bluuebunny/crossref_metadata_2025 huggingface dataset:
Updated world map of the Köppen-Geiger climate classification
Authors: Peel M. C. , Finlayson B. L. , McMahon T. A.
Published: April 2010

Abstract. Although now over 100 years old, the classification of climate originally formulated by Wladimir Köppen and modified by his collaborators and successors, is still in widespread use. It is widely used in teaching school and undergraduate courses on climate. It is also still in regular use by researchers across a range of disciplines as a basis for climatic regionalisation of variables and for assessing the output of global climate models. Here we have produced a new global map of climate using the Köppen-Geiger system based on a large global data set of long-term monthly precipitation and temperature station time series. Climatic variables used in the Köppen-Geiger system were calculated at each station and interpolated between stations using a two-dimensional (latitude and longitude) thin-plate spline with tension onto a 0.1°×0.1° grid for each continent. We discuss some problems in dealing with sites that are not uniquely classified into one climate type by the Köppen-Geiger system and assess the outcomes on a continent by continent basis. Globally the most common climate type by land area is BWh (14.2%, Hot desert) followed by Aw (11.5%, Tropical savannah). The updated world Köppen-Geiger climate map is freely available electronically at https://www.hydrol-earth-syst-sci.net/????.
Modelling the water budget and the riverflows of the Maritsa basin in Bulgaria
Authors: Artinyan E. , Habets F. , Noilhan J. , Ledoux E. , Dimitrov D. , Martin E. , Le Moigne P.
Published: April 2010

Abstract. A soil-vegetation-atmosphere transfer model coupled with a macroscale distributed hydrological model was used in order to simulate the water cycle for a large region in Bulgaria. To do so, an atmospheric forcing was built for two hydrological years (1 October 1995 to 30 September 1997), at an eight km resolution. It was based on the data available at the National Institute of Meteorology and Hydrology (NIMH) of Bulgaria. Atmospheric parameters were carefully checked and interpolated with a high level of detail in space and time (3-h step). Comparing computed Penman evapotranspiration versus observed pan evaporation validated the quality of the implemented forcing. The impact of the human activities on the rivers (especially hydropower or irrigation) was taken into account. Some improvements of the hydrometeorological model were made: for better simulation of summer riverflow, two additional reservoirs were added to simulate the slow component of the runoff. Those reservoirs were calibrated using the observed data of the 1st year, while the 2nd year was used for validation. 56 hydrologic stations and 12 dams were used for the model calibration while 41 rivergages were used for the validation of the model. The results compare well with the daily-observed discharges, with good results obtained over more than 25% of the rivergages. The simulated snow depth was compared to daily measurements at 174 stations and the evolution of the snow water equivalent was validated at 5 sites. The process of melting and refreezing of snow was found to be important on this region. The comparison of the normalized values of simulated versus measured soil moisture showed good correlation. The surface water budget shows large spatial variations due to the elevation influence on the precipitations, soil properties and vegetation variability. An inter annual difference was observed in the water cycle as the first year was more influenced by Mediterranean climate, while the second year was characterised by continental influence. Energy budget shows a dominating sensible heat component in summer, due to the fact that the water stress limits the evaporation. This study is a first step for the implementation of an operational hydrometeorological model that could be used for real time monitoring and forecast the water budget and the riverflow of Bulgaria.
Development of a window correlation matching method for improved radar rainfall estimation
Authors: Piman T. , Babel M. S. , Gupta A. D. , Weesakul S.
Published: April 2010

Abstract. The present study develops a method called window correlation matching method (WCMM) to reduce collocation and timing errors in matching pairs of radar measured reflectivity, Ze, and gauge measured rainfall intensity, R, for improving the accuracy of the estimation of Ze−R relationships. This method is compared with the traditional matching method (TMM) and the probability matching method (PMM). The relationship Ze=18.05 R1.45 obtained from 7×7 km of space window and both present and 5 min previous time of radar observation for time window (S77T5) produces the best results for radar rainfall estimates for orographic rain over the Mae Chaem Watershed in north of Thailand. The comparison shows that the Ze−R relationships obtained from WCMM provide more accuracy in radar rainfall estimates as compared with the other two methods. The Ze−R relationships estimated using TMM and PMM show large overestimation and underestimation, respectively, of mean areal rainfall. Based on the overall results, it can be concluded that WCMM can reduce collocation and timing errors in Ze−R pairs matching and improve the estimation of Ze−R relationships for radar rainfall. WCMM is therefore a promising method for improved radar-measured rainfall, which is an important input for hydrological and environmental modeling and water resources management.
Weathering rates and origin of inorganic carbon as influenced by river regulation in the boreal sub-arctic region of Sweden
Authors: Brink J. , Humborg C. , Sahlberg J. , Rahm L. , Mörth C.-M.
Published: April 2010

Abstract. Major environmental stressors of boreal and sub-arctic rivers are hydrological changes and global warming and both factors will significantly influence the future evolution of the river chemistry in high latitudes. We tested the hypothesis whether lower concentrations of dissolved constituents observed in regulated rivers come along with lower weathering rates, though specific discharge as a major force for physical erosion and weathering is often higher in regulated river systems. In this study the river chemistry, weathering rates and related carbon dioxide consumption in two large watersheds in the sub arctic region of Sweden, one regulated river (Lule River) and one unregulated river (Kalix River), was investigated. Weathering rates of silicates in the two watersheds are shown to be different; the silicate weathering rate in Kalix River catchment is almost 30% higher than in the Lule River catchment. This is most likely a result of constructing large reservoirs in the former river valleys inundating the alluvial deposits and thus decreasing soil/water contact resulting in lower weathering rates. Furthermore, the difference observed in weathering rates between lowland regions and headwaters suggests that weathering in sub arctic boreal climates is controlled by the residence time for soil water rock interactions followed by lithology. The chemistry in the two rivers shows weathering of silicates as the origin for 68% of the inorganic carbon in the Lule River and 74% for Kalix River. The study clearly shows that river regulation significantly decreases alkalinity export to the sea because lower weathering rates gives less carbon dioxide ending up as DIC. By considering sources for inorganic carbon we here report that the inorganic carbon load that originates from respiration of organic matter in soils makes up of 30% and 35% of the total C export for the watersheds of the Kalix River and Lule River, respectively. Therefore, both the inorganic (i.e. the origin of carbon in DIC) and organic carbon load carbon must be considered when studying climate changes on the organic carbon load since effects from increased degradation of organic matter may lead to more weathering (higher production of DIC).
A spatially distributed analysis of erosion susceptibility and sediment yield in a river basin by means of geomorphic parameters and regression relationships
Authors: Grauso S. , Fattoruso G. , Crocetti C. , Montanari A.
Published: April 2010

Abstract. In the present work, an application of statistical regression relationships utilising geomorphic parameters is attempted in a spatially distributed mode, in order to predict the amount of river sediment supply at varying sections of the drainage network. Simple and multiple regression relationships utilising drainage density Dd and hierarchical anomaly index Δa as independent variables were applied to the Calvano watershed (Central Italy) at different degree of subdivision in tributary drainage basins, so as to assess their contribution to the whole watershed sediment yield balance. In the same way, the role of small hill-reservoirs as sediment-trap and that of areas affected by badlands and of tributary basins exposure were also investigated. Results were tested on the basis of sedimentation estimates from selected reservoirs. The relationships provided a yearly specific sediment yield (SSY) value for the Calvano stream which is according to the average observed SSY in river basins of central Italy flowing to the Adriatic Sea. The use of simple statistical relationships, such as those here adopted, can allow to recognise the sections along the main stream which are more critical in terms of sediment accumulation, which, on turn, can cause sudden water discharge increments and dangerous floods. This approach can provide a tool enabling to locate the hydraulic risk and to point out the areas where soil conservation practices or hydraulic works, such as periodic maintenance of riverbeds, are needed in order to reduce soil erosion and sediment accumulation.
Precipitation and temperature ensemble forecasts from single-value forecasts
Authors: Schaake J. , Demargne J. , Hartman R. , Mullusky M. , Welles E. , Wu L. , Herr H. , Fan X. , Seo D. J.
Published: April 2010

Abstract. A procedure is presented to construct ensemble forecasts from single-value forecasts of precipitation and temperature. This involves dividing the spatial forecast domain and total forecast period into a number of parts that are treated as separate forecast events. The spatial domain is divided into hydrologic sub-basins. The total forecast period is divided into time periods, one for each model time step. For each event archived values of forecasts and corresponding observations are used to model the joint distribution of forecasts and observations. The conditional distribution of observations for a given single-value forecast is used to represent the corresponding probability distribution of events that may occur for that forecast. This conditional forecast distribution subsequently is used to create ensemble members that vary in space and time using the "Schaake Shuffle" (Clark et al, 2004). The resulting ensemble members have the same space-time patterns as historical observations so that space-time joint relationships between events that have a significant effect on hydrological response tend to be preserved. Forecast uncertainty is space and time-scale dependent. For a given lead time to the beginning of the valid period of an event, forecast uncertainty depends on the length of the forecast valid time period and the spatial area to which the forecast applies. Although the "Schaake Shuffle" procedure, when applied to construct ensemble members from a time-series of single value forecasts, may preserve some of this scale dependency, it may not be sufficient without additional constraint. To account more fully for the time-dependent structure of forecast uncertainty, events for additional "aggregate" forecast periods are defined as accumulations of different "base" forecast periods. The generated ensemble members can be ingested by an Ensemble Streamflow Prediction system to produce ensemble forecasts of streamflow and other hydrological variables that reflect the meteorological uncertainty. The methodology is illustrated by an application to generate temperature and precipitation ensemble forecasts for the American River in California. Parameter estimation and dependent validation results are presented based on operational single-value forecasts archives of short-range River Forecast Center (RFC) forecasts and medium-range ensemble mean forecasts from the National Weather Service (NWS) Global Forecast System (GFS).
Prediction of runoff and discharge in the Simiyu River (tributary of Lake Victoria, Tanzania) using the WetSpa model
Authors: Rwetabula J. , De Smedt F. , Rebhun M.
Published: April 2010

Abstract. A spatially distributed hydrologic model (WetSpa) is used to estimate daily river water discharge in the Simiyu river a tributary of Lake Victoria, Tanzania. The model combines topography, landuse and soil maps, and observed daily meteorological time series to predict discharge hydrographs and the spatial distribution of hydrological parameters in the catchment. The elevations in the catchment range from 2000 to 1100 m at the outlet, with average slope of 1.4%. The dominant landuse types are, wasteland, grassland, bushland, cultivated land, and a very small area is covered by surface water. The dominant soil types are sandy loam, followed by sandy clay loam, clay loam, clay, loam and sandy clay. There are two distinctive seasons in the Simiyu catchment. Short rains mainly in November, December and January, and long rains in March to May, resulting in a total average annual precipitation of 700 to 1000 mm. The annual potential evapotranspiration is about 1300 mm, and the river discharge at the catchment outlet ranges from 0 to about 200 m3/s. Global parameters of the model are calibrated using three years of daily observed discharge values measured at the mouth of the river at Lake Victoria. The estimated average travel time of the runoff to the outlet of the catchment is about 2.4 d and maximum 8 d for the most remote areas. The model results also show that the surface runoff and interflow provide respectively 38.6% and 61.4% of the total runoff, while the contribution of groundwater drainage is nil. The absence of groundwater drainage is probably due to the high evaporation demand of the atmosphere, which accounts for about 90% of the total precipitation being lost by evapotranspiration. The annual water balance estimated with the model reveals that the total outflow to Lake Victoria is about 500×106 m3 per year, which occurs mainly in the wet seasons, i.e. from March to May and from November to January. The volume of runoff produced by agricultural land amounts to about 9% of the total runoff annually.
Soft combination of local models in a multi-objective framework
Authors: Fenicia F. , Solomatine D. P. , Savenije H. H. G. , Matgen P.
Published: April 2010

Abstract. Conceptual hydrologic models are useful tools as they provide an interpretable representation of the hydrologic behaviour of a catchment. Their representation of catchment's hydrological processes and physical characteristics, however, implies simplification of the complexity and heterogeneity of reality. As a result, those models often show a lack of flexibility in reproducing the vast spectrum of catchment responses. Hence, the accuracy in reproducing certain aspects of the system behaviour is often paid in terms of a lack of accuracy in the representation of other aspects. By acknowledging the structural limitations of those models, a modular approach to hydrological simulation is proposed. Instead of using a single model to reproduce the full range of catchment responses, multiple models are used, each of them assigned to a specific task. The approach is here demonstrated in the case where the different models are associated with different parameter realizations within a fixed model structure. We show that using a composite "global" model, obtained by a combination of individual "local" models, the accuracy of the simulation is improved. We argue that this approach can be useful because it partially overcomes the structural limitations that a conceptual model might exhibit. The approach is shown in application to the discharge simulation of the experimental Alzette River basin in Luxembourg, with a conceptual model that follows the structure of the HBV model.
Probability distribution of flood flows in Tunisia
Authors: Abida H. , Ellouze M.
Published: April 2010

Abstract. L (Linear) moments are used in identifying regional flood frequency distributions for different zones Tunisia wide. 893 site-years of annual maximum stream flow data from a total of 37 stations with an average record length of 24.14 years are considered. The country is divided into two homogeneous regions (northern and central/southern Tunisia) using a heterogeneity measure, based on the spread of the sample L-moments among the sites in a given region. Then, selection of the corresponding distribution is achieved through goodness-of-fit comparisons in L-moment diagrams and verified using an L-moment based regional test that compares observed to theoretical values of L-skewness and L-kurtosis for various candidate distributions. The distributions used, which represent five of the most frequently used distributions in the analysis of hydrologic extreme variables are: (i) Generalized Extreme Value (GEV), (ii) Pearson Type III (P3), (iii) Generalized Logistic (GLO), (iv) Generalized Normal (GN), and (v) Generalized Pareto (GPA) distributions. Spatial trends, with respect to the best-fit flood frequency distribution, are distinguished: Northern Tunisia was shown to be represented by the GEV distribution while the GLO distribution gives the best fit in central/southern Tunisia.
Estimation of streamflow by slope Regional Dependency Function
Authors: Altunkaynak A.
Published: April 2010

Abstract. Kriging is one of the most developed methodologies in the regional variable modeling. However, one of its drawbacks is that the influence radius can not be determined by this method. In which distance and in what ratio that pivot station is influenced from adjacent sites is rather often encountered problem in practical applications. Regional weighting functions obtained from available data consist of several broken lines. Each line has different slopes which represent the similarity and the contribution of adjacent stations as a weighting coefficient. The approach in this study is called as Slope Regional Dependency Function (SRDF). The main idea of this approach is to express the variability in value differences [γ(d)] and distances together. Originally proposed SRDF and Trigonometric Point Cumulative Semi-Variogram (TPCSV) methods are used to predict streamflow. Also TPCSV and Point Cumulative Semi-Variogram (PCSV) approaches are compared with each other. Prediction performance of all three methods stays below 10% relative error which is acceptable for the engineering applications. It is shown that SRDF outperforms PCSV and TPCSV with very high differences. It can be used for missing data completion, determination of measurement sites location, calculation of influence radius, and determination of regional variable potential. The proposed method is applied for the 38 stream flow measurement sites located in the Mississippi River basin.
Development of a river ice jam by a combined heat loss and hydraulic model
Authors: Eliasson J. , Orri Gröndal G.
Published: April 2010

Abstract. This paper discusses and shows the heat loss theory and the hydraulic theory for the analysis of the development of wide channel ice jams. The heat loss theory has been used in Iceland for a long time, while the hydraulic theory largely follows the classical ice-jam build-up theories used in known CFD models. The results are combined in a new method to calculate the maximum thickness and the extent of an ice jam. The results compare favorably to the HEC-RAS model for the development of a very large ice jam in Thjorsa River in Iceland. They are also in good agreement with historical data, collected where a hydroelectric dam project, Urridafoss, is being planned in the Thjorsa River.
Simulating typhoon-induced storm hydrographs in subtropical mountainous watershed: an integrated 3-layer TOPMODEL
Authors: Huang J.-C. , Lee T.-Y. , Kao S.-J.
Published: April 2010

Abstract. A three-layer TOPMODEL is here constructed by integrating three components, diffusion wave approach into surface flow, soil moisture deficit into interflow and exponential recession curve function into base flow. Sensitivity analysis reveals that D (soil depth), K (hydraulic conductivity), and mi (soil moisture decay) predominate simulated hydrograph shape and total discharge, yet, there are distinct effects on the three flows. A subtropical mountainous watershed, Heng-Chi and eighteen typhoon-induced storms with various rainfall type and wide-ranged total rainfall (81 to 1026 mm) were applied. The global best-fitted combination gives an average efficient coefficient of 75.1% and 76.0% for calibration (14 cases) and validation (4 cases), respectively. Most discharges of validation events fall within the 90% confidence interval derived from calibration events. Those results demonstrate the capability of the 3-layer TOPMODEL in subtropical watershed. Meanwhile, the upper confidence limit is suggested preferably when considering the flood assessment.
Thermodynamics of the hydraulic head, pressure head, and gravitational head in subsurface hydrology, and principles for their spatial averaging
Authors: de Rooij G. H.
Published: April 2010

Abstract. In order to establish a thermodynamic justification of the theoretical relationship between the hydraulic, pressure/matric, and gravitational head in subsurface hydrology, the thermodynamic literature pertaining to subsurface flow processes is reviewed. The incompressibility of liquids negates a thermodynamic definition of pressure, which gives rise to several inconsistencies in pore scale theories. At larger scales, the gravitational potential and fluid pressure are treated as additive potentials. This superposition principle is replicated in the well-established relationship between the various heads according to subsurface hydrological theory. The necessary requirement that the superposition be maintained across scales is combined with conservation of energy during volume integration to establish consistent upscaling equations for the various heads. The power of these upscaling equations is demonstrated by the derivation of an upscaled water content-matric head relationship and the resolution of an apparent paradox reported in the literature that is shown to have arisen from a violation of the superposition principle.
Incorporating landscape characteristics in a distance metric for interpolating between observations of stream water chemistry
Authors: Lyon S. W. , Seibert J. , Lembo A. J. , Steenhuis T. S. , Walter M. T.
Published: April 2010

Abstract. Spatial patterns of water chemistry along stream networks can be quantified using synoptic or "snapshot" sampling. The basic idea is to sample stream water at many points over a relatively short period of time. Even for intense sampling campaigns, the number of sample points is limited and interpolation methods, like kriging, are commonly used to produce continuous maps of water chemistry based on the point observations from the synoptic sampling. Interpolated concentrations are influenced heavily by how distance between points along the stream network is defined. In this study, we investigate different ways to define distance and test these based on data from a snapshot sampling campaign in a 37-km2 watershed in the Catskill Mountains region (New York State). Three distance definitions (or metrics) were compared: Euclidean or straight-line distance, in-stream distance, and in-stream distance adjusted according characteristics of the local contributing area, i.e., an adjusted in-stream distance. Using the adjusted distance metric resulted in a lower cross-validation error of the interpolated concentrations, i.e., a better agreement of kriging results with measurements, than the other distance definitions. The adjusted distance metric can also be used in an exploratory manner to test which landscape characteristics are most influential for the spatial patterns of stream water chemistry and, thus, to target future investigations to gain process-based understanding of in-stream chemistry dynamics.
Improvement, calibration and validation of a distributed hydrological model over France
Authors: Quintana Seguí P. , Martin E. , Habets F. , Noilhan J.
Published: April 2010

Abstract. The hydrometeorological model SAFRAN-ISBA-MODCOU (SIM) computes water and energy budgets on the land surface and riverflows and the level of several aquifers at the scale of France. SIM is composed of a meteorological analysis system (SAFRAN), a land surface model (ISBA) and a hydrogeological model (MODCOU). In this study, an exponential profile of hydraulic conductivity at saturation is introduced to the model and its impact analysed. It is also studied how calibration modifies the performance of the model. A very simple method of calibration is implemented and applied to the parameters of hydraulic conductivity and subgrid runoff. The study shows that a better description of the hydraulic conductivity of the soil is important to simulate more realistic discharges. It is also shown that the calibrated model is more robust than the original SIM. In fact, the calibration mainly affects the processes related to the dynamics of the flow (drainage and runoff), and the rest of relevant processes (like evaporation) remain stable. It is also proven that it is only worth introducing the new empirical parameterization of hydraulic conductivity if it is accompanied by a calibration of its parameters, otherwise the simulations can be degraded. In conclusion, it is shown that the new parameterization is necessary to obtain good simulations. Calibration is a tool that must be used to improve the performance of distributed models like SIM that have some empirical parameters.
Understanding and managing a complex estuary: the process towards more congruence between the physical system characteristics and the management system of the Westerschelde (Netherlands)
Authors: van Buuren A. , Gerrits L.
Published: April 2010

Abstract. In this article, we expand on the relationship between the social processes of policymaking, management and research in the context of the Westerschelde estuary. This complex estuary system, located in Belgium and the Netherlands, has its own morphological and ecological characteristics and dynamics, and has three core functions: economically, it makes the port of Antwerp accessible; ecologically, it generates habitats for certain unique species; and in terms of safety, it prevents the hinterland from being flooded. We analyze how the social processes of policymaking, management and analysis have focused on these three aspects, and how they have affected the estuary. We proceed to develop a framework for evaluating the social system of policy-making, management and research. This framework focuses on the social system's adaptive capabilities (how it evolved in a non-linear fashion), integrative capacity (how the system's interconnectivity was taken into account), and participative competencies (how the different interests and insights regarding the estuary were absorbed). This framework was then applied to twenty years of policymaking about, management of, and research on the Westerschelde estuary. We conclude that, because of policy learning effects, policy/management and research take the estuary's self-organizing capacities into account much more than they did in the past. However, the self-referential behaviour of policymakers, managers and researchers makes it possible that an anthropocentric and technocratic approach towards managing the estuary, indicating a disconnection between the social and physical systems, could return.
Staged cost optimization of urban storm drainage systems based on hydraulic performance in a changing environment
Authors: Maharjan M. , Pathirana A. , Gersonius B. , Vairavamoorthy K.
Published: April 2010

Abstract. Urban flooding causes large economic losses, property damage and loss of lives. The impact of environmental changes mainly, the urbanization and the climatic change leads to increased runoff and increased peak flows which the drainage system must be able to cope with to overcome possible damage and inconveniences caused by the induced flooding. Allowing for detention storage to compliment the capacity of the drainage system network is one of the approaches to reduce urban floods. The traditional practice was to design systems against stationary environmental forcings – including design rainfall, landuse, etc. Due to the rapid change in climate-environment, this approach is no longer economically viable and safe, and explicit consideration of changes that gradually take place during the life-time of the drainage system is warranted. In this paper, a staged cost optimization tool based on the hydraulic performance of the drainage system is presented. A one dimensional hydraulic model is used for hydraulic evaluation of the network together with a genetic algorithm based optimization tool to determine optimal intervention timings and amounts throughout the lifespan of the drainage network. The model was applied in a case study area in the city of Porto Alegre, Brazil. It was concluded that considerable financial savings and/or additional level of flood-safety can be achieved by approaching the design problem as a staged plan rather than one-off scheme.
Scale effects on runoff generation in meso-scale and large-scale sub-basins in the Luanhe River Basin
Authors: Feng P. , Li J. Z.
Published: April 2010

Abstract. The scale effects on runoff coefficients have been observed by several researchers on plots or small watersheds, however, little research has been done on meso-scale and large-scale catchments. So six meso-scale and large-scale sub-basins of the Luanhe river basin, in northeast of China, were selected for calculating the runoff coefficients of single event during 1956–2002. An obvious reduction in average runoff coefficients from 0.43 (Liuhe basin) to 0.10 (Luanhe basin) was found with increasing basin area. And for the annual runoff coefficients from 1956 to 2002, the same trend was also observed. In addition, runoff coefficients varied wildly from one rainstorm to the other. One of the reasons is that at the beginning of the storm, the rainfall is absorbed in the soil and fills in the macropores of the soil, and after runoff generation rainfall infiltrates during the routing process. And the spatial variability of rainfall, the groundwater discharge ability can also lead to runoff coefficients reduction with the increasing basin area. The study on the scale effects on runoff coefficient is very important to develop a physically-based hydrological model and parameter estimation on different scales.
From near-surface to root-zone soil moisture using an exponential filter: an assessment of the method based on in-situ observations and model simulations
Authors: Albergel C. , Rüdiger C. , Pellarin T. , Calvet J.-C. , Fritz N. , Froissard F. , Suquia D. , Petitpa A. , Piguet B. , Martin E.
Published: April 2010

Abstract. A long term data acquisition effort of profile soil moisture is under way in southwestern France at 13 automatic weather stations. This ground network was developed in order to validate remote sensing and model soil moisture estimates. In this paper, both those in situ observations and a synthetic data set covering continental France are used to test a simple method to retrieve the root zone soil moisture from a time series of surface soil moisture information. A recursive exponential filter equation using a time constant, T, is used to compute a soil water index. The Nash and Sutcliff coefficient is used as a criterion to optimise the T parameter for each ground station and for each model pixel of the synthetic data set. In general, the soil water indices derived from the surface soil moisture observations and simulations agree well with the reference root-zone soil moisture. Overall, the results show the potential of the exponential filter equation and of its recursive formulation to derive a soil water index from surface soil moisture estimates. This paper further investigates the correlation of the time scale parameter T with soil properties and climate conditions. While no significant relationship could be determined between T and the main soil properties (clay and sand fractions, bulk density and organic matter content), the modelled spatial variability and the observed inter-annual variability of T suggest that a climate effect exists.
Estimating surface fluxes over the north Tibetan Plateau area with ASTER imagery
Authors: Ma W. , Ma Y. , Li M. , Hu Z. , Zhong L. , Su Z. , Ishikawa H. , Wang J.
Published: April 2010

Abstract. Surface fluxes are important boundary conditions for climatological modeling and Asian monsoon system. The recent availability of high-resolution, multi-band imagery from the ASTER (Advanced Space-borne Thermal Emission and Reflection radiometer) sensor has enabled us to estimate surface fluxes. ASTER covers a wide spectral region with 14 bands from the visible to the thermal infrared with high spatial, spectral and radiometric resolution. The spatial resolution varies with wavelength: 15 m in the visible and near-infrared (VNIR), 30 m in the short wave infrared (SWIR), and 90 m in the thermal infrared (TIR). A parameterization method based on ASTER data and field observations has been proposed and tested for deriving surface albedo, surface temperature, Normalized Difference Vegetation Index (NDVI), Modified Soil Adjusted Vegetation Index (MSAVI), vegetation coverage, Leaf Area Index (LAI), net radiation flux, soil heat flux, sensible heat flux and latent heat flux over heterogeneous land surface in this paper. As a case study, the methodology was applied to the experimental area of the Coordinated Enhanced Observing Period (CEOP) Asia-Australia Monsoon Project (CAMP) on the Tibetan Plateau (CAMP/Tibet), which located at the north Tibetan Plateau. The ASTER data of 24 July 2001, 29 November 2001 and 12 March 2002 was used in this paper for the case of summer, winter and spring. To validate the proposed methodology, the ground-measured surface variables (surface albedo and surface temperature) and land surface heat fluxes (net radiation flux, soil heat flux, sensible heat flux and latent heat flux) were compared to the ASTER derived values. The results show that the derived surface variables and land surface heat fluxes in three different months over the study area are in good accordance with the land surface status. Also, the estimated land surface variables and land surface heat fluxes are in good accordance with ground measurements, and all their absolute percent difference (APD) is less than 10% in the validation sites. It is therefore concluded that the proposed methodology is successful for the retrieval of land surface variables and land surface heat fluxes using the ASTER data and filed observation over the study area.
An artificial neural network model for rainfall forecasting in Bangkok, Thailand
Authors: Hung N. Q. , Babel M. S. , Weesakul S. , Tripathi N. K.
Published: April 2010

Abstract. The present study developed an artificial neural network (ANN) model to overcome the difficulties in training the ANN models with continuous data consisting of rainy and non-rainy days. Among the six models analyzed the ANN model which used generalized feedforward type network and a hyperbolic tangent function and a combination of meteorological parameters (relative humidity, air pressure, wet bulb temperature and cloudiness), and the rainfall at the point of forecasting and rainfall at the surrounding stations, as an input for training of the model was found most satisfactory in forecasting rainfall in Bangkok, Thailand. The developed ANN model was applied to derive rainfall forecast from 1 to 6 h ahead at 75 rain gauge stations in the study area as forecast point from the data of 3 consecutive years (1997–1999). Results were highly satisfactory for rainfall forecast 1 to 3 h ahead. Sensitivity analysis indicated that the most important input parameter beside rainfall itself is the wet bulb temperature in forecasting rainfall. Based on these results, it is recommended that the developed ANN model can be used for real-time rainfall forecasting and flood management in Bangkok, Thailand.
Modelling water-harvesting systems in the arid south of Tunisia using SWAT
Authors: Ouessar M. , Bruggeman A. , Abdelli F. , Mohtar R. H. , Gabriels D. , Cornelis W. M.
Published: April 2010

Abstract. In many arid countries, runoff water-harvesting systems support the livelihood of the rural population. Little is known, however, about the effect of these systems on the water balance components of arid watersheds. The objective of this study was to adapt and evaluate the GIS-based watershed model SWAT (Soil Water Assessment Tool) for simulating the main hydrologic processes in arid environments. The model was applied to the 270-km2 watershed of wadi Koutine in southeast Tunisia, which receives about 200 mm annual rain. The main adjustment for adapting the model to this dry Mediterranean environment was the inclusion of water-harvesting techniques and a modification of the crop growth processes. The adjusted version of the model was named SWAT-WH. Model evaluation was performed based on 38 runoff events recorded at the Koutine station between 1973 and 1985. The model predicted that the average annual watershed rainfall of the 12-year evaluation period (209 mm) was split into ET (72%), groundwater recharge (22%) and outflow (6%). The evaluation coefficients for calibration and validation were, respectively, R2 (coefficient of determination) 0.77 and 0.76; E (Nash-Sutcliffe coefficient) 0.73 and 0.43; and MAE (Mean Absolute Error) 2.6 mm and 3.0 mm, indicating that the model could reproduce the observed events reasonably well. Discrepancies remained mainly due to uncertainties in the observed rainfall and runoff data. Recommendations for future research include the installation of additional rainfall and runoff gauges with continuous data logging and the collection of more field data to refine the input parameters (soil and land use). In addition, crop growth and yield monitoring is needed for a proper evaluation of the crop growth submodel, to allow the economic assessment of the different water uses in the watershed.
Analysis of surface and root-zone soil moisture dynamics with ERS scatterometer and the hydrometeorological model SAFRAN-ISBA-MODCOU at Grand Morin watershed (France)
Authors: Paris Anguela T. , Zribi M. , Hasenauer S. , Habets F. , Loumagne C.
Published: April 2010

Abstract. Spatial and temporal variations of soil moisture strongly affect flooding, erosion, solute transport and vegetation productivity. Its characterization, offers an avenue to improve our understanding of complex land surface–atmosphere interactions. In this paper, soil moisture dynamics at soil surface (first centimeters) and root-zone (up to 1.5 m depth) are investigated at three spatial scales: local scale (field measurements), 8×8 km2 (hydrological model) and 25×25 km2 scale (ERS scatterometer) in a French watershed. This study points out the quality of surface and root-zone soil moisture data for SIM model and ERS scatterometer for a three year period. Surface soil moisture is highly variable because is more influenced by atmospheric conditions (rain, wind and solar radiation), and presents RMS errors up to 0.08 m3 m−3. On the other hand, root-zone moisture presents lower variability with small RMS errors (between 0.02 and 0.06 m3 m-3). These results will contribute to satellite and model verification of moisture, but also to better application of radar data for data assimilation in future.
Interannual variability of winter precipitation in the European Alps: relations with the North Atlantic Oscillation
Authors: Bartolini E. , Claps P. , D'Odorico P.
Published: April 2010

Abstract. The European Alps rely on winter precipitation for various needs in terms of hydropower and other water uses. Major European rivers originate from the Alps and rely on winter precipitation and the consequent spring snow melt for their summer base flows. Understanding the fluctuations in winter rainfall in this region is crucially important to the study of changes in hydrologic regime in streams and rivers, as well as to the management of their water resources. Despite the recognized relevance of winter precipitation to the water resources of the Alps and surrounding regions, the magnitude and mechanistic explanation of interannual precipitation variability in the Alpine region remain unclear and poorly investigated. Here we use gridded precipitation data from the CRU TS 1.2 to study the interannual variability of winter alpine precipitation. We found that the Alps are the region with the highest interannual variability in winter precipitation in Europe. This variability cannot be completely explained by large scale climate patterns such as the AO, NAO or the EA-WR, even though regions below and above the Alps demonstrate connections with these patterns. Significant trends were detected only in small areas within this region, and were of opposite sign between the eastern and western part of the Alps.
Uncertainties on mean areal precipitation: assessment and impact on streamflow simulations
Authors: Moulin L. , Gaume E. , Obled C.
Published: April 2010

Abstract. This paper investigates the influence of mean areal rainfall estimation errors on a specific case study: the use of lumped conceptual rainfall-runoff models to simulate the flood hydrographs of three small to medium-sized catchments of the upper Loire river. This area (3200 km2) is densely covered by an operational network of stream and rain gauges. It is frequently exposed to flash floods and the improvement of flood forecasting models is then a crucial concern. Particular attention has been drawn to the development of an error model for rainfall estimation consistent with data in order to produce realistic streamflow simulation uncertainty ranges. The proposed error model combines geostatistical tools based on kriging and an autoregressive model to account for temporal dependence of errors. It has been calibrated and partly validated for hourly mean areal precipitation rates. Simulated error scenarios were propagated into two calibrated rainfall-runoff models using Monte Carlo simulations. Three catchments with areas ranging from 60 to 3200 km2 were tested to reveal any possible links between the sensitivity of the model outputs to rainfall estimation errors and the size of the catchment. The results show that a large part of the rainfall-runoff (RR) modelling errors can be explained by the uncertainties on rainfall estimates, especially in the case of smaller catchments. These errors are a major factor limiting accuracy and sharpness of rainfall-runoff simulations, and thus their operational use for flood forecasting.
A precipitation-based regionalization for Western Iran and regional drought variability
Authors: Raziei T. , Bordi I. , Pereira L. S.
Published: April 2010

Abstract. The spatial distribution of the seasonal and annual precipitation was analyzed in western Iran using data from 140 stations covering the period 1965–2000. Applying the Precipitation Concentration Index (PCI), the intra-annual precipitation variability was also studied. Furthermore, nine precipitation-derived parameters were used to regionalize climate in western Iran using principal component analysis and clustering techniques. Results suggest that five spatially homogenous sub-regions can be identified characterized by different precipitation regimes. The spatial pattern of seasonal precipitation seems to be highly controlled by the wide latitudinal extent of the region and by the pronounced orographic relieves, and the time of occurrence of the maximum precipitation varies from spring in the north to winter in the south. The time variability of dry and wet periods in the identified sub-regions was analyzed using the Precipitation Index (PI) and the existence of any long-term trend was tested. Results show that the northern and southern regions of western Iran are characterized by different climatic variability. Furthermore, a negative long-term linear trend in the north and a weak positive trend in the south of the study area have been detected though they are not statistically significant.
Cost-effective raingauge deployment and rainfall heterogeneity effect on hydrograph simulation in mountainous watersheds
Authors:   Jr-Chuan Huang,   Shuh-Ji Kao,   Kang-Tsung Chang,   Chuan-Yao Lin,   Pao-Liang Chang
Published: April 2010

Abstract. To what extent hydrograph simulation was influenced by the representativeness of rainfall input were examined in meso-scale subtropical mountainous watersheds, accordingly, cost-effective raingauge deployment was suggested. Two nested watersheds in northern Taiwan and two extreme typhoons with torrential rains were undertaken as case studies. The input of radar rainfall estimates with high spatial resolution of 1.3 km2 served as a reference, which was applied onto hydrograph simulation in TOPMODEL. After calibration, optimal parameters were obtained and fixed to examine effect of deviated rainfall on hydrograph. To mimic possible raingauge networks we designed four raingauge number classes: very low (3 points/total pixels), low (10 points/total), medium (20 points/total), and high (50 points/total) based on radar rainfall for the two watersheds in different size, thus, creating wide spectrum of raingauge density. All the corresponding hydrographs were compared with the reference hydrograph to probe errors in event discharge induced by calculated rainfall input. Results showed that with the decreasing of raingauge density the biases (indicated by RMSE) of rainfall field estimates increase and the potential variability in rainfall field due to random sampling in raingauge location is exaggerated. By contrast, biases in model hydrographs are significantly smaller than that in rainfall field. When the raingauge governing area is <10 km2/gauge, the biased rainfall field shows no detectable effect on hydrographs. Incomparably lower RMSE in hydrograph indicates that surplus and deficit rainfalls at different locations were compensated in model simulation. In term of reliable hydrograph simulation, obviously, the criterion for raingauge density is not as high as that for rainfall estimate. When gauge governing is <20 km2/gauge, both the rainfall and discharge were successfully (±10% error) estimated in term of total volume. Accordingly, we suggested that covering area ~20 km2/gauge is acceptable for raingauge deployment to constrain the inherent variability in rainfall field and hydrograph simulation in mountainous watersheds.