985 resultados para hillslope hydrology


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An understanding of the influence of soil chemistry on soil hydraulic properties is of critical importance for the management of sodic soils under irrigation. The hydraulic conductivity of sodic soils has been shown to be affected by properties of the applied solution including pH (Suarez et al. 1984), sodicity and salt concentration (McNeal and Coleman 1966). The changes in soil hydraulic conductivity are the result of changes in the spacing between clay layers in response to changes in soil solution chemistry. While the importance o f soil chemistry in controlling hydraulic conductivity is known, the exact impacts of sodic soil amelioration on hydraulic conductivity and deep drainage at a given location are difficult to predict. This is because the relationships between soil chemical factors and hydraulic conductivity are soil specific and because local site specific factors also need to be considered to determine the actual impacts on deep drainage rates.

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The export of sediments from coastal catchments can have detrimental impacts on estuaries and near shore reef ecosystems such as the Great Barrier Reef. Catchment management approaches aimed at reducing sediment loads require monitoring to evaluate their effectiveness in reducing loads over time. However, load estimation is not a trivial task due to the complex behaviour of constituents in natural streams, the variability of water flows and often a limited amount of data. Regression is commonly used for load estimation and provides a fundamental tool for trend estimation by standardising the other time specific covariates such as flow. This study investigates whether load estimates and resultant power to detect trends can be enhanced by (i) modelling the error structure so that temporal correlation can be better quantified, (ii) making use of predictive variables, and (iii) by identifying an efficient and feasible sampling strategy that may be used to reduce sampling error. To achieve this, we propose a new regression model that includes an innovative compounding errors model structure and uses two additional predictive variables (average discounted flow and turbidity). By combining this modelling approach with a new, regularly optimised, sampling strategy, which adds uniformity to the event sampling strategy, the predictive power was increased to 90%. Using the enhanced regression model proposed here, it was possible to detect a trend of 20% over 20 years. This result is in stark contrast to previous conclusions presented in the literature. (C) 2014 Elsevier B.V. All rights reserved.

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We consider the development of statistical models for prediction of constituent concentration of riverine pollutants, which is a key step in load estimation from frequent flow rate data and less frequently collected concentration data. We consider how to capture the impacts of past flow patterns via the average discounted flow (ADF) which discounts the past flux based on the time lapsed - more recent fluxes are given more weight. However, the effectiveness of ADF depends critically on the choice of the discount factor which reflects the unknown environmental cumulating process of the concentration compounds. We propose to choose the discount factor by maximizing the adjusted R-2 values or the Nash-Sutcliffe model efficiency coefficient. The R2 values are also adjusted to take account of the number of parameters in the model fit. The resulting optimal discount factor can be interpreted as a measure of constituent exhaustion rate during flood events. To evaluate the performance of the proposed regression estimators, we examine two different sampling scenarios by resampling fortnightly and opportunistically from two real daily datasets, which come from two United States Geological Survey (USGS) gaging stations located in Des Plaines River and Illinois River basin. The generalized rating-curve approach produces biased estimates of the total sediment loads by -30% to 83%, whereas the new approaches produce relatively much lower biases, ranging from -24% to 35%. This substantial improvement in the estimates of the total load is due to the fact that predictability of concentration is greatly improved by the additional predictors.

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We consider estimating the total load from frequent flow data but less frequent concentration data. There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates that minimizes the biases and makes use of informative predictive variables. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized rating-curve approach with additional predictors that capture unique features in the flow data, such as the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and the discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. Forming this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach for two rivers delivering to the Great Barrier Reef, Queensland, Australia. One is a data set from the Burdekin River, and consists of the total suspended sediment (TSS) and nitrogen oxide (NO(x)) and gauged flow for 1997. The other dataset is from the Tully River, for the period of July 2000 to June 2008. For NO(x) Burdekin, the new estimates are very similar to the ratio estimates even when there is no relationship between the concentration and the flow. However, for the Tully dataset, by incorporating the additional predictive variables namely the discounted flow and flow phases (rising or recessing), we substantially improved the model fit, and thus the certainty with which the load is estimated.

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A method is presented for identification of parameters in unconfined aquifers from pumping tests, based on the optimisation of the objective function using the least squares approach. Four parameters are to be evaluated, namely: The hydraulic conductivity in the radial and the vertical directions, the storage coefficient and the specific yield. The sensitivity analysis technique is used for solving the optimisation problem. Besides eliminating the subjectivity involved in the graphical procedure, the method takes into account the field data at all time intervals without classifying them into small and large time intervals and does not use the approximation that the ratio of the storage coefficient to the specific yield tends to zero. Two illustrative examples are presented and it is found that the parameter estimates from the computational and graphical procedures differ fairly significantly.

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Tillage is defined here in a broad sense, including disturbance of the soil and crop residues, wheel traffic and sowing opportunities. In sub-tropical, semi-arid cropping areas in Australia, tillage systems have evolved from intensively tilled bare fallow systems, with high soil losses, to reduced and no tillage systems. In recent years, the use of controlled traffic has also increased. These conservation tillage systems are successful in reducing water erosion of soil and sediment-bound chemicals. Control of runoff of dissolved nutrients and weakly sorbed chemicals is less certain. Adoption of new practices appears to have been related to practical and economic considerations, and proved to be more profitable after a considerable period of research and development. However there are still challenges. One challenge is to ensure that systems that reduce soil erosion, which may involve greater use of chemicals, do not degrade water quality in streams. Another challenge is to ensure that systems that improve water entry do not increase drainage below the crop root zone, which would increase the risk of salinity. Better understanding of how tillage practices influence soil hydrology, runoff and erosion processes should lead to better tillage systems and enable better management of risks to water quality and soil health. Finally, the need to determine the effectiveness of in-field management practices in achieving stream water quality targets in large, multi-land use catchments will challenge our current knowledge base and the tools available.

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A model of root water extraction is proposed, in which a linear variation of extraction rate with depth is assumed. Five crops are chosen for simulation studies of the model, and soil moisture depletion under optimal conditions from different layers for each crop is calculated. Similar calculations are also made using the constant extraction rate model. Rooting depth is assumed to vary linearly with potential evapotranspiration for each crop during the vegetative phase. The calculated depletion patterns are compared with measured mean depletion patterns for each crop. It is shown that the constant extraction rate model results in large errors in the prediction of soil moisture depletion, while the proposed linear extraction rate model gives satisfactory results. Hypothetical depletion patterns predicted by the model in combination with a moisture tension-dependent sink term developed elsewhere are indicated.

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Northern peatlands are thought to store one third of all soil carbon (C). Besides the C sink function, peatlands are one of the largest natural sources of methane (CH4) to the atmosphere. Climate change may affect the C gas dynamics as well as the labile C pool. Because the peatland C sequestration and CH4 emissions are governed by high water levels, changes in hydrology are seen as the driving factor in peatland ecosystem change. This study aimed to quantify the carbon dioxide (CO2) and CH4 dynamics of a fen ecosystem at different spatial scales: plant community components scale, plant community scale and ecosystem scale, under hydrologically normal and water level drawdown conditions. C gas exchange was measured in two fens in southern Finland applying static chamber and eddy covariance techniques. During hydrologically normal conditions, the ecosystem was a CO2 sink and CH4 source to the atmosphere. Sphagnum mosses and sedges were the most important contributors to the community photosynthesis. The presence of sedges had a major positive impact on CH4 emissions while dwarf shrubs had a slightly attenuating impact. C fluxes varied considerably between the plant communities. Therefore, their proportions determined the ecosystem scale fluxes. An experimental water level drawdown markedly reduced the photosynthesis and respiration of sedges and Sphagnum mosses and benefited shrubs. Consequently, changes were smaller at the ecosystem scale than at the plant group scale. The decrease in photosynthesis and the increase in respiration, mostly peat respiration, made the fen a smaller CO2 sink. CH4 fluxes were significantly lowered, close to zero. The impact of natural droughts was similar to, although more modest than, the impact of the experimental water level drawdown. The results are applicable to the short term impacts of the water level drawdown and to climatic conditions in which droughts become more frequent.

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Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) Karst.) forests dominate in Finnish Lapland. The need to study the effect of both soil factors and site preparation on the performance of planted Scots pine has increased due to the problems encountered in reforestation, especially on mesic and moist, formerly spruce-dominated sites. The present thesis examines soil hydrological properties and conditions, and effect of site preparation on them on 10 pine- and 10 spruce-dominated upland forest sites. Finally, the effects of both the site preparation and reforestation methods, and soil hydrology on the long-term performance of planted Scots pine are summarized. The results showed that pine and spruce sites differ significantly in their soil physical properties. Under field capacity or wetter soil moisture conditions, planted pines presumably suffer from excessive soil water and poor soil aeration on most of the originally spruce sites, but not on the pine sites. The results also suggested that site preparation affects the soil-water regime and thus prerequisites for forest growth over two decades after site preparation. High variation in the survival and mean height of planted pine was found. The study suggested that on spruce sites, pine survival is the lowest on sites that dry out slowly after rainfall events, and that height growth is the fastest on soils that reach favourable aeration conditions for root growth soon after saturation, and/or where the average air-filled porosity near field capacity is large enough for good root growth. Survival, but not mean height can be enhanced by employing intensive site preparation methods on spruce sites. On coarser-textured pine sites, site preparation methods don t affect survival, but methods affecting soil fertility, such as prescribed burning and ploughing, seem to enhance the height growth of planted Scots pines over several decades. The use of soil water content in situ as the sole criterion for sites suitable for pine reforestation was tested and found to be a relatively uncertain parameter. The thesis identified new potential soil variables, which should be tested using other data in the future.

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Wood is an important biological resource which contributes to nutrient and hydrology cycles through ecosystems, and provides structural support at the plant level. Thousands of genes are involved in wood development, yet their effects on phenotype are not well understood. We have exploited the low genomic linkage disequilibrium (LD) and abundant phenotypic variation of forest trees to explore allelic diversity underlying wood traits in an association study. Candidate gene allelic diversity was modelled against quantitative variation to identify SNPs influencing wood properties, growth and disease resistance across three populations of Corymbia citriodora subsp. variegata, a forest tree of eastern Australia. Nine single nucleotide polymorphism (SNP) associations from six genes were identified in a discovery population (833 individuals). Associations were subsequently tested in two smaller populations (130160 individuals), validating our findings in three cases for actin 7 (ACT7) and COP1 interacting protein 7 (CIP7). The results imply a functional role for these genes in mediating wood chemical composition and growth, respectively. A flip in the effect of ACT7 on pulp yield between populations suggests gene by environment interactions are at play. Existing evidence of gene function lends strength to the observed associations, and in the case of CIP7 supports a role in cortical photosynthesis.

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A transformation is suggested which can transform a non-Gaussian monthly hydrological time series into a Gaussian one. The suggested approach is verified with data of ten Indian rainfall time series. Incidentally, it is observed that once the deterministic trends are removed, the transformation leads to an uncorrelated process for monthly rainfall. The procedure for normalization is general enough in that it should be also applicable to river discharges. This is verified to a limited extent by considering data of two Indian river discharges.

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An analytical solution is presented, making use of the Schwartz-Christoffel transformation, for determining the seepage characteristics for the problem of flow under a weir having two unequal sheetpiles at the ends and embedded in an anisotropic porous medium of finite thickness. Results for several particular cases of simple hydraulic structures can be obtained from the general solution presented. Numerical results in nondimensional form have been given for quantity of seepage and exit gradient distribution for various conditions in the equivalent transformed isotropic section and, by making use of the physical parameters in the actual anisotropic plane and the set of transformation relations given, these quantities (seepage loss, exit gradient) can be interpreted in the actual anisotropic physical plane.

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This paper introduces a policy-making support tool called ‘Micro-level Urban ecosystem Sustainability IndeX (MUSIX)’. The index serves as a sustainability assessment model that monitors six aspects of urban ecosystems, hydrology, ecology, pollution, location, design, and efficiency based on parcel-scale indicators. This index is applied in a case study investigation in the Gold Coast City, Queensland, Australia. The outcomes reveal that there are major environmental problems caused by increased impervious surfaces from growing urban development in the study area. The findings suggest that increased impervious surfaces are linked to increased surface runoff, car dependency, transport-related pollution, poor public transport accessibility, and unsustainable built environment. This paper presents how the MUSIX outputs can be used to guide policy-making through the evaluation of existing policies.

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Metanogeenit ovat hapettomissa oloissa eläviä arkkien pääryhmään kuuluvia mikrobeja, joiden ainutlaatuisen aineenvaihdunnan seurauksena syntyy metaania. Ilmakehässä metaani on voimakas kasvihuonekaasu. Yksi suurimmista luonnon metaanilähteistä ovat kosteikot. Pohjoisten soiden metaanipäästöt vaihtelevat voimakkaasti eri soiden välillä ja yhden suon sisälläkin, riippuen muun muassa vuodenajasta, suotyypistä ja kasvillisuudesta. Väitöskirjatyössä tutkittiin metaanipäästöjen vaihtelun mikrobiologista taustaa. Tutkimuksessa selvitettiin suotyypin, vuodenajan, tuhkalannoituksen ja turvesyvyyden vaikutusta metanogeeniyhteisöihin sekä metaanintuottoon kolmella suomalaisella suolla. Lisäksi tutkittiin ei-metanogeenisia arkkeja ja bakteereita, koska ne muodostavat metaanin tuoton lähtöaineet osana hapetonta hajotusta. Mikrobiyhteisöt analysoitiin DNA- ja RNA-lähtöisillä, polymeraasiketjureaktioon (PCR) perustuvilla menetelmillä. Merkkigeeneinä käytettiin metaanin tuottoon liittyvää mcrA-geeniä sekä arkkien ja bakteerien ribosomaalista 16S RNA-geeniä. Metanogeeniyhteisöt ja metaanintuotto erosivat huomattavasti happaman ja vähäravinteisen rahkasuon sekä ravinteikkaampien sarasoiden välillä. Rahkasuolta löytyi lähes yksinomaan Methanomicrobiales-lahkon metanogeeneja, jotka tuottavat metaania vedystä ja hiilidioksidista. Sarasoiden metanogeeniyhteisöt olivat monimuotoisempia, ja niillä esiintyi myös asetaattia käyttäviä metanogeeneja. Vuodenaika vaikutti merkittävästi metaanintuottoon. Talvella havaittiin odottamattoman suuri metaanintuottopotentiaali sekä viitteitä aktiivisista metanogeeneista. Arkkiyhteisön koostumus sen sijaan vaihteli vain vähän. Tuhkalannoitus, jonka tarkoituksena on edistää puiden kasvua ojitetuilla soilla, ei merkittävästi vaikuttanut metaanintuottoon tai -tuottajiin. Ojitetun suon yhteisöt kuitenkin muuttuivat turvesyvyyden mukaan. Vertailtaessa erilaisia PCR-menetelmiä todettiin, että kolmella mcrA-geeniin kohdistuvalla alukeparilla havaittiin pääosin samat ojitetun suon metanogeenit, mutta lajien runsaussuhteet riippuvat käytetyistä alukkeista. Soilla havaitut bakteerit kuuluivat pääjaksoihin Deltaproteobacteria, Acidobacteria ja Verrucomicrobia. Lisäksi löydettiin Crenarchaeota-pääjakson ryhmiin 1.1c ja 1.3 kuuluvia ei-metanogeenisia arkkeja. Tulokset ryhmien esiintymisestä hapettomassa turpeessa antavat lähtökohdan selvittää niiden mahdollisia vuorovaikutuksia metanogeenien kanssa. Tutkimuksen tulokset osoittivat, että metanogeeniyhteisön koostumus heijastaa metaanintuottoon vaikuttavia kemiallisia tai kasvillisuuden vaihteluita kuten suotyyppiä. Soiden metanogeenien ja niiden fysiologian parempi tuntemus voi auttaa ennustamaan ympäristömuutosten vaikutusta soiden metaanipäästöihin.

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Accurate estimations of water balance are needed in semi-arid and sub-humid tropical regions, where water resources are scarce compared to water demand. Evapotranspiration plays a major role in this context, and the difficulty to quantify it precisely leads to major uncertainties in the groundwater recharge assessment, especially in forested catchments. In this paper, we propose to assess the importance of deep unsaturated regolith and water uptake by deep tree roots on the groundwater recharge process by using a lumped conceptual model (COMFORT). The model is calibrated using a 5 year hydrological monitoring of an experimental watershed under dry deciduous forest in South India (Mule Hole watershed). The model was able to simulate the stream discharge as well as the contrasted behaviour of groundwater table along the hillslope. Water balance simulated for a 32 year climatic time series displayed a large year-to-year variability, with alternance of dry and wet phases with a time period of approximately 14 years. On an average, input by the rainfall was 1090 mm year(-1) and the evapotranspiration was about 900 mm year(-1) out of which 100 mm year(-1) was uptake from the deep saprolite horizons. The stream flow was 100 mm year(-1) while the groundwater underflow was 80 mm year(-1). The simulation results suggest that (i) deciduous trees can uptake a significant amount of water from the deep regolith, (ii) this uptake, combined with the spatial variability of regolith depth, can account for the variable lag time between drainage events and groundwater rise observed for the different piezometers and (iii) water table response to recharge is buffered due to the long vertical travel time through the deep vadose zone, which constitutes a major water reservoir. This study stresses the importance of long term observations for the understanding of hydrological processes in tropical forested ecosystems. (C) 2009 Elsevier B.V. All rights reserved.