Spatial Variability of Groundwater Depth and Quality Parameters in the National Capital Territory of Delhi

The groundwater quantity and quality scenario is of much concern in the National Capital Territory of Delhi, India, which necessitates an investigation to envisage the extent of spatial variability of groundwater depth and pollutant concentration levels in this region. Therefore, in this study, an effort was made to generate the spatial variability map of groundwater depth and quality parameters (viz. chloride, electrical conductivity, fluoride, magnesium, and nitrate). Ordinary kriging was used to analyze the spatial variability of groundwater depth and quality parameters, whereas indicator kriging was used to analyze groundwater quality parameters equal to or greater than the pollution threshold values. It was observed that the semivariogram parameters fitted well in the exponential model for water depth and in the spherical model for water quality parameters. The generated spatial variability maps indicated that in 43% of the study area, groundwater depth was within 20 m. The salinity level was higher than 2.5 dS m⁻¹ in 69% of the study area and the nitrate concentration exceeded 45 mg l⁻¹ in 36% of the area. The probability maps showed that about 24% of the area had the highest probability (0.8–1.0) of exceedence of the threshold electrical conductivity value and an area of 2% exhibited the highest probability of exceedence of the threshold value of nitrate concentration in the groundwater. The generated spatial variability and probability maps will assist water resource managers and policymakers in development of guidelines in judicious management of groundwater resources for agricultural and drinking purposes in the study area.     

A novel method to determine buffer strip effectiveness on deep soils

Unfertilized buffer strips (BS) generally improve surface water quality. High buffer strip effectiveness (BSE) has been reported for sloping shallow aquifers, but experimental data for plain landscapes with deeply permeable soils is lacking. We tested a novel method to determine BSE on a 20-m-deep, permeable sandy soil. Discharge from soil to ditch was temporarily collected in an in-stream reservoir to measure its quantity and quality, both for a BS and a reference (REF) treatment. Treatments were replicated once for the first, and three times for the next three leaching seasons. No significant BSE was obtained for nitrogen and phosphorus species in the reservoirs. Additionally, water samples were taken from the upper groundwater below the treatments. The effect of BS for nitrate was much bigger in upper groundwater than in the reservoirs that also collected groundwater from greater depths that were not influenced by the treatments. We conclude that measuring changes in upper groundwater to assess BSE is only valid under specific hydrogeological conditions. We propose an alternative experimental set-up for future research, including extra measurements before installing the BS and REF treatments to deal with spatial and temporal variability. The use of such data as covariates will increase the power of statistical tests by decreasing between-reservoir variability.     

Baseflow nitrate in relation to stream order and agricultural land use

Management of agricultural nonpoint-source pollution continues to be a challenge because of spatial and temporal variability. Using stream order as an index, we explored the distribution of nitrate concentration and load along the stream network of a large agricultural watershed in Pennsylvania-the East Mahantango Creek Watershed and two of its sub-watersheds. To understand nitrate concentration variation in the stream water contributed from ground water, this study focused on baseflow. Impacts of agricultural land use area on baseflow nitrate in the stream network were investigated. Nitrate concentration showed a general decreasing trend with increasing stream order based on stream order averaged values; however, considerable spatial and temporal variability existed within each snapshot sampling. Nitrate loads increased with stream order in a power function because of the dominant effect of stream flow rate over the nitrate concentration. Within delineated sub-watersheds based on stream orders, positive linear functions were found between agricultural land use area percentage and the baseflow nitrate concentration and between agricultural drainage area and the nitrate load. The slope of the positive linear regression between the baseflow nitrate concentration and percent agricultural land area seems to be a valuable indicator of a watershed's water quality as influenced by agricultural practices, watershed size, and specific physiographic setting. Stream order seems to integrate, to a certain degree, the source and transport aspects of nonpoint-source pollution on a yearly averaged basis and thus might provide a quick estimate of the overall trend in baseflow nitrate concentration and load distribution along complex stream networks in agricultural watersheds.     

THE FLEXIBLE TOLERANCE METHOD FOR ESTIMATING HYDROLOGIC PARAMETERS IN THE ROOT ZONE1

In this study, a constrained minimization method, the flexible tolerance method, was used to solve the optimization problems for determining hydrologic parameters in the root zone: water uptake rate, spatial root distribution, infiltration rate, and evaporation. Synthetic soil moisture data were first generated using the Richards' equation and its associated initial and boundary conditions, and these data were then used for the inverse analyses. The results of inverse simulation indicate the following. If the soil moisture data contain no noise, the rate of estimated water uptake and spatial root distribution parameters are equal to the true values without using constraints. If there is noise in the observed data, constraints must be used to improve the quality of the estimate results. In the estimation of rainfall infiltration and surface evaporation, interpolation methods should be used to reduce the number of unknowns. A fewer number of variables can improve the quality of inversely estimated parameters. Simultaneous estimation of spatial root distribution and water uptake rate or estimation of evaporation and water uptake rate is possible. The method was used to estimate the water uptake rate, spatial root distribution, infiltration rate, and evaporation using long‐term soil moisture data collected from Nebraska's Sand Hills.     

Small-scale spatial variability of atrazine and dinoseb adsorption parameters in an alluvial soil

Soil sorption processes largely control the environmental fate of herbicides. Therefore, accuracy of sorption parameters is crucial for accurate prediction of herbicide mobility in agricultural soils. A combined experimental and statistical study was performed to investigate the small-scale spatial variability of sorption parameters for atrazine and dinoseb in soils and to establish the number of samples needed to provide a value of the distribution coefficient (K(d)) next to the mean, with a given precision. The study explored sorption properties of the two herbicides in subsurface samples collected from four pits distributed along a transect of an alluvial soil; two to four samples were taken at about 30 cm apart at each sampling location. When considering all the data, the distribution coefficients were found to be normally and log-normally distributed for atrazine and dinoseb, respectively; the CVs were relatively high (close to 50% for dinoseb and 40% for atrazine). When analyzed horizon by horizon, the data revealed distribution coefficients normally distributed for both herbicides, whatever the soil layer, with lower CVs. The K(d) values were shown to vary considerably between samples collected at very short distance (a few centimeters), suggesting that taking a single soil sample to determine sorption properties through batch experiments can lead to highly unrepresentative results and to poor sorption/mobility predictions.     

Cluster analysis and quality assessment of logged water at an irrigation project, eastern Saudi Arabia

A multivariate statistical technique, cluster analysis, was used to assess the logged surface water quality at an irrigation project at Al-Fadhley, Eastern Province, Saudi Arabia. The principal idea behind using the technique was to utilize all available hydrochemical variables in the quality assessment including trace elements and other ions which are not considered in conventional techniques for water quality assessments like Stiff and Piper diagrams. Furthermore, the area belongs to an irrigation project where water contamination associated with the use of fertilizers, insecticides and pesticides is expected. This quality assessment study was carried out on a total of 34 surface/logged water samples. To gain a greater insight in terms of the seasonal variation of water quality, 17 samples were collected from both summer and winter seasons. The collected samples were analyzed for a total of 23 water quality parameters including pH, TDS, conductivity, alkalinity, sulfate, chloride, bicarbonate, nitrate, phosphate, bromide, fluoride, calcium, magnesium, sodium, potassium, arsenic, boron, copper, cobalt, iron, lithium, manganese, molybdenum, nickel, selenium, mercury and zinc. Cluster analysis in both Q and R modes was used. Q-mode analysis resulted in three distinct water types for both the summer and winter seasons. Q-mode analysis also showed the spatial as well as temporal variation in water quality. R-mode cluster analysis led to the conclusion that there are two major sources of contamination for the surface/shallow groundwater in the area: fertilizers, micronutrients, pesticides, and insecticides used in agricultural activities, and non-point natural sources.     

Effects of Land Management Change on Spatial Variability of Organic Matter and Nutrients in Paddy Field: A Case Study of Pinghu,China

The Household Responsibility System initiated in the late 1970s in China has brought a profound change to its rural economy. The shift from the collective farming system to individual family farms has changed land management. The change, including fertilization and crop systems, may have significant effects on soil quality and agro-environmental sustainability. However, very little research is being carried out on the impact of reformed land tenure systems on the spatial variability of soil nutrients. In this study, geostatistics was applied to analyze changes in the spatial variability of soil organic matter and nutrients in paddy fields in Pinghu County, China after 20 years of land management change. In 1984 and 2002, 617 and 131 locations were selected, respectively, for collecting surface soil samples to analyze soil organic matter (SOM), total nitrogen (TN), available phosphorus (AP), and available potassium (AK). From 1984 to 2002, variability of the SOM and TN changed from strongly to moderately spatial-dependent, and the variability of AP remained weakly dependent on space, but that of the AK changed from moderately to weakly spatial-dependent. That the trend of the variability of four soil properties in 2002 became weaker than that in 1984 showed that the extrinsic factors (soil management practices, such as fertilization) weakened the effect by intrinsic factors (soil formation factors, such as soil parent materials) owing to a long period of land management change. The temporal geographic maps of the SOM and nutrients spatial distributions suggested that the concentrations of the SOM and nutrients had been changed to different extents during the period. Significant increase in AP and decrease in AK were noted. The changes were likely due to the imbalance between N, P, and K fertilizers and increased grain yield.     

Long-term effects of nitrogen fertilizer use on ground water nitrate in two small watersheds

Changes in agricultural management can minimize NO3-N leaching, but then the time needed to improve ground water quality is uncertain. A study was conducted in two first-order watersheds (30 and 34 ha) in Iowa's Loess Hills. Both were managed in continuous corn (Zea mays L.) from 1964 through 1995 with similar N fertilizer applications (average 178 kg ha(-1) yr(-1)), except one received applications averaging 446 kg N ha(-1) yr(-1) between 1969 and 1974. This study determined if NO3-N from these large applications could persist in ground water and baseflow, and affect comparison between new crop rotations implemented in 1996. Piezometer nests were installed and deep cores collected in 1996, then ground water levels and NO3-N concentrations were monitored. Tritium and stable isotopes (2H, 18O) were determined on 33 water samples in 2001. Baseflow from the heavily N-fertilized watershed had larger average NO3-N concentrations, by 8 mg L(-1). Time-of-travel calculations and tritium data showed ground water resides in these watersheds for decades. "Bomb-peak" precipitation (1963-1980) most influenced tritium concentrations near lower slope positions, while deep ground water was dominantly pre-1953 precipitation. Near the stream, greater recharge and mixed-age ground water was suggested by stable isotope and tritium data, respectively. Using sediment-core data collected from the deep unsaturated zone between 1972 and 1996, the increasing depth of a NO3-N pulse was related to cumulative baseflow (r2 = 0.98), suggesting slow downward movement of NO3-N since the first experiment. Management changes implemented in 1996 will take years to fully influence ground water NO3-N. Determining ground water quality responses to new agricultural practices may take decades in some watersheds.     

REGIONAL NITRATE LEACHING VARIABILITY: WHAT MAKES A DIFFERENCE IN NORTHEASTERN COLORADO

ABSTRACT: The high spatial variability of nitrate concentrations in ground water of many regions is thought to be closely related to spatially-variable leaching rates from agricultural activities. To clarify the relative roles of the different nitrate leaching controlling variables under irrigated agriculture in northeastern Colorado, we conducted an extensive series of leaching simulations with the NLEAP model using best estimates of local agricultural practices. The results of these simulations were then used with GIS to estimate the spatial variability of leachate quality for a 14,000 ha area overlying the alluvial aquifer of the South Platte River. Simulations showed that in the study area, differences in soil type might lead to 5–10 kg/ha of N variation in annual leaching rates while variability due to crop rotations was as much as 65 kg-N/ha for common rotations. Land application of manure from confined animal feeding operations may account for more than 100 kg-N/ha additional leaching. For a selected index rotation, the simulated nitrogen leaching rates across the area varied from 10 to 299 kg/ha and simulated water volumes leached ranged from 13 to 76 cm/yr depending on soil type, irrigation type, and use of manure. Resulting leachate concentrations of 3.5–140 mg/l NO₃ as N were simulated. Land application of manure was found to be the most important factor determining the mass flux of nitrate leached and the combination of sprinkler irrigation and manure application yields the highest leachate concentrations.     

ECONOMIC AND WATER QUALITY EFFECTS OF VARIABLE AND UNIFORM APPLICATION OF NITROGEN1

ABSTRACT: Nitrogen (N) fertilizer rates for achieving optimum crop yields often vary within a field due to spatial variability in soil moisture and nitrogen content and other crop growth factors. When there is substantial within-field variability in these factors, uniform application of N (UAN) may not be economically efficient in terms of maximizing net return because N is likely to be over-applied in some areas and under-applied in other areas of the field. In addition, over-application can adversely affect water quality. A sample of fields in a Midwestern agricultural watershed is used to test for statistically significant differences in N application rates, crop yields, surface and ground water quality and net returns between UAN and variable application of N (VAN) for four cropping systems. Profitability and water quality benefits of VAN are sensitive to the distribution of soil types within a field. Water quality effects and profitability of UAN and VAN vary with cropping systems. VAN is not uniformly superior to UAN in terms of increasing net returns and improving water quality for the farming systems and watershed evaluated in this study.     

Estimating dissolved reactive phosphorus concentration in surface runoff water from major Ontario soils

Phosphorus (P) loss from agricultural land in surface runoff can contribute to eutrophication of surface water. This study was conducted to evaluate a range of environmental and agronomic soil P tests as indicators of potential soil surface runoff dissolved reactive P (DRP) losses from Ontario soils. The soil samples (0- to 20-cm depth) were collected from six soil series in Ontario, with 10 sites each to provide a wide range of soil test P (STP) values. Rainfall simulation studies were conducted following the USEPA National P Research Project protocol. The average DRP concentration (DRP30) in runoff water collected over 30 min after the start of runoff increased (p < 0.001) in either a linear or curvilinear manner with increases in levels of various STPs and estimates of degree of soil P saturation (DPS). Among the 16 measurements of STPs and DPSs assessed, DPS(M3) 2 (Mehlich-3 P/[Mehlich-3 Al + Fe]) (r2 = 0.90), DPS(M3)-3 (Mehlich-3 P/Mehlich-3 Al) (r2 = 0.89), and water-extractable P (WEP) (r2 = 0.89) had the strongest overall relationship with runoff DRP30 across all six soil series. The DPS(M3)-2 and DPS(M3)-3 were equally accurate in predicting runoff DRP30 loss. However, DPS(M3)-3 was preferred as its prediction of DRP30 was soil pH insensitive and simpler in analytical procedure, ifa DPS approach is adopted.     

Spatial variability of nitrous oxide emissions and their soil-related determining factors in an agricultural field

To evaluate spatial variability of nitrous oxide (N2O) emissions and to elucidate their determining factors on a field-scale basis, N2O fluxes and various soil properties were evaluated in a 100- x 100-m onion (Allium cepa L.) field. Nitrous oxide fluxes were determined by a closed chamber method from the one-hundred 10- x 10-m plots. Physical (e.g., bulk density and water content), chemical (e.g., total N and pH), and biological (e.g., microbial biomass C and N) properties were determined from surface soil samples (0-0.1 m) of each plot. Geostatistical analysis was performed to examine spatial variability of both N2O fluxes and soil properties. Multivariate analysis was also conducted to elucidate relationships between soil properties and observed fluxes. Nitrous oxide fluxes were highly variable (average 331 microg N m(-2) h(-1), CV 217%) and were log-normally distributed. Log-transformed N2O fluxes had moderate spatial dependence with a range of >75 m. High N2O fluxes were observed at sites with relatively low elevation. Multivariate analysis indicated that an organic matter factor and a pH factor of the principal component analysis were the main soil-related determining factors of log-transformed N2O fluxes. By combining multivariate analysis with geostatistics, a map of predicted N2O fluxes closely matched the spatial pattern of measured fluxes. The regression equation based on the soil properties explained 56% of the spatially structured variation of the log-transformed N2O fluxes. Site-specific management to regulate organic matter content and water status of a soil could be a promising means of reducing N2O emissions from agricultural fields.     

Evaluation of spatial and temporal variation in water quality by pattern recognition techniques: A case study on Jajrood River (Tehran,Iran)

In this paper, principal component analysis (PCA) and hierarchical cluster analysis (CA) methods have been used to investigate the water quality of Jajrood River (Iran) and to assess and discriminate the relative magnitude of anthropogenic and “natural” influences on the quality of river water. T, EC, pH, TDS, NH₄, NO₃, NO₂, Turb., T.Hard., Ca, Mg, Na, K, Cl, SO₄, SiO₂ as physicochemical and TC, FC as biochemical variables have been analyzed in the water samples collected every month over a three-year period from 18 sampling stations along a 50 km section of Jajrood River that is under the influence of anthropogenic and natural changes. Exploratory analysis of experimental data has been carried out by means of PCA and CA in an attempt to discriminate sources of variation in water quality. PCA has allowed identification of a reduced number of mean 5 varifactors, pointing out 85% of both temporal and spatial changes. CA classified similar water quality stations and indicated Out-Meygoon as the most polluted one. Ahar, Baghgol, Rooteh, Befor Zaygan, Fasham, Roodak and Lashgarak were identified as affected by organic pollution. A Scree plot of stations in the first and second extracted components on PCA also gave us a classification of stations due to the similarity of pollution sources. CA and PCA led to similar results, though Out-Meygoon was identified as the most polluted station in both methods. Box-plots showed that PCA could approximately demonstrate temporal and spatial variations. CA gave us an overview of the problem and helped us to classify and better explain the PCA results.     

Impact of sampling techniques on measured stormwater quality data for small streams

Science-based sampling methodologies are needed to enhance water quality characterization for setting appropriate water quality standards, developing Total Maximum Daily Loads, and managing nonpoint source pollution. Storm event sampling, which is vital for adequate assessment of water quality in small (wadeable) streams, is typically conducted by manual grab or integrated sampling or with an automated sampler. Although it is typically assumed that samples from a single point adequately represent mean cross-sectional concentrations, especially for dissolved constituents, this assumption of well-mixed conditions has received limited evaluation. Similarly, the impact of temporal (within-storm) concentration variability is rarely considered. Therefore, this study evaluated differences in stormwater quality measured in small streams with several common sampling techniques, which in essence evaluated within-channel and within-storm concentration variability. Constituent concentrations from manual grab samples and from integrated samples were compared for 31 events, then concentrations were also compared for seven events with automated sample collection. Comparison of sampling techniques indicated varying degrees of concentration variability within channel cross sections for both dissolved and particulate constituents, which is contrary to common assumptions of substantial variability in particulate concentrations and of minimal variability in dissolved concentrations. Results also indicated the potential for substantial within-storm (temporal) concentration variability for both dissolved and particulate constituents. Thus, failing to account for potential cross-sectional and temporal concentration variability in stormwater monitoring projects can introduce additional uncertainty in measured water quality data.     

Vegetation as an Indicator of Soil Properties and Water Quality in the Akarçay Stream (Turkey)

In this study, the relationship among water quality, soil properties, and plant coverage in the region of the Akarçay stream was examined. Correlation analyses were carried out between soil samples taken from each of four plant communities in the Akarçay basin and water in the Akarçay stream. The four plant communities in the study area are as follows: Limonium lilacinum (Boiss. et Bal.) Wag., Alhagi pseudalhagi (M. Bieb.) Desv. Peganum harmala L., and Hordeum marinum Huds. subsp. marinum. B, Cl, EC, K, Mg, Na, pH, and SO₄ data from both soil and water samples were subjected to statistical analysis, and significant correlations were obtained (p < 0.05). These correlations indicated that the chemical features of the soil had a major effect on water quality. The important parameters were B, Cl, EC, K, Mg, Na, pH, and SO₄ for Limonium lilacinum communities; Ca, K, and pV for Peganum harmala; and B, Cl, Mg, pH, and pV for Alhagi pseudalhagi. There were also statistically significant relationships (p < 0.05) among the parameters examined. These findings strongly suggested that these plant communities can be used as indicators for soil chemistry and water quality.     

NITRATE CONCENTRATIONS IN KARST SPRINGS IN AN EXTENSWELY GRAZED AREA1

ABSTRACT: The impact on water quality by agricultural activity in karst terrain is an important consideration for resource management within the Appalachian Region. Karst areas comprise about 18 percent of the Region's land area. An estimated one-third of the Region's farms, cattle, and agricultural market value are located on karst terrain. Nitrate concentrations were measured in several karst springs in Southeastern West Virginia in order to determine the impact of animal agriculture on nitrate pollution of the karst ground water system. Karst basins with 79, 51, 16, and 0 percent agriculture had mean nitrate concentrations of 15.8, 12.2, 2.7, and 0.4 mg/l, respectively. A strong linear relationship between nitrate concentration and percent agricultural land was shown. Median nitrate concentration increased about 0.19 mg l^-1 per percent increase in agricultural land. Weather patterns were also found to significantly affect the median nitrate concentrations and the temporal variability of those concentrations. Lower nitrate concentrations and lower temporal variability were observed during a severe drought period. It was concluded that agriculture was significantly affecting nitrate concentrations in the karst aquifer. Best management practices may be one way to protect the ground water resource.     

The Water‐Year Water Balance of the Colorado River Basin

Model‐estimated monthly water balance components (i.e., potential evapotranspiration, actual evapotranspiration, and runoff (R)) for 146 United States (U.S.) Geological Survey 8‐digit hydrologic units located in the Colorado River Basin (CRB) are used to examine the temporal and spatial variability of the CRB water balance for water years 1901 through 2014 (a water year is the period from October 1 of one year through September 30 of the following year). Results indicate that the CRB can be divided into six subregions with similar temporal variability in monthly R. The water balance analyses indicated that approximately 75% of total water‐year R is generated by just one CRB subregion and that most of the R in the basin is derived from surplus (S) water generated during the months of October through April. Furthermore, the analyses show that temporal variability in S is largely controlled by the occurrence of negative atmospheric pressure anomalies over the northwestern conterminous U.S. (CONUS) and positive atmospheric pressure anomalies over the southeastern CONUS. This combination of atmospheric pressure anomalies results in an anomalous flow of moist air from the North Pacific Ocean into the CRB, particularly the Upper CRB. Additionally, the occurrence of extreme dry and wet periods in the CRB appears to be related to variability of the Atlantic Multidecadal Oscillation and the Pacific Decadal Oscillation.     

Spatial variability of soil carbon in forested and cultivated sites: implications for change detection

The potential to sequester atmospheric carbon in agricultural and forest soils to offset greenhouse gas emissions has generated interest in measuring changes in soil carbon resulting from changes in land management. However, inherent spatial variability of soil carbon limits the precision of measurement of changes in soil carbon and hence, the ability to detect changes. We analyzed variability of soil carbon by intensively sampling sites under different land management as a step toward developing efficient soil sampling designs. Sites were tilled cropland and a mixed deciduous forest in Tennessee, and old-growth and second-growth coniferous forest in western Washington, USA. Six soil cores within each of three microplots were taken as an initial sample and an additional six cores were taken to simulate resampling. Soil C variability was greater in Washington than in Tennessee, and greater in less disturbed than in more disturbed sites. Using this protocol, our data suggest that differences on the order of 2.0 Mg C ha(-1) could be detected by collection and analysis of cores from at least five (tilled) or two (forest) microplots in Tennessee. More spatial variability in the forested sites in Washington increased the minimum detectable difference, but these systems, consisting of low C content sandy soil with irregularly distributed pockets of organic C in buried logs, are likely to rank among the most spatially heterogeneous of systems. Our results clearly indicate that consistent intramicroplot differences at all sites will enable detection of much more modest changes if the same microplots are resampled.     

Changes in ground water quality in an irrigated area of southern Alberta

Few studies have documented spatial and temporal variations in ground water quality in areas with high densities of animal farming operations (AFOs), or the long-term effects on surface-water quality. Changes in ground water quality were characterized in an irrigated area with a high density of AFOs in southern Alberta, Canada to evaluate the effect on ground water quality of manure application to fields. Fifty-five piezometers in the oxidized zone were sampled once or twice annually from 1995 to 2001, and temporal changes were analyzed using mixed model analysis. Average NO3- -N increased significantly from 12.5 to 17.4 mg L(-1) and average Cl- increased significantly from 19.4 to 34.4 mg L(-1) in piezometers installed in an unconfined sand aquifer at locations receiving fertilizer and manure. Compared with these manured locations, nitrate and chloride concentrations were significantly lower in shallow aquifer water in areas of pasture or native range, and concentrations did not change significantly with time. Nitrate and chloride concentrations in shallow ground water in fine-textured manured locations did not change significantly. Ground water below about 6 m in till and fine lacustrine sediments contains 18O signatures indicative of recharge under preirrigation or glacially influenced conditions, suggesting this ground water has a low vulnerability to agricultural contamination. Evaluations suggest that shallow ground water discharge will cause NO3- -N and Cl- in the Oldman River to increase by factors of at least 4.3 and 1.3, respectively, with more significant effects in smaller streams and under low-flow conditions.     

Mitigating the Effects of Landscape Development on Streams in Urbanizing Watersheds

This collaborative study examined urbanization and impacts on area streams while using the best available sediment and erosion control (S&EC) practices in developing watersheds in Maryland, United States. During conversion of the agricultural and forested watersheds to urban land use, land surface topography was graded and vegetation was removed creating a high potential for sediment generation and release during storm events. The currently best available S&EC facilities were used during the development process to mitigate storm runoff water quality, quantity, and timing before entering area streams. Detailed Geographic Information System (GIS) maps were created to visualize changing land use and S&EC practices, five temporal collections of LiDAR (light detection and ranging) imagery were used to map the changing landscape topography, and streamflow, physical geomorphology, and habitat data were used to assess the ability of the S&EC facilities to protect receiving streams during development. Despite the use of the best available S&EC facilities, receiving streams experienced altered flow, geomorphology, and decreased biotic community health. These impacts on small streams during watershed development affect sediment and nutrient loads to larger downstream aquatic ecosystems such as the Chesapeake Bay.