the scheme of peri-urban river rehabilitation. The Nansha

divided river sub-basin artificially and then collected the

River was currently seriously contaminated by urban and

runoff and the water quality data series from 2003 to 2008

rural pollutants from both nonpoint sources (NPS) and

to calibrate the parameters and validate the model. After

point sources (PS). First, the study assessed the pollutant

analyzing flow production, non-point pollutant space

loads from point sources and nonpoint sources in the

distribution and contribution of different types of land use,

Nansha River watershed. Then, a coupled model, derived

they concluded that low coverage meadow, construction

from the Environmental Fluid Dynamics Code and Water

land and cultivated land produced the most runoff in this

Quality Analysis Simulation Program, was developed to

area.

simulate the hydrodynamics and water quality in the Two different models were implemented by

Nansha River.

According to the characteristics of the

Wang et al. (2011b) to simulate the urban NPS pollution.

typical peri-urban river, three different PS and NPS control

The results exhibited that residual pollutant should be

scenarios were designed and examined by modeling

considered in pollutant when the total runoff volume is less

analysis. Based on this study, a river rehabilitation scheme

than 30 mm.

was recommended for implementation.

After being calibrated and verified with

observed data from an urban catchment in the Los Angeles

Yin et al. (2011) used a mathematical SWAT

County, the model was more capable of simulating

model to establish a database of non-point source pollution

nonpoint source pollution from urban storm runoff with

from Tumen River watershed in the northeast of China.

consideration of residual pollutant than that without

The hydrologic simulation, runoff and soil erosion were

consideration of residual pollutant. Wang et al. (2011c)

calculated for 5 sub-basins and 46 hydrologic response

analyzed back propagation (BP) neutral network model

units (HRUs) which were divided from watershed. The

structure to simulate COD pollution load.

The result

investigation suggested that the urban construction and

presented that mean error was 0.284% when the precision

economic development in the areas not only brought the

was 0.001 and hidden layer neuron number 19 for BP

prosperity, but also led to the vegetation deterioration and

neural network. This BP neural network model had high

decline of conservation capacity to the water and soil,

accuracy.

resulting in serious water and soil loss in these areas. The results revealed that the agricultural non-point source

1647 Water Environment Research, Volume 84, Number 10—Copyright © 2012 Water Environment Federation

pollution mainly happened in the joint area of Hailan River

in systems where nonpoint source pollutant delivery was

and Buerhatong River, and the middle area of Tumen River

diffuse and hydrologic residence time was short.

watershed.

These might be caused by the highly

Jankowski et al. (2011) used computer models for

contribution of non-point source pollution from the Yanji

simulating the consequences of nonpoint source pollution.

city, the capital of Yanbian state.

By combining a dynamic, event-based nonpoint source

It was reported that the main cause of

pollution models with geographic information systems

groundwater contamination in suburban areas of Shanghai

(GIS). A computerized system was developed to overcome

was non-point source pollution. Huang et al. (2011) found

the problems appeared

that due to the seriously pollution, both of the surface and

Doubling the agricultural nonpoint source pollution model

groundwater were not suitable to drink.

The average

(AGNPS) with pc-ARC/INFO, a menu-driven system was

content of total nitrogen in surface water was 6.34 mg/L

developed with use of the pc-ARC/INFO macro language,

and 16.85 mg/L in the groundwater, both of them were over

Pascal, and batch programming.

in

the simulating process.

the standard of Grade V surface water (less than or equal to

Zhu et al. (2011) connected two powerful

2.0 mg/L) according to the national standard (GB 3838--

watershed and water quality models (AnnAGNPS and CE-

2002). In addition, the content of nitrate nitrogen from

QUALW2) to control the water quality of Jinpen Reservoir

about 20% of the sampling sites fell into Grade V

with the main objective of supply water and irrigation for

groundwater (>30 mg/L) based on the national standard

Xi’an city, China. AnnAGNPS model outputted with the

(GB/T14848--1993).

To interpret and extrapolate field

nonpoint source pollution loading as the CE-QUAL-W2

observations, a process-based biogeochemical model

model inputted. The results disclosed that the impact of

DeNitrification-DeComposition (DNDC) and an empirical

nonpoint source pollutions had significant difference

hydrologic model L-THIA were employed.

between the flood and non-flood period when predicting

L-THIA

simulated N losses through leaching and found about 1.7%

reservoir water quality.

of annual accumulated soil N leached into the surface water

great impact for water quality of Jinpen Reservoir in the

via the surface runoff and 5.8% to the groundwater and

flood period, but less impact in the non-flood period.

3.5% in the soil liquid phase.

A possibilistic stochastic water management

Steinman et al. (2011) investigated functional and structural

responses

of

Nonpoint source pollution had

periphyton

communities

(PSWM) model was developed and applied to evaluate the

to

water quality management practices within an agricultural

simulated nonpoint source (NPS) pollution over a 2-year

system in China (Zhang et al., 2011d).

period. The study results demonstrated that the influence

exhibited useful information for feasible decision schemes

of nonpoint source pollutants on periphyton might be either

of agricultural activities, including the trade-offs between

modest or too difficult to detect using traditional endpoints

The results

economic and environmental considerations. Moreover, a

1648 Water Environment Research, Volume 84, Number 10—Copyright © 2012 Water Environment Federation

strong desire to acquire high agricultural income would run

processes, new strategies for controlling the nonpoint

into the risk of potentially violating the water quality

source pollution can be reached in the future work.

standards, while willingness to accept low agricultural

Ge et al. (2011) established a water quality

income would increase the risk of potential system failure

module of SWAT model according to the data from 1995 to

(violating system constraints). The results suggested that

2004 to solve the serious water environment problems of

the developed approach was also applicable to many

the Haihe River Basin.

practical problems where hybrid uncertainties exist.

values in calibration and validation were 0.70, 0.55

The Nash-Sut-cliffe efficiency

Based on the observation on a pasture hill slope

respectively. It was reported that the urban runoff non-

in the Sand Mountain region of North Alabama, United

point pollution was the highest in pollution loadings

States, Sen et al. (2011) used a physically based, fully

contribution, which is 38.6%, the next is point pollution

distributed

Runoff/On

which is 31.1%. Based on the computation and simulation

hydrologic model to model infiltration excess as the

of SWAT model, the key source areas were identified after

dominant runoff generation mechanism on a pasture hill

analyzing temporal and spatial distribution of pollution

slope. Three rainfall events of varying intensity and

loadings. The pollution loading contributions for studying

duration were simulated for a highly instrumented pasture

key source areas were also computed.

hill slope to study the dynamics of runoff generation and

results proposed that there was a good correlation between

runon areas.

Calibration and cross validation were

pollution loadings and surface flow. The key source areas

performed on all three rainfall events. Root mean squared

were southwest and northeast of the urban district, east of

error, coefficient of determination and Nash-Sutcliffe

Xiqing and Dongli, north of Jinnan and Tanggu.

Hortonian

Infiltration

and

The modeling

coefficient of efficiency were used to evaluate the

Chinh et al. (2011) investigated a convenient and

performance of the Hortonian Infiltration and Runoff/On–

powerful tool for resolving the rainfall runoff and pollutant

simulated hydrographs. The calibrated model for the first

load measurement problems.

event resulted in a root mean squared error of 1.18 m3 for

system (HEC-HMS) and GIS software extension tool were

runoff volume; the next two events resulted in root mean

used for simulations of elevation, drainage line definition,

squared errors of less than 1 m3. Similarly, the coefficient

watershed delineation, drainage feature characterization,

of

of

and geometric network generation. A new development for

efficiency values for all three events were greater than 0.70

data input processing with HEC-HMS was introduced for

for the calibrated model. From the results which displayed

optimizing parameters of the model. Results indicated that

interactions among hydrologic and climatic characteristics,

the proposed model was applicable to simulate the rainfall

and

runoff and pollutant load in the Chikugo River basin and

determination

their

and

connections

Nash-Sutcliffe

to

surface

coefficient

runoff–generation

A hydrologic modeling

1649 Water Environment Research, Volume 84, Number 10—Copyright © 2012 Water Environment Federation

could be a useful tool for optimizing the water surface

AGNSP

management of this river basin.

constructed.

pollutants

in

drainage

ditch

system

was

Schaffner et al. (2011) focused on conventional

The impacts of land-use change in the riparian

river water quality models preventing the determination of

corridor under different geographical scales were qualified

effective mitigation measures of non-point sources. The

by the use of an integrated modeling approach. Liu and

results underlined the importance of non-point source

Tong

pollution control in tropical lowland delta areas such as the

Program-Fortran (HSPF) model to develop a hydrologic

Central Plains of Thailand.

The specific benefit of

and water quality model for the Upper Little Miami River

applying a Material Flow Model in this context was gaining

basin, a headwater subwatershed in Ohio, USA. After

an overview on NPS key problems with limited data

calibration and validation, the model was used to predict

availability and getting a supportive basis for determining

the hydrologic and water quality impacts under various

consecutive in-depth research requirements.

scenarios of buffer zones. Results designated that the 60 m,

(2011)

adopted

the

Hydrological

Simulation

Based on the agricultural non-point source

90 m, and 120 m riparian forest and wetland buffers were

pollution (AGNSP) characteristic, Li et al. (2011d) divided

able to reduce the mean annual flow by 0.26 to 0.28%,

the AGNSP model into “Sources” module and “Sinks”

nitrite plus nitrate by 2.9 to 6.1% and total phosphorus by

module. Loads quantitative calculation was applied to do

3.2 to 7.8%. HSPF was an effective tool to model NPS

the basic part of control, evaluation and management of

from riparian land-use changes, even in a small sub-

AGNSP. Here, “Sources” module was further divided into

watershed

farmland irrigation drainage sub-module which was

influences.

with

relatively

minimal

anthropogenic

calculated by DRAINMOD model based on the principle of

A dynamic model of phosphorus (P) movement

water balance on farmland and contaminants concentrations

through the Peel-Harvey watershed in South Western

in farmland drainage estimating sub-module. Meanwhile,

Australia was developed by Rivers et al. (2011) using

the model used the synthesis of fertilization and irrigation

STELLA dynamic modeling software.

as an impulse input to the farmland and the pollutant

simulated a 200 year time-frame to reflect 100 years to the

concentration change in agricultural drainage as the

present day since initial land development, and forecast 100

response process corresponding to the impulse input. In

years into the future to illustrate watershed P flux and of

addition, the complex migration and transformation process

predicting future P loss scenarios. Although the watershed

of pollutant in soil was expressed impliedly by Inverse

had an annual P loss target of 70 t per annum (tpa), the

Gaussian Probability Density Function.

Based on the

measured present daily loss was doubled this amount (140

equation of continuity of flow and pollutants migration and

tpa) and was projected to rise to 1600 tpa if current land

transformation, the one-dimensional transport model of

management practices continued.

The model

This had significant

1650 Water Environment Research, Volume 84, Number 10—Copyright © 2012 Water Environment Federation

implications for both future land use and subsequent water

land use scenarios in the upstream watershed of Miyun

quality in the watershed.

Reservoir in Beijing, China. These models provided a new

In the study of Li et al. (2011e), a projection

approach for land use optimization towards non-point

pursuit cluster (PPC) model was used to analyze the

source pollution control. The study showed that improper

regional partitioning of agricultural non-point source

land use was one major cause of non-point source

pollution in China. The cluster results of the PPC model

pollution. It also indicated that increase of orchards and

mirrored the actual regional partitioning of the agricultural

loss of forest cover has led to an increase in the potential

non-point source pollution in China. A novel optimization

pollution loads of nitrogen by 5.27% and phosphorus by

algorithm called Free search (FS) was introduced to

4.03%.

optimize the projection direction of the PPC model.

It

pollution control scenario, pollution loads of nitrogen

strongly indicated that the PPC model is a powerful tool in

decreased by 13.94% and phosphorus by 9.86%, resulting

multi-factor cluster analysis, and could be a new method

from the establishment of riparian vegetation buffers and

for the regional partitioning of agricultural non-point

restoring forest on unutilized land and slope arable land.

source pollution.

However, in the agricultural non-point source

Lai et al. (2011) developed an integrated two-

New Modeling and Enhanced Modeling of

model system composed of a multimedia watershed model

NPS Pollution: EcoHAT, a new model created by Yang et

and a river water quality model to effectively simulate the

al. (2011), was formed by coupling the Xinanjiang model

impacts of non-point source (NPS) pollution on river water

and SWAT. It can predict the runoff volume within a range

quality. NPS pollution loadings from Kaoping River Basin

of acceptable accuracy which was reflected by a large

were

coefficient of determination. It included algorithms for the

Management Model (IWMM). Lai et al. (2011) combined

hydrological cycle, nutrient cycle, and plant growth cycle

the Water Quality Analysis Simulation Program (WASP)

and was aimed at assessing the non-point source pollution

with the IWMM model for the Kaoping River water quality

in Hainan by simulating the non-point source pollution for

evaluation. Results indicated that land use patterns of

the watershed in calculated grid cell units based on remote

orchard farms and farmland areas were the major causes of

sensing data.

The results disclosed that with 40%

the NPS pollution. In the wet seasons, NPS pollution

fertilization reduction, 7.51% and 7.76% reduction on TN

loadings increased due to the higher flow rates (>200 m3/s).

and TP loads respectively could be reached.

And the integral approach could develop a direct linkage

The Conversion of Land Use and its Effect at

calculated

using

the

Integrated

Watershed

between upstream land use changes and downstream water

Small regional extent (CLUE-S) and Soil and Water

quality.

Assessment Tool (SWAT) models were coupled by Zhang

Tang et al. (2011a) applied a combination model

et al. (2011e) to simulate pollution loads under different

of source controlling (concentration)-sewage interception

1651 Water Environment Research, Volume 84, Number 10—Copyright © 2012 Water Environment Federation

(conduction)-recycling to solve rural nonpoint source pollution problems. which

were

In order to remove carbonaceous and nitrogenous

The model included three patterns pound

applied a biofilm process with the attached bacterial growth

purification recycling, and constructed wetland purification

onto ceramic media. The results showed that a packing

recycling. More than 56% COD and TP, nearly 68% TN,

ratio above 0.15 was required to simultaneously achieve

NH4+-N and NO3--N, 82% NO2—N could be removed by

stable COD removal and nitrification efficiency. The inter-

this approach. Economic benefits could be increased by

event period and packing ratio seemed to have no

almost 50% to 300,000 Yuan in 2010. It not only brought

significant influence on the COD removal efficiency.

environmental

biogas

benefits,

purification

but

also

recycling,

pollutants from nonpoint water source, Choi et al. (2011)

produced

notable

According to current researches which were

economic benefits.

focused on the development of modern technology for NPS control, single application of grassed swales technology

NPS Pollution Management

might be inadequate to reduce NPS. Wang et al. (2011d)

New Methods to Manage NPS Pollution:

proposed a combination of grassed swales technology and

Without remediation method applied, the degradation of

other non-point source pollution control technology as a

NPS pollution has been reported to be slow. Xiao et al.

development direction in urban non-point source pollution

(2011)

control.

analyzed

non-point

source

pollution

of

organochlorine pesticides (OCPs) by runoff. The results

Best Management Practice Implementation:

showed that the concentrations of OCPs were relatively

In the assessment of NPS, the cost to abate the NPS is one

high even after 30 days, suggesting that the degradation of

important factor that must be considered. Zheng and Fu

OCPs in the soil was very slow. It strongly indicated the

(2011) pointed out that some programs such as water

importance of new methods to manage NPS pollution.

quality trading (WQT) programs have been applied to the

Udawatta et al. (2011) reported that agroforestry

CWA’s effluent limitations to reduce the pollution

and grass buffers could be designed to improve water

abatement costs. In order to reach the goal of reducing

quality while minimizing the amount of land taken out of

nutrient loads, best management practices (BMP) were

production.

According to the experiment, buffers in

required. Among the management practices available for

association with grazing and row crop management

water quality enhancement, riparian buffer strips had

reduced runoff by 49 and 19%, respectively, during the

proven effective in mitigating the removal of nutrients and

study period as compared with respective control

other pollutants in the surface waters. Estimates of riparian

treatments.

buffer costs would be valuable for developing policy

On average, grass and agroforestry buffers

reduced sediment, TN, and TP losses by 32, 42, and 46%

related to WQT and other conservation programs.

compared with the control treatments.

1652 Water Environment Research, Volume 84, Number 10—Copyright © 2012 Water Environment Federation

Campbell

a

pollution of diatom assemblages, Lebkuecher et al. (2011)

foster

studied six streams in the Red River Watershed of North-

environmental behavior change among resource users, and

Central Tennessee and found that the three most abundant

compared the adoption of agricultural best management

diatom taxa collected were Nitzschia linearis (16%),

practices

collaborative

et

al.

watershed

(BMPs)

(2011)

implemented

management

and

non-

Navicula reichardtiana (15%), and Navicula tripunctata

out

that

(7%). Excessive sediments and nutrient enrichment on the

collaboration had a higher level of BMP adoption in some

structure of diatom assemblages, oxygen dynamics, and

special cases compared to non-collaborative settings. But

potential for excessive algal growth had affected water

typically farmers in the watershed with the partnership do

bodies in streams of the Red River Watershed.

collaborative

between

settings.

collaborative

to

Results

pointed

not have higher rates of BMPs adoption than farmers in the watershed with a traditional, agency-based approach

References

encouraging BMP adoption.

Aprígio, P. O.; Brandão, J. L. B. (2011) Impact Assessment of Non-Point Source Pollution with the L-THIA Model.

Due to the complexity in estimating system

World Environmental and Water Resources Congress

design factors for best management practices (BMPs), Cha

2011: Bearing Knowledge for Sustainability, Palm

et al. (2011) analyzed the storm water discharge from an Springs, CA, May 22–26, 732–741.

agricultural area in Korea. Four field studies categorized Campbella, J. T.; Koontza, T. M.; Bonnella, J. E. (2011) Does

by rainfall type were then employed to assess the pollutant

Collaboration Promote Grass-Roots Behavior Change?

and flow coefficient of variation (PFCoV) values which

Farmer Adoption of Best Management Practices in Two

were used to explain the storm water runoff in the

Watersheds. Soci. Natu. Resour., 11 (24), 1127–1141.

agricultural area. The physical meaning of PFCoV values

Cha, S. M.; Lee, S. W.; Kim, L. H.; Min, K. S.; Lee, S.; Kim, J. H.

indicated the variation of NPS pollutants during a storm

(2011) Investigation of Stormwater Runoff Strength in an Agricultural Area, Korea. Desal. Water Treat., 38 (1–3),

event.

360–365.

Moore et al. (2011) used the stated preference

Chen, Y. T.; Wu, J. Y.; Cheng, H. G.; Pu, X.; Zhou, T. (2011)

methods and a unique survey design to find the lower Estimate Model of Non-Point Source Pollution Load in

bound on the benefits of reducing runoff enough to universally increase water clarity.

Plain River-Net Area: A Case Study in Dafeng City.

Since current water

Electrical and Control Engineering (ICECE), 2011

clarity in Green Bay is spatially variable, the value that a

International Conference; Yichang, Hubei, China, Sept

household places on this universal improvement depended

16–18, 3463–3466. Chinh, L. V.; Iseri , H.; Hiramatsu, K.; Harada, M.; Mori, M.

on the distance of the household’s residence from the bay

(2011) Simulation of Rainfall Runoff and Pollutant Load

and on the particular geospatial location of the residence. In order to evaluate the impacts of nonpoint source

1653 Water Environment Research, Volume 84, Number 10—Copyright © 2012 Water Environment Federation

for Chikugo River Basin in Japan Using a GIS-Based

Jankowski, P. (2011) Integrated Geographic Information System

Distributed Parameter Model. Paddy Water Environ, 1–16.

for

Modeling

Nonpoint

Source

Pollution

Events.

Chiwa, M.; Onikura, N.; Ide, J.; Kume, A. (2011) Impact of N-

Proceedings of the 4th Annual Simulation, and Planning in

Saturated Upland Forests on Downstream N Pollution in the

High Autonomy Systems Conference; Tucson, AZ, USA,

Tatara River Basin, Japan. Ecosystems, 15 (2), 230–241.

Sep 20–22, 90–94.

Choi, G. C; Lee, J. H.; Yu, J. C.; Ju, D. J; Park, J. J. (2011)

Jia, H. F.; Wang, S.; Wei, M. J.; Zhang, Y. S. (2011) Scenario

Laboratory Assessment of Biofilm Process and Its

Analysis of Water Pollution Control in the Typical Peri-

Microbial Characteristics for Treating Nonpoint Source

Urban River Using a Coupled Hydrodynamic-Water Quality

Pollution. Korean J. Chem. Eng., 5 (28), 1207–1213.

Model. Front. Environ. Sci. Eng. China, 5 (2), 255–265.

Ding, X. W. (2011) Agricultural Non-Point Source Nitrogen

Kaushal, S. S.; Groffman, P. M.; Band, L. E.; Elliott, E. M.;

Simulation Research of Yongding River in Hebei

Shields, C. A.; Kendall, C. (2011) Tracking Nonpoint

Province. Water Resource and Environmental Protection

Source

(ISWREP), 2011 International Symposium; Xi’an, Shanxi,

Watersheds. Environ. Sci. Technol., 19 (45), 8225–8232.

China, May 20–22, 3, 2150–2153.

Nitrogen

Pollution

in

Human-Impacted

Lai, Y.C.; Yang, C.P.; Hsieh, C.Y.; Wu, C.Y. ; Kao, C.M. (2011)

Gao, X.; Meng, H. T.; Yi, X. J. (2011a) Analysis of Nitrogen

Evaluation of Non-Point Source Pollution and River Water

Pollution Characteristics in Water Bodies of Tianjin. China

Quality Using a Multimedia Two-Model System. J.

Water Wastewater, 27 (15), 51–55.

Hydro., 3–4 (409), 583–595.

Gao, Y.; Zhua, B.; Wang, T.; Wang, Y. F. (2011b) Seasonal Change

of

Non-Point

Source

Bioavailable Phosphorus Loss:

Langendoen, E. J. (2011) Application of the CONCEPTS Channel

Pollution-Induced

Evolution Model in Stream Restoration Strategies. Geophys.

A Case Study of

Monogr. Ser., 194, 487–502. Lebkuecher, J. G.; Rainey, S. M.; Williams, C. B.; Hall, A. J.

Southwestern China. J. Hydrol., 420–421, 373–379. Ge, H. F.; Qin, D. Y.; Zhou, Z. H.; Sang, X. F. (2011) Analysis of

(2011) Impacts of Nonpoint-Source Pollution on the

Key Source Areas and Pollution Type in the Lower Haihe

Structure of Diatom Assemblages, Whole-Stream Oxygen

River Based on Pollution Loading Movement and

Metabolism, and Growth of Selenastrum capricornutum in

Transformation. J. Hydraul. Eng., 42 (1), 61–67.

the Red River Watershed of North-Central Tennessee. Castanea, 3 (76), 279–292.

Gozzarda, E.; Mayes, W. M.; Potter, H. A. B.; Jarvis, A. P. (2011)

Li, D.; Hao, Z. C.; Xue, L. Q. (2011c) Using Pattern Recognition

Seasonal and Spatial Variation of Diffuse (Non-Point) Source Zinc Pollution in A Historically Metal Mined River

Technique

Catchment, UK. Environ. Pollut., 10 (159), 3113–3122.

Agricultural

for

Non-Uniform

Nonpoint

Source

Field

Sampling

Pollution.

of

Natural

Computation, 4, 291–295.

Huang, X. M.; Shen, G. R.; Zhou, P. (2011) Modeling Impacts of on

Li, J. K.; Li, H. E.; Shen, B.; Li, Y. J. (2011b) Effect of Non-Point

Groundwater in a Suburban Area of Shanghai, China. J.

Source Pollution on Water Quality of the Weihe River. Int.

Agro-Environ. Sci., 30 (7), 1378–1384.

J. Sedi. Res., 1 (26), 50–61.

Cropland

Non-point

Source

Nitrogen

Pollution

1654 Water Environment Research, Volume 84, Number 10—Copyright © 2012 Water Environment Federation

Li, P. F.; Zheng, B. F.; Liu, C. L.; Zhou, W. B.; Yu, J. X.; Liu, Y.

Moore, R.; Provencher, B.; Bishop, R. C. (2011) Valuing a

F. (2011a) Prediction on Pollution Contribution of N and P

Spatially Variable Environmental Resource: Reducing

From Agricultural Non-Point Source Pollution in Poyang

Non-Point-Source Pollution in Green Bay, Wisconsin.

Lake Watershed. Remote Sensing, Environment and

Land Econo., 1 (87), 45–59.

Transportation Engineering (RSETE), 2011 International

Qin, Y. M.; Li, H. E.; Li, J. K.; Zhu, L. (2011) Impact of Nonpoint

Conference; Nanjing, China, June 24–26, 4268–4271.

Source Pollution on Water Quality of the Bahe River.

Li, Q. K.; Sun, J.; Hu, Y. W. (2011d) Preliminary Establishment of Agricultural

Non-Point

Source

Pollution

Water Resource and Environmental Protection (ISWREP),

Model.

2011 International Symposium; Xi’an, Chongqing, China,

Proceedings of Water Resource and Environmental

May 20–22, 2121–2124.

Protection (ISWREP), 2011 International Symposium;

Ren, C. Y.; Wang, Z. M.; Song, K. S.; Zhang, B.; Zhang, S. M.

Xi’an, China, May 20–22, 3, 1636–1639.

(2011) Spatial Distribution of Non-Point Source Pollution

Li, X. H.; Zhao, C. Y.; Wang, B.; Feng, G. (2011e) Regional

and its Relation to Land Use Structure in Muling River

Partitioning of Agricultural Non-Point Source Pollution in

Watershed, Sanjiang Plain. Remote Sensing, Environment

China Using a Projection Pursuit Cluster Model. J. Arid

and

Land, 4 (3), 278–284.

International Conference; Nanjing, Jiangshu, China, June

Liu, F. R.;

Guo, Y.;

Zhao, P.;

He, Y. H. (2011) The Crucial

Transportation

Engineering

(RSETE),

2011

24–26, 4423–4426.

Factor of Non-Point Pollution (N, P) Controlling in Weihe

Rivers, M. R.; Weavera, D. M.; Smettema, K. R. J.; Daviesd, P. M.

River Basin—Study and Evaluation of Slow-Release

(2011) Estimating Future Scenarios for Farm–Watershed

Compound Fertilizer. Water Resource and Environmental

Nutrient Fluxes Using Dynamic Simulation Modeling.

Protection (ISWREP), 2011 International Symposium;

Phys. Chem. Ear., 36 (9–11), 420–423

Xi’an, Shanxi, China, May 20–22, 2, 1267–1270..

Schaffner, M.; Bader, H. P.; Scheidegger, R. (2011) Modeling

Liu, Z.; Tong, S. T. Y. (2011) Using HSPF to Model the

Non-Point Source Pollution from Rice Farming in The

Hydrologic and Water Quality Impacts of Riparian Land-

Thachin River Basin. Environ. Develop. Sustain., 2 (13),

Use Change in a Small Watershed. J. Environ. Infor., 17 (1),

403–422.

1–14.

Schelker, J.; Burns, D. A.; Weiler, M.; Laudon, H. (2011)

Ma, X.; Li, Y.; Zhang, M.; Zheng, F. Z.; Du, S. (2011) Assessment and

Analysis of Non-Point

Source Nitrogen

Hydrological Mobilization of Mercury and Dissolved

and

Organic Carbon in a Snow-Dominated, Forested Watershed:

Phosphorus Loads in The Three Gorges Reservoir Area of

Conceptualization and Modeling. J. Geophy. Res., 116, 17. Sen, S.; Srivastava, P.; Clement, T.P.; Dane, J.H.; Meng, H. (2011)

Hubei Province, China. Sci. Tot. Environ., 412–413, 154–

Simulating Hydrologic Response of a Pasture Hillslope in

161. Moltz, Heidi L. N.; Rast, W.; Lopes, V. L.; Ventura, S. J. (2011)

North Alabama Using the Hortonian Infiltration and

Use of Spatial Surrogates to Assess the Potential for Non-

Runoff/On Model. J. Soil. Water. Conservation, 6 (55),

Point Source Pollution in Large Watersheds. Lakes

411– 422.

Reserv.: Res. Manage., 1 (16), 3–13.

1655 Water Environment Research, Volume 84, Number 10—Copyright © 2012 Water Environment Federation

Shan, N.; Ruan, X. H.; Ao, J. (2011) RS and GIS Based Temporal-

Washoff Models for Simulating Storm Runoff Quality in

Spatial Variation and Multi-Factor Spatial Analysis on

the Los Angeles County. Environ. Pollut., 7 (159), 1932–

Nonpoint Source Pollution. Geoinformatics, 2011 18th

1940.

International Conference; Beijing, China, June 18–20, 1–

Wen, Q. C.; Chen, X.; Shi, Y.; Ma, J.; Zhao, Q. (2011) Analysis on

4.

Composition and Pattern of Agricultural Nonpoint Source

Steinman, A. D.; Ogdahl, M. E.; Wessell, K.; Biddanda, B.;

Pollution in Liaohe River Basin, China. Proc. Environ.

Kendall, S.; Nold, S. (2011) Periphyton Response to

Sci., 8, 26–33.

Simulated Nonpoint Source Pollution: Local Over

Xia, Y.; Huang, L. G.; Xu, L. G. (2011) Characteristics of Diffuse

Regional Control. Aquat. Ecol., 4 (45), 439–454.

Source N Pollution in Lean River Catchment. Procedia

Tang, A. P.; Wan, J. B.; Lan X. Y.; Liu F. (2011) The Combination

Environ. Sci., 10, Part C, 2437–2443.

Mode of Source Controlling (Concentration)-Sewage

Xiao, C. Y.; Zhao T. Q.; Tai C.; He X. Q. (2011) Study on

Interception (Conduction) -Recycling for Rural Non-Point

Mechanism

Pollution Treatment. Bioinformatics and Biomedical

Organochlorine

Engineering, (iCBBE) 2011 5th International Conference;

Method. Computer Distributed Control and Intelligent

Wuhan, Hubei, China, May 10–12, 1–4.

Environmental Monitoring (CDCIEM), 2011 International

Udawatta, R. P.; Garrett, H. E.; Kallenbach, R. (2011)

of

Non-point Pesticides

Source

with

Pollution

Rainfall

of

Simulation

Conference; Changsha, Hunan, China, Feb 19–20, 1756–

Agroforestry Buffers for Nonpoint Source Pollution

1759.

Reductions from Agricultural Watersheds. J. Environ.

Yang, S. T.; Dong, G. T.; Zheng, D. H.; Xiao, H. L.; Gao, Y. F.;

Qual., 3 (40), 800–806.

Lang, Y. (2011) Coupling Xinanjiang Model and SWAT

Wang, B. Q.; Ma, Q. T.; Sun, Y. C.;

Liu, H. L. (2011c)

to Simulate Agricultural Non-Point Source Pollution in

Simulation of Non-Point Source COD Pollution Load by

Songtao Watershed of Hainan, China. Ecol. Model., 222

BP Neural Network. Remote Sensing, Environment and

(20–22), 3701–3717.

Transportation Engineering (RSETE), 2011 International

Yin, G.; Wang, N.; Yuan, X.; Zhang, J. (2011) Non-point Source

Conference; Nanjing, China, June 24–26, 8488–8491. Wang, J. C.;

Wu, Y. Q.;

Hu, A. Y.;

Pollution of Nitrogen and Phosphorus Nutrients Using

Ren, Q. R. (2011a)

SWAT Model in Tumen River Watershed, China. J. Agro-

Application and Establishment Model of Non-Point Source

Environ. Sci., 4 (30), 704–710.

Pollution Based on Statistical Data. Water Resource and

Zhang R.; Wan Y.H.; Fan H. (2011a) Estimating of Non-Point

Environmental Protection (ISWREP), 2011 International

Source Pollutants Load in Runoff at Small Site. Electric

Symposium; Xi’an, Shanxi, China, May 20–22, 854–858.

Technology and Civil Engineering (ICETCE), 2011

Wang, J.; Yin, W.; Ye, M.; Lei, A. L.; Li, S. M. (2011d) Advance

International Conference; Lushan, Nanchang, China, April

on Grassed Swales Technology in Non-Point Source

22–24, 1209–1211.

Pollution Control. Environ. Sci. Tech., 5 (34), 90–94.

Zhang, H.; Huang, G. H. (2011) Assessment of Non-Point Source

Wang, L.; Wei, J. H.; Huang, Y. F.; Wang, G. Q.; Maqsood, I.

Pollution Using a Spatial Multicriteria Analysis Approach.

(2011b) Urban Nonpoint Source Pollution Buildup and

Ecol. Model., 2 (222), 313–321.

1656 Water Environment Research, Volume 84, Number 10—Copyright © 2012 Water Environment Federation

Zhang, L.; Lu, W.X.; An, Y. L.; Li, D.; Gong, L. (2011c) Response of Non-Point Source Pollutant Loads to Climate Change in the Shitoukoumen Reservoir Catchment. Environ. Monit. Assess., 1 (184), 581–594. Zhang, M. H.; Xu, J. M. (2011) Nonpoint Source Pollution, Environmental Quality, and Ecosystem Health in China: Introduction to the Special Section. J. Environ. Qual., 40, 1685–1694. Zhang, P.; Liu, Y. H.; Pan, Y.; Yua, Z. R. (2011e) Land Use Pattern Optimization Based on Clue-S And Swat Models for Agricultural Non-Point Source Pollution Control. Mathemat. Comput. Model., 1–8. Zhang, X. D.; Huang, G. H.; Nie, X. H. (2011d) Possibilistic Stochastic Water Management Model for Agricultural Nonpoint Source Pollution. J. Water Resour. Planning and Management-ASCE, 1 (137), 101–112. Zhang, Y. L.; Wu, G. Y.; Li, H. E.; Cai, Y. L.; Wang, P. H. (2011b) Application of Land Use Relation Approach for Nonpoint

Source

Pollution

Load

Prediction.

Bioinformatics and Biomedical Engineering, (iCBBE) 2011 5th International Conference; Wuhan, China, May 10–12, 3–5. Zheng, N.; Fu, C. (2011) Research on Non-Point Source Pollution Resulted from Livestock Breeding in Jiangxi Province. Advanced Materials Res., 356–360, 2344–2348. Zhu, L.;

Li, J. K.;

Li, H. E.;

Dong, W. (2011) Connecting

Annagnps and CE-QUAL-W2 Models for Reservoir Water Quality Prediction.

Electric

Technology and

Civil

Engineering (ICETCE), 2011 International Conference; Lushan, Jiangxi, China, April 22–24, 1120– 1124.

1657 Water Environment Research, Volume 84, Number 10—Copyright © 2012 Water Environment Federation

Suggest Documents