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Seismic object detection is a relatively new field in which 3-D bodies are visualized and spatial relationships between objects of different origins are studied in order to extract geologic information. In this paper, we propose a method for finding an optimal classifier with the help of a statistical feature ranking technique and combining different classifiers. The method, which has general applicability, is demonstrated here on a gas chimney detection problem. First, we evaluate a set of input seismic attributes extracted at locations labeled by a human expert using regularized discriminant analysis (RDA). In order to find the RDA score for each seismic attribute, forward and backward search strategies are used. Subsequently, two non-linear classifiers: multilayer perceptron (MLP) and support vector classifier (SVC) are run on the ranked seismic attributes. Finally, to capitalize on the intrinsic differences between both classifiers, the MLP and SVC results are combined using logical rules of maximum, minimum and mean. The proposed method optimizes the ranked feature space size and yields the lowest classification error in the final combined result. We will show that the logical minimum reveals gas chimneys that exhibit both the softness of MLP and the resolution of SVC classifiers.

Conventional streamflow models operate under the assumption of constant variance or season-dependent variances (e.g. ARMA (AutoRegressive Moving Average) models for deseasonalized streamflow series and PARMA (Periodic AutoRegressive Moving Average) models for seasonal streamflow series). However, with McLeod-Li test and Engle's Lagrange Multiplier test, clear evidences are found for the existence of autoregressive conditional heteroskedasticity (i.e. the ARCH (AutoRegressive Conditional Heteroskedasticity) effect), a nonlinear phenomenon of the variance behaviour, in the residual series from linear models fitted to daily and monthly streamflow processes of the upper Yellow River, China. It is shown that the major cause of the ARCH effect is the seasonal variation in variance of the residual series. However, while the seasonal variation in variance can fully explain the ARCH effect for monthly streamflow, it is only a partial explanation for daily flow. It is also shown that while the periodic autoregressive moving average model is adequate in modelling monthly flows, no model is adequate in modelling daily streamflow processes because none of the conventional time series models takes the seasonal variation in variance, as well as the ARCH effect in the residuals, into account. Therefore, an ARMA-GARCH (Generalized AutoRegressive Conditional Heteroskedasticity) error model is proposed to capture the ARCH effect present in daily streamflow series, as well as to preserve seasonal variation in variance in the residuals. The ARMA-GARCH error model combines an ARMA model for modelling the mean behaviour and a GARCH model for modelling the variance behaviour of the residuals from the ARMA model. Since the GARCH model is not followed widely in statistical hydrology, the work can be a useful addition in terms of statistical modelling of daily streamflow processes for the hydrological community.

This paper addresses the use of the methods of nonlinear dynamics and chaos theory for building a predictive chaotic model from time series. The chaotic model predictions are made by the adaptive local models based on the dynamical neighbors found in the reconstructed phase space of the observables. We implemented the univariate and multivariate chaotic models with direct and multi-steps prediction techniques and optimized these models using an exhaustive search method. The built models were tested for predicting storm surge dynamics for different stormy conditions in the North Sea, and are compared to neural network models. The results show that the chaotic models can generally provide reliable and accurate short-term storm surge predictions.

With the help of four years (2002–2005) of CHAMP accelerometer data we have investigated the dependence of low and mid latitude thermospheric density on the merging electric field, Em, during major magnetic storms. Altogether 30 intensive storm events (Dstmin <−100 nT) are chosen for a statistical study. In order to achieve a good correlation Em is preconditioned. Contrary to general opinion, Em has to be applied without saturation effect in order to obtain good results for magnetic storms of all activity levels. The memory effect of the thermosphere is accounted for by a weighted integration of Em over the past 3 h. In addition, a lag time of the mass density response to solar wind input of 0 to 4.5 h depending on latitude and local time is considered. A linear model using the preconditioned Em as main controlling parameter for predicting mass density changes during magnetic storms is developed: ρ =0.5Em+ρamb, where ρamb is based on the mean density during the quiet day before the storm. We show that this simple relation predicts all storm-induced mass density variations at CHAMP altitude fairly well especially if orbital averages are considered.

The water sector is dependent on effective institutions and organisations, and, therefore, on strong competences at the individual level. In this paper we describe competence formation and competence needs in a case study of the Directorate General of Water Resources (DGWR) in the Ministry of Public Works in Indonesia. A framework is introduced for the water sector comprising three aggregate competences for technical issues, management, and governance, and a meta-competence for continuous learning and innovation. The four competences are further organised in a T-shaped competence profile. Though DGWR professionals have a firmly "technical" orientation, both surveys and interviews reveal a strong perceived requirement for other competences: in particular the learning meta-competence, as well as the aggregate competence for management. The aggregate competence for governance systematically scores lower. Further, a discrepancy appears to exist between the competences that staff perceive as needed in daily work, and those that can be acquired during post-graduate water education. In both locally-based and international post-graduate water education, the aggregate competences for management as well as governance are reportedly addressed modestly, if at all. With low competence in these fields, it is difficult for professionals to communicate and collaborate effectively in a multidisciplinary way. As a result, the horizontal bar of the T-shaped profile remains weakly developed. In international post-graduate education, this is partially compensated by the attention to continuous learning and innovation. The exposure to a different culture and learning format is experienced as fundamentally formative.

This study evaluated between-sample memory in isotopic measurements of ϐ2H and ϐ18O in water samples by laser spectroscopy. Ten isotopically depleted water samples spanning a broad range of oxygen and hydrogen isotopic compositions were measured by three generations of offaxis integrated cavity output spectroscopy and cavity ringdown spectroscopy instruments. The analysis procedure encompassed small (less than 2‰ for ϐ2H and 1‰ for ϐ18O) and large (up to 201‰ for ϐ2H and 25‰ for ϐ18O) differences in isotopic compositions between adjacent sample vials. Samples were injected 18 times each, and the betweensample memory effect was quantified for each analysis run. Results showed that samples adversely affected by betweensample isotopic differences stabilised after seven–eight injections. The between-sample memory effect ranged from 14% and 9% for ϐ2H and ϐ18O measurements, respectively, but declined to negligible carryover (between 0.1% and 0.3% for both isotopes) when the first ten injections of each sample were discarded. The measurement variability (range and standard deviation) was strongly dependent on the isotopic difference between adjacent vials. Standard deviations were up to 7.5‰for ϐ2H and 0.54‰for ϐ18O when all injections were retained in the computation of the reportable ϐ-value, but a significant increase in measurement precision (standard deviation in the range 0.1 ‰–1.0‰ for ϐ2H and 0.05‰– 0.17‰for ϐ18O) was obtained when the first eight injections were discarded. In conclusion, this study provided a practical solution to mitigate between-sample memory effects in the isotopic analysis of water samples by laser spectroscopy.

An analytical model for tidal dynamics has been applied to the Yangtze Estuary for the first time, to describe the tidal propagation in this large and typically branched estuary with three-order branches and four outlets to the sea. This study shows that the analytical model developed for a single-channel estuary can also accurately describe the tidal dynamics in a branched estuary, particularly in the downstream part. Within the same estuary system, the North Branch and the South Branches have a distinct tidal behaviour: the former being amplified demonstrating a marine character and the latter being damped with a riverine character. The satisfactory results for the South Channel and the South Branch using both separate and combined topographies confirm that the branched estuary system functions as an entity. To further test these results, it is suggested to collect more accurate and dense bathymetric and tidal information.

The importance of hydrological processes for landslide activity is generally accepted. However, the relationship between precipitation, hydrological responses and movement is not straightforward. Groundwater recharge is mostly controlled by the hydrological material properties and the structure (e.g., layering, preferential flow paths such as fissures) of the unsaturated zone. In slow-moving landslides, differential displacements caused by the bedrock structure complicate the hydrological regime due to continuous opening and closing of the fissures, creating temporary preferential flow paths systems for infiltration and groundwater drainage. The consecutive opening and closing of fissure aperture control the formation of a critical pore water pressure by creating dynamic preferential flow paths for infiltration and groundwater drainage. This interaction may explain the seasonal nature of the slow-moving landslide activity, including the often observed shifts and delays in hydrological responses when compared to timing, intensity and duration of precipitation. The main objective of this study is to model the influence of fissures on the hydrological dynamics of slow-moving landslide and the dynamic feedbacks between fissures, hydrology and slope stability. For this we adapt the spatially distributed hydrological and slope stability model (STARWARS) to account for geotechnical and hydrological feedbacks, linking between hydrological response of the landside and the dynamics of the fissure network and applied the model to the hydrologically controlled Super-Sauze landslide (South French Alps).

In this paper, a database of water-related insurance damage claims related to private properties and content was analysed. The aim was to investigate whether the probability of occurrence of rainfall-related damage was associated with the intensity of rainfall. Rainfall data were used for the period of 2003–2009 in the Netherlands based on a network of 33 automatic rain gauges operated by the Royal Netherlands Meteorological Institute. Insurance damage data were aggregated to areas within 10-km range of the rain gauges. Through a logistic regression model, high claim numbers were linked to maximum rainfall intensities, with rainfall intensity based on 10-min to 4-h time windows. Rainfall intensity proved to be a significant damage predictor; however, the explained variance, approximated by a pseudo-R2 statistic, was at most 34% for property damage and at most 30% for content damage. When directly comparing predicted and observed values, the model was able to predict 5–17% more cases correctly compared to a random prediction. No important differences were found between relations with property and content damage data. A considerable fraction of the variance is left unexplained, which emphasizes the need to study damage generating mechanisms and additional explanatory variables.

The complex interactions of runoff generation processes underlying the hydrological response of streams remain not entirely understood at the catchment scale. Extensive research has demonstrated the utility of tracers for both inferring flow path distributions and constraining model parameterizations. While useful, the common use of linearity assumptions, i.e. time invariance and complete mixing, in these studies provides only partial understanding of actual process dynamics. Here we use long-term (<20 yr) precipitation, flow and tracer (chloride) data of three contrasting upland catchments in the Scottish Highlands to inform integrated conceptual models investigating different mixing assumptions. Using the models as diagnostic tools in a functional comparison, water and tracer fluxes were then tracked with the objective of exploring the differences between different water age distributions, such as flux and resident water age distributions, and characterizing the contrasting water age pattern of the dominant hydrological processes in the three study catchments to establish an improved understanding of the wetness-dependent temporal dynamics of these distributions. The results highlight the potential importance of partial mixing processes which can be dependent on the hydrological functioning of a catchment. Further, tracking tracer fluxes showed that the various components of a model can be characterized by fundamentally different water age distributions which may be highly sensitive to catchment wetness history, available storage, mixing mechanisms, flow path connectivity and the relative importance of the different hydrological processes involved. Flux tracking also revealed that, although negligible for simulating the runoff response, the omission of processes such as interception evaporation can result in considerably biased water age distributions. Finally, the modeling indicated that water age distributions in the three study catchments do have long, power-law tails, which are generated by the interplay of flow path connectivity, the relative importance of different flow paths as well as by the mixing mechanisms involved. In general this study highlights the potential of customized integrated conceptual models, based on multiple mixing assumptions, to infer system internal transport dynamics and their sensitivity to catchment wetness states.

The snowpack is a complicated multiphase mixture with mechanical, hydraulic, and thermal properties highly variable during the year in response to climatic forcings. Bulk density is a macroscopic property of the snowpack used, together with snow depth, to quantify the water stored. In seasonal snowpacks, the bulk density is characterized by a strongly non-linear behaviour due to the occurrence of both dry and wet conditions. In the literature, bulk snow density estimates are obtained principally with multiple regressions, and snowpack models have put the attention principally on the snow depth and snow water equivalent. Here a one-dimensional model for the temporal dynamics of the snowpack, with particular attention to the bulk snow density, has been proposed, accounting for both dry and wet conditions. The model represents the snowpack as a two-constituent mixture: a dry part including ice structure, and air; and a wet part constituted by liquid water. It describes the dynamics of three variables: the depth and density of the dry part and the depth of liquid water. The model has been calibrated and validated against hourly data registered at three SNOTEL stations, western US, with mean values of the Nash–Sutcliffe coefficient ≈0.73–0.97 in the validation period.

This paper analyses the design and impact of capacity building programmes aimed at enhancing capacities of riparian professionals to address and resolve transboundary issues in international river basins. The case study is a programme developed by the Mekong River Commission (MRC). A post-training evaluation was applied to assess its impact in terms of individual capacity enhancement and change (use and application of knowledge, factors hampering application, and change in function and opportunities within the organisation). The design of the Capacity Building Programme of the MRC Flood Management and Mitigation Programme required a well balanced range of subjects (such as IWRM (integrated water resources management), model and decision support systems, and international water law). The post-training evaluation, 6 months after the last training workshop, showed an increase in familiarity with the topics for all 37 respondents, with the highest increase for the respondents with few years of working experience and from training and education institutions. The relevance of the subjects taught was highlighted by 95% of the respondents, and 78% of the participants had already used some of the acquired knowledge in their job. The respondents indicated that they did not have sufficient opportunities to apply all knowledge. The phased implementation and training of lecturers during the training workshops had a good impact, directly through increasing involvement in facilitation and delivery of the capacity building programme and through the use of the knowledge gained in short courses and development of curricula at their institute. For these types of capacity building programmes, a few recommendations can be made. The selection of participants is crucial for the application of the learned knowledge in their work. The integrative nature of transboundary water issues calls for a capacity building programme addressing a wide range of subjects, which can be understood by a wide range of professionals from different sectors. Training methods should also address this integrative nature through, e.g. roleplays and case studies. A successful capacity building programme needs to address the three levels of capacity building (enabling environment, organisations, and individual staff) and involve national and regional training and education institutes.

The present paper investigated the extent of the flood propagation in the Vietnamese Mekong Delta under different projected flood hydrographs, considering the 2000 flood event (the 20-yr return period event, T. V. H. Le et al., 2007) as the basis for computation. The analysis herein was done to demonstrate the particular complexity of the flood dynamics, which was simulated by the 1-D modelling system ISIS used by the Mekong River Commission. The floods of the year 2050 are simulated using a projected sea level rise of +30 cm. The future flood hydrograph changes at Kratie, Cambodia, were also applied for the upstream boundary condition by using an adjusted regional climate model. Two future flood hydrographs were applied at the upstream part of the delta, the first one in a scenario of climate change without considering developments in the Mekong Basin,and the second one in a scenario of climate change taking into account future development of the delta. Analyses were done to identify the areas sensitive to floods, considering the uncertainty of the projection of both the upstream and downstream boundary conditions. In addition, due to the rice-dominated culture in the Vietnamese Mekong Delta, possible impacts of floods on the rice-based farming systems were also analysed.

This paper reports the experience of a regional network of academic departments involved in water education that started as a project and evolved, over a period of 12 yr, into an independent network organisation. The paper pursues three objectives. First, it argues that it makes good sense to organise postgraduate education and research on water resources on a regional scale and presents the WaterNet experience as an example that a regional approach can work. Second, it presents preliminary findings and conclusions that the regional approach presented by WaterNet did make a contribution to the capacity needs of the region both in terms of management and research capacity. Third, it draws two generalised lessons from the WaterNet experience. Lesson one pertains to the importance of legitimate ownership and an accountability structure for network effectiveness. Lesson two is related to the financial and intellectual resources required to jointly developing educational programmes through shared experience.

Global environmental changes introduce new challenges and expose future university graduates in hydrology and related fields to problems of unprecedented complexity and magnitude. The T-shape model is proposed as a generic competency profile guiding the design of university curricula. This model differentiates between cognitive competencies in a certain field (i.e. hydrology; vertical leg of the T), and other cognitive/knowledge competencies in neighboring fields (e.g. hydraulics, aquatic ecology, land use management etc.) and functional, personal and values competencies and meta-competencies (all summarized in the horizontal bar of the T). It is based on the holistic model of professional competencies by Cheetham and Chivers (1996) and related studies (Oskam, 2009). The T-shape profile should apply to all levels of higher education (1st degree till doctorate level) in hydrology and related fields. For the effectiveness of hydrologists as professionals, a variable mix of competencies is required and further discussed. Key aspects are an open attitude for learning, continuous professional development (lifelong learning), and integrative and team working skills. Furthermore, a stimulating learning environment that promotes active learning is essential. As examples that substantiate the proposed T-shape model, the post-graduate education programmes of UNESCO-IHE and the main outcomes from a university curriculum workshop to promote education for sustainable development are introduced.

Solving today's complex hydrological problems requires originality, creative thinking and trans-disciplinary approaches. Hydrological education that was traditionally teacher centred, where the students look up to the teacher for expertise and information, should change to better prepare hydrologists to develop new knowledge and apply it in new contexts. An important first step towards this goal is to change the concept of education in the educators' minds. The results of an investigation to find out whether didactic training influences the beliefs of hydrology educators about their teaching styles is presented. Faculty of UNESCO-IHE has been offered a didactic certification program named university teaching qualification (UTQ). The hypothesis that UTQ training will significantly alter the teaching style of faculty at UNESCO-IHE from expert/formal authority traits towards facilitator/delegator traits was tested. A first survey was conducted among the entire teaching staff (total 101, response rate 58%). The results indicated that there are significantly higher traits of facilitator and delegator teaching styles among UTQ graduates compared to faculty who were not significantly trained in didactics. The second survey which was conducted among UTQ graduates (total 20, response rate 70%), enquiring after their teaching styles before and after UTQ, corroborated these findings.

Data assimilation (DA) holds considerable potential for improving hydrologic predictions as demonstrated in numerous research studies. However, advances in hydrologic DA research have not been adequately or timely implemented in operational forecast systems to improve the skill of forecasts for better informed real-world decision making. This is due in part to a lack of mechanisms to properly quantify the uncertainty in observations and forecast models in real-time forecasting situations and to conduct the merging of data and models in a way that is adequately efficient and transparent to operational forecasters. The need for effective DA of useful hydrologic data into the forecast process has become increasingly recognized in recent years. This motivated a hydrologic DA workshop in Delft, the Netherlands in November 2010, which focused on advancing DA in operational hydrologic forecasting and water resources management. As an outcome of the workshop, this paper reviews, in relevant detail, the current status of DA applications in both hydrologic research and operational practices, and discusses the existing or potential hurdles and challenges in transitioning hydrologic DA research into cost-effective operational forecasting tools, as well as the potential pathways and newly emerging opportunities for overcoming these challenges. Several related aspects are discussed, including (1) theoretical or mathematical aspects in DA algorithms, (2) the estimation of different types of uncertainty, (3) new observations and their objective use in hydrologic DA, (4) the use of DA for real-time control of water resources systems, and (5) the development of community-based, generic DA tools for hydrologic applications. It is recommended that cost-effective transition of hydrologic DA from research to operations should be helped by developing community-based, generic modeling and DA tools or frameworks, and through fostering collaborative efforts among hydrologic modellers, DA developers, and operational forecasters.

Knowledge of the water fluxes within the soil-vegetation-atmosphere system is crucial to improve water use efficiency in irrigated land. Many studies have tried to quantify these fluxes, but they encountered difficulties in quantifying the relative contribution of evaporation and transpiration. In this study, we compared three different methods to estimate evaporation fluxes during simulated summer conditions in a grass-covered lysimeter in the laboratory. Only two of these methods can be used to partition total evaporation into transpiration, soil evaporation and interception. A water balance calculation (whereby rainfall, soil moisture and percolation were measured) was used for comparison as a benchmark. A HYDRUS-1D model and isotope measurements were used for the partitioning of total evaporation. The isotope mass balance method partitions total evaporation of 3.4 mm d−1 into 0.4 mm d−1 for soil evaporation, 0.3 mm d−1 for interception and 2.6 mm d−1 for transpiration, while the HYDRUS-1D partitions total evaporation of 3.7 mm d−1 into 1 mm d−1 for soil evaporation, 0.3 mm d−1 for interception and 2.3 mm d−1 for transpiration. From the comparison, we concluded that the isotope mass balance is better for low temporal resolution analysis than the HYDRUS-1D. On the other hand, HYDRUS-1D is better for high temporal resolution analysis than the isotope mass balance.

This paper evaluates the impact of climate change on sediment yield in the Nam Ou basin located in northern Laos. Future climate (temperature and precipitation) from four general circulation models (GCMs) that are found to perform well in the Mekong region and a regional circulation model (PRECIS) are downscaled using a delta change approach. The Soil and Water Assessment Tool (SWAT) is used to assess future changes in sediment flux attributable to climate change. Results indicate up to 3.0 °C shift in seasonal temperature and 27% (decrease) to 41% (increase) in seasonal precipitation. The largest increase in temperature is observed in the dry season while the largest change in precipitation is observed in the wet season. In general, temperature shows increasing trends but changes in precipitation are not unidirectional and vary depending on the greenhouse gas emission scenarios (GHGES), climate models, prediction period and season. The simulation results show that the changes in annual stream discharges are likely to range from a 17% decrease to 66% increase in the future, which will lead to predicted changes in annual sediment yield ranging from a 27% decrease to about 160% increase. Changes in intra-annual (monthly) discharge as well as sediment yield are even greater (−62 to 105% in discharge and −88 to 243% in sediment yield). A higher discharge and sediment flux are expected during the wet seasons, although the highest relative changes are observed during the dry months. The results indicate high uncertainties in the direction and magnitude of changes of discharge as well as sediment yields due to climate change. As the projected climate change impact on sediment varies remarkably between the different climate models, the uncertainty should be taken into account in both sediment management and climate change adaptation.

Adoption of soil conservation structures (SCS) has been low in high rainfall areas of Ethiopia mainly due to crop yield reduction, increased soil erosion following breaching of SCS, incompatibility with the tradition of cross plowing and water-logging behind SCS. A new type of conservation tillage (CT) involving contour plowing and the construction of invisible subsoil barriers using a modified Maresha winged "subsoiler" is suggested as a means to tackle these problems as an integral part of the SCS. We investigated the effect of integrating the CT with SCS on the surface runoff, water-logging, soil loss, crop yield and plowing convenience. The new approach of conservation tillage has been compared with traditional tillage (TT) on 5 farmers' fields in a high rainfall area in the upper Blue Nile (Abbay) river basin. Test crops were wheat [triticum vulgare] and tef [eragrostis tef]. Farmers found CT convenient to apply between SCS. Surface runoff appeared to be reduced under CT by 48 and 15%, for wheat and tef, respectively. As a result, CT reduced sediment yield by 51 and 9.5%, for wheat and tef, respectively. Significantly reduced water-logging was observed behind SCS in CT compared to TT. Grain yields of wheat and tef increased by 35 and 10%, respectively, although the differences were not statistically significant apparently due to high fertility variations among fields of participating farmers. Farmers who tested CT indicated that they will continue this practice in the future.