Spatial Distribution Of Total Nitrogen Research Articles

Improvements in the InVEST water purification model for detecting spatio-temporal changesintotal nitrogen and total phosphorus discharges in the Huai river watershed, China

Improving water quality to provide freshwater is an urgent requirement for regional and even global social development. More accurate simulation of non-point sources pollution, monitored mainly by total nitrogen (TN) and total phosphorus (TP), has always been a challenge for InVEST water purification model, particularly in agricultural areas. This can be attributed to the fact that there is no reference data for TN and TP to rectify the outcomes modelled by this model. This paper provided these data to rectify simulation results of TN and TP to ensure their accuracy. The Huai River watershed (HRW) is an important grain production area with slow economic development, and non-point source pollution has exceeded point-source pollution. There is an urgent need for water management authorities to obtain complete spatio-temporal data on TN and TP loads and their exports to improve water quality. The reference data onloads and exports of TN and TP were estimated for the entire watershed and its sub-watersheds through an investigation-evaluation technique during 1980–2018. TN and TP loads generated from the agricultural sector were the major pollution sources in the HRW and had similar time trends during the same period. The spatial distribution of TN and TP exports was modelled byusingthe InVEST water purification model, and it was found that the temporal trends for the final exports of TN and TP into river systems were similar to those for TN and TP loads in the HRW for 1980–2018. Key driving factors were detected using the Geo-detector method to quantify the contribution rates of factors to the spatiotemporal exports of TN and TP. Our results showed that individual factors, such as precipitation and land use/cover, were the most important factors driving spatio-temporal variations in TN and TP exports in the HRW from 1980 to 2018. Meanwhile, the contribution rates of interactions between land use/cover and other factors were consistently highest in this watershed during the same period. In this study, we estimated the loads and exports of TN and TP, and modelled their spatial patterns in this watershed from 1980 to 2018, providing important information on TN and TP for water-related management authorities. We also provide a method for other river systems to calibrate the parameters in the biophysical table of InVEST water purification model based on final exports of TN and TP.

The effect of anthropogenic activities on the spatial distribution of total nitrogen and total phosphate in Lake Maninjau

This study aimed to analyse the effect of anthropogenic activities on the spatial distribution of total nitrogen (TN) and total phosphate (TP) in Lake Maninjau, Indonesia, during the dry season. Sampling was carried out at ten observation locations representative for various activities around the lake. Cluster analysis and ANOVA were used to classify pollutant sources and observe differences between TN and TP at each site. Concentrations of TN and TP are categorised as oligotrophic-eutrophic. The ANOVA showed spatially that some sampling locations, such as the Tanjung Sani River, floating net cages, and hydropower areas have different TN concentrations. At the same time, TP levels were consistently significantly different across sampling sites. ANOVA and cluster analysis confirmed that floating net cages were the first cluster and the primary contributor to TN and TP. The second and third clusters come from anthropogenic activities around the lake, such as agriculture, settlement, and livestock. The fourth cluster with the lowest TN and TP is the river that receives the anthropogenic activity load but has a high flow velocity. The cluster change analysis needs to be conducted when there are future changes in the composition of floating net cages, agriculture, and settlements.

Spatial distribution of non-point source pollution from total nitrogen and total phosphorous in the African city of Mwanza (Tanzania)

Rapid urbanization has caused widespread environmental pollution in Africa, restricting sustainable development programs. Today, non-point source pollution has become a major threat to many African cities. In this study, we have classified urban land use followed by the identification of urban functional areas based on multi-source data. We have then evaluated non-point source pollution based on nitrogen and phosphorus loads at a spatial scale in Mwanza city (Tanzania). We have estimated the spatial distribution of total nitrogen (TN) and total phosphorus (TP) loads at a scale of 1 square kilometer grid. The results show that ① the built-up area of the city was identified as 28.9 km2, accounting for 6.8% of the total area of the city. The area of informal settlements was 56.9 km2, accounting for 13.4% of the total area of the city. About 90.38% of 2.41×105 kg of the total TN load and 87.23% of 4.00×104 kg of the total TP load in the city were derived from the informal settlements alone in 2020. ② The average load intensities of TN and TP in Mwanza city were 6.90 kg·hm-2·yr-1 and 1.14 kg·hm-2·yr-1, respectively. The average TN and TP intensities in Mwanza city were slightly higher than the average TN and TP load intensities in the Lake Victoria basin. However, given the high population density of the Mwanza city area, the average TN and TP intensities were found to be consistent. ③ The TN and TP pollution loads were relatively concentrated in the inner urban area, including the lower reaches of the Mirongo River basin, the eastern side of the Nyamagana Peninsula, and the lakeside area extending north and south from the peninsula, and gradually decreased toward the city’s outskirts. We propose that the identified riparian areas in our study should be prioritized as potentially key construction zones for pollution treatment plant facilities and urban renewal pilot programs for restraining the widespread informal settlements. This study contributes to the development of an innovative urban non-point source pollution control measure, which may be applicable to low-income countries in Africa and elsewhere.

Spatial Distribution and Sources of Organic Matter in the Surface Sediments of Fuxian Lake, SW China

Sedimentary organic matter is an important component of the metabolism of a lake’s ecosystem, and it is generally derived from both the watershed and the primary productivity of a lake. Understanding the sources of organic matter in lakes and lake trophic status is important when evaluating the quality of lake ecosystems. We summarize the spatial distribution of total nitrogen (TN), total organic carbon (TOC), TOC/TN (C/N) molar ratios, and organic carbon isotope (δ13Corg) of the surface sediments of Fuxian Lake, Yunnan–Guizhou Plateau, Southwest China, which is the second deepest freshwater oligotrophic lake in China. The results show that the distributions of TN, TOC, C/N, and δ13Corg of the surface sediments are spatially heterogeneous, which is also the case for the trophic conditions of the lake. Compared with the adjacent eutrophic lakes and typical lakes in other areas with strong human activities, the content of organic matter is at a low level. Meanwhile, the autochthonous organic carbon in the surface sediments was characterized by lower δ13Corg (−25.3~−28.5) and C/N (8.7~12.9), suggesting that the biological carbon pump effect plays a significant part in the stability of carbon sinks by coupling with carbonate weathering. Our results emphasize the importance of the carbon sink of coupled carbonate weathering and aquatic photosynthesis in the evolution of the carbon cycle in lakes. Although modern monitoring shows that Fuxian Lake is an oligotrophic lake, there are potential risks of organic nitrogen pollution with respect to surface sediments, especially in northern and southern shallow-water areas. The organic pollution of lakes can be reduced by controlling the discharge of wastewater and reducing the nutrient loading of agricultural runoff.

Satellite and Machine Learning Monitoring of Optically Inactive Water Quality Variability in a Tropical River

Large-scale monitoring of water quality parameters (WQPs) is one of the most critical issues for protecting and managing water resources. However, monitoring optically inactive WQPs, such as total nitrogen (TN), ammoniacal nitrogen (AN), and total phosphorus (TP) in inland waters, is still challenging. This study constructed retrieval models to explore the spatiotemporal evolution of TN, AN, and TP by Landsat 8 images, water quality sampling, and five machine learning algorithms (support vector regression, SVR; random forest regression, RFR; artificial neural networks, ANN; regression tree, RT; and gradient boosting machine, GBM) in the Nandu River downstream (NRD), a tropical river in China. The results indicated that these models can effectively monitor TN, AN, and TP concentrations at in situ sites. In particular, TN by RFR as well as AN and TP by ANN had better accuracy, in which the R2 value ranged between 0.44 and 0.67, and the RMSE was 0.03–0.33 mg/L in the testing dataset. The spatial distribution of TN, AN, and TP was seasonal in NRD from 2013–2022. TN and AN should be paid more attention to in normal wet seasons of urban and agricultural zones, respectively. TP, however, should be focus on in the normal season of agricultural zones. Temporally, AN decreased significantly in the normal and wet seasons while the others showed little change. These results could provide a large-scale spatial overview of the water quality, find the sensitive areas and periods of water pollution, and assist in identifying and controlling the non-point source pollution in the NRD. This study demonstrated that multispectral remote sensing and machine learning algorithms have great potential for monitoring optically inactive WQPs in tropical large-scale inland rivers.

Spatial Distribution of Soil Organic Carbon and Total Nitrogen in a Ramsar Wetland, Dafeng Milu National Nature Reserve

The invasion and expansion of Spartina alterniflora in coastal salt marsh wetlands have greatly affected the material cycle of the ecosystem. A total of 372 topsoil samples were collected from 124 sites representing two land-cover types by implementing an unprecedented high sampling density study in the Dafeng Milu National Nature Reserve. Classical statistics and geostatistics were used to quantify soil organic carbon (SOC) and total nitrogen (TN) spatial distribution. Redundancy analysis (RDA) was used to detect correlations between environmental factors, SOC, and TN. The results showed that SOC and TN have moderate variability. The spatial distributions of SOC and TN were similar, and the highest values were observed in the southwest of the study area. In different land cover types, the SOC and TN in the vegetation coverage areas with Spartina alterniflora as the dominant species were significantly higher than those in bare land. RDA showed that TN and aboveground biomass significantly affected the spatial distribution of SOC, while SOC and AGB dominated the spatial distribution of TN.

Spatial–Temporal Variations of Total Nitrogen and Phosphorus in Poyang, Dongting and Taihu Lakes from Landsat-8 Data

Poyang Lake, Dongting Lake, and Taihu Lake are the largest freshwater lakes in the middle and lower reaches of the Yangtze River, China. In recent years, the eutrophication level of lakes has increased with the development of the social economy and caused many environmental and social problems. The concentrations of total nitrogen (TN) and total phosphorus (TP) are the key indicators of the degree of eutrophication, but the traditional ground monitoring methods are not capable of capturing such parameters in whole lakes with high spatial-temporal resolution. In this paper, empirical models are established and evaluated between the TN and TP and remote sensing spectral factors in the three lakes using Landsat 8 Operational Land Imager (OLI) satellite data and in-situ data. The results show that the inversion accuracy is higher than 75%. The TN and TP concentrations in the three lakes are inversed based on the Google Earth Engine (GEE) platform from 2014 to 2020 and their spatial-temporal variations are analyzed. The results show that the concentrations of TN and TP in Poyang Lake were decreased by 5.99% and 7.13% over 7 years, respectively, and the TN in Dongting Lake was decreased by 5.25% while the TP remained stable. The temporal changes in TN and TP concentrations displayed seasonal variations. A low concentration was observed in summer and high concentrations were in spring and winter. The average concentrations of TN and TP in Taihu Lake were higher than that of the other two lakes. The TP concentration was increased by 17.3% over 7 years, while the TN concentration remained almost stable. The variation in TN in Taihu Lake was the same as the growth cycle of algae, with higher value in spring and winter and lower value in summer, while the concentration of TP was lower in spring and winter and higher in summer. The spatial distribution of TN and TP concentrations in the three major lakes was significantly affected by human activities, and the concentrations of TN and TP were higher in areas near cities and agricultural activities.

Retrieval model for total nitrogen concentration based on UAV hyper spectral remote sensing data and machine learning algorithms – A case study in the Miyun Reservoir, China

Monitoring the water pollution level in real time is the most critical issue for protecting the water quality of water reservoirs. Due to the restrictions on flight areas of Unmanned Arial Vehicles (UAV), four sensitive regions with the area of 1–2 km2 were first selected in this study based on the spatial distribution of total nitrogen (TN) concentration changes estimated by the Landsat remote sensing data. And then twelve machine learning algorithms including Support Vector Machine (SVM), Artificial Neural Networks (ANN), Bayesian Ridge Regression (BRR), Lasso Regression (Lasso), Elastic Net (EN), Linear Regression (LR), Decision Tree Regression (DTR), K Neighbors Regression (KNR), Random Forest Regression (RFR), Extra Trees Regression (ETR), AdaBoost Regression (ABR) and Gradient Boosting Regression (GBR) were compared to construct a more accurate retrieval model by using the UAV hyper spectral remote sensing and ground monitoring data. And then the TN concentration was estimated after the process of dimensionality reduction and compressed sensing denoing. Finally, spatial heterogeneity of the TN concentration was analyzed in four sensitive areas of the Miyun reservoir. The results demonstrated that among the tested algorithms the Extra Trees Regression was best suitable for the construction of a TN concentration retrieval model on the basis of UAV hyper spectral data, and its absolute squared error was 0.000065. The spatial distribution of the TN showed that the concentration was highest within the water area of the Bulaotun village and the Houbajiazhuang village, while it was relatively low for the Chao river dam and Bai river dam. Additionally, no significant differences regarding the concentrations were shown in the single UAV flight area except the Houbajia village, which indicated that the water quality in Miyun reservoir was relatively stable and changed in a small interval. These conclusions can provide scientific references for water quality monitoring and management in the water reservoir.

Fine-Resolution Mapping of Soil Total Nitrogen across China Based on Weighted Model Averaging

Accurate estimates of the spatial distribution of total nitrogen (TN) in soil are fundamental for soil quality assessment, decision making in land management, and global nitrogen cycle modeling. In China, current maps are limited to individual regions or are of coarse resolution. In this study, we compiled a new 90-m resolution map of soil TN in China by the weighted summation of random forest and extreme gradient boosting. After harmonizing soil data from 4022 soil profiles into a fixed soil depth (0–20 cm) by equal area spline, 18 environmental covariates were employed to characterize the spatial pattern of soil TN in topsoil across China. The accuracy assessments from independent validation data showed that the weighted model averaging gave the best predictions with an acceptable R2 (0.41). The prediction map showed that high-value areas of soil TN were mainly distributed in the eastern Tibetan Plateau, central Qilian Mountains and the north of the Greater Khingan Range. Climate factors had a considerable influence on the variation of the soil TN, and land-use types played a pivotal part in each climate zone. This high-resolution and high-quality soil TN data set in China can be very useful for future inventories of soil nitrogen, assessments of soil nutrient status, and management of arable land.

Spatial variability of soil total nitrogen, phosphorus and potassium in Renshou County of Sichuan Basin, China

Understanding soil nutrient distributions and the factors affecting them are crucial for fertilizer management and environmental protection in vulnerable ecological regions. Based on 555 soil samples collected in 2012 in Renshou County, located in the purple soil hilly area of Sichuan Basin, China, the spatial variability of soil total nitrogen (TN), total phosphorus (TP) and total potassium (TK) was studied with geostatistical analysis and the relative roles of the affecting factors were quantified using regression analysis. The means of TN, TP and TK contents were 1.12, 0.82 and 9.64 g kg−1, respectively. The coefficients of variation ranged from 30.56 to 38.75% and the nugget/sill ratios ranged from 0.45 to 0.61, indicating that the three soil nutrients had moderate variability and spatial dependence. Two distribution patterns were observed. TP and TK were associated with patterns of obvious spatial distribution trends while the spatial distribution of TN was characterized by higher variability. Soil group, land use type and topographic factors explained 26.5, 35.6 and 8.4% of TN variability, respectively, with land use being the dominant factor. Parent material, soil group, land use type and topographic factors explained 17.5, 10.7, 12.0 and 5.0% of TP variability, respectively, and both parent material and land use type played important roles. Only parent material and soil type contributed to TK variability and could explain 25.1 and 13.7% of TK variability, respectively. More attention should focus on adopting reasonable land use types for the purposes of fertilizer management and consider the different roles of the affecting factors at the landscape scale in this purple soil hilly area.

Spatio-Temporal Distribution of Total Nitrogen and Phosphorus in Dianshan Lake, China: The External Loading and Self-Purification Capability

In this article, long-term data, statistical analysis, and spatial interpolation method were applied to the analyses of the spatial and temporal changes of total nitrogen (TN) and total phosphorus (TP) in Dianshan Lake. We also estimated the self-purification capability of TN and TP in Dianshan Lake. The results showed that interannual variability of the average concentration of TN in Dianshan Lake changed significantly, showing a characteristic increase before a decline, and the average concentration of TN showed an obvious downward trend, especially after 2007. Interannual variability of the average concentration of TP in Dianshan Lake fluctuated, and the average concentration of TP showed a downward trend after 2007. The seasonal variations of TN and TP in Dianshan Lake were similar. Higher TN concentration occurred in winter and spring, while higher TP concentration appeared in summer, autumn, and winter. The spatial distribution of TN and TP in Dianshan Lake were similar, showing a characteristic which decreased from north to south and west to east. The highest TN and TP values were mainly distributed in the inlet monitoring sites, while the lowest TP values were distributed in the outlet monitoring sites. The self-purification capability of TN and TP were about 2289.97 t/yr and 112.16 t/yr, which suggested a deterioration of natural water quality. Our research showed that Dianshan Lake was highly eutrophic and that water quality showed a substantial improvement from 1996 to 2015.

Influencing factors of non-point source pollution of watershed based on boosted regression tree algorithm.

Non-point source (NPS) pollution has become a key water pollution problem under the condition of point source pollution was controlled. The complexity and uncertainty research of NPS pollution influential factors has always been important and difficult. This paper simulated NPS pollution of the Fanhe River watershed in 2003-2012 by the soil and water assessment tool (SWAT) and analyzed its spatial distribution. Meanwhile, the boosted regression tree (BRT) method was proposed to quantitatively analyze the corresponding influential factors including land use, soil, elevation and slope. The results showed that NPS pollution in the Fanhe River watershed had high spatial heterogeneity. The spatial distribution of total nitrogen (TN) had greater difference than that of total phosphorus (TP). The three pollutants, TN, TP and sediment, were all positively related to slope gradients (P<0.01). The slope gradients played the strongest role in determining the sediment and TP output with the contribution rate of 46.5% and 38.2%, respectively. Land use had important influence on sediment and TP loads, with the contribution rate of 27.2% and 35.3%, respectively. TN was produced abundantly in low-elevation and steep-slope locations and with cultivated land use. Cinnamon soil was most vulnerable to the TN load while meadow soil took the second place in terms of soil erosion and TP load. The paper overcame the complexity of influential factors for NPS pollution by BRT, and deepened the understanding of NPS pollution mechanism.

SPARROW Modeling of Nitrogen Sources and Transport in Rivers and Streams of California and Adjacent States, U.S.

AbstractThe SPARROW (SPAtially Referenced Regressions On Watershed attributes) model was used to evaluate the spatial distribution of total nitrogen (TN) sources, loads, watershed yields, and factors affecting transport and decay in the stream network of California and portions of adjacent states for the year 2002. The two major TN sources to local catchments on a mass basis were fertilizers and manure (51.7%) and wastewater discharge (15.9%). Other sources contributed &lt; 12%. Fertilizer use is widespread in the Central Valley region of California, and also important in several other regions because of the diversity of California agriculture. Precipitation, sand content of surficial soils, wetlands, and tile drains were important for TN movement to stream reaches. Median streamflow in the study area is about 0.04 m3/s. Aquatic losses of nitrogen were found to be most important in intermittent and small to medium sized streams (0.2‐14 m3/s), while larger streams showed less loss, and therefore are important for TN transport. Nitrogen loss in reservoirs was found to be insignificant, possibly because most of the larger ones are located upstream of nitrogen sources. The model was used to show loadings, sources, and tributary inputs to several major rivers. The information provided by the SPARROW model is useful for determining both the major sources contributing nitrogen to streams and the specific tributaries that transport the load.

Hyperspectral imaging for mapping of total nitrogen spatial distribution in pepper plant.

Visible/near-infrared (Vis/NIR) hyperspectral imaging was employed to determine the spatial distribution of total nitrogen in pepper plant. Hyperspectral images of samples (leaves, stems, and roots of pepper plants) were acquired and their total nitrogen contents (TNCs) were measured using Dumas combustion method. Mean spectra of all samples were extracted from regions of interest (ROIs) in hyperspectral images. Random frog (RF) algorithm was implemented to select important wavelengths which carried effective information for predicting the TNCs in leaf, stem, root, and whole-plant (leaf-stem-root), respectively. Based on full spectra and the selected important wavelengths, the quantitative relationships between spectral data and the corresponding TNCs in organs (leaf, stem, and root) and whole-plant (leaf-stem-root) were separately developed using partial least-squares regression (PLSR). As a result, the PLSR model built by the important wavelengths for predicting TNCs in whole-plant (leaf-stem-root) offered a promising result of correlation coefficient (R) for prediction (RP = 0.876) and root mean square error (RMSE) for prediction (RMSEP = 0.426%). Finally, the TNC of each pixel within ROI of the sample was estimated to generate the spatial distribution map of TNC in pepper plant. The achievements of the research indicated that hyperspectral imaging is promising and presents a powerful potential to determine nitrogen contents spatial distribution in pepper plant.

Geostatistical analyses of spatial distribution and origin of soil nutrients in long-term wastewater-irrigated area in Beijing, China

The purpose of this study was to investigate the current status of soil fertility in the long-term wastewater-irrigated agricultural areas of Beiyechang District in the suburb of Beijing. A total of 103 soil samples from the top 20 cm of soil layer were collected and analyzed for macro- and micronutrient elements. The mean values of these elements were: total nitrogen (TN), 0.08 ± 0.02%; available nitrogen (AN), 60.34 ± 10.08 mg/kg; available phosphorus (AP), 19.59 ± 9.75 mg/kg; available potassium (AK), 84.22 ± 19.66 mg/kg; and availabilities of trace elements (B, Cu, Fe, Mn, Mo, and Zn), 0.29 ± 0.12, 1.44 ± 0.34, 8.97 ± 2.05, 5.44 ± 0.95, 0.27 ± 0.16, 1.16 ± 0.42 mg/kg, respectively. Compared with other similar areas, the overall soil nutrient content in the study area was still at a low level after nearly 30 years of wastewater irrigation. The organic matter content of wastewater-irrigated soils has significant impact on the accumulation of nutrient elements in these soils. Geostatistical analyses suggested that the spatial distribution of TN and AP was on account of agricultural practices, such as wastewater irrigation and fertilizer use. The availability of P, Mo, Cu and Zn may be due to the joint effect of soil parent material and wastewater irrigation. The availability of K, Fe and Mn was attributed to soil parent material. A significant availability of some elements occurred around sewage outfalls in the irrigation area and water canals, where the wastewater could be easily lifted. The knowledge of spatial distribution and sources of soil nutrients in such areas is the basis for undertaking appropriate farming and irrigation activities with rationalized utilization of treated wastewater.

Combining CLUE-S and SWAT models to forecast land use change and non-point source pollution impact at a watershed scale in Liaoning Province, China

Non-point source (NPS) pollution has become a major source of water pollution. A combination of models would provide the necessary direction and approaches designed to control NPS pollution through land use planning. In this study, NPS pollution load was simulated in urban planning, historic trends and ecological protection land use scenarios based on the Conversion of Land Use and its Effect at Small regional extent (CLUE-S) and Soil and Water Assessment Tool (SWAT) models applied to Hunhe-Taizi River Watershed, Liaoning Province, China. Total nitrogen (TN) and total phosphorus (TP) were chosen as NPS pollution indices. The results of models validation showed that CLUE-S and SWAT models were suitable in the study area. NPS pollution mainly came from dry farmland, paddy, rural and urban areas. The spatial distribution of TN and TP exhibited the same trend in 57 sub-catchments. The TN and TP had the highest NPS pollution load in the western and central plains, which concentrated the urban area and farm land. The NPS pollution load would increase in the urban planning and historic trends scenarios, and would be even higher in the urban planning scenario. However, the NPS pollution load decreased in the ecological protection scenario. The differences observed in the three scenarios indicated that land use had a degree of impact on NPS pollution, which showed that scientific and ecologically sound construction could effectively reduce the NPS pollution load in a watershed. This study provides a scientific method for conducting NPS pollution research at the watershed scale, a scientific basis for non-point source pollution control, and a reference for related policy making.

Study on Spatial Distribution of OM, N, P in Surface Soil around Lake Chaohu

The concentration of total nitrogen (TN), total phosphorus (TP) and organic material (OM) at sixty grid division in Lake Chaohu basin around the lake was studied, in order to investigate their spatial distribution characteristics. The results showed that the average concentrations of TN, TP and OM were 1027 mg/kg, 483 mg/kg, 1.95%, and their concentrations ranged from 253 mg/kg to 2273 mg/kg, 223 mg/kg to 1173 mg/kg and 0.291% to 5.48%, respectively. The high concentration areas were located at the basins of Tuogao river and Zhao river while the low concentration areas were located at basins of Pai river, Nanfei river and Dianpu river. The concentrations of TN and OM were higher in East part than in West part. The spatial distribution of TN, TP and OM concentrations of the surface soil showed inconsistent with those of the water quality of the inflow rivers and the lake and the TN and TP of lake sediment studied.

Total nitrogen and total phosphorous in urban soils used for different purposes in Beijing, China

The concentration and spatial distribution of total nitrogen (TN) and total phosphorus (TP), as well as variations in their levels, in land used for various activities were investigated, and the Kriging interpolation method was applied to describe the spatial distribution of TN and TP in urban soils in Beijing, China. The concentration of soil TP was higher in the middle of the city and lower in the outsides of the city. However, the levels of soil TN had no definite spatial distribution pattern. The contents of TN and TP were compared in land used for different purposes, and the spatial distribution of TN and TP, as well as the impact of human activities on TN and TP contents, in urban soils were also analyzed. Our results demonstrated that the TN levels depend on the coverage of natural vegetation at each type of site, and the TP content is affected by the usage and disposal of phosphorus-containing materials at each type of site.

The distributions and effects of nutrients in the sediments of a shallow eutrophic Chinese lake

The temporal and spatial distribution of total nitrogen and total phosphate in the sediments of a shallow eutrophic Chinese lake (Lake Chao), and their relationships with the physical and chemical features of sediments, and their effects on the lake water quality and trophic state, are presented in this paper. The following results were obtained: (1) higher concentration of Tot-N and Tot-P in the sediments occurred in the summer and the autumn seasons; (2) higher annual average Tot-N and Tot-P concentrations were observed in the sediments near the various river mouths and in the western part of the lake; (3) Tot-N and Tot-P concentration in the lake sediments generally increased with increase in lake sediment Eh, pH, and Al2O3, and declined with decrease in lake sediment size diameters and SiO2; and, (4) correlations were observed in both the temporal and spatial distributions between the trophic state, Tot-N and Tot-P concentration in the lake water, and the Tot-N and Tot-P concentration found in the lake sediments.

Modelagem da Poluição não Pontual na Bacia do Rio Cuiabá Baseada em Geoprocessamento

Hydrologic modeling has been one of the analytic instruments available to help water resources management. The possibility of water quality monitoring resulting from the leaching of pollutants as a result of agricultural activities, called diffuse(non-point) pollution, is the central hypothesis of this study which seeks to identify and quantify water quality changes in the Cuiaba river basin, as a function of soil cover and land use. This basin was chosen because it lies in the state of Mato Grosso which has an eminently agricultural vocation, and is located upstream from the Pantanal complex, constituting an important area for environmental studies in Brazil. The Cuiaba River basin has a drainage area of approximately 29,000 km2. RBRH – Revista Brasileira de Recursos Hidricos Volume 8 n.4 Out/Dez 2003, 115-135 135 In this context, an attempt was made to develop a distributed hydrologic model based on geoprocessing via a geographic information system (GIS). Specifically, the spatial distribution of total nitrogen and total phosphorus as pollutants in the basin is evaluated, based on the integration of data on hydrometeorology, water quality, physiography, land use and occupation and images from the Landsat 7 – ETM+ sensor in a GIS environment. The results obtained by the model, when compared to historical water quality series in the Cuiaba river basin, indicated the acceptability of the methodology proposed as an indicator of spatial variability of mean water quality.