bluuebunny/crossref_metadata_2025 huggingface dataset:
Spatial rainfall variability and runoff response during an extreme event in a semi-arid catchment in the South Pare Mountains, Tanzania
Authors: Mul M. L. , Savenije H. H. G. , Uhlenbrook S.
Published: April 2010

Abstract. This paper describes an extreme flood event that occurred in the South Pare Mountains in northern Tanzania. A high spatial and temporal resolution data set was gathered in a previously ungauged catchment. This data was analysed using a multi-method approach, to gather information about the processes that resulted in the flood event. On 1 March 2006, extreme rainfall occurred in the Makanya catchment, (300 km2), where up to 100 mm were recorded in Bangalala village in only 3 h. Runoff was devastating, inundating large parts of the flood plain. The spatial variability of the rainfall during the event was very large, even in areas with the same altitude. The Vudee sub-catchment (25.8 km2) was in the centre of the rainfall event, receiving about 75 mm in 3 h divided over the two upstream tributaries: the Upper-Vudee and Ndolwa. The peak flow at the weir site has been determined using the slope-area method and gradually varied flow calculations, indicating a peak discharge of 32 m3 s−1. Rise and fall of the flood was very sharp, with the peak flow occurring just one hour after the peak of the rainfall. The flow receded to 1% of the maximum flow within 24 h. Hydrograph separation using hydrochemical parameters indicates that at the peak of the flow 50% was generated by direct surface runoff (also indicated by the large amount of sediments in the samples), whereas the recession originated from displaced groundwater (>90 %). The subsequent base flow in the river remained at 75 l s−1 for the rest of the season, which is substantially higher than the normal base flow observed during the previous rainy seasons (15 l s−1) indicating significant groundwater recharge during this extreme event.
Analysis of virtual water flows associated with the trade of maize in the SADC region: importance of scale
Authors: Dabrowski J. M. , Masekoameng E. , Ashton P. J.
Published: April 2010

Abstract. The concept of virtual water encourages a country to view agricultural crops in terms of the amount of water required to produce those crops, with a view to implementing trading policies that promote the saving of scarce water resources. Recently, increased attention has focussed on partitioning the virtual water content of crops into green and blue water (derived from rainfall and irrigation, respectively) as the latter has higher opportunity costs associated with its use and therefore impacts directly on scarcity. Maize is the most important crop traded within the SADC region. South Africa is the largest producer and exporter of maize, with the majority of its exports destined for other SADC countries. In comparison to other SADC countries, South Africa produces maize relatively efficiently, with a low virtual water content and a high green (868 m3 tonne−1) to blue (117 m3 tonne−1) water ratio. The blue water content is however higher than for maize produced in all other SADC countries, with the exception of Namibia (211 m3 tonne−1). Current trade patterns therefore result in a net expenditure of blue water (66×106 m3), almost all of which is exported by South Africa (65×106 m3). South Africa is one of the most water scarce countries in the region and analysis of virtual water flows indicates that current SADC maize trading patterns are influenced by national productivity as opposed to water scarcity. The virtual water content of maize was estimated for each of South Africa's nineteen Water Management Area's (WMA) and used as a proxy to represent water use efficiency for maize production. The virtual water content varied widely across all of the WMAs, ranging from 360 m3 tonne-1 in the Ustutu Mhlatuze to 1000 m3 tonne−1 in the Limpopo. A comparison of the virtual water content and production of maize (expressed as a percentage of the total national production) identified those WMAs where maize production is highly water inefficient (e.g. Lower Orange and Limpopo WMAs). Results suggest that, while a national estimate of the virtual water content of a crop may indicate a relatively efficient use of water, an analysis of the virtual water content at smaller scales can reveal inefficient use of water for the same crop. Therefore, analysis of the virtual water content of crops and trading of agricultural products at different spatial scales (i.e. regional, national and WMA) could be an important consideration within the context of water allocation, water use efficiency and alleviation of water scarcity.
The role of integrated high resolution stratigraphic and geophysic surveys for groundwater modelling
Authors: Margiotta S. , Mazzone F. , Negri S. , Calora M.
Published: April 2010

Abstract. This work sets out a methodology of integrated geological, hydrogeological and geophysical surveys for the characterization of contaminated sites. The flow model of the shallow aquifer in the Brindisi area (recognized to be at significant environmental risk by the Italian government) and the impact of an antrophic structure on the groundwater flow have been evaluated. The stratigraphic and hydrogeological targets used for the calibration phase of the flow model provide a means of assessing calibration quality. The good calibration of the model point out the key role of a detailed knowledge of the physical-stratigraphycal attributes of the area to be studied and field data collection. Geoelectrical tomography focus the attention on an area resulted of particular interest by the flow model obtained. This method permit to reconstruct in detail the lateral and vertical lithological variations in the geological formations improving the spatial resolution of the data and consequently the scale of observation. Besides, anomaly resistivity values have been correlated with pollution. Chemical analysis have confirmed this correlation.
A look at the links between drainage density and flood statistics
Authors: Pallard B. , Castellarin A. , Montanari A.
Published: April 2010

Abstract. We investigate the links between the drainage density of a river basin and selected flood statistics, namely the mean, standard deviation, coefficient of variation and coefficient of skewness of annual maximum series of peak flows. The investigation is carried out through a three-stage analysis. First, a numerical simulation is performed by using a spatially distributed hydrological model in order to highlight how flood statistics change with varying drainage density. Second, a conceptual hydrological model is used in order to analytically derive the dependence of flood statistics on drainage density. Third, the dependence between flood statistics and drainage density is analysed for 44 watersheds located in northern Italy. The three-level analysis seems to suggest that a critical value of the drainage density exists for which a minimum is attained in both the coefficient of variation and the absolute value of the skewness coefficient. Such minima in the flood statistics correspond to a minimum of the flood quantile for a given exceedance probability (i.e., recurrence interval). Therefore, the results of this study may provide useful indications for flood risk assessment in ungauged basins.
Assessing snow water equivalent of an Alpine catchment using snow dynamic model calibrated with satellite images
Authors: Corbari C. , Ravazzani G. , Martinelli J. , Mancini M.
Published: April 2010

Abstract. This paper presents a simplified numerical model of snow dynamic implemented into a continuous distributed hydrological model for hydrograph simulations at basin scale. This snow model is based on air temperature thresholds that rule the snow melt and accumulation processes. A procedure to calibrate these temperature thresholds from NOAA satellite snow cover maps is discussed. We show that, for an accurate model calibration from satellite images, it is necessary to consider the presence of areas with complex topography such as mountain slopes. Snow model performance is tested both at local and basin scale on Alpine catchment. At local scale a good agreement between modelled snow dynamic and observed snow height data at snow gauge stations in the river Anza basin (Italy) is shown; at basin scale agreement between observed and simulated hydrographs at the discharge station of river Toce (Italy) is reported.
Threshold behavior in hydrological systems and geo-ecosystems: manifestations, controls and implications for predictability
Authors: Zehe E. , Sivapalan M.
Published: April 2010

Abstract. The aim of this paper is to provide evidence that the dynamics of hydrological systems and geo-ecosystems is often influenced by threshold behavior at a variety of space and time scales. Based on well known characteristics of elementary threshold phenomena we suggest criteria for detecting threshold behavior in hydrological systems. The most important one is intermittence of phenomena, i.e. the rapid switching of related state variables/fluxes from zero to finite values, or existence of behavior regimes where the same process/response appears qualitatively differently at the macroscopic level. From the literature we present several examples for intermittent hydrological phenomena, ranging from overland flow generation in different landscapes, including the effects of hydrophobicity, to soil water flow occurring in the matrix continuum or via preferential pathways, including the case of cracking soils, nonlinear subsurface stormflow response of hillslopes during severe rainfall events, and long-term catchment flooding responses. Since threshold phenomena are often associated with environmental hazards such as floods, soil erosion, and contamination of shallow groundwater resources, we discuss common difficulties that complicate predictions of whether or not they might even occur. Predicting the onset of threshold phenomena requires a thorough understanding of the underlying controls. Through examples we illustrate that threshold behavior in hydrological systems can manifest at (a) the process level, (b) the response level, and (c) the functional level, and explain that the complexity of the underlying controls and of the interacting phenomena that determine threshold behavior become increasingly complex at the higher levels. Finally we provide evidence from field observations and model predictions that show that within an "unstable range" of system states "close" to a threshold, it is difficult to predict whether or not the system will switch behavior, for instance, as a result of the expected rainfall forcing. The term close, in this respect, depends on the expected (rainfall) forcing and the accuracy of our data/knowledge on the macroscopic state of the system.
On the derivation of soil surface roughness from multi parametric PolSAR data and its potential for hydrological modelling
Authors: Marzahn P. , Ludwig R.
Published: April 2010

Abstract. The potential of multi parametric polarimetric SAR (PolSAR) data for soil surface roughness estimation is investigated and its potential for hydrological modeling is evaluated. The study utilizes microwave backscatter collected from the DEMMIN test-site in the north-east of Germany during the AgriSAR 2006 campaign using fully polarimetric L-Band E-SAR data. In addition to various measurements of soil physical properties, soil surface roughness was measured extensively using photogrammetric image matching techniques for ground truthing. The resulting micro-DEMs are analyzed to correlate soil surface roughness indices to three well established polarimetric roughness estimators. Good results are obtained for Re[ρRRLL] vs. RMS Height, which is thus used to produce multi-temporal roughness maps of the test site. The spatial quality of maps is limited due to the fact that the presence and growth of particular plants is affecting the derivation process significantly. However, roughness derivation for bare soil surfaces is sufficiently accurate to allow for an first order assessment of soil-hydrological parameters (soil porosity, void ratio, micro depression storage capacity), which are crucial for the initialization and operation of hydrological surface models. While uncertainties remain, the dependency of soil bulk parameters from surface roughness can be shown and thus highlights the potential of the retrieval approach for hydrological model applications.
Temporal variation of soil moisture over the Wuding River Basin assessed with an eco-hydrological model, in-situ observations and remote sensing
Authors: Liu S. , Mo X. , Zhao W. , Naeimi V. , Dai D. , Shu C. , Mao L.
Published: April 2010

Abstract. For integrative management of soil and water in the Wuding River basin, Loess plateau, China, where severe soil erosion damages are incurred, the ecohydrological behavior of the region is needed to be explored. In this study we focus on the evolution of soil moisture (SM) in the basin. Since there are only twelve years in-situ SM measurements available at two stations from 1992 to 2004, an eco-hydrological processes-based model (VIP, Vegetation Interface Processes model) is employed to simulate the long-term SM, evapotranspiration (ET), vegetation cover and production variation from 1956 to 2004, for the mechanical analysis of SM change. In-situ SM observations and a remotely sensed SM dataset retrieved by the Vienna University of Technology are used to validate the model. The results show that the model is able to capture seasonal SM variations. The seasonal pattern, multi-year variation, standard deviation and CV (coefficient of the variation) of SM at the daily, monthly and annual scale are well explained by the climatic and ecological factors such as precipitation, temperature, net radiation, evapotranspiration, and Leaf Area Index (LAI, denoted as LAI). The annual and inter-annual variability of SM is the lowest comparing with that for other 11-ecohydrological variables. The trend analysis shows that SM is in decreasing tendency at ∝=0.01 level of significance. Its significance is lower than that of runoff and that of temperature (∝=0.001), whereas higher than that of precipitation (∝=0.1). The products of these long-term SM data aim to help integrative management of soil and water resources.
Estimation of Mediterranean crops evapotranspiration by means of remote-sensing based models
Authors: Minacapilli M. , Agnese C. , Blanda F. , Cammalleri C. , Ciraolo G. , D'Urso G. , Iovino M. , Pumo D. , Provenzano G. , Rallo G.
Published: April 2010

Abstract. Actual evapotranspiration from typical Mediterranean crops has been assessed in a Sicilian study area by using Surface Energy Balance and Agro-Hydrological models. Both modelling approaches require remotely sensed data to estimate evapotranspiration fluxes in a spatially distributed way. The first approach exploits visible (VIS), near-infrared (NIR) and thermal (TIR) observations to solve the surface energy balance equation. To this end two different schemes have been tested: the two-sources TSEB model, where soil and vegetation components of the surface energy balance are treated separately, and the widely used one-source SEBAL model, where soil and vegetation are considered as a sole source. Actual evapotranspiration estimates by means of the two surface energy balance models have been compared with the results of the Agro-Hydrological model SWAP, applied in a spatially distributed way to simulate one-dimensional water flow in the soil-plant-atmosphere continuum. In this latter model, remote sensing data in the VIS and NIR spectral ranges have been used to infer spatially distributed vegetation parameters needed to set up the upper boundary condition of SWAP. In the comparison presented here, actual evapotranspiration values obtained from the application of the soil water balance model SWAP have been considered as the reference. Considering that the study area is characterized by typical Mediterranean sparse vegetation, i.e. olive, citrus and vineyards, we focused the attention on the main conceptual differences between SEBAL and TSEB. Airborne hyperspectral data acquired during a NERC campaign in 2005 have been used. The results of the investigation evidenced that the remote sensing two-sources approach used in TSEB model describes turbulent and radiative surface fluxes in a more realistic way than the one-source approach.
Influence of wave phase difference between surface soil heat flux and soil surface temperature on land surface energy balance closure
Authors: Gao Z. , Horton R. , Liu H. P. , Wen J. , Wang L.
Published: April 2010

Abstract. The sensitivity of climate simulations to the diurnal variation in surface energy budget encourages enhanced inspection into the energy balance closure failure encountered in micrometeorological experiments. The diurnal wave phases of soil surface heat flux and temperature are theoretically characterized and compared for both moist soil and absolute dry soil surfaces, indicating that the diurnal wave phase difference between soil surface heat flux and temperature ranges from 0 to π/4 for natural soils. Assuming net radiation and turbulent heat fluxes have identical phase with soil surface temperature, we evaluate potential contributions of the wave phase difference on the surface energy balance closure. Results show that the sum of sensible heat flux (H) and latent heat flux (LE) is always less than surface available energy (Rn-G0) even if all energy components are accurately measured, their footprints are strictly matched, and all corrections are made. The energy balance closure ratio (ε) is extremely sensitive to the ratio of soil surface heat flux amplitude (A4) to net radiation flux amplitude (A1), and large value of A4/A1 causes a significant failure in surface energy balance closure. An experimental case study confirms the theoretical analysis.
A multi-scale ''soil water structure'' model based on the pedostructure concept
Authors: Braudeau E. , Mohtar R. H. , El Ghezal N. , Crayol M. , Salahat M. , Martin P.
Published: April 2010

Abstract. Current soil water models do not take into account the internal organization of the soil medium and, a fortiori, the physical interaction between the water film surrounding the solid particles of the soil structure, and the surface charges of this structure. In that sense they empirically deal with the physical soil properties that are all generated from this soil water-structure interaction. As a result, the thermodynamic state of the soil water medium, which constitutes the local physical conditions, namely the pedo-climate, for biological and geo-chemical processes in soil, is not defined in these models. The omission of soil structure from soil characterization and modeling does not allow for coupling disciplinary models for these processes with soil water models. This article presents a soil water structure model, Kamel®, which was developed based on a new paradigm in soil physics where the hierarchical soil structure is taken into account allowing for defining its thermodynamic properties. After a review of soil physics principles which forms the basis of the paradigm, we describe the basic relationships and functionality of the model. Kamel® runs with a set of 15 soil input parameters, the pedohydral parameters, which are parameters of the physically-based equations of four soil characteristic curves that can be measured in the laboratory. For cases where some of these parameters are not available, we show how to estimate these parameters from commonly available soil information using published pedotransfer functions. A published field experimental study on the dynamics of the soil moisture profile following a pounded infiltration rainfall event was used as an example to demonstrate soil characterization and Kamel® simulations. The simulated soil moisture profile for a period of 60 days showed very good agreement with experimental field data. Simulations using input data calculated from soil texture and pedotransfer functions were also generated and compared to simulations of the more ideal characterization. The later comparison illustrates how Kamel® can be used and adapt to any case of soil data availability. As physically based model on soil structure, it may be used as a standard reference to evaluate other soil-water models and also pedotransfer functions at a given location or agronomical situation.
Evaluation of the Surface Energy Balance System (SEBS) applied to ASTER imagery with flux-measurements at the SPARC 2004 site (Barrax, Spain)
Authors: van der Kwast J. , Timmermans W. , Gieske A. , Su Z. , Olioso A. , Jia L. , Elbers J. , Karssenberg D. , de Jong S.
Published: April 2010

Abstract. Accurate quantification of the amount and spatial variation of evapotranspiration is important in a wide range of disciplines. Remote sensing based surface energy balance models have been developed to estimate turbulent surface energy fluxes at different scales. The objective of this study is to evaluate the Surface Energy Balance System (SEBS) model on a landscape scale, using tower-based flux measurements at different land cover units during an overpass of the ASTER sensor over the SPARC 2004 experimental site in Barrax (Spain). Additionally, the effect of replacement of empirical roughness functions in the model by field estimates or literature values is investigated. Modelled fluxes correspond better with flux measurements over uniform land cover compared to cases where different land covers are mixed in the measurement footprint. Furthermore SEBS underestimates sensible heat flux, which is common in one source models.
Use of satellite data to assess the impacts of irrigation withdrawals on Upper Klamath Lake, Oregon
Authors: Tang Q. , Rosenberg E. A. , Lettenmaier D. P.
Published: April 2010

Abstract. The competition for scarce water resources in the Upper Klamath River Basin, Oregon has generated conflict among its stakeholders, as demonstrated by recent regulations on withdrawals from Upper Klamath Lake. Information on agricultural water usage can help assess the hydrologic impacts of irrigation and support operational decisions. This paper presents an experimental satellite-based evapotranspiration estimation system that is combined with the Variable Infiltration Capacity (VIC) hydrological model to estimate irrigation consumption, which is then used to assess the effects of irrigated agriculture on lake storage volumes and water levels. The hydrological model is calibrated with streamflow observations and used to estimate unmeasured lake inflows and guide water balance calculations. When combined with the VIC model, the satellite-based evapotranspiration estimation system shows that irrigation caused a decline of 0.3 m in average annual water levels and 0.5 m in mean October water levels, and an increase of 0.5 m in annual water level ranges at the lake from 2001 to 2005. The results demonstrate the potential of satellite data for agricultural water resource management at the regional scale.
Some practical notes on the land surface modeling in the Tibetan Plateau
Authors: Yang K. , Chen Y.-Y. , Qin J.
Published: April 2010

Abstract. The Tibetan Plateau is a key region of land-atmosphere interactions, as it provides an elevated heat source to the middle-troposphere. The Plateau surfaces are typically characterized by alpine meadows and grasslands in the central and eastern part while by alpine deserts in the western part. This study evaluates performance of three state-of-the-art land surface models (LSMs) for the Plateau typical land surfaces. The LSMs of interest are SiB2 (the Simple Biosphere), CoLM (Common Land Model), and Noah. They are run with default parameters at typical alpine meadow sites in the central Plateau and typical alpine desert sites in the western Plateau. The recognized key processes and modeling issues are as follows. First, soil stratification is a typical phenomenon beneath the alpine meadows, with dense roots and soil organic matters within the topsoil, and it controls the profile of soil moisture in the central and eastern Plateau; all models significantly under-estimate the soil moisture within the topsoil. Second, a soil surface resistance controls the surface evaporation from the alpine deserts but it has not been reasonably modeled in LSMs; a new scheme is proposed to determine this resistance from soil water content. Third, an excess resistance controls sensible heat fluxes from dry bare-soil or sparsely vegetated surfaces, and all LSMs significantly under-predict the ground-air temperature difference in the daytime. A parameterization scheme for this resistance has been shown effective to remove this bias.
Analyzing influence of spatial resolution on the estimated evapotranspiration by using remote sensing data over an oasis area in Northwestern China
Authors: Tian H. , Wen J. , Su Z. B. , Ma Y. M. , Wang L. , Shi X. K. , Liu R. , Zhang T. T. , Zhang J. H.
Published: April 2010

Abstract. In this paper, the influence of spatial resolution on the precision of estimates was analyzed through evapotranspiration (ET hereafter) modeling over a typical oasis in northwestern China by using the Landsat-TM and MODIS data. A relatively high consistency was observed between the TM-based latent heat flux and daily ET estimates and in-situ measurements, with relative errors of 9.7% and 8.8%, respectively. Despite lower precision of the relative errors of 22.4% and 17.0%, respectively, the MODIS-based latent heat flux and ET estimates can effectively depict the basic trend of the spatial distribution of the land surface processes. When the visible and near-infrared information of 250 m resolution was syncretized into MODIS LST retrieval algorithm, the precision of latent heat flux prediction was improved evidently. Additionally, the diurnal variation of the reference ET fraction shows that the temporal upscaling method of ET is suitable for the study area. In spite of suffering the influence of the heterogeneity of land surface, the moderate resolution MODIS data, combined with the parameterization model of land surface energy flux applied in this investigation, are suitable for the ET mapping at large scale while high-resolution data can serve as an important supplement.
Terrain surfaces and 3-D landcover classification from small footprint full-waveform lidar data: application to badlands
Authors: Bretar F. , Chauve A. , Bailly J.-S. , Mallet C. , Jacome A.
Published: April 2010

Abstract. This article presents the use of new remote sensing data acquired from airborne full-waveform lidar systems. They are active sensors which record altimeter profiles. This paper introduces a set of methodologies for processing these data. These techniques are then applied to a particular landscape, the badlands, but the methodologies are designed to be applied to any other landscape. Indeed, the knowledge of an accurate topography and a landcover classification is a prior knowledge for any hydrological and erosion model. Badlands tend to be the most significant areas of erosion in the world with the highest erosion rate values. Monitoring and predicting erosion within badland mountainous catchments is highly strategic due to the arising downstream consequences and the need for natural hazard mitigation engineering. Additionaly, beyond the altimeter information, full-waveform lidar data are processed to extract intensity and width of echoes. They are related to the target reflectance and geometry. Wa will investigate the relevancy of using lidar-derived Digital Terrain Models (DTMs) and to investigate the potentiality of the intensity and width information for 3-D landcover classification. Considering the novelty and the complexity of such data, they are presented in details as well as guidelines to process them. DTMs are then validated with field measurements. The morphological validation of DTMs is then performed via the computation of hydrological indexes and photo-interpretation. Finally, a 3-D landcover classification is performed using a Support Vector Machine classifier. The introduction of an ortho-rectified optical image in the classification process as well as full-waveform lidar data for hydrological purposes is then discussed.
A novel approach to parameter uncertainty analysis of hydrological models using neural networks
Authors: Shrestha D. L. , Kayastha N. , Solomatine D. P.
Published: April 2010

Abstract. In this study, a methodology has been developed to replicate time consuming Monte Carlo (MC) simulation by using an Artificial Neural Network (ANN) for assessment of model parametric uncertainty. First, MC simulation of a given process model is run. Then an ANN is trained to approximate the functional relationships between the input variables of the process model and the synthetic uncertainty descriptors estimated from the realizations. The trained ANN model encapsulates the underlying characteristics of the parameter uncertainty and can be used to predict uncertainty descriptors for the new data vectors. This approach was validated by comparing the uncertainty descriptors in the verification data set with those obtained by MC simulation. The method is applied to estimate parameter uncertainty of a lumped conceptual hydrological model, HBV, for the Brue catchment in UK. The results are quite promising as the prediction intervals estimated by ANN are reasonably accurate. The proposed techniques could be useful in real time applications when it is not practicable to run a large number of simulations for complex hydrological models and when the forecast lead time is very short.
The artificial water catchment "Chicken Creek" as an observatory for critical zone processes and structures
Authors: Gerwin W. , Raab T. , Biemelt D. , Bens O. , Hüttl R. F.
Published: April 2010

Abstract. In order to better understand the processes of the "Critical Zone" investigations are mainly carried out in watersheds as they represent parts of the landscape having more or less defined outlines. However, natural watersheds must, in some cases, be characterized as "black boxes" with respect to e.g. structures in the underground or catchment boundaries which are generally unknown and need great efforts to be explored. Artificially created watersheds might, thus, be an appropriate alternative as boundaries and inner structures can be planned and defined in advance. This paper presents a recently launched project dealing with the initial phase of ecosystem development with a man-made catchment as central research site. The research site has an area of 6 ha and can be regarded as one of the largest artificial watersheds developed for scientific purposes worldwide. It was completed in 2005 and left for an unrestricted ecosystem succession. This paper introduces the creation and main properties of this site as well as first results of an ongoing monitoring program.
Comparison of empirical models with intensively observed data for prediction salt intrusion in the Sumjin River estuary, Korea
Authors: Shaha D. C. , Cho Y.-K.
Published: April 2010

Abstract. Intensive measurements of salt intrusion in the Sumjin River estuary were taken at high and low waters during both spring and neap tides in each season from August 2004 to April 2007. The estuary demonstrated partially- and well-mixed characteristics during the spring tide and stratified condition during the neap tide. The salt intrusion at high water varied from about 13.39 km in summer 2005 to 25.62 km in autumn 2006. The salt intrusion depended primarily on the freshwater discharges rather than those of spring-neap tidal oscillations. Analysis of three years of observed salinity data indicated that the salt intrusion length scale in the Sumjin River estuary was proportional to the river discharge to the −1/5 power. Five empirical models were applied to the Sumjin River estuary to explore the most suitable as an easy-to-use tool for prediction of the salt intrusion length as functions of the geometry, river discharge and tide. Comparative results showed that the Nguyen and Savenije (2006) model developed under both partially- and well-mixed estuaries yielded the most satisfactory results of all the models studied for computing the salt intrusion length in the Sumjin River estuary. Our study suggests that the model can generate reasonable results for stratified conditions also.
Seasonal and diurnal variations in moisture, heat and CO2 fluxes over a typical steppe prairie in Inner Mongolia, China
Authors: Gao Z. , Lenschow D. H. , He Z. , Zhou M. , Wang L. , Wang Y. , He J. , Shi J.
Published: April 2010

Abstract. In order to examine energy partitioning and CO2 exchange over a steppe prairie in Inner Mongolia, China, fluxes of moisture, heat and CO2 in the surface layer from June 2007 through June 2008 were calculated using the eddy covariance method. The study site was homogenous and approximately 1500 m×1500 m in size. Seasonal and diurnal variations in radiation components, energy components and CO2 fluxes are examined. Results show that all four radiation components changed seasonally, resulting in a seasonal variation in net radiation. The radiation components also changed diurnally. Winter surface albedo was higher than summer surface albedo because during winter the snow-covered surface increased the surface albedo. The seasonal variations in both sensible heat and CO2 fluxes were stronger than those of latent heat and soil heat fluxes. This implies that both sensible heat and CO2 fluxes may be more significant climate signals than latent heat and soil fluxes. Sensible heat flux was the main consumer of available energy for the entire experimental period. The energy imbalance problem was encountered and the causes are analyzed.
A general real-time formulation for multi-rate mass transfer problems
Authors: Silva O. , Carrera J. , Kumar S. , Dentz M. , Alcolea A. , Willmann M.
Published: April 2010

Abstract. Many flow and transport phenomena, ranging from delayed storage observed in pumping tests to tailing in river or aquifer tracer breakthrough curves, display non-equilibrium behavior. Usually, they are modeled by non-local in time formulations, such as multi-porosity, multiple processes non equilibrium, continuous time random walk, memory functions, integro-differential equations, fractional derivatives or multi-rate mass transfer (MRMT), among others. We develop a MRMT algorithm that can be used to represent all these formulations. The method is accurate, computationally inexpensive and easy to implement in groundwater or river flow and transport codes. In fact, we present a module that can be linked to existing programs with minimal programming effort. Its accuracy is verified by comparison with existing solutions.
Retrieval of Canopy component temperatures through Bayesian inversion of directional thermal measurements
Authors: Timmermans J. , Verhoef W. , van der Tol C. , Su Z.
Published: April 2010

Abstract. In remote sensing evapotranspiration is estimated using a single surface temperature. This surface temperature is an aggregate over multiple canopy components. The temperature of the individual components can differ significantly, introducing errors in the evapotranspiration estimations. The temperature aggregate has a high level of directionality. An inversion method is presented in this paper to retrieve four canopy component temperatures from directional brightness temperatures. The Bayesian method uses both a priori information and sensor characteristics to solve the ill-posed inversion problem. The method is tested using two case studies: 1) a sensitivity analysis, using a large forward simulated dataset, and 2) in a reality study, using two datasets of two field campaigns. The results of the sensitivity analysis show that the Bayesian approach is able to retrieve the four component temperatures from directional brightness temperatures with good success rates using multi-directional sensors (ℜspectra≈0.3, ℜgonio≈0.3, and ℜAATSR≈0.5), and no improvement using mono-angular sensors (ℜ≈1). The results of the experimental study show that the approach gives good results for high LAI values (RMSEgrass=0.50 K, RMSEwheat=0.29 K, RMSEsugar beet=0.75 K, RMSEbarley=0.67 K), but for low LAI values the measurement setup provides extra disturbances in the directional brightness temperatures, RMSEyoung maize=2.85 K, RMSEmature maize=2.85 K. As these disturbances, were only present for two crops and can be eliminated using masked thermal images the method is considered successful.
Ice breakup forecast in the reach of the Yellow River: the support vector machines approach
Authors: Zhou H. , Li W. , Zhang C. , Liu J.
Published: April 2010

Abstract. Accurate lead-time forecast of ice breakup is one of the key aspects for ice flood prevention and reducing losses. In this paper, a new data-driven model based on the Statistical Learning Theory was employed for ice breakup prediction. The model, known as Support Vector Machine (SVM), follows the principle that aims at minimizing the structural risk rather than the empirical risk. In order to estimate the appropriate parameters of the SVM, Multiobjective Shuffled Complex Evolution Metropolis (MOSCEM-UA) algorithm is performed through exponential transformation. A case study was conducted in the reach of the Yellow River. Results from the proposed model showed a promising performance compared with that from artificial neural network, so the model can be considered as an alternative and practical tool for ice breakup forecast.
Landscape scale patterns in the character of natural organic matter in a Swedish boreal stream network
Authors: Temnerud J. , Düker A. , Karlsson S. , Allard B. , Köhler S. , Bishop K.
Published: April 2010

Abstract. This paper defines landscape-scale patterns in the character of natural organic matter (NOM) and tests for relationships to catchment soil, vegetation and topography. The drainage network of a boreal catchment, subcatchment size 0.12–78 km2, in Northern Sweden was sampled in August 2002 during a period of stable low water flow. The NOM was characterized with UV/Vis spectroscopy, fluorescence, XAD-8 fractionation (%humic substances), gel permeation chromatography (apparent molecular weight), and elemental composition (C:N). The largest spatial variation was found for C:N, absorbance ratio, and specific visible absorptivity. The lowest variation was in fluorescence index, %humic substances and molecular retention time. But the variation in total organic carbon (TOC), iron and aluminium concentration was more than twice that of C:N. Between headwater and downstream sites no significant changes were distinguished in the NOM character. At stream reaches, junctions and lakes little change (<10%) in NOM character was observed. Common factor analysis and partial least squares regression (PLS) revealed that the spatial variation in surface coverage of lakes and mires could explain some of the variation of TOC and NOM character. Our suggestion is that the mosaic of landscape elements (different amounts of water from lakes, forest soil and mires) delivers NOM with varying characteristics to a channel network that mixes conservatively downstream, with possible small changes at some stream reaches, junctions and lakes.
The snowmelt runoff forecasting model of coupling WRF and DHSVM
Authors: Zhao Q. , Liu Z. , Li M. , Wei Z. , Fang S.
Published: April 2010

Abstract. This study used the Weather Research and Forecasting (WRF) modeling system and the Distributed Hydrology-Soil-Vegetation Model (DHSVM) to forecast the snowmelt runoff in the 800 km2 Juntanghu watershed of the northern slope of Tianshan Mountains from 29 February–6 March 2008. This paper made an exploration for snowmelt runoff forecasting model combing closely practical application in meso-microscale. It included: (1) A limited-region 24-h Numeric Weather Forecasting System was established by using the new generation atmospheric model system WRF with the initial fields and lateral boundaries forced by Chinese T213L31 model. (2) The DHSVM hydrological model driven by WRF forecasts was used to predicate 24 h snowmelt runoff at the outlet of Juntanghu watershed. The forecasted result shows a good agreement with the observed data, and the average absolute relative error of maximum runoff simulation result is less than 15%. The result demonstrates the potential of using meso-microscale snowmelt runoff forecasting model for flood forecast. The model can provide a longer forecast period compared to traditional models such as those based on rain gauges, statistical forecast.
Integrating field and numerical modeling methods for applied urban karst hydrogeology
Authors: Epting J. , Romanov D. , Huggenberger P. , Kaufmann G.
Published: April 2010

Abstract. Infrastructures that are constructed on unstable geologic formations are prone to subsidence. Data have been collected in the context of an upgrading project for a highway located beside a river dam that was constructed on gypsum-containing formations. Surface water infiltrates upstream of the dam, circulates through the gravel deposits and into the weathered bedrock around and beneath the dam, and exfiltrates downstream into the river. As a result, an extended weathering zone within the bedrock and preferential flow paths within voids and conduits developed as part of a rapidly evolving karst system. These processes enhance karstification in the soluble units of the gypsum-containing formations and resulted in the subsidence of the dam and the highway. Since 2006 changes in the hydrogeologic flow regime have been investigated continuously by different methods that also allow the evaluation of the long-term performance of the infrastructures. Geological (outcrops, lithostratigraphic information of boreholes), hydrometrical (extensive groundwater monitoring, dye tracer tests) and hydrogeophysical (Electrical Resistivity Tomography, ERT) field data of varying quality were integrated into high-resolution 3-D hydrogeological and 2-D karst evolution models. The applied investigative methods are validated and the sensitivity of relevant parameters governing the processes determined. It could be demonstrated that the applied methods for karst aquifer characterization complement each other and allow the interpretation of short-term impacts and long-term development on system-dynamics in the context of hydrogeologic flow regimes of karst areas. This includes the description of the transient character of the hydrogeologic flow regime during and after episodic flood events (surface-groundwater interaction, conduit and diffuse model outflow) as well as the evaluation of time scales for karst evolution. Results allow the optimization of investigative methods for similar subsidence problems, leading from general measurements and monitoring technologies to tools with predictive character.
The turbidity behavior in an Amazon floodplain
Authors: Alcântara E. , Novo E. , Stech J. , Lorenzzetti J. , Barbosa C. , Assireu A. , Souza A.
Published: April 2010

Abstract. The main objective of this study is to understand the turbidity behavior of an Amazon Floodplain Lake. Observations of turbidity provide quantitative information about water quality. However, the number of available in situ measurements for water quality determination is usually limited in time and space. Here, we present an analysis of the temporal and spatial variability using two approaches: (i) the first is based on wavelet analysis of a turbidity time series measured by an automatic monitoring system; (ii) the second is based on turbidity samples measured in different locations and then interpolated by an ordinary kriging algorithm. The space/time turbidity variability is clearly related to the Amazon River flood pulses in the floodplain. When the water level in the floodplain is rising or receding, the exchange between the Amazon River and the floodplain is the major driving force in turbidity variability. At high water level, the turbidity variability is controlled by the lake bathymetry. Finally, when the water level is low, the wind action and lake morphometry are the main causes of turbidity variability. The combined use of temporal and spatial data showed a great potential for understanding the turbidity behavior in a complex aquatic system, like the Amazon floodplain.
Hourly soil moisture mapping over West Africa using AMSR-E observations and a satellite-based rainfall product
Authors: Pellarin T. , Tran T. , Cohard J.-M. , Galle S. , Laurent J.-P. , de Rosnay P. , Vischel T.
Published: April 2010

Abstract. This paper provides an original and simple methodology to map surface soil moisture with a fine temporal and spatial resolution over large areas based on a satellite rainfall accumulation product and soil microwave emission measurements at C-band. The first motivation of this study was to obtain high temporal frequency (~1 h) in order to study the possible feedback mechanisms between soil moisture and convection in West Africa. The use of soil moisture maps derived from satellite microwave measurements was not possible due to the low (at best daily) temporal resolution. Thus, a rainfall accumulation product based on Meteosat geostationary satellite measurements was used together with a simple Antecedent Precipitation Index (API) model to produce soil moisture map at the 10×10 km2 and 30 min resolution. Due to uncertainties on the satellite-based rainfall accumulation product, derived soil moisture maps were found to be erroneous. An assimilation technique based on AMSR-E C-band measurements into a microwave emission model was developed. The assimilation technique described in this study consists of modulating the rainfall accumulation estimate between two successive AMSR-E brightness temperatures (TB) measurements in order to match simulated and observed TB. When a rainfall event happens, the initial rainfall accumulation estimate is modulated using a multiplicative factor ranging from 0 to 7. The best solution is given by the rainfall rate which minimizes the difference between observed and simulated TB. Ground-based soil moisture measurements obtained at three sites in Niger, Mali and Benin were used to assess the methodology which was found to improve the soil moisture estimates over the three sites.