waterquality of the Lower Aransas River Basin could be impacted by changes in LULC and precipitation would provide useful information for adaptive management of the coastal and estuarine environment.
Coastal areas of the M-A region have recreational value that has driven urban development, especially in Aransas County (Morehead, Beyer, and Dunton 2007). Tourism and population has driven much of the increased concentration of urbanization along the coast. Most counties in the Aransas region have been experiencing population increases with communities becoming more densely populated (Morehead, Beyer, and Dunton 2007). The tourism industry and population dynamics are likely to cause increases in urban area. Furthermore, previous work has shown that developed land is expanding at fairly rapid rate. The expansion of developed land is characterized by the removal of permeable vegetative cover and the expansion of impervious surfaces that reduces infiltration; allowing greater amounts of rainfall to be converted to surface runoff that washes out sediment and pollutants stored on the surface to receiving water bodies. Thus, simulating SWAT with various scenarios of increasing development and precipitation within the Lower Aransas River Basin could provide some insight on how watershedhydrology could be impacted in the future.
Climate and landuse changeimpacts are related to the hydrology of a watershed. An effective watershed management integrates these complex relationships among climate, landuse cover, soil, water and the environment. Under changing conditions, hydrologic models can be employed as management tool to create scenario and simulate hydrological components in a watershed (Mango et al., 2011). Different hydrologic models have been developed and applied to help understand such interactions. They provide a framework for investigating the complex effects of landuse change (Wang et al., 2014; Khadka, 2012; Gyamfi et al., 2016), climate change (Aich et al., 2014; Yira et al., 2017; Fang et al., 2015) and combined impacts of climate and landuse changes on watershedhydrology (Legesse et al., 2003; Qi et al., 2009; Sead et al., 2010; Mango et al., 2011; Khoi and Suetsugi, 2014). Sead et al. (2010) studied the impacts of landuse and climate change on streamflow in the Blue Nile River using the Soil and Water Assessment Tool (SWAT) model. The simulated results showed that, in the future, changes in climate and landuse will have a significant impact on streamflow. Mango et al. (2011) applied the SWAT model to assess the hydrological impacts to changes in landuse and climate change in the Mara river basin, Kenya. They reported that further deforestation would increase peak flows and reduce dry season flows while rising temperature caused by climate change will increase evapotranspiration and reduced runoff. Qi et al. (2009) applied the Precipitation Runoff Modeling System (PRMS) model to evaluate the hydrologic response to changes in climate and landuse in North Carolina. They reported that the catchment is more sensitive to changes in climate than landuse change, though both can cause significant water quantity and quality problems. Gyamfi et al. (2016) reports the impacts of various landuse and coverchange in the olifants Basin, South Africa. They reported a 46.97% increase in runoff as a result of decrease in rangeland while agricultural land, urban and forest lands were increased. Khoi and Suetsugi (2014) studied the impacts of climate and land-use changes in Be
The potential for growing cellulosic crops such as Alamo switchgrass, Miscanthus × giganteus, big bluestem and biomass sorghum as bioenergy crops was studied by several researchers in different parts of the world through field experimentation (Heaton et al., 2008; Zatta et al., 2014; Yimam et al., 2014, 2015; Oikawa et al., 2015; Zhang et al., 2015a) and hydrologic and waterqualitymodeling (Wright, 2007; Jain et al., 2010; Qin et al., 2011; Zhuang et al., 2013; Qin et al., 2015). Alamo switchgrass is a perennial C4 warm-season bunch grass native to North America, and it is found in low, moist areas and prairies of north-central Texas (Diggs et al., 1999). Miscanthus × giganteus is also a C4 warm-season perennial grass (Heaton et al., 2004, 2008) that is native to Southeast Asia (Ohwi, 1964) and Africa (Adati and Shiotani, 1962). Big bluestem is a C4 warm-season perennial native grass that comprises as much as 80% of the plant biomass in prairies in the Midwestern grasslands of North America (Gould and Shaw, 1983; Knapp et al., 1998). Biomass sorghum is an annual photoperiod sensitive C4 type cellulosic crop that adapts to the subtropical and temperate climates (Rooney et al., 2007). Several field studies that evaluate the feasibility of growing these bioenergy crops/grasses are in progress in the THP. However, evaluation of long-term effects of growing cellulosic bioenergy crops would be necessary before adopting them on a large-scale, and hydrologic and waterquality models are very useful for such purposes.
We now focus on the possibility of triggering convection by considering the atmospheric conditions. Figure 11 shows the median of the diurnal cycle of the planetary boundary layer (PBL), lifting condensation level (LCL), level of free convection (LFC), and convective available potential energy (CAPE) calculated at the lowest model level, of the 18 cases in the REF experiment. We show the median because the mean is influenced more by outliers from individual cases. For REF+1, FUT, and FUT+1, the average difference with regards to REF is given for each of these variables. The dif- ferences are normalized with respect to the mean values in REF, so a relative increase is given at every time. On aver- age, the PBL increases to about 800 m during daytime and reaches the LCL at around 09:00 UTC. In the figure, the LFC remains well above the PBL and LCL. In many in- dividual cases, however, the LFC drops to about 800 m as well, permitting (deep) convection. The LFC reaches its low- est level at 11:00 UTC. This coincides with the time of the highest precipitation intensities in the model (Fig. 8). CAPE increases up to 09:00 UTC, while the LFC decreases and then stabilizes because of the rain and associated temperature and humidity changes. The early onset and intensification of pre- cipitation in the model (Fig. 8) contributes to the small build- up of CAPE and could explain the underestimation of ex-
Collection of socio-economic data was initiated by a reconnaissance survey for obtaining a general understanding of the study area and for work planning. A household survey based on questionnaire was conducted in 124 households randomly sampled from the two studied Kebeles, which had a total of 1222 households. Among the respondents 23 were female headed households. Two (2) focus group discussions in each Kebele were held for the purpose of generating qualitative information that could complement data from questionnaire and remote sensing. Further, twelve (12) key informants having lived long time in study area were interviewed. Those included natural resource management experts, local elders, environmental and land management experts and administration staff at Kebele and woreda level and both from the upstream and downstream sites. The selection of key informants was made with the help of district and Kebele officers. The purpose was to triangulate information and obtaining an in-depth understanding of drivers of landusechange in the study area.
The estimated impacts of LUC on global mean DRE ignores the potential for more substantial regional changes in climate driven by LUC. Figure 3 illustrates the regional aerosol DRE from four idealized LUC scenarios: i) tropical deforestation and replacement by agriculture (soybean); ii) tropical deforestation and replacement by oil palm; (iii) boreal forest fire followed by natural succession, (iv) temperate hardwood deforestation and replacement by agriculture and pine plantation. We focus here on aerosols; the complex response of ozone to changes in emissions and deposition at various spatial scales is not easily captured in these idealized scenarios. We estimate changes in aerosol sources based on literature values for emission factors, biomass density and BSOA yields, assume a 5 day atmospheric lifetime, and apply median AeroCom radiative efficiencies from Myhre et al. 131 to convert these changes
different methods. For example, based on statistical models of two-year flood events, Moglen et al. (2004) reported HDIs for individual floods that were three to four times larger in small urban catchments than similar rural catchments. Statistical modeling of flood risks in the Upper Coastal Plain of South Carolina—based on observed urban floods—found that urban two-year instantaneous peak discharges had increased over comparable rural two-year discharges by a multiple of 13.5; i.e., ratios of urban-to-rural two-year discharges (HDI_Q 2 ) were 13.5 (Bohman, 1992). Moreover, Bohman (1992) demonstrated lower multiples for larger floods and predicted larger multiples for smaller stormflows. This study corroborates Bohman’s findings by confirming that smaller, frequently occurring storm flows have larger multiples than the two- to five-hundred-year events that he studied. This supports the second hypothesis that urban peak discharges— standardized for rainfall—increased substantially in the RBW. Apparently, the highly permeable, sandy soils and hilly topography of the Carolina Sandhills exaggerate the influence of urbanization on runoff. Conversion of forested surfaces in the Sandhills to buildings and pavement generates a larger increase in runoff than would occur with similar urbanization on less permeable surfaces in the Piedmont or less hilly surfaces in the lower Coastal Plain.
Figure 3: Diagram demonstrating the Transposition Cycle for the São Francisco river. In order to optimize hydroelectric generation in the basin, biomass may be planted in locations with low hydropower potential. Biomass, especially eucalyptus, require large quantities of water. If the plantation is located at the São Francisco river mouth, the water will be used for irrigation and will be released into the atmosphere as moisture in the air. The strong trade winds carry the moisture back inland from the São Francisco river mouth, in the opposite direction of the São Francisco river flow. This moisture may increase rainfall in the São Francisco basin and, thus, it may create a partially closed artificial water cycle, as described in Figure 3, having a positive impact on hydroelectric generation in the basin, reducing the amount of water that returns to the ocean and increasing the water availability in Brazil.
The world population has been increasing while, similarly, both the number of environmental disasters and the loss resulting from those have been on the rise. It is also expected that the trend will continue. Especially, what is notice- able is that more and more people and property concentrate on cities. In fact, urbanization is a major global trend simply because most people want to get their jobs, raise and educate their children, and enjoy riches of diverse cul- tures, recreation activities, and entertainment, which cities can provide to them. Urbanization always involves transforming the natural environment into a man-made environment, contributing to changes in landuse and landcover patterns as well as in landscape and hydrology in the built-up areas. These changes, in turn, negatively influence the natural environment because those changes almost always tend to result in the disruption of its fragile eco- systems in balance. In addition, the changes mean the land used, for example, for a natural ecosystem may be converted into an impervious land, which can increase human vulnerability to floods, causing human and property losses. There has been some research done to investigate the relationship between landuse/landcoverchange and environmental hazards. However, little re- search has been conducted to test direct effects of landcoverchange on envi- ronmental disasters such as floods, hurricanes, and hazardous material re- leases by using GIS and remote sensing technologies. Therefore, this research aimed to analyze the effect of landcoverchange on floods. More specifically, the research tested whether landcoverchange is related to flood disasters in Texas from 1993 to 2012. One of the main findings of this research is that both decrease in forest areas and increase in urban built-up areas contributed to the property damage resulting from flood events.
reference landuse and landcover classes, and on the biomass changes calculated for the scenarios; gains are considered only within the extent of occurrence of each species. We did not consider other factors than habitat that could affect species capacity of moving or adapting to changes.
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 landuse/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.
considered to as an alteration of the surface components. Change detection is used in Forest or vegetation, landscape and urban change. The process of identifying differences in the state of an object or phenomenon by observing it at different times. It is useful in many applications such as landuse changes, habitat fragmentation, rate of deforestation, coastalchange, urban sprawl and other cumulative changes. It involve the application of multi temporal datasets to quantatively analyze the temporal effects. Therefore, we have used RS and GIS to study landuselandcover Samastipur district, Samastipur is one of the thirty- eight districts of Bihar. Samastipur is a district in Bihar which is spread over an area of 2904 sq. kms. The people of Samastipur mainly speak Hindi. According to the 2011 census, Population Density in the District is 1465 per sq.km. and the total population is 4.25 million. The district comprises of 4 sub-divisions, and 20 Blocks. The latitude of Samastipur, Bihar, India is 25.862968, and the longitude is 85.781029. Samastipur, Bihar, India is located at India country in the Cities place category with the gps coordinates of 25° 51’46.6848”N and 85° 46’51.7044”E.
Another complication is that LULC data obtained from the SWFWMD are based on photo interpretations of digital imagery and that digital imagery is not always collected in the same season every year and the scale of these datasets may differ from year to year, therefore there is likely room for some inconsistency within this data set. In addition, LULC data were not collected annually prior to 2005, this means that for basins such as 151, with long-term waterquality sampling, there is not annual LULC data to compare to. For this study, only two years of LULC data was used that coincided with the available waterquality sampling period, an initial and final year. This limited the available data for the correlation and regression analysis and likely limited the amount and/or strength of the relationships that were found. Especially for the regression, as it was ultimately decided to remove several land-use types because they only had ≤ 5 data points and were causing misleading results within the models.
Landuse is the “series of operations and associated inputs on land, carried out by humans, with the intention to obtain products and/or benefits through using land resources” (McConnell and Moran, 2006). Since landcoverchange is the result of overlapping multiple landuse processes, therefore there is not a one-to-one relationship between landuse and landcover, and it is a strong possibility that a single piece of land will have only one landcover but may have many land uses (Cihlar and Jansen, 2001). Because of this complexity, research into the patterns, processes and impacts of landuse and landcover therefore requires multiple disciplines and employs a range of methods, including remote sensing, census data analysis, and qualitative field based methods. The main focus of this chapter has been to study urban expansion and landcoverchange of a rapidly urbanizing district. Following paragraphs throw light on how the combination of RS and field methods can help research to move across scales, ultimately providing data that is more useful to policy- and decision-makers. Whereas the satellite data provided extent and coverage i.e. answered the “what & where” questions but human geographers are also interested in “why” it happened. Thus field work and qualitative method such as participant observation; interviews, focus group discussions and perimeter walks, all have quenched the thirst of the researcher regarding the integration of local perceptions of landcover and landuse directly into the remote sensing portion of the analysis. In fact the field work has provided the researcher with an opportunity for his own mental mapping of the area based on remote sensing and local human knowledge. Thus it can safely be said that qualitative field-based methods helped the researcher a lot to gain insights into the multiple meanings of landcover and landuse that were hidden using remote sensing methods. Likely remote sensing helped the people to recognise their area. For instance, in this research many participants and interviewees had difficulty in recalling the changing use of the area, land prices at different periods of time, the industrialization process of the area, etc. Ultimately, with the help of satellite images, they were able to recall and recognise many features.In a nutshell, in this research, qualitative and remote sensing data both were used as a system of checks and balances on each other, providing a multi-layered picture of urbanization and its land uses.
García-Ruiz JM, Lasanta T, Ruiz-Flaño P, Ortigosa L, White S, González C, Martí C. 1996. Land-use changes and sustainable development in mountain areas: A case study in the Spanish Pyrenees. Landscape Ecology 11(5):267–277. González-Martínez SC, Bravo F. 2001. Density and population structure of the natural regeneration of Scots pine (Pinus sylvestris L.) in the High Ebro Basin (Northern Spain). Annales des Sciences Forestières 58:277–288. Latron J. 2003. Estudio del funcionamiento hidrológico de una cuenca mediterránea de montaña (Vallcebre, Pirineos Catalanes) [PhD thesis]. Barcelona, Spain: Facultat de Geologia, Universitat de Barcelona. Latron J, Anderton S, White S, Llorens P, Gallart, F. 2003. Seasonal characteristics of the hydrological response in a Mediterranean mountain research catchment (Vallcebre, Catalan Pyrenees): Field investigations and modelling. In: Servat E, Wajdi N, Leduc C, Shakeel A, editors. Hydrology of the Mediterranean and Semiarid Regions. International Association of Hydrological Sciences (IAHS), Proceedings of an International Symposium, IAHS 278; Montpellier, France: International Association of Hydrological Sciences, pp 106–110.
The Hisar district, a part of the Indo – Gangetic alluvial plain, is situated between 2853’45” to 2949’15” North latitudes and 7513’15” to 7618’15” East longitudes (Fig.1). It occupies a total area of 3983sq.km. Hisar district comprises of three major physiographic units i.e. Aeolian plain, Older alluvial plain and Chautang flood plain. The district lies in semi-arid region, which is nearly 30 km northeast of the Rajasthan desert. It generally experiences a sub-tropical, continental type of climate. According to 2011 Census, Hisar district recorded a population of 17, 42,815 persons, which made the district 2nd most populous district of the state. The district observed population density of 438 persons per square km. The Population of the district comprised of 931,535 Male and 811,280 female. The district made rapid progress in agricultural production during post Green Revolution period. As a matter of fact the dry climatic conditions of the district necessitated the development of alternative source of water, essential for cultivation of crops.
Another valuable dataset is Ecological Vegetation Classes (EVCs), which describe native vegetation using a system of classification introduced by the Victorian Department of Sustainability and Environment in the 1990’s. EVC mapping was implemented as part of the Regional Forest Agreements (RFAs), driven by a need to determine a Forest Reserve System. The EVC mapping was undertaken by initially outlining native vegetation patches and any obvious related patterns via interpretation of aerial photographs. The range of aerial photograph patterns was then field checked and lists of plant species recorded (Davies et al., 2002). EVCs are the basic mapping unit used for forest ecosystem assessments, biodiversity planning and conservation management at the regional scale in Victoria. EVC mapping constitutes baseline data for planning decisions at all levels of government and is invaluable data for the conservation and management of remnant vegetation and for the development of vegetation programs. It has become one of the key sets used in terrestrial biodiversity management. For this study, the EVC map is taken as depicting the current situation of landuse and landcover and as such can be regarded as a good reference during derivation of the past landuse and landcover classification.
In this era of limited government funding for new initiatives, we need to start with leveraging current and largely successful approaches such as satellite observation of LULCC. Specifically, for example, continuation of Landsat, Terra, Aqua, Sentinel, and other similar satellite missions by various nations and space agency policies that allow free access to Earth observation data are needed for international transparency for monitoring LULCC (De Sy et al. 2012; Herold and Johns 2007). These activities should include database development and easy access to quality-assured data. Spaceborne observa- tion and monitoring platforms could be particularly useful for developing nations where historical data may not be available (Herold et al. 2011). We rec- ognize that processing and analysis of the data still require resources and budgetary support. However, the level of funding needed for these steps is rela- tively small even in an already con strained national budget. As shown in Brazil’s approach to the reduc- tion in deforestation, moni toring transparency and appropriate policies can lead to significant lowering of adverse impacts of LULCCs (Instituto Nacional de Pesquisas Especias 2013).
Abstract. Pressure on land resources is expected to increase as global population continues to climb and the world be- comes more affluent, swelling the demand for food. Chang- ing climate may exert additional pressures on natural lands as present-day productive regions may shift, or soil quality may degrade, and the recent rise in demand for biofuels increases competition with edible crops for arable land. Given these projected trends there is a need to understand the global cli- mate impacts of landuse and landcoverchange (LULCC). Here we quantify the climate impacts of global LULCC in terms of modifications to the balance between incoming and outgoing radiation at the top of the atmosphere (radiative forcing, RF) that are caused by changes in long-lived and short-lived greenhouse gas concentrations, aerosol effects, and land surface albedo. We attribute historical changes in terrestrial carbon storage, global fire emissions, secondary organic aerosol emissions, and surface albedo to LULCC us- ing simulations with the Community Land Model version 3.5. These LULCC emissions are combined with estimates of agricultural emissions of important trace gases and min- eral dust in two sets of Community Atmosphere Model sim- ulations to calculate the RF of changes in atmospheric chem- istry and aerosol concentrations attributed to LULCC. With all forcing agents considered together, we show that 40 % (±16 %) of the present-day anthropogenic RF can be at- tributed to LULCC. Changes in the emission of non-CO 2 greenhouse gases and aerosols from LULCC enhance the total LULCC RF by a factor of 2 to 3 with respect to the LULCC RF from CO 2 alone. This enhancement factor also applies to projected LULCC RF, which we compute for four future scenarios associated with the Representative Concen- tration Pathways. We attribute total RFs between 0.9 and 1.9 W m − 2 to LULCC for the year 2100 (relative to a prein- dustrial state). To place an upper bound on the potential of