Water shortage is one of the real challenges facing many countries in the world. As water scarcity has increased globally, waterallocation plans and agreements have increasing significance in resolving international, regional and local conflicts over access to water . In Myanmar, the process of population growth, urbanization and industrialization are occurring at an ever increasing phase at every year. According to report from Asian Development Bank, total water available water resources in Myanmar are around 89% for agriculture, 10% for municipalities and 1% for industries, respectively. Approximately 91% of the total water withdraw comes from surfacewater . River basins are cradles of many of the ancient civilizations on the earth where humanity is endowed with numerous social and economic services that flowing water provides. The seasonal flow patterns of rivers decide agricultural practices, replenish nutrients in the soil, and support fisheries that feed societies, provide transportation which is the cheapest and the only mode of haulage in several places, supply power and basic water needs for daily life and form the overall cultures and religions in a region. Over the years, a number of computer-based tools that employ simulation and optimization techniques for waterallocation have been developed. Among them, AQUARIUS is a state-of-the-art computer model devoted to the temporal and spatial allocation of water among competing uses in a riverbasin . The waterallocation evaluates the hydrologic and economic linkages from water used by hydropower irrigation and navigation for the UpperAyeyarwadyRiverBasin. The AyeyarwadyRiver flows through the heartlands of Myanmar. It is Myanmar’s largest river (about 2170 km long) and it is the most important commercial waterway. It originates at the confluence of the Mali Hka and Mai Hka rivers in Kachin State. Flow network are used to determine waterallocation for hydropower, irrigation and navigation in the UpperAyeyarwadyBasin.
Canopy method, Surface method and Rainfall Loss method were used to model the hydrologic process in the sub-basin. The Snyder unit hydrograph method was chosen for this model in order use time-series precipitation data in daily time. Constant Monthly Base flow is the simplest base flow model in HEC-HMS. It represents base flow as a constant flow; this may vary monthly. This user-specified flow is added to the direct runoff computed from rainfall for each time step of the simulation. The meteorology component was used spatially and temporally model precipitation and evaporation processes in the basins. Evaporation is one of the loss components included in the continuous model simulation. Thiessen polygon weighted precipitation of the nine sub-catchments method (Gauge weights) was used to weigh the rainfall distribution for the selected stations.
Previous efforts at assessing impacts of climate change on water resources in the upper Pangani Basin has often focused mainly on using outputs from General Circulation Models (GCMs) as input to hydrological models to assess impact of climate change on water resources. In this study, we have taken a step further by using a model-coupling ap- proach through taking advantage of SWAT’s capability in representing hydrological processes and WEAP’s strength in waterallocation using scenarios. Hydrological models, like the SWAT model, are designed to provide an understanding of response of catchments to hydrological events while wa- ter resource planning models e.g WEAP are primarily cus- tomized for waterallocation within a water management con- text e.g., supply and demand decisions (Yates et al., 2009). Thus, the coupling of SWAT and WEAP models provides a useful platform for analyzing impacts of climate change on water resources – from both management and planning perspectives. The output of GCM provides insights on fu- ture climate but at a coarser resolution. Such coarse spatial scales of GCM’s are not useful at catchment and or riverbasin scales of the order of upper Pangani RiverBasin, with an area of 12 829 km 2 . This requires downscaling outputs of GCM’s to desired scales of which the Long Ashton Research Station Weather Generator (LARS-WG) approach was used (Semenov et al., 1998) in this study.
The Sudeten Mountains is the region which is not very well recognized in terms of runoff formation, particularly during floods occurrence. Lack of elaborations causes that it is impossible to estimate the maximum outflow from rivers and streams that flow from mountains. This is- sue is very important because some of the rivers which have their sources in mountains supply in waters the upper and middle Odra River, some- times causing the superposition of flood waves of tributary and recipient during flood events. This phenomenon creates an additional threat in the Odra River valley. The Sudeten Mountains them- selves are vulnerable to flooding. Floods occur frequently and the flood risk is high, especially in mountain valleys and for towns and villages located along the rivers and streams. Therefore, it is worth to know the quantity of water that is drained by mountainous watercourses during floods. Such information will be useful for engi- neering issues related not only to flood protection but also to water retention (what volume of water Volume 16, Issue 5, Nov. 2015, pages 206–212
Upper Ganga Riverbasin has been suffering from chronic water shortages for the past few decades. Population growth is the primary driver behind gradual urbanization and indus- trialization in this region. In addition, infrastructure develop- ment activities and agriculture have also intensified. Hence, the natural resources of the UGRB are overexploited. Sus- tainable water resources planning and management by policy makers and planners require an understanding of the nexus between components of population growth, LULC transfor- mations and water quality at both regional and local scales. A 20.45 % increase in PGR leads to a 43.4 % increase in built- up areas. It was identified as the most dynamic LULC class in the region followed by wasteland. The Mann–Kendall rank test revealed that water quality parameters are highly variable in time and space, with no significant trends. Even though gross rural population is much higher in the lower reaches of the riverbasin, the PGR is higher in the urban population of upper reaches. The water quality of the ma- jority of the stations was the most degradable in monsoon season. The water quality of the upper reaches (Uttarkashi and Rishikesh) remained in the excellent to acceptable (1.38– 1.81) class from 2001 to 2012, whereas it changed from the acceptable to slightly polluted class (1.87–2.79) in the lower reaches (Kanpur, Allahabad and Varanasi). In the UGRB, BOD, DO and total coliform are the parameters most influ- enced by anthropogenic activities. Conversely, the remaining parameters, viz. pH, F, hardness (CaCO 3 ) and turbidity, are
Abstract. As recognized in the European Water Frame- work Directive, groundwater-dependent wetlands and their diverse ecosystems have important functions which need to be protected. The vegetation in such habitats is often de- pendent on quality, quantity and patterns of river discharge and groundwater-surfacewater interaction on a local or reach scale. Since groundwater-surfacewater exchange studies on natural rivers and wetlands with organic soils are scarce, more functional analysis is needed. To this end we combined different field methods including piezometer nests, temper- ature as tracer and seepage meter measurements. Some of these measurements were used as inputs and/or as valida- tion for the numerical 1-D heat transport model STRIVE. In transient mode the model was used to calculate spatially dis- tributed vertical exchange fluxes from temperature profiles measured at the upper Biebrza River in Poland over a pe- riod of nine months. Time series of estimated fluxes and hy- draulic head gradients in the hyporheic zone were used to es- timate the temporal variability of groundwater-surfacewater exchange.
DOI: 10.4236/ojbm.2019.73089 1281 Open Journal of Business and Management In order to further analyze the spatial correlation between GDP and water re- sources utilization in the upper reaches of Minjiang River, the bivariatespatial auto-correlation analysis method was used to study the spatial correlation be- tween total water consumption and GDP, primary industry GDP and water consumption, secondary industry GDP and water consumption, tertiary indus- try GDP and water consumption, and explore the spatial correlation between industrial water consumption and industrial GDP. From the figure, we can see that GDP and total water consumption shows a positive correlation trend, Mo- ran’s I index is 0.0278731 (Figure 4(a)), which shows that GDP and water re- sources have a strong spatial correlation. In the spatial correlation between in- dustrial GDP and water consumption, primary industry GDP is negatively cor- related with water consumption (Figure 4(b). Secondary industry GDP is posi- tively correlated with water consumption, and its Moran’s I index is 0.261119 (Figure 4(c). The tertiary industry GDP is negatively correlated with water consumption (Figure 4(d)). The main reasons are as follows: first, the upper reaches of Minjiang RiverBasin are vast in territory and rich in resources, but it has a rough and steep terrain that restricts the development of primary industry, and there is unreasonable allocation of water consumption and low water use ef- ficiency, so it has a greater impact on the local auto-correlation index. Second, with the support of production and construction in the upper reaches of Min- jiang RiverBasin, the basic industry has developed rapidly, showing the aggrega- tion tendency of the second industry GDP and water consumption in the first and the fourth quadrant; In addition, with the rise of tourism and service indus- try, the tertiary industry’s dependence on water resources is weakened. There- fore, the GDP of some counties with high water consumption of tertiary indus- try remains lower, while that of some counties with low water consumption of tertiary industry keeps higher.
Some of these assumptions are known to be imprecise. It is reported that there have been changes in land cover in the upper part of the basin, but the extent and impact are not known and cannot therefore be accurately represented in the model. There has been a shift from cotton to grapes in some parts of the basin during this period but because year-to-year changes are not known accurately the present cropping pattern has been assumed to be constant throughout the model period. Further, scenarios based on the current cropping pattern are likely to be more realistic than those based on an outdated cropping pattern. Another simplification in the model is the way water is distributed during water-short periods. Most Irrigation Associations try to spread water stress equally over their area, while the modeling conditions, as defined above, do not assume such a proportional reduction. However, such a proportional reduction will result, in most cases, in the tail- end areas getting stressed the most, as assumed by the model conditions.
There are several shortcomings in this study. First, there are no crop or livestock production data at the riverbasin level. We have to calculate them based on crop or livestock dis- tribution maps with statistics for administrative units. Such calculations can lead to errors, but this method will remain necessary when statistical data are not available at the riverbasin level. Our study is the first attempt for the assessment of WF at the HRB, and it is very difficult to validate the results obtained from the models used, such as the VWC of crop from the CROPWAT model. More monitoring ef- forts can help such validation. Second, for the EFR value, we choose 80 % as a threshold based on Hoekstra et al. (2011, 2012). It is still questionable whether such a threshold can be used for river basins in arid and semi-arid regions such as the HRB. To address this issue, further efforts are still needed to study the environment flows that are required to sustain freshwater ecosystems and human livelihoods and wellbeing that depend on these ecosystems. One effective way is to set up a baseline of a “normal” water status, and evaluate the ac- tual water requirements, especially from the local ecological systems. Third, it is very difficult to separate internal and ex- ternal WF of HRB and separate productive WF (e.g. through transpiration) and non-productive WF (e.g. through evapora- tion). Internal and external WF have been calculated by Cai et al. (2012) for Gansu province, which covers 43 % of the HRB. The results show that the virtual water export of the agricultural products accounted for 10 % of the total water re- source and 25 % of the total water use in the province (Cai et al., 2012). Hence, the amount of virtual water trade was quite large in such an arid region. We did not provide a compre- hensive calculation of internal and external WF in this paper for the HRB because previous research on virtual water trade was based on input-output models, but our approach in this paper is based on the Water Footprint Network method. For the Water Footprint Network method, either the food trade data or the food consumption data should be used to estimate virtual water trade. Unfortunately, both the datasets have not yet collected successfully. As to productive/non-productive water uses, Wang and D’Odorico (2008) suggested that a fo- cus should be on maximizing transpiration water loss and minimizing evaporation water loss. Technologies such as sta- ble isotope analysis can be helpful to trace the water cy- cling processes and provide an approach for the partition- ing of productive and non-productive WF(Wang L. et al., 2010, 2012).
frequently (greater than 50 percent of blank samples), was detected in environmental samples at amounts exceeding water-quality standards or goals, or was important to the interpretation of water-quality data. For example, DOC is a critical constituent because it can react with chlorine to form disinfection byproducts, most commonly trihalomethanes, which are dominated by trichloromethane (chloroform) (Thurman, 1985). Trihalomethanes are of concern to human heath and are regulated under the U.S. Environmental Protection Agency’s drinking water standards and health advisories (U.S. Environmental Protection Agency, 2000). Nitrate also is considered a critical constituent because of its potential affect on human health when standards are exceeded. Phosphorus is an important component in aquatic health, whereas mercury has a potential affect on human health and is of particular interest in the Sacramento Valley because of its wide occurrence and distribution both from natural sources and as a remnant of gold and mercury mining. Mercury and the pesticides diazinon and chlorpyrifos are critical constituents because they are being considered for future regulation. The pesticides molinate, thiobencarb, and carbofuran are critical constituents because of ongoing regulatory controls.
The behavior of arsenic in alkaline environments is little documented and still poorly understood. A previous study reported high levels of dissolved arsenic in the waters of the Pantanal, the largest wetland on the planet, and more specifically in the vast sub region "Nhecolândia". On the one hand, our data collected at the level of the UPRB show that the rivers that supply the alluvial plain of the Pantanal have low As contents. All concentrations are below 2 μg L -1 , that is to say in the range for non-arsenic-contaminated river waters. The relative mobility of arsenic in relation to sodium is slightly higher than the global average, but remains moderate. In addition to the absence of noticeable As source on the plateaus upstream of the alluvial plain, the data show a lack of significant As release from the alluvial plain towards the main draining rivers, namely the Cuiaba and Paraguay rivers. On the other hand, the study confirms the high dissolved As levels in the alkaline waters of Nhecolândia. The relations between As and the major ions are similar in the 3 sites studied, which confirms that As responds to the same control processes throughout the region. The chemical speciation indicates that it mainly occurs in the form of As(V). In surfacewater, the proportions are substantially the same in the 3 sites and increase with the sodium amount, itself resulting from long-term cumulative evaporation over many years. In the soil solution, the As levels in the surface aquifer depend on the type of saturated soil horizon, the organic horizons having As/Na ratio 5 to 10 times higher, compared to the trend in the rest of the samples. Future studies should therefore focus on details of arsenic dynamics within the alkaline lake and associated soil system.
The excess of Ca 2+ causes kidney or bladder stone and irritation in urinary passages. Magnesium is a beneficial metal, but it is toxic at high concentration. Mg 2+ salts are cathartic and divertic may cause laxative effect, while deficiency may cause structural and functional changes. Mg ions in surfacewater varied from 25 to 35 mg/L. It is essential as an activator of many enzymes. The content of Mg 2+ in groundwater ranges from 19 to 368 mg/L (Fig. 15). Mg 2+ content are mostly due to weathering of magnesium minerals and leachy of dolomites.
This abnormal results could be explained by different mix- ing modes occurring at the riverine points when the inflow joined the reservoir, which could be represented by the dif- ferences in physical properties like temperature and turbid- ity (Summerfield, 1991). As shown in Fig. 10, the inlets had higher effluxes when the inflow water was warmer and con- tained less suspended sediment than the receiving waterbody. It was suggested that the seasonal variation in effluxes was regulated by both flow mixing modes and reservoir man- agement (Striegl and Michmerhuizen, 1998). Even though in the rainy season intense precipitation could bring plenty of sediment with organic matter, the turbid water might be discharged directly downstream for electricity, because of the relatively small storage capacity of the reservoir. The in- flow water with high sediment concentration was heavier and colder than the reservoir water, thus it plunged into the wa- ter column in the reservoir and became an underflow (hy- perpycnal flow, Fig. 10; Summerfield, 1991). The reservoir surface was less affected by the underflow and maintained a relatively low emission rate (Pacheco et al., 2015) as contin- uous water discharging allowed little time for the mineraliza- tion of OC (Assireu et al., 2011; ¸Sentürk, 1994), in spite of the high flow velocity. However, in the dry season the clean inflow water was lighter and warmer than the reservoir wa-
Fish fauna in the upper and middle Ceyhan Riverbasin were investigated with the distribution and systematical determination from May 2001 to April 2004. The fish specimens were obtained by electro fishing and gill nets from two lakes, two reservoirs and 18 streams. A total of 2,414 specimens were collected and 1,156 of these were investigated diagnostic characteristics. Twenty species belong to 10 families were determined. The fish species determined in the study are: Anguilla anguilla, Salmo trutta macrostigma, Cyprinus carpio, Acanthobrama sp., Alburnus orontis, Pseudophoxinus zekayi, Squalius kottelati, Garra rufa, Chondrostoma regium, Luciobarbus pectoralis, Capoeta angorae, Capoeta erhani, Cobitis evreni, Schistura ceyhanensis, Oxynemacheilus sp., Silurus glanis, Clarias gariepinus, Aphanius mento, Gambusia affinis and Salaria fluviatilis. Endemic species Pseudophoxinus zekayi, Capoeta erhani, Schistura ceyhanensis and Cobitis evreni reported in recent years were described.
Table 2 shows the average monthly model results for the period 2001-2005. The most striking feature of these re- sults is the fact that the total TRMM 3B43 precipitation for the entire basin based equals 311 mm y -1 , while the total modelled stream ﬂ ow at Besham Qila equals 359 mm y -1 . The modelled discharges match the observed discharge and it is concluded that there must be an additional sour- ce of water to explain the reported stream ﬂ ow, especially considering that actual evapotranspiration is not accoun- ted for. There are two possibilities. Firstly, precipitation is signiﬁ cantly underestimated, but this seams unlikely, be- cause a recent study that assessed TRMM 3B43 satellite biases on the Tibetan plateau concluded that the TRMM 3B43 consistently overestimates observed precipitation (Yin et al. 2008). This would yield the opposite namely that the difference between basin precipitation and observed discharge would even be larger.
Lichenic associations are used as bio-indicators because lichens are long-lived, known to be sensitive to changes in the habitat and environment, and obtain their nutrients from the atmosphere. In this study we quantified the Pb, Cr, As, Co and Cd metals absorbed by the Ramalina celastri, Usnea sp., Flavopunctelia flaventor, Teloschiste sexilis, Punctelia subrudecta, Parmotrema simulans, Ramalina complanata, Parmotrema bangii, Everniastrum columbiense, Parmotrema praesorediosum, Parmotrema reticulatum, and Heterodermial eucomela lichens gathered on the west bank of the river Bogotá, Colombia, in its upperbasin near the town of Villapinzón, where the air and the health of the community on its banks have been affected for decades by the emissions of particulates into the air and shedding of waste waters into the river by the local tanning industry. The study found high levels of the bio-accumulation of Cd, Co, As and Cr in the lichens, with Pb values which range from 4.1 to 25.8 ppm, with the highest levels in Parmotrema reticulatum. The levels of Cd ranged from 0.8 to 45.7 ppm, with Parmotrema simulans showing the highest level. The levels of Co ranged from 0.8 to 6.3 ppm, with Heterodermia leucomela showing the highest bio-accumulation. The levels of As ranged from 9.8 to 76 ppm, with Heterodermia leucomela showing the highest level. And the levels of Cr ranged from 0.1 to 141.0 ppm, with the highest levels in Teloschiste sexilis. The results show a high accumulation of heavy metals in the lichens we studied, which were mainly derived from particulate material and indicate an impact on the community which lives in the area.
Abstract The PRMS model was established for Zhenjiangguan watershed in the upper reach of the Minjiang Riverbasin, China. The results showed that PRMS had an acceptable performance in simulating monthly runoff in the study area. The analysis on the impacts of precipitation changes on hydrological processes indicated that both runoff and evapotranspiration increased with the increase of precipitation. Moreover, evapotranspiration had larger sensitivity to the change of precipitation than runoff.
According to the hydro geological characteristics in area of study, the groundwater’s that feed springs/fountains are stored mainly in packages of Neogene aged rocks. The erosion processes that occurred along time, opened aquifers stratum and their water come up in the slopes of river valleys, large ravines and valleys. Over the level of rocks base erosion are spread the sub layer of rocks from inferior and medium Sarmatian. In these layers are concentrated the aquifers with stable exchange potential for spring’s formation. Lower Sarmatian aquifer which has the greatest importance in the regional water supply is largely spread. The waters are concentrated in the limestone formations of shale cracked inclusions, sandstone and sand. Their thickness is ranging from 20 to 30 up to 50 m. The discharge of the springs/fountains is from 0.05 to 1.0 m 3 /s, but sometimes some of the water record exceeds the norm with more
With the North East Regional Model (NERM), Khan et al. (2005) studied the impact on the water resources of Sylhet Basin of the proposed Tipaimukh Dam to be built across the Barak River in India ~70 km upstream of the Amalshid border point and where the Barak River bifurcates into Surma and Kushiyara Rivers (Figure 1.3b). The NERM is an ensemble hydrologic-hydrodynamic model developed from the lumped rainfall-runoff model NAM (Nedbør-Afstrømnings- Model) (DHI, 2009a) and the river hydrodynamic model MIKE11 (DHI, 2009a). Since the early 1990s the NERM model has been used and updated periodically by the Flood Forecasting and Warning Centre (FFWC), a wing of the BWDB, to forecast riverwater stage and flooding in the northeast region of Bangladesh (FFWC, 2011; Liong et al., 2000). In the NERM modelling platform, each river within a subbasin receives surface runoff, generated from the prior calibrated lumped rainfall-runoff NAM model, and headwater inflows, if any, from upper tributaries. Observed river flows and stages at about 20 gauge stations established along the frontier of Bangladesh and India were used as boundary conditions of the NERM model. Upon receiving boundary observed flow data, the model can predict water stages of the Meghna River at Bhairab Bazar with a maximum lead time of three days (Islam et al., 2010). Although this model can satisfactorily produce hydraulics of river’s water in the Sylhet Basin its prediction ability is highly subjected to boundary flow conditions along the frontier. Moreover, use of such a model in assessing the catchment’s response to different forcings such as climate and land use change is restricted as about 68% of the entire UMRB, lying in India, is not explicitly modelled but is instead represented by observed water levels/flows as boundary inputs to the model.
Abstract. Decomposition analysis of water footprint (WF) changes, or assessing the changes in WF and identifying the contributions of factors leading to the changes, is im- portant to water resource management. Instead of focusing on WF from the perspective of administrative regions, we built a framework in which the input-output (IO) model, the structural decomposition analysis (SDA) model and the gen- erating regional IO tables (GRIT) method are combined to implement decomposition analysis for WF in a riverbasin. This framework is illustrated in the WF in Haihe Riverbasin (HRB) from 2002 to 2007, which is a typical water-limited riverbasin. It shows that the total WF in the HRB increased from 4.3 × 10 10 m 3 in 2002 to 5.6 × 10 10 m 3 in 2007, and the agriculture sector makes the dominant contribution to the in- crease. Both the WF of domestic products (internal) and the WF of imported products (external) increased, and the pro- portion of external WF rose from 29.1 to 34.4 %. The techno- logical effect was the dominant contributor to offsetting the increase of WF. However, the growth of WF caused by the economic structural effect and the scale effect was greater, so the total WF increased. This study provides insights about water challenges in the HRB and proposes possible strategies for the future, and serves as a reference for WF management and policy-making in other water-limited river basins.