watersheds in the Pacific Northwest region of the United States: Burnt Bridge Creek, Salmon Creek, and the Tualatin River. All three watersheds have had many of their waterquality parameters exceeding Total Maximum Daily Loads as required by their state’s environmental agencies in the past decades. By using the National LandCover Datasets classified by the United States Geological Survey (USGS) for 1992, 2001 and 2006 and waterquality data for a period between 1991 and 2010, this paper aims to examine whether changes in landcover are causing changes in waterquality at two different spatialscales - at the sub-watershed scale and at a 100 meter riparian buffer scale. We used spatial regression models to identity the major determinants of changes in water temperature (WT), total suspended solids (TSS), dissolved oxygen (DO), and total phosphorus (TP) over time at different scales. The results show that each parameter reacts differently to landcoverchange depending on the scale of analysis. Both DO and WT showed significant relationships with landcover parameters on the watershed scale but not as much on the riparian buffer scale. TP shows significant relationships at the watershed scale, but TSS shows no significant relationships at the watershed scale. WT shows the only significant change in waterquality over the past twenty years and is positively related to change in urbanlandcover. Topographic variables become significant in explaining the variations in WT and TP at the riparian scale. DO is mostly explained by mean slope for both 1992 and 2001 at both scales, but urbanlandcover became an important predictor in 2006 at both scales. Our analysis also suggested that there may be a potential lag between changes in land management and changes in waterquality across different scales.
Thus, there is considerable variation in predicted outcomes for climate change, landcoverchange, and their potential im- pacts on streams (Praskievicz and Chang, 2009). Previous research in the Midwest, however, consistently indicates a strong likelihood of increased storm intensity and total pre- cipitation delivery in this region (Jha et al., 2004; Takle et al., 2010). Further, it has been suggested that small basins may experience greater impacts than larger ones (Praskevicz and Chang, 2009). The potential impacts of these changes on small streams in urban areas require additional investiga- tion in order to better elucidate their separate and combined effects and to identify appropriate mitigation strategies. In the research described in this paper, we examined five wa- tersheds from among 20 small urban headwater streams for which we collected waterquality and water quantity data over two years, 2011 and 2012. The five watersheds were purposefully selected to represent a gradient of percent IS, ranging from 5.3 to 37.1 %. Climate and landcoverchange were projected to the year 2040 using regressions based on historical data. We then used SWMM to create hydrological models for these watersheds to answer the following ques- tions:
Applications of TRAIN for the land-use classes represent- ing cropland were carried out assuming one growing season, with the cultivation of winter crops. This might lead to an un- derestimation of irrigation water requirements for those agri- cultural areas on which summer crops are grown. However, no information about criteria for the cultivation of summer crops were available. Also, no spatially explicit data set on the agricultural areas equipped for irrigation exists on the re- quired spatial resolution. Therefore, irrigation was assumed to be possible on any of the pixels allocated as agricultural land, unless the criteria described in Sect. 2.3 are fulfilled. So far, the growing seasons of the individual crops as well as of natural vegetation were held static, i.e., no year-to-year vari- ations due to differing meteorological conditions were taken into account. TRAIN was iteratively run on those grid cells which are expected to contain a high degree of sub-grid vari- ability, such as heterogeneous soil and land-use/land-cover combinations. For example, the land-use class “urban” was divided into two sub-classes representing sealed surfaces and park areas.
The study demonstrates the link between landcover/use and waterquality and the role of temporal (historical data analysis) and spatialscales (buffer areas) in understanding the influence of landcover and management of land use activities on waterquality. The databases used showed that when the spatial heterogeneity of the catchment was altered, either by human influences such as agriculture or by natural events such as fires, it was reflected in changes in the waterquality and quantity available as stream flow. Changes in land management could have a substantial impact in waterquality improvement, especially relevant where cost-efficient solutions to waterquality impairment are a requirement. This could include more efficient use of fertilizers in agricultural land management by reducing quantities of fertilizer applied or maintaining and/or establishing riparian buffer areas to mitigate the impacts to streams from the land-based activities. Vegetation (indigenous or exotic) as riparian buffers can also influence waterquality and a proper understanding of that role is necessary for effective land and water management.
An unexpected result of our analysis shows that there is essentially no variation in stormwater inlet and outlet levels among our study catchments (outside of the two “Well- Drained” cluster catchments), but the land-cover patterns that feed these networks are highly variable. It is plausible that variations in vegetation and building patterns, especially those that share edge boundaries with roads, could influence pollutant loads that reach streams via pipe networks. For example, “Lawn Mowers” catchments could see increased amounts of chemical-laden runoff flowing into stormwater networks as opposed to catchments featuring canopy covered developments like the “Shaded Urban Homestead” and “Semi-City Living” clusters. Cutting direct connections to streams could help mitigate any damaging effects (Hatt et al., 2004), but in order to develop a truly effective prescription we must first acknowledge the drivers of land-cover pattern variation.
2.2.3 General NPS pollution Models
A wide range of models have been developed to aid understanding of the NPS prob- lems. These models include simple screening and planning models, (Section 2.3). These hydrological and waterquality models serve different purposes but a good NPS pollution model should represent the spatial variability of the area and simulate the distributed physical process of water pollution (Kang and Bartholic, 1994; León et al., 2000). However, this type of distributed model not only requires large volumes of input data, but also creates equal (or more) amounts of output results. The difficulty in modelling NPS is the problem of identifying sources of pollution and quantifying the loads (León, et al., 2000). In contrast to a point source, diffuse pollution is an ag- gregate of small contaminant inputs distributed throughout a basin. Since the early 1970s, a large number of NPS models have been developed. There are two approach- es to model diffuse pollution. The more widely used are lumped-parameter models, while models that are more complex are based on the distributed-parameter concept. Reviews of the available runoff-waterquality models applicable to diffuse pollution modelling of urban and agricultural catchments cover a wide range of models (León et al., 2000). Some of the most relevant NPS models are ARMHSPF, AGNPS (Young et al., 1987) and N-SPECT (NOAA Coastal Services Center, 2004). Most of these models simulate processes of interception, infiltration, surface storage, and sur- face flow for the hydrological component. Some of them use the Soil Conservation Service (SCS) runoff curve number approach. For example, AGNPS calculates sur- face runoff for each grid-cell using the SCS Curve Number (CN) method (Grunwald, and Norton, 1999). The key parameter in this method is the curve number, which is dependent on land-use, soil type, and hydrologic condition. Surface runoff calculated in each grid cell is routed through the watershed based on flow directions from one grid cell to the next until it reaches the drainage outlet.
Water is basic to individuals and the biggest accessible wellspring of crisp water lies underground. Expanded requests for water have animated investigation of underground water assets. Water assets get contaminated because of fast industrialization, headway in agrarian methods, expanding populace and other unfavourable effects of situations. Every one of these elements may bring about changing the hydrological cycle. The urban natural quality dependably relies upon the utilization of land. The nature of the earth is controlled by concentrate the land utilize highlights and their effects are investigated. In the present investigation, an endeavour is had to assess the effect of land use/landcover on groundwater nature of Zone VII under the Greater Hyderabad Municipal Corporation (GHMC) zone. Different topical maps are set up from the toposheet on 1:50000 scale utilizing ArcGIS Software. The land-use/landcover guide of the investigation region is set up from the straightly improved melded information of IRS-1D PAN and LISS-III satellite symbolism by utilizing Visual Interpretation Techniques. Groundwater tests were haphazardly gathered at pre-decided inspecting areas dependent on satellite symbolism of the investigation zone. Every one of the examples was broken down for different physical-synthetic parameters embracing standard conventions for the age of trait information. In view of the outcomes got maps demonstrating spatial circulation of chose waterquality parameters is set up for the examination region. The varieties in the groupings of waterquality parameters showed high convergences of Alkalinity, TDS, Fluoride, Hardness, Nitrates are surpassed as far as possible while different parameters like Sodium, Sulfate and Chloride were inside as far as possible aside from in a couple of zones like Golnaka, Imlibun, Kamalanagar and so forth., which might be ascribed to leakage of residential squanders through open nallahs and modern squanders. The waterquality file (WQI) in the examination region is computed to decide the appropriateness of groundwater for drinking reason. Diverse appraisals of waterquality have been seen which showed falling apart nature of groundwater. Control and therapeutic measures for the change of groundwater quality in the examination zone are proposed.
In April 2008, citing the lack of adequate planning and effects of urbanization as major threats, the advocacy group American Rivers named the Catawba River the most endangered river in America (American Rivers, 2008). Mecklenburg County, NC, is the largest urban area along the course of the Catawba River. Its population of nearly 860,000 has nearly doubled in size since 1988. As might be expected, this growth has resulted in much environmental change in the county. More than 73 percent of the major stream miles in Mecklenburg County have been designated by the Environmental Protection Agency (EPA) as impaired, or not meeting the EPA’s designated uses (LUESA 2008). Degradation of these urbanstreams impacts local citizens’ recreational opportunities, property values, and public health. Since Mecklenburg County draws nearly all of its water from the Catawba River, environmental changes affect not only the river, but also the county’s long-‐term success.
Agricultural land conversion is strongly associated with changes
in waterquality, but the effect varies by parameter.
• What is the effect of restoration on stream waterquality?
It is early to tell the effectiveness of riparian restoration. Other
Landcover is a fundamental variable that impacts and links many parts of the human and physical environments. Landcoverchange is regarded as the single most important variable of global change affecting ecological systems (Vitousek, 1994) with an impact on the environment that is at least as large as that associated with climate change (Skole et al., 1994; Chen, 2002). Land usage that could increase the environmental quality is highly recommended to prevent flooding, make sure the soil water availability and so on. Land use change is one specific area that needed some researches to be done as we see its ecological impact that significant to the environment (Fang et al. 2006; Chen et al. 2003). Thus, a study is needed to be done in order to allocating the appropriate way to utilize the space according to its condition and environmental carrying capacity.
Abstract: Several waterquality and hydrologic parameters were measured to determine the physical, chemical and biological characters of six streams which flow into the Ömerli Reservoir (İstan- bul). It was aimed to investigate the effects of the streams on drinkable water reservoir. For this purpose water samples were collected from twelve sites in six streams at monthly intervals be- tween June 2005 and July 2006. Fifteen physical and chemical variables were measured to de- termine the waterquality. Principal components analysis (PCA) results indicated that stream width, flow rate and Chlorophyll-a were the most important variables in the streams. Total phosphate, ortho-phosphate, nitrite and dissolved oxygen were also found important. It is de- termined that human impacts, land use and geology of streams were the most important factors influencing chemical features of the stream water. Ömerli Reservoir was affected negatively by mainly the Paşaköy Stream. The Riva Stream which is discharge water of the reservoir had also a serious pollution problem. The other streams are relatively clear in terms of nutrient enrich- ment. Zooplankton species (25) were identified and canonical correspondence analysis (CCA) results indicated that nitrate, nitrite, orthophosphate, Chl-a, pH, water temperature, suspended solid material, oxygen and stream width were the most important variables influencing zoo- plankton diversity. Zooplankton species were quite poor in all of the streams with the excep- tion of Paşaköy and Riva streams. Indicator zooplankton species of eutrophication were found as dominant species in Paşaköy and Riva streams.
For further analysis, we subdivided the world into sub- basins, starting with subbasins larger than 30 000 km 2 (com- parable in size to the Meuse basin in Europe or the Allegheny basin in the USA). Subbasins smaller than 30 000 km 2 , mostly small endorheic or coastal basins covering only a few grid cells, were grouped. A few such small subbasins which do not border other small subbasins were not grouped into larger subbasins, so some subbasins smaller than 30 000 km 2 remain. This resulted in 3995 subbasins, with a mean area of 33 396 km 2 , ranging from 19.4 to 3 047 270 km 2 . The lat- ter large area consists of small subbasins grouped together along the Canadian and Greenlandic Arctic coast. Within these subbasins a further division was made based on the dominant landcoverchange (for instance, mainly a reduc- tion in tall natural vegetation and an increase in pasture; see Fig. A5) and the predominant Köppen–Geiger class, us- ing the Köppen–Geiger classification of climatic zones from Kottek et al. (2006). Table 2 shows the areas in these sub- basins. Most of the area within these subbasins experiences increased pasture cover at the expense of both tall and short natural vegetation (2000 minus 1850 landcover; green and red in Fig. A5, this also follows from Fig. 4). Conversion from tall natural vegetation to pasture is dominant in trop- ical South America and Africa as well as north and east- ern Australia (note that tall natural vegetation includes sa- vannas and shrubs as well as forests; see Sect. 2.2). Over midwest North America, southern South America, southern Africa, the Arabian Peninsula, central Asia and southwest Australia the main landcoverchange is from short natural
The household survey was carried out with a sample of randomly selected respondents with a pre-tested questionnaire. Households to be interviewed were randomly selected from the sampling frame developed through generating of random numbers (Aaker et al., 2003) assigned after homestead mapping with help of the local sub- chiefs and village elders of administrative areas from the households in each sub-location. The household was the sampling unit whereby both natives and immigrants were interviewed in the settlement clusters of urban, rural/urban and rural sub-locations. For each household, husband and wife were interviewed. In cases where a man had multiple wives, the resident woman in the household was selected for interview. Interviews were also carried out with women who were heads of households. A questionnaire containing both open-ended and closed-ended questions was administered to four hundred and nineteen households.The interviews were done by trained enumerators under the supervision of the principal researcher. The parameters covered included causes of land use/landcoverchange, current and future trends, and community perception on environmental easement and zoning with respect to land use master plan.
A spokesman for the district administration told the author that Katchi abadis are only acknowledged by the government if over 100 dwelling units in a cluster are located on government land, while slums can be located on public or private lands but they are not legally acknowledged by local, provincial or federal governments. According to him, katchi abadis are a subset of slums—ones whose existence is acknowledged by the government. Squatter settlements are again another subset of slums and refer to settlements where the occupants have unilaterally occupied land without permission or payment. Thus to get the status of being legally accepted as “katchi abadis” the residents of illegal slums sometimes manoeuvre things with the help of politicians. Usually with the help of lower government staff, these slums are shown in the government records as the dwellings that were growing very fast to force the district administration to give them the status of legal Katchi abadis, and further, after getting this status, to include them within the jurisdictional limits of city. In this way the urban limits of any city increases legally or illegally. While government interventions such as land regulations, property rights, and taxation and infrastructure investments are necessary for residents of urban areas, these slums, which are exempt in the sense of being outside the system, become serious obstacles to the development of cities. All of the participants admitted that the socio-economic conditions of the inhabitants of these squatter settlements are quite different from those of normal settlements. Some FG representatives, who belonged to big slums of Rawalpindi such as Shah Jewan colony, Sawan colony, Sadiq colony, Ahmadabad and Quaid-i-Azam colony, responded to my question about how life is in slums as follows: “Life is not treating us very kindly.” A woman (Rashida) during a visit to slum responded “Although life here’s not fair, but we do not have any other option”.
Landcover is the physical material at the surface of the earth. Land covers include grass, asphalt, trees, bare ground, water, etc. There are two primary methods for capturing information on landcover: field survey and analysis of remotely sensed imagery. Landcover is distinct from land use despite the two terms often being used interchangeably. Land use is a description of how people utilize the land and socio- economic activity - urban and agricultural land uses are two of the most commonly known land use classes. At any one point or place, there may be multiple and alternate land uses, the specification of which may have a political dimension. The origins of the „landcover / land use‟ couplet and the implications of their confusion are discussed in Fisher et al. (2005). One of the major landcover issues (as with all natural resource inventories) is that every survey defines similarly named categories in different ways. For instance, there are many definitions of „Forest‟, sometimes within the same organization, that may or may not incorporate a number of different forest features (stand height, canopy cover, strip width, inclusion of grasses, rates of growth for timber production). Areas without trees may be classified as forest cover if the intention is to re-plant (UK and Ireland), while areas with many trees may not be labelled as forest if the trees are not growing fast enough.
value. The upstream boundary was set so that the tracer was pumped into a constricted area of flow to encourage uniform distribution of the tracer vertically and laterally within the stream channel. The salt solution was injected over a 20 min period, and conductivity was measured at upstream and downstream locations to characterize the passage of the pulse. The pulse was measured every thirty seconds at a point below the injection where the water was sufficiently mixed (10-50 m downstream) and at the downstream end of the reach using Onset HOBO Fresh Water Conductivity Data Loggers. Data were recorded until all tracer had moved beyond the study reach, i.e., background SpC conditions returned. The rate of lateral inflow or outflow was calculated as the difference between upstream and downstream discharge divided by the reach length. Pre-injection background measurements of SpC were subtracted from readings during and after the injection to obtain the increase in SpC due solely to the injection (Mulholland et al. 1994). The background-corrected downstream conductivity values were used to define the breakthrough curve (BTC), which was further analyzed to parameterize hydrologic processes.
Water samples from all sampling sites were collected and stored in cool and dark containers and then preserved in a 90
refrigerator before being analyzed for other variables in the Water and Soil Quality Analysis Laboratory at Cuenca University. Particularly, ammonium (NH4 + ), nitrite (NO2 - ), nitrate (NO3 - ) and orthophosphate (PO4 3- ) were determined spectrophotometrically (low-range Hach test kits with Hach DR3900). Moreover, water samples were kept frozen until shipment to Belgium for further analyses, i.e. biochemical oxygen demand (BOD5), chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP). Details of the Hach kits can be found in the Supplementary Material S1. Hydro- 95
waterquality in surface drainage. This study used intolerant, tolerant and resistant benthic species as bioindicators of changes in waterquality of twostreams, taking in account particle size of sediments and volatile solids. Eight points were sampled in the stream Bandeirinha and four points in the stream Josefa Gomes in January and September 2013 in the municipality of Formosa-GO. The twostreams were chosen in order to study two different environments. The study used the diversity indexes of Shannon (H), Equitability (E) and Bray-Curtis Similarity and the grouping analysis method UPGMA (Unweighted Pair Group Method with Arithmetic Mean). The results of particle size and volatile solids study of Bandeirinha stream located in rural areas showed bioindicator species intolerant of changes in waterquality. The stream Josefa Gomes, completely inserted in an urban environment, showed alteration identified by tolerant and resistant species. The results demonstrate differences in waterquality in the rural and urban environments and the relationship of bioindicators with sediments. The study aids the interpretation of changes in the waterquality of the two drainages areas. Analysis of waterquality based upon benthic biological indicators associated with physical-chemical and geochemical analyses of water and sediments provide a better interpretation of the results.
1.8 Discussion of Findings
Between 1986 and 2003, urban areas increased significantly by 17.81 km 2 due to expansion in residential area coupled with increased anthropogenic activities over the region resulting from dynamic population growth that occurred between those years, and completion of development projects that were planned for that period. Vegetative cover lost a total of 11.48 km 2 , covering 46% of the study area by 2003, having dropped from 57% in 1986. This indicated that forest resources have been on the degradation due to effects of climate change, farming, logging activities, woods for domestic uses, construction of urban areas and other anthropogenic factors. The effects might not be immediate but if not curtailed it could be devastating especially if carbon is not sunk through the forest, and this was depicted in the results of the land surface temperature analysis. During this period, the mean land surface temperature increased by 6.5 0 C from 20.6 0 C to 27.1 0 C, an increase that was due to the growing urbanisation that occurred during this period. Built up areas were associated with average temperatures of 22.2 0 C
Another dominant pollutant source is BOD. Domestic waste causes oxygen content in low waters and high BOD . BOD comes from domestic waste home and home industry which is discharged directly to secondary canal which leads to Parit Tokaya. The next predominant pollutant indicator is the total value of coliform. Coliform bacteria is an indicator of the contamination of faeces or faeces of humans and animals in the waters, so its presence in the water is not desired, whether in terms of health, aesthetics, cleanliness and the possibility of a dangerous infection. Some types of diseases can be transmitted by coliform bacteria through water, especially stomach diseases such as typhoid, cholera, and dysentery . The total value of the coliform at the point 1 and the point 4 still include the threshold of the criteria for the quality of the river water class I, while at other points of observation is beyond the required threshold. Domestic waste water discharged without processing into the secondary canal that leads to the Parit Tokaya is one of the causes of pollution and the high value of total coliform in the canal. Another pollutant source that is quite dominant in Parit Tokaya is pathogenic E. Coli. Positive values (+) of pathogenic E. Coli obtained point 2 and point 4. The source of pollutants of the point 2 comes from the settlements around the secondary canal of Tanjungpura Street, while at the point 4 comes from the settlements located around the secondary canal of Ahmad Yani Street. Inadequate environmental sanitation conditions, for example, there is no communal WWTP (Waste Water Treatment Plant) in densely populated areas, so that household effluent discharged without processing into secondary canals leads to the Parit Tokaya is one of the causes of the discovery of contaminated pathogenic E. Coli water in the canal.