Hydrological simulations at catchment scale repose on the quality and data availability both for soil and rainfall data. Soil data are quite easy to be collected, although their quality depends on the resources devoted to this task, rainfall data observations, instead, need further effort because of their spatiotemporal variability. Rainfalls are normally recorded with rain gauges located in the catchment, they can provide detailed temporal data, but, the representativeness is limited to the point where the data are collected. Combining different gauges in space can provide a better representation of the rainfall event but the spatialization is often the main obstacle to obtain data close to the reality. Since several years, radar observations overcome this gap providing continuous data registration, that, when properly calibrated, can offer an adequate, continuous, cover in space and time for medium-wide catchments. Here, we use radar records for the south of the France on the La Peyne catchment with the protocol there adopted by the national meteo agency, with resolution of 1 km space and 5' time scale observations. We present here the realisation of a model able to perform from rainfall radar observations, continuous hydrological and soil erosion simulations. The model is semi-theoretically based, once it simulates water fluxes (infiltration-excess overland flow, saturation overland flow, infiltration and channel routing) with a cinematic wave using the St. Venant equation on a simplified "bucket" conceptual model for ground water, and, an empirical representation of sediment load as adopted in models such as STREAM-LANDSOIL (Cerdan et al., 2002, Ciampalini et al., 2012). The advantage of this approach is to furnish a dynamic representation - simulation of the rainfall-runoff events more easily than using spatialized rainfalls from meteo stations and to offer a new look on the spatial component of the events.
A data-based approach is presented to analyse the response behaviour of hydrological models at the catchment scale. The approach starts with a number of sequential time series processing steps, applied to available rainfall, ETo and river flow observation series. These include separation of the high frequency (e.g., hourly, daily) river flow series into subflows, split of the series in nearly independent quick and slow flow hydrograph periods, and the extraction of nearly independent peak and low flows. Quick-, inter- and slow-subflow recession behaviour, sub-responses to rainfall and soil water storage are derived from the time series data. This data-based information on the catchment response behaviour can be applied on the basis of: - Model-structure identification and case-specific construction of lumped conceptual models for gauged catchments; or diagnostic evaluation of existing model structures; - Intercomparison of runoff responses for gauged catchments in a river basin, in order to identify similarity or significant differences between stations or between time periods, and relate these differences to spatial differences or temporal changes in catchment characteristics; - (based on the evaluation of the temporal changes in previous point:) Detection of temporal changes/trends and identification of its causes: climate trends, or land use changes; - Identification of asymptotic properties of the rainfall-runoff behaviour towards extreme peak or low flow conditions (for a given catchment) or towards extreme catchment conditions (for regionalization, ungauged basin prediction purposes); hence evaluating the performance of the model in making extrapolations beyond the range of available stations' data; - (based on the evaluation in previous point:) Evaluation of the usefulness of the model for making extrapolations to more extreme climate conditions projected by for instance climate models. Examples are provided for river basins in Belgium, Ethiopia, Kenya
Paniconi, Claudio; Wood, Eric F.
A catchment scale numerical model is developed based on the three-dimensional transient Richards equation describing fluid flow in variably saturated porous media. The model is designed to take advantage of digital elevation data bases and of information extracted from these data bases by topographic analysis. The practical application of the model is demonstrated in simulations of a small subcatchment of the Konza Prairie reserve near Manhattan, Kansas. In a preliminary investigation of computational issues related to model resolution, we obtain satisfactory numerical results using large aspect ratios, suggesting that horizontal grid dimensions may not be unreasonably constrained by the typically much smaller vertical length scale of a catchment and by vertical discretization requirements. Additional tests are needed to examine the effects of numerical constraints and parameter heterogeneity in determining acceptable grid aspect ratios. In other simulations we attempt to match the observed streamflow response of the catchment, and we point out the small contribution of the streamflow component to the overall water balance of the catchment.
Dunn, S. M.; Lilly, A.
There are now many examples of hydrological models that utilise the capabilities of Geographic Information Systems to generate spatially distributed predictions of behaviour. However, the spatial variability of hydrological parameters relating to distributions of soils and vegetation can be hard to establish. In this paper, the relationship between a soil hydrological classification Hydrology of Soil Types (HOST) and the spatial parameters of a conceptual catchment-scale model is investigated. A procedure involving inverse modelling using Monte-Carlo simulations on two catchments is developed to identify relative values for soil related parameters of the DIY model. The relative values determine the internal variability of hydrological processes as a function of the soil type. For three out of the four soil parameters studied, the variability between HOST classes was found to be consistent across two catchments when tested independently. Problems in identifying values for the fourth 'fast response distance' parameter have highlighted a potential limitation with the present structure of the model. The present assumption that this parameter can be related simply to soil type rather than topography appears to be inadequate. With the exclusion of this parameter, calibrated parameter sets from one catchment can be converted into equivalent parameter sets for the alternate catchment on the basis of their HOST distributions, to give a reasonable simulation of flow. Following further testing on different catchments, and modifications to the definition of the fast response distance parameter, the technique provides a methodology whereby it is possible to directly derive spatial soil parameters for new catchments.
Current societal problems and questions demand that we increasingly build hydrologic models for regional or even continental scale assessment of global change impacts. Such models offer new opportunities for scientific advancement, for example by enabling comparative hydrology or connectivity studies, and for improved support of water management decision, since we might better understand regional impacts on water resources from large scale phenomena such as droughts. On the other hand, we are faced with epistemic uncertainties when we move up in scale. The term epistemic uncertainty describes those uncertainties that are not well determined by historical observations. This lack of determination can be because the future is not like the past (e.g. due to climate change), because the historical data is unreliable (e.g. because it is imperfectly recorded from proxies or missing), or because it is scarce (either because measurements are not available at the right scale or there is no observation network available at all). In this talk I will explore: (1) how we might build a bridge between what we have learned about catchment scale processes and hydrologic model development and evaluation at larger scales. (2) How we can understand the impact of epistemic uncertainty in large scale hydrologic models. And (3) how we might utilize large scale hydrologic predictions to understand climate change impacts, e.g. on infectious disease risk.
Skaugen, Thomas; Mengistu, Zelalem
In this study, we propose a new formulation of subsurface water storage dynamics for use in rainfall-runoff models. Under the assumption of a strong relationship between storage and runoff, the temporal distribution of catchment-scale storage is considered to have the same shape as the distribution of observed recessions (measured as the difference between the log of runoff values). The mean subsurface storage is estimated as the storage at steady state, where moisture input equals the mean annual runoff. An important contribution of the new formulation is that its parameters are derived directly from observed recession data and the mean annual runoff. The parameters are hence estimated prior to model calibration against runoff. The new storage routine is implemented in the parameter parsimonious distance distribution dynamics (DDD) model and has been tested for 73 catchments in Norway of varying size, mean elevation and landscape type. Runoff simulations for the 73 catchments from two model structures (DDD with calibrated subsurface storage and DDD with the new estimated subsurface storage) were compared. Little loss in precision of runoff simulations was found using the new estimated storage routine. For the 73 catchments, an average of the Nash-Sutcliffe efficiency criterion of 0.73 was obtained using the new estimated storage routine compared with 0.75 using calibrated storage routine. The average Kling-Gupta efficiency criterion was 0.80 and 0.81 for the new and old storage routine, respectively. Runoff recessions are more realistically modelled using the new approach since the root mean square error between the mean of observed and simulated recession characteristics was reduced by almost 50 % using the new storage routine. The parameters of the proposed storage routine are found to be significantly correlated to catchment characteristics, which is potentially useful for predictions in ungauged basins.
Yeo, I. Y.; Lang, M.; Lee, S.; Huang, C.; Jin, H.; McCarty, G.; Sadeghi, A.
The wetland ecosystem plays crucial roles in improving hydrological function and ecological integrity for the downstream water and the surrounding landscape. However, changing behaviours and functioning of wetland ecosystems are poorly understood and extremely difficult to characterize. Improved understanding on hydrological behaviours of wetlands, considering their interaction with surrounding landscapes and impacts on downstream waters, is an essential first step toward closing the knowledge gap. We present an integrated wetland-catchment modelling study that capitalizes on recently developed inundation maps and other geospatial data. The aim of the data-model integration is to improve spatial prediction of wetland inundation and evaluate cumulative hydrological benefits at the catchment scale. In this paper, we highlight problems arising from data preparation, parameterization, and process representation in simulating wetlands within a distributed catchment model, and report the recent progress on mapping of wetland dynamics (i.e., inundation) using multiple remotely sensed data. We demonstrate the value of spatially explicit inundation information to develop site-specific wetland parameters and to evaluate model prediction at multi-spatial and temporal scales. This spatial data-model integrated framework is tested using Soil and Water Assessment Tool (SWAT) with improved wetland extension, and applied for an agricultural watershed in the Mid-Atlantic Coastal Plain, USA. This study illustrates necessity of spatially distributed information and a data integrated modelling approach to predict inundation of wetlands and hydrologic function at the local landscape scale, where monitoring and conservation decision making take place.
Shope, C. L.; Maharjan, G. R.; Tenhunen, J.; Seo, B.; Kim, K.; Riley, J.; Arnhold, S.; Koellner, T.; Ok, Y. S.; Peiffer, S.; Kim, B.; Park, J.-H.; Huwe, B.
Land use and climate change have long been implicated in modifying ecosystem services, such as water quality and water yield, biodiversity, and agricultural production. To account for future effects on ecosystem services, the integration of physical, biological, economic, and social data over several scales must be implemented to assess the effects on natural resource availability and use. Our objective is to assess the capability of the SWAT model to capture short-duration monsoonal rainfall-runoff processes in complex mountainous terrain under rapid, event-driven processes in a monsoonal environment. To accomplish this, we developed a unique quality-control gap-filling algorithm for interpolation of high frequency meteorological data. We used a novel multi-location, multi-optimization calibration technique to improve estimations of catchment-wide hydrologic partitioning. We calibrated the interdisciplinary model to a combination of statistical, hydrologic, and plant growth metrics. In addition, we used multiple locations of different drainage area, aspect, elevation, and geologic substrata distributed throughout the catchment. Results indicate scale-dependent sensitivity of hydrologic partitioning and substantial influence of engineered features. While our model accurately reproduced observed discharge variability, the addition of hydrologic and plant growth objective functions identified the importance of culverts in catchment-wide flow distribution. The results of this study provide a valuable resource to describe landscape controls and their implication on discharge, sediment transport, and nutrient loading. This study also shows the challenges of applying the SWAT model to complex terrain and extreme environments. By incorporating anthropogenic features into modeling scenarios, we can greatly enhance our understanding of the hydroecological impacts on ecosystem services.
Tran, Quoc Quan; Willems, Patrick; Pannemans, Bart; Blanckaert, Joris; Pereira, Fernando; Nossent, Jiri; Cauwenberghs, Kris; Vansteenkiste, Thomas
Based on an international literature review on model structures of existing rainfall-runoff and hydrological models, a generalized model structure is proposed. It consists of different types of meteorological components, storage components, splitting components and routing components. They can be spatially organized in a lumped way, or on a grid, spatially interlinked by source-to-sink or grid-to-grid (cell-to-cell) routing. The grid size of the model can be chosen depending on the application. The user can select/change the spatial resolution depending on the needs and/or the evaluation of the accuracy of the model results, or use different spatial resolutions in parallel for different applications. Major research questions addressed during the study are: How can we assure consistent results of the model at any spatial detail? How can we avoid strong or sudden changes in model parameters and corresponding simulation results, when one moves from one level of spatial detail to another? How can we limit the problem of overparameterization/equifinality when we move from the lumped model to the spatially distributed model? The proposed approach is a step-wise one, where first the lumped conceptual model is calibrated using a systematic, data-based approach, followed by a disaggregation step where the lumped parameters are disaggregated based on spatial catchment characteristics (topography, land use, soil characteristics). In this way, disaggregation can be done down to any spatial scale, and consistently among scales. Only few additional calibration parameters are introduced to scale the absolute spatial differences in model parameters, but keeping the relative differences as obtained from the spatial catchment characteristics. After calibration of the spatial model, the accuracies of the lumped and spatial models were compared for peak, low and cumulative runoff total and sub-flows (at downstream and internal gauging stations). For the distributed models, additional
Vannier, Olivier; Braud, Isabelle; Anquetin, Sandrine
The estimation of catchment-scale soil properties, such as water storage capacity and hydraulic conductivity, is of primary interest for the implementation of distributed hydrological models at the regional scale. This estimation is generally done on the basis of information provided by soil databases. However, such databases are often established for agronomic uses and generally do not document deep weathered rock horizons (i.e. pedologic horizons of type C and deeper), which can play a major role in water transfer and storages. Here we define the Drainable Storage Capacity Index (DSCI), an indicator that relies on the comparison of cumulated streamflow and precipitation to assess catchment-scale storage capacities. The DSCI is found to be reliable to detect underestimation of soil storage capacities in soil databases. We also use the streamflow recession analysis methodology defined by Brutsaert and Nieber (Water Resources Research 13(3), 1977) to estimate water storage capacities and lateral saturated hydraulic conductivities of the non-documented deep horizons. The analysis is applied to a sample of twenty-three catchments (0.2 km² - 291 km²) located in the Cévennes-Vivarais region (south of France). In a regionalisation purpose, the obtained results are compared to the dominant catchments geology. This highlights a clear hierarchy between the different geologies present in the area. Hard crystalline rocks are found to be associated to the thickest and less conductive deep soil horizons. Schist rocks present intermediate values of thickness and of saturated hydraulic conductivity, whereas sedimentary rocks and alluvium are found to be the less thick and the most conductive. Consequently, deep soil layers with thicknesses and hydraulic conductivities differing with the geology were added to a distributed hydrological model implemented over the Cévennes-Vivarais region. Preliminary simulations show a major improvement in terms of simulated discharge when
Medici, Chiara; Wade, Andrew; Frances, Felix
Nitrogen is present in both terrestrial and aquatic ecosystems and research is needed to understand its storage, transportation and transformations in river catchments world-wide because of its importance in controlling plant growth and freshwater trophic status (Vitousek et al. 2009; Chu et al. 2008; Schlesinger et al 2006; Ocampo et al. 2006; Green et al., 2004; Arheimer et al., 1996). Numerous mathematical models have been developed to describe the nitrogen dynamics, but there is a substantial gap between the outputs now expected from these models and what modellers are able to provide with scientific justification (McIntyre et al., 2005). In fact, models will always necessarily be simplification of reality; hence simplifying assumptions are sources of uncertainty that must be well understood for an accurate model results interpretation. Therefore, estimating prediction uncertainties in water quality modelling is becoming increasingly appreciated (Dean et al., 2009, Kruger et al., 2007, Rode et al., 2007). In this work the lumped LU4-N model (Medici et al., 2008; Medici et al., EGU2009-7497) is subjected to an extensive regionalised sensitivity analysis (GSA, based on Monte Carlo simulations) in application to the Fuirosos catchment, Catalonia. The main results are: 1) the hydrological model is greatly affected by the maximum static storage water content (Hu_max), which defines the amount of water held in soil that can leave the catchment only by evapotranspiration. Thus, it defines also the amount of water not retained that is free to move and supplies the other model tanks; 2) the use of several objective functions in order to take into account different hydrograph characteristic helped to constrain parameter values; 3) concerning nitrogen, to obtain a sufficient level of behavioural parameter sets for the statistical analysis, not very severe criteria could be adopted; 4) stream water concentrations are sensitive to the shallow aquifer parameters, especially
Skaugen, T.; Mengistu, Z.
In this study we propose a new formulation of subsurface water storage dynamics for use in rainfall-runoff models. Under the assumption of a strong relationship between storage and runoff, the temporal distribution of storage is considered to have the same shape as the distribution of observed recessions (measured as the difference between the log of runoff values). The mean subsurface storage is estimated as the storage at steady-state, where moisture input equals the mean annual runoff. An important contribution of the new formulation is that its parameters are derived directly from observed recession data and the mean annual runoff and hence estimated prior to calibration. Key principles guiding the evaluation of the new subsurface storage routine have been (a) to minimize the number of parameters to be estimated through the, often arbitrary fitting to optimize runoff predictions (calibration) and (b) maximize the range of testing conditions (i.e. large-sample hydrology). The new storage routine has been implemented in the already parameter parsimonious Distance Distribution Dynamics (DDD) model and tested for 73 catchments in Norway of varying size, mean elevations and landscape types. Runoff simulations for the 73 catchments from two model structures; DDD with calibrated subsurface storage and DDD with the new estimated subsurface storage were compared. No loss in precision of runoff simulations was found using the new estimated storage routine. For the 73 catchments, an average of the Nash-Sutcliffe Efficiency criterion of 0.68 was found using the new estimated storage routine compared with 0.66 using calibrated storage routine. The average Kling-Gupta Efficiency criterion was 0.69 and 0.70 for the new and old storage routine, respectively. Runoff recessions are more realistically modelled using the new approach since the root mean square error between the mean of observed and simulated recessions was reduced by almost 50 % using the new storage routine.
Benettin, P.; Queloz, P.; Bailey, S. W.; McGuire, K. J.; Rinaldo, A.; Botter, G.
Water age distributions can be used to address a number of environmental challenges, such as modeling the dynamics of river water quality, quantifying the interactions between shallow and deep flow systems and understanding nutrient loading persistence. Moreover, as the travel time of a water particle is the time available for biogeochemical reactions, it can be explicitly used to predict the concentration of non-conservative solutes, as e.g. those derived by mineral weathering. In recent years, many studies acknowledged the dynamic nature of streamflow age and linked it to observed variations in stream water quality. In this new framework, water stored within a catchment can be seen as a pool that is selectively "sampled" by streams and vegetation, determining the chemical composition of discharge and evapotranspiration. We present results from a controlled lysimeter experiment and real-world catchments, where the theoretical framework has been used to reproduce water quality datasets including conservative tracers (e.g. chloride and water stable isotopes) and weathering-derived solutes (like silicon and sodium). The approach proves useful to estimate the catchment water storage involved in solute mixing and sheds light on how solutes and water of different ages are selectively removed by vegetation and soil drainage.
Maurer, Thomas; Caviedes-Voullième, Daniel; Hinz, Christoph; Gerke, Horst H.
Landscapes that are heavily disturbed or newly formed by either natural processes or human activity are in a state of disequilibrium. Their initial development is thus characterized by highly dynamic processes under all climatic conditions. The primary distribution and structure of the solid phase (i.e. mineral particles forming the pore space) is one of the decisive factors for the development of hydrological behavior of the eco-hydrological system and therefore (co-) determining for its - more or less - stable final state. The artificially constructed ‚Hühnerwasser' catchment (a 6 ha area located in the open-cast lignite mine Welzow-Süd, southern Brandenburg, Germany) is a landscape laboratory where the initial eco-hydrological development is observed since 2005. The specific formation (or construction) processes generated characteristic sediment structures and distributions, resulting in a spatially heterogeneous initial state of the catchment. We developed a structure generator that simulates the characteristic distribution of the solid phase for such constructed landscapes. The program is able to generate quasi-realistic structures and sediment compositions on multiple spatial levels (1 cm up to 100 m scale). The generated structures can be i) conditioned to actual measurement values (e.g., soil texture and bulk distribution); ii) stochastically generated, and iii) calculated deterministically according to the geology and technical processes at the excavation site. Results are visualized using the GOCAD software package and the free software Paraview. Based on the 3D-spatial sediment distributions, effective hydraulic van-Genuchten parameters are calculated using pedotransfer functions. The hydraulic behavior of different sediment distribution (i.e. versions or variations of the catchment's porous body) is calculated using a numerical model developed by one of us (Caviedes-Voullième). Observation data are available from catchment monitoring are available
Famiglietti, J. S.; Wood, E. F.; Sivapalan, M.; Thongs, D. J.
A catchment scale water balance model is presented and used to predict evaporation from the King's Creek catchment at the First ISLSCP Field Experiment site on the Konza Prairie, Kansas. The model incorporates spatial variability in topography, soils, and precipitation to compute the land surface hydrologic fluxes. A network of 20 rain gages was employed to measure rainfall across the catchment in the summer of 1987. These data were spatially interpolated and used to drive the model during storm periods. During interstorm periods the model was driven by the estimated potential evaporation, which was calculated using net radiation data collected at site 2. Model-computed evaporation is compared to that observed, both at site 2 (grid location 1916-BRS) and the catchment scale, for the simulation period from June 1 to October 9, 1987.
Benettin, Paolo; Bertuzzo, Enrico
This paper presents the
tran-SAS package, which includes a set of codes to model solute transport and water residence times through a hydrological system. The model is based on a catchment-scale approach that aims at reproducing the integrated response of the system at one of its outlets. The codes are implemented in MATLAB and are meant to be easy to edit, so that users with minimal programming knowledge can adapt them to the desired application. The problem of large-scale solute transport has both theoretical and practical implications. On the one side, the ability to represent the ensemble of water flow trajectories through a heterogeneous system helps unraveling streamflow generation processes and allows us to make inferences on plant-water interactions. On the other side, transport models are a practical tool that can be used to estimate the persistence of solutes in the environment. The core of the package is based on the implementation of an age master equation (ME), which is solved using general StorAge Selection (SAS) functions. The age ME is first converted into a set of ordinary differential equations, each addressing the transport of an individual precipitation input through the catchment, and then it is discretized using an explicit numerical scheme. Results show that the implementation is efficient and allows the model to run in short times. The numerical accuracy is critically evaluated and it is shown to be satisfactory in most cases of hydrologic interest. Additionally, a higher-order implementation is provided within the package to evaluate and, if necessary, to improve the numerical accuracy of the results. The codes can be used to model streamflow age and solute concentration, but a number of additional outputs can be obtained by editing the codes to further advance the ability to understand and model catchment transport processes.
Sonnentag, O.; Helbig, M.; Connon, R.; Hould Gosselin, G.; Ryu, Y.; Karoline, W.; Hanisch, J.; Moore, T. R.; Quinton, W. L.
The permafrost region of the Northern Hemisphere has been experiencing twice the rate of climate warming compared to the rest of the Earth, resulting in the degradation of the cryosphere. A large portion of the high-latitude boreal forests of northwestern Canada grows on low-lying organic-rich lands with relative warm and thin isolated, sporadic and discontinuous permafrost. Along this southern limit of permafrost, increasingly warmer temperatures have caused widespread permafrost thaw leading to land cover changes at unprecedented rates. A prominent change includes wetland expansion at the expense of Picea mariana (black spruce)-dominated forest due to ground surface subsidence caused by the thawing of ice-rich permafrost leading to collapsing peat plateaus. Recent conceptual advances have provided important new insights into high-latitude boreal forest hydrology. However, refined quantitative understanding of the mechanisms behind water storage and movement at subcatchment and catchment scales is needed from a water resources management perspective. Here we combine multi-year daily runoff measurements with spatially explicit estimates of evapotranspiration, modelled with the Breathing Earth System Simulator, to characterize the monthly growing season catchment scale ( 150 km2) hydrological response of a boreal headwater peatland complex with sporadic permafrost in the southern Northwest Territories. The corresponding water budget components at subcatchment scale ( 0.1 km2) were obtained from concurrent cutthroat flume runoff and eddy covariance evapotranspiration measurements. The highly significant linear relationships for runoff (r2=0.64) and evapotranspiration (r2=0.75) between subcatchment and catchment scales suggest that the mineral upland-dominated downstream portion of the catchment acts hydrologically similar to the headwater portion dominated by boreal peatland complexes. Breakpoint analysis in combination with moving window statistics on multi
Until the seventies, scientific development in the field of groundwater hydrology concentrated mainly on a better understanding of the physics of subsurface flow in homogeneous or simply stratified porous respectively fractured media. Then, since mid of the seventies, a much more complex vision of groundwater hydrology gradually developed. A more realistic description of the subsurface including its heterogeneity, predominant physico-chemical-biological reactions and also technologies for the efficient clean-up of contaminants developed during the past 30 years, much facilitated by the advancement in numerical modelling techniques and the boost in computer power. Even though the advancements in this field have been very significant, a new grand challenge evolved during the past 10 years trying to bring together the fields needed to build Integrated Watershed Management Systems (IWMS). The fundamental conceptual question is: Do we need new approaches to groundwater hydrology, maybe even new paradigms in order to successfully build IWMS - or can we simply extrapolate our existing concepts and tool-sets to the scale of catchments and watersheds and simply add some interfaces to adjacent disciplines like economy, ecology and others? This lecture tries to provide some of the answers by describing some successful examples.
Oudin, Ludovic; Salavati, Bahar; Furusho-Percot, Carina; Ribstein, Pierre; Saadi, Mohamed
The impacts of urbanization on floods, droughts and the overall river regime have been largely investigated in the past few decades, but the quantification and the prediction of such impacts still remain a challenge in hydrology. We gathered a sample of 142 catchments that have a documented increase in urban areas over the hydrometeorological record period in the United States. The changes in river flow regimes due to urban spread were differentiated from climate variability using the GR4J conceptual hydrological model. High, low and mean flows were impacted at a threshold of a 10% total impervious area. Moreover, the historical evolution of urban landscape spatial patterns was used to further detail the urbanization process in terms of extent and fragmentation of urban areas throughout the catchment and to help interpret the divergent impacts observed in streamflow behaviors. Regression analysis pointed out the importance of major wastewater treatment facilities that might overpass the effects of imperviousness, and therefore further research should either take them explicitly into account or select a wastewater facility-free catchment sample to clearly evaluate the impacts of urban landscape on low flows.
A major challenge to understanding the impact of environmental management is lack of data support and techniques to quantify the effectiveness of management treatments. We address aspects of this challenge in the context of a catchment-scale study of the hydrologic, ecological, a...
Lewis, C.; Xu, X.; Albertson, J.; Kiely, G.
GEOtop represents the new generation of distributed hydrological model driven by geospatial data (e.g. topography, soils, vegetation, land cover). It estimates rainfall-runoff, evapotranspiration and provides spatially distributed outputs as well as routing water and sediment flows through stream and river networks. The original version of GEOtop designed in Italy, includes a rigorous treatment of the core hydrological processes (e.g. unsaturated and saturated flow and transport, surface energy balances, and streamflow generation/routing). Recently GEOtop was extended to include treatment of shallow landslides. The GEOtop model is built on an open-source programming framework, which makes it well suited for adaptation and extension. GEOtop has been run very successfully in a number of alpine catchments (such as Brenta) but has not been used on Irish catchments before. The cell size used for the spatially distributed inputs varies from catchment to catchment. In smaller catchments (less than 2000ha) 50 by 50m cells have been used and 200 by 200 for larger catchments. Smaller cell sizes have been found to significantly increase the computational time so a larger cell size is used providing it does not significantly affect the performance of the model. Digital elevation model, drainage direction, landuse and soil type maps are the minimum spatial requirements with precipitation, radiation, temperature, atmospheric pressure and wind speed been the minimum meteorological requirements for a successful run. The soil type maps must also contain information regarding texture and hydraulic conductivity. The first trial of GEOtop in Ireland was on a small 1524 ha catchment in the south of Ireland. The catchment ranges from 50 to just over 200m, the land use is predominately agricultural grassland and it receives on average 1400mm of rain per year. Within this catchment there is a meteorological tower which provides the meteorological inputs, soil moisture is also recorded at
Silasari, Rasmiaditya; Broer, Martine; Blöschl, Günter
During rainfall events, the formation of overland flow can occur under the circumstances of saturation excess and/or infiltration excess. These conditions are affected by the soil moisture state which represents the soil water content in micropores and macropores. Macropores act as pathway for the preferential flows and have been widely studied locally. However, very little is known about their spatial structure and conductivity of macropores and other flow characteristic at the catchment scale. This study will analyze these characteristics to better understand its importance in hydrological processes. The research will be conducted in Petzenkirchen Hydrological Open Air Laboratory (HOAL), a 64 ha catchment located 100 km west of Vienna. The land use is divided between arable land (87%), pasture (5%), forest (6%) and paved surfaces (2%). Video cameras will be installed on an agricultural field to monitor the overland flow pattern during rainfall events. A wireless soil moisture network is also installed within the monitored area. These field data will be combined to analyze the soil moisture state and the responding surface runoff occurrence. The variability of the macropores spatial structure of the observed area (field scale) then will be assessed based on the topography and soil data. Soil characteristics will be supported with laboratory experiments on soil matrix flow to obtain proper definitions of the spatial structure of macropores and its variability. A coupled physically based distributed model of surface and subsurface flow will be used to simulate the variability of macropores spatial structure and its effect on the flow behaviour. This model will be validated by simulating the observed rainfall events. Upscaling from field scale to catchment scale will be done to understand the effect of macropores variability on larger scales by applying spatial stochastic methods. The first phase in this study is the installation and monitoring configuration of video
The interaction between the physical properties of a catchment (form) and climatic forcing of precipitation and energy control how water is partitioned, stored, and conveyed through a catchment (function). Hydrologic Landscapes (HLs) were previously developed across Oregon and de...
Troch, Peter A.; Mancini, Marco; Paniconi, Claudio; Wood, Eric F.
The validity of some of the simplifying assumptions in a conceptual water balance model is investigated by comparing simulation results from the conceptual model with simulation results from a three-dimensional physically based numerical model and with field observations. We examine, in particular, assumptions and simplifications related to water table dynamics, vertical soil moisture and pressure head distributions, and subsurface flow contributions to stream discharge. The conceptual model relies on a topographic index to predict saturation excess runoff and on Philip's infiltration equation to predict infiltration excess runoff. The numerical model solves the three-dimensional Richards equation describing flow in variably saturated porous media, and handles seepage face boundaries, infiltration excess and saturation excess runoff production, and soil driven and atmosphere driven surface fluxes. The study catchments (a 7.2 sq km catchment and a 0.64 sq km subcatchment) are located in the North Appalachian ridge and valley region of eastern Pennsylvania. Hydrologic data collected during the MACHYDRO 90 field experiment are used to calibrate the models and to evaluate simulation results. It is found that water table dynamics as predicted by the conceptual model are close to the observations in a shallow water well and therefore, that a linear relationship between a topographic index and the local water table depth is found to be a reasonable assumption for catchment scale modeling. However, the hydraulic equilibrium assumption is not valid for the upper 100 cm layer of the unsaturated zone and a conceptual model that incorporates a root zone is suggested. Furthermore, theoretical subsurface flow characteristics from the conceptual model are found to be different from field observations, numerical simulation results, and theoretical baseflow recession characteristics based on Boussinesq's groundwater equation.
Raeke, Julia; Lechtenfeld, Oliver J.; Oosterwoud, Marieke R.; Bornmann, Katrin; Tittel, Jörg; Reemtsma, Thorsten
Increasing concentrations of dissolved organic matter (DOM) in rivers of temperate catchments in Europe and North Amerika impose new technical challenges for drinking water production. The driving factors for this decadal increase in DOM concentration are not conclusive and changes in annual temperatures, precipitation and atmospheric deposition are intensely discussed. It is known that the majority of DOM is released by few but large hydrologic events, mobilizing DOM from riparian wetlands for export by rivers and streams. The mechanisms of this mobilization and the resulting molecular composition of the released DOM may be used to infer long-term changes in the biogeochemistry of the respective catchment. Event-based samples collected over two years from streams in three temperate catchments in the German mid-range mountains were analyzed after solid-phase extraction of DOM for their molecular composition by ultra-high resolution mass spectrometry (FT-ICR MS). Hydrologic conditions, land use and water chemistry parameters were used to complement the molecular analysis. The molecular composition of the riverine DOM was strongly dependent on the magnitude of the hydrologic events, with unsaturated, oxygen-enriched compounds being preferentially mobilized by large events. This pattern is consistent with an increase in dissolved iron and aluminum concentrations. In contrast, the relative proportions of nitrogen and sulfur bearing compounds increased with an increased agricultural land use but were less affected by the mobilization events. Co-precipitation experiments with colloidal aluminum showed that unsaturated and oxygen-rich compounds are preferentially removed from the dissolved phase. The precipitated compounds thus had similar chemical characteristics as compared to the mobilized DOM from heavy rain events. Radiocarbon analyses also indicated that this precipitated fraction of DOM was of comparably young radiocarbon age. DOM radiocarbon from field samples
Bronstert, Axel; Heistermann, Maik; Francke, Till
Hydrological models aim at quantifying the hydrological cycle and its constituent processes for particular conditions, sites or periods in time. Such models have been developed for a large range of spatial and temporal scales. One must be aware that the question which is the appropriate scale to be applied depends on the overall question under study. Therefore, it is not advisable to give a general applicable guideline on what is "the best" scale for a model. This statement is even more relevant for coupled hydrological, ecological and atmospheric models. Although a general statement about the most appropriate modelling scale is not recommendable, it is worth to have a look on what are the advantages and the shortcomings of micro-, meso- and macro-scale approaches. Such an appraisal is of increasing importance, since increasingly (very) large / global scale approaches and models are under operation and therefore the question arises how far and for what purposes such methods may yield scientifically sound results. It is important to understand that in most hydrological (and ecological, atmospheric and other) studies process scale, measurement scale, and modelling scale differ from each other. In some cases, the differences between theses scales can be of different orders of magnitude (example: runoff formation, measurement and modelling). These differences are a major source of uncertainty in description and modelling of hydrological, ecological and atmospheric processes. Let us now summarize our viewpoint of the strengths (+) and weaknesses (-) of hydrological models of different scales: Micro scale (e.g. extent of a plot, field or hillslope): (+) enables process research, based on controlled experiments (e.g. infiltration; root water uptake; chemical matter transport); (+) data of state conditions (e.g. soil parameter, vegetation properties) and boundary fluxes (e.g. rainfall or evapotranspiration) are directly measurable and reproducible; (+) equations based on
Modeling greenhouse gas emissions (CO2, N2O, CH4) from managed arable soils with a fully coupled hydrology-biogeochemical modeling system simulating water and nutrient transport and associated carbon and nitrogen cycling at catchment scale
Klatt, Steffen; Haas, Edwin; Kraus, David; Kiese, Ralf; Butterbach-Bahl, Klaus; Kraft, Philipp; Plesca, Ina; Breuer, Lutz; Zhu, Bo; Zhou, Minghua; Zhang, Wei; Zheng, Xunhua; Wlotzka, Martin; Heuveline, Vincent
The use of mineral nitrogen fertilizer sustains the global food production and therefore the livelihood of human kind. The rise in world population will put pressure on the global agricultural system to increase its productivity leading most likely to an intensification of mineral nitrogen fertilizer use. The fate of excess nitrogen and its distribution within landscapes is manifold. Process knowledge on the site scale has rapidly grown in recent years and models have been developed to simulate carbon and nitrogen cycling in managed ecosystems on the site scale. Despite first regional studies, the carbon and nitrogen cycling on the landscape or catchment scale is not fully understood. In this study we present a newly developed modelling approach by coupling the fully distributed hydrology model CMF (catchment modelling framework) to the process based regional ecosystem model LandscapeDNDC for the investigation of hydrological processes and carbon and nitrogen transport and cycling, with a focus on nutrient displacement and resulting greenhouse gas emissions in a small catchment at the Yanting Agro-ecological Experimental Station of Purple Soil, Sichuan province, China. The catchment hosts cypress forests on the outer regions, arable fields on the sloping croplands cultivated with wheat-maize rotations and paddy rice fields in the lowland. The catchment consists of 300 polygons vertically stratified into 10 soil layers. Ecosystem states (soil water content and nutrients) and fluxes (evapotranspiration) are exchanged between the models at high temporal scales (hourly to daily) forming a 3-dimensional model application. The water flux and nutrients transport in the soil is modelled using a 3D Richards/Darcy approach for subsurface fluxes with a kinematic wave approach for surface water runoff and the evapotranspiration is based on Penman-Monteith. Biogeochemical processes are modelled by LandscapeDNDC, including soil microclimate, plant growth and biomass allocation
Shuster, William; Rhea, Lee
stormwater runoff volume management, with potential benefits for management of both separated and combined sewer systems. We also discuss lessons-learned with regard to monitoring design for catchment-scale hydrologic studies.
Glaser, Barbara; Jackisch, Conrad; Hopp, Luisa; Klaus, Julian
Numerous experimental studies showed the importance of preferential flow for solute transport and runoff generation. As a consequence, various approaches exist to incorporate preferential flow in hydrological models. However, few studies have applied models that incorporate preferential flow at hillslope scale and even fewer at catchment scale. Certainly, one main difficulty for progress is the determination of an adequate parameterization for preferential flow at these spatial scales. This study applies a 3D physically based model (HydroGeoSphere) of a headwater region (6 ha) of the Weierbach catchment (Luxembourg). The base model was implemented without preferential flow and was limited in simulating fast catchment responses. Thus we hypothesized that the discharge performance can be improved by utilizing a dual permeability approach for a representation of preferential flow. We used the information of bromide irrigation experiments performed on three 1m2 plots to parameterize preferential flow. In a first step we ran 20.000 Monte Carlo simulations of these irrigation experiments in a 1m2 column of the headwater catchment model, varying the dual permeability parameters (15 variable parameters). These simulations identified many equifinal, yet very different parameter sets that reproduced the bromide depth profiles well. Therefore, in the next step we chose 52 parameter sets (the 40 best and 12 low performing sets) for testing the effect of incorporating preferential flow in the headwater catchment scale model. The variability of the flow pattern responses at the headwater catchment scale was small between the different parameterizations and did not coincide with the variability at plot scale. The simulated discharge time series of the different parameterizations clustered in six groups of similar response, ranging from nearly unaffected to completely changed responses compared to the base case model without dual permeability. Yet, in none of the groups the
Liu, D.; Li, H. Y.; Tian, F.; Leung, L. R.
Macropore flow is an important hydrological process that generally enhances the soil infiltration capacity and velocity of subsurface water. Up till now, macropore flow is mostly simulated with high-resolution models. One possible drawback of this modeling approach is the difficulty to effectively represent the overall typology and connectivity of the macropore networks. We hypothesize that modeling macropore flow directly at the catchment scale may be complementary to the existing modeling strategy and offer some new insights. Tsinghua Representative Elementary Watershed model (THREW model) is a semi-distributed hydrology model, where the fundamental building blocks are representative elementary watersheds (REW) linked by the river channel network. In THREW, all the hydrological processes are described with constitutive relationships established directly at the REW level, i.e., catchment scale. In this study, the constitutive relationship of macropore flow drainage is established as part of THREW. The enhanced THREW model is then applied at two catchments with deep soils but distinct climates, the humid Asu catchment in the Amazon River basin, and the arid Wei catchment in the Yellow River basin. The Asu catchment has an area of 12.43km2 with mean annual precipitation of 2442mm. The larger Wei catchment has an area of 24800km2 but with mean annual precipitation of only 512mm. The rainfall-runoff processes are simulated at a hourly time step from 2002 to 2005 in the Asu catchment and from 2001 to 2012 in the Wei catchment. The role of macropore flow on the catchment hydrology will be analyzed comparatively over the Asu and Wei catchments against the observed streamflow, evapotranspiration and other auxiliary data.
Saari, Markus; Rossi, Pekka; Blomberg von der Geest, Kalle; Mäkinen, Ari; Postila, Heini; Marttila, Hannu
High metal concentrations in natural waters is one of the key environmental and health problems globally. Continuous in-situ analysis of metals from runoff water is technically challenging but essential for the better understanding of processes which lead to pollutant transport. Currently, typical analytical methods for monitoring elements in liquids are off-line laboratory methods such as ICP-OES (Inductively Coupled Plasma Optical Emission Spectroscopy) and ICP-MS (ICP combined with a mass spectrometer). Disadvantage of the both techniques is time consuming sample collection, preparation, and off-line analysis at laboratory conditions. Thus use of these techniques lack possibility for real-time monitoring of element transport. We combined a novel high resolution on-line metal concentration monitoring with catchment scale physical hydrological modelling in Mustijoki river in Southern Finland in order to study dynamics of processes and form a predictive warning system for leaching of metals. A novel on-line measurement technique based on micro plasma emission spectroscopy (MPES) is tested for on-line detection of selected elements (e.g. Na, Mg, Al, K, Ca, Fe, Ni, Cu, Cd and Pb) in runoff waters. The preliminary results indicate that MPES can sufficiently detect and monitor metal concentrations from river water. Water and Soil Assessment Tool (SWAT) catchment scale model was further calibrated with high resolution metal concentration data. We show that by combining high resolution monitoring and catchment scale physical based modelling, further process studies and creation of early warning systems, for example to optimization of drinking water uptake from rivers, can be achieved.
Coates, Victoria; Pattison, Ian
A dominant feature in the agricultural landscape in the UK are field boundaries. Two thirds of England has been continuously hedged for over a thousand years although most modern hedges were planted during the Enclosures Acts 1720-1840. However, the use of larger agricultural machinery has resulted in the removal of some field boundaries and the subsequent increase in field sizes over the 20th Century. The multiple benefits of hedgerows in ecology have been extensively studied, but the impact of these widespread features on hydrology and flood risk has seen very little attention. Nature-based solutions are increasingly being seen as a complementary approach to hard engineered flood defences. It is hypothesised that hedgerows play a part in this through modifying hillslope hydrological processes, including (a) changing the spatial distribution of precipitation due to sheltering effects; (b) biological loss of water through transpiration; (c) infiltration increased through improved soil structure at the boundaries; and (d) throughflow effected by modified hydraulic gradients. An extensive monitoring programme of a 20m transect through a hedgerow in the Skell Catchment, Northern England occurred from April 2014 to October 2015. The holistic hydrological cycle was monitored, including precipitation and soil moisture at different distances from the hedgerow, leaf wetness interception, stemflow collars, and throughfall gauges, and transpiration losses from the hedgerow. Results indicate that hedgerows modify precipitation volumes at different distances along the transect, but that relationships are complex, probably related to event specific weather conditions such as wind direction and speed and rainfall intensity. Soil moisture levels are significantly (p<0.001) lower along the hedgerow compared to 1, 3 and 10m away from it in all seasons. It has also been shown that hedgerows modify hydrological connectivity at the catchment scale.
Ross, C.; Ali, G.; Oswald, C. J.; McMillan, H. K.; Walter, K.
A hydrologic threshold is a critical point in time when runoff behavior rapidly changes, often in response to the activation of specific storage-driven or intensity-driven processes. Hydrologic thresholds can be viewed as characteristic signatures of hydrosystems, which makes them useful for site comparison as long as their presence (or lack thereof) can be evaluated in a standard manner across a range of environments. While several previous studies have successfully identified thresholds at a variety of individual sites, only a limited number have compared dynamics prevailing at the hillslope versus catchment scale, or distinguished the role of storage versus intensity thresholds. The objective of this study was therefore to examine precipitation input thresholds as well as "precipitation minus evapotranspiration" thresholds in environments with contrasted climatic and geographic characteristics. Historical climate and hydrometric datasets were consolidated for one hillslope site located at the Panola Mountain Research Watershed (Southeastern USA) and catchments located in the HJ Andrew's Experimental Forest (Northwestern USA), the Catfish Creek Watershed (Canadian prairies), the Experimental Lakes Area (Canadian boreal ecozone), the Tarrawarra catchment (Australia) and the Mahurangi catchment (New Zealand). Individual precipitation-runoff events were delineated using the newly introduced software HydRun to derive event-specific hydrograph parameters as well surrogate measures of antecedent moisture conditions and evapotranspiration in an automated and consistent manner. Various hydrograph parameters were then plotted against those surrogate measures to detect and evaluate site-specific threshold dynamics. Preliminary results show that a range of threshold shapes (e.g., "hockey stick", heaviside and dirac) were observed across sites. The influence of antecedent precipitation on threshold magnitude and shape also appeared stronger at sites with lower topographic
Li, Qiaoling; Li, Zhijia; Zhu, Yuelong; Deng, Yuanqian; Zhang, Ke; Yao, Cheng
Regionalisation provides a way of transferring hydrological information from gauged to ungauged catchments. The past few decades has seen several kinds of regionalisation approaches for catchment classification and runoff predictions. The underlying assumption is that catchments having similar catchment properties are hydrological similar. This requires the appropriate selection of catchment properties, particularly the inclusion of observed hydrological information, to explain the similarity of hydrological behaviour. We selected observable catchments properties and flow duration curves to reflect the hydrological behaviour, and to regionalize rainfall-runoff response for runoff prediction. As a case study, we investigated 15 catchments located in the Yangtze and Yellow River under multiple hydro-climatic conditions. A clustering scheme was developed to separate the catchments into 4 homogeneous regions by employing catchment properties including hydro-climatic attributes, topographic attributes and land cover etc. We utilized daily flow duration curves as the indicator of hydrological response and interpreted hydrological similarity by root mean square errors. The combined analysis of similarity in catchment properties and hydrological response suggested that catchments in the same homogenous region were hydrological similar. A further validation was conducted by establishing a rainfall-runoff coaxial correlation diagram for each catchment. A common coaxial correlation diagram was generated for each homogenous region. The performances of most coaxial correlation diagrams met the national standard. The coaxial correlation diagram can be transferred within the homogeneous region for runoff prediction in ungauged catchments at an hourly time scale.
Gärdenäs, A.; Jarvis, N.; Alavi, G.
The spatial variability of soil characteristics was studied in a small agricultural catch- ment (Vemmenhög, 9 km2) at the field and catchment scales. This analysis serves as a basis for assumptions concerning upscaling approaches used to model pesticide leaching from the catchment with the MACRO model (Jarvis et al., this meeting). The work focused on the spatial variability of two key soil properties for pesticide fate in soil, organic carbon and clay content. The Vemmenhög catchment (9 km2) is formed in a glacial till deposit in southernmost Sweden. The landscape is undulating (30 - 65 m a.s.l.) and 95 % of the area is used for crop production (winter rape, winter wheat, sugar beet and spring barley). The climate is warm temperate. Soil samples for or- ganic C and texture were taken on a small regular grid at Näsby Farm, (144 m x 144 m, sampling distance: 6-24 m, 77 points) and on an irregular large grid covering the whole catchment (sampling distance: 333 m, 46 points). At the field scale, it could be shown that the organic C content was strongly related to landscape position and height (R2= 73 %, p < 0.001, n=50). The organic C content of hollows in the landscape is so high that they contribute little to the total loss of pesticides (Jarvis et al., this meeting). Clay content is also related to landscape position, being larger at the hilltop locations resulting in lower near-saturated hydraulic conductivity. Hence, macropore flow can be expected to be more pronounced (see also Roulier & Jarvis, this meeting). The variability in organic C was similar for the field and catchment grids, which made it possible to krige the organic C content of the whole catchment using data from both grids and an uneven lag distance.
David Eiriksson; Michael Whitson; Charles H. Luce; Hans Peter Marshall; John Bradford; Shawn G. Benner; Thomas Black; Hank Hetrick; James P. McNamara
Lateral downslope flow in snow during snowmelt and rain-on-snow (ROS) events is a well-known phenomenon, yet its relevance to water redistribution at hillslope and catchment scales is not well understood. We used dye tracers, geophysical methods, and hydrometric measurements to describe the snow properties that promote lateral flow, assess the relative velocities of...
Zapata-Rios, X.; Brooks, P. D.; Troch, P. A. A.; McIntosh, J. C.
Landscape, climate, and vegetation interactions play a fundamental role in controlling the distribution of available water in hillslopes and catchments. In mid-latitudes, terrain aspect can regulate surface and subsurface hydrological processes, which not only affect the partitioning of energy and precipitation on short time scales, but also soil development, vegetation characteristics on long time scales. In Redondo Peak in northern New Mexico, a volcanic resurgent dome, first order streams drain different slopes around the mountain. In this setting, we study three adjacent first order catchments that share similar physical characteristics, but drain different aspects, allowing for an empirical study of how topographically controlled microclimate and soil influence the integrated hydrological and vegetation response. From 2008 to 2012, catchments were compared for the way they partition precipitation and how vegetation responds to variable water fluxes. Meteorological variables were monitored in 5 stations around Redondo Peak and surface runoff was monitored at the catchments' outlets. Hydrological partitioning at the catchment scale was estimated with the Horton Index, defined as the ratio between vaporization and wetting and it represents a measure of catchment-scale vegetation water use. Vegetation response was estimated using remotely sensed vegetation greenness (NDVI) derived from MODIS every 16 days with a spatial resolution of 250 m. Results show that the predominantly north facing catchment has the largest and least variable baseflow and discharge, consistent with greater mineral weathering fluxes and longer water transit times. In addition, vaporization, wetting and Horton Index, as well as NDVI, are smaller in the north facing catchment compared to the south east facing catchments. The predominant terrain aspect controls soil development, which affects the partitioning of precipitation and vegetation response at the catchment scale. These results also
Quinn, D.; Brooks, E. S.; Robichaud, P. R.; Dobre, M.; Brown, R. E.; Wagenbrenner, J.
The cascading consequences of fire-induced ecological changes have profound impacts on both natural and managed forest ecosystems. Forest managers tasked with implementing post-fire mitigation strategies need robust tools to evaluate the effectiveness of their decisions, particularly those affecting hydrological recovery. Various hillslope-scale interfaces of the physically-based Water Erosion Prediction Project (WEPP) model have been successfully validated for this purpose using fire-effected plot experiments, however these interfaces are explicitly designed to simulate single hillslopes. Spatially-distributed, catchment-scale WEPP interfaces have been developed over the past decade, however none have been validated for post-fire simulations, posing a barrier to adoption for forest managers. In this validation study, we compare WEPP simulations with pre- and post-fire hydrological records for three forested catchments (W. Willow, N. Thomas, and S. Thomas) that burned in the 2011 Wallow Fire in Northeastern Arizona, USA. Simulations were conducted using two approaches; the first using automatically created inputs from an online, spatial, post-fire WEPP interface, and the second using manually created inputs which incorporate the spatial variability of fire effects observed in the field. Both approaches were compared to five years of observed post-fire sediment and flow data to assess goodness of fit.
Lutz, Stefanie R.; van der Velde, Ype; Elsayed, Omniea F.; Imfeld, Gwenaël; Lefrancq, Marie; Payraudeau, Sylvain; van Breukelen, Boris M.
Compound-specific stable isotope analysis (CSIA) has proven beneficial in the characterization of contaminant degradation in groundwater, but it has never been used to assess pesticide transformation on catchment scale. This study presents concentration and carbon CSIA data of the herbicides S-metolachlor and acetochlor from three locations (plot, drain, and catchment outlets) in a 47 ha agricultural catchment (Bas-Rhin, France). Herbicide concentrations at the catchment outlet were highest (62 µg L-1) in response to an intense rainfall event following herbicide application. Increasing δ13C values of S-metolachlor and acetochlor by more than 2 ‰ during the study period indicated herbicide degradation. To assist the interpretation of these data, discharge, concentrations, and δ13C values of S-metolachlor were modelled with a conceptual mathematical model using the transport formulation by travel-time distributions. Testing of different model setups supported the assumption that degradation half-lives (DT50) increase with increasing soil depth, which can be straightforwardly implemented in conceptual models using travel-time distributions. Moreover, model calibration yielded an estimate of a field-integrated isotopic enrichment factor as opposed to laboratory-based assessments of enrichment factors in closed systems. Thirdly, the Rayleigh equation commonly applied in groundwater studies was tested by our model for its potential to quantify degradation on catchment scale. It provided conservative estimates on the extent of degradation as occurred in stream samples. However, largely exceeding the simulated degradation within the entire catchment, these estimates were not representative of overall degradation on catchment scale. The conceptual modelling approach thus enabled us to upscale sample-based CSIA information on degradation to the catchment scale. Overall, this study demonstrates the benefit of combining monitoring and conceptual modelling of concentration
Mirus, Benjamin B.; Loague, Keith
Improved understanding of the complex dynamics associated with spatially and temporally variable runoff response is needed to better understand the hydrology component of interdisciplinary problems. The objective of this study was to quantitatively characterize the environmental controls on runoff generation for the range of different streamflow-generation mechanisms illustrated in the classic Dunne diagram. The comprehensive physics-based model of coupled surface-subsurface flow, InHM, is employed in a heuristic mode. InHM has been employed previously to successfully simulate the observed hydrologic response at four diverse, well-characterized catchments, which provides the foundation for this study. The C3 and CB catchments are located within steep, forested terrain; the TW and R5 catchments are located in gently sloping rangeland. The InHM boundary-value problems for these four catchments provide the corner-stones for alternative simulation scenarios designed to address the question of how runoff begins (and ends). Simulated rainfall-runoff events are used to systematically explore the impact of soil-hydraulic properties and rainfall characteristics. This approach facilitates quantitative analysis of both integrated and distributed hydrologic responses at high-spatial and temporal resolution over the wide range of environmental conditions represented by the four catchments. The results from 140 unique simulation scenarios illustrate how rainfall intensity/depth, subsurface permeability contrasts, characteristic curve shapes, and topography provide important controls on the hydrologic-response dynamics. The processes by which runoff begins (and ends) are shown, in large part, to be defined by the relative rates of rainfall, infiltration, lateral flow convergence, and storage dynamics within the variably saturated soil layers.
Loperfido, John V.; Noe, Gregory B.; Jarnagin, S. Taylor; Hogan, Dianna M.
Urban stormwater runoff remains an important issue that causes local and regional-scale water quantity and quality issues. Stormwater best management practices (BMPs) have been widely used to mitigate runoff issues, traditionally in a centralized manner; however, problems associated with urban hydrology have remained. An emerging trend is implementation of BMPs in a distributed manner (multi-BMP treatment trains located on the landscape and integrated with urban design), but little catchment-scale performance of these systems have been reported to date. Here, stream hydrologic data (March, 2011–September, 2012) are evaluated in four catchments located in the Chesapeake Bay watershed: one utilizing distributed stormwater BMPs, two utilizing centralized stormwater BMPs, and a forested catchment serving as a reference. Among urban catchments with similar land cover, geology and BMP design standards (i.e. 100-year event), but contrasting placement of stormwater BMPs, distributed BMPs resulted in: significantly greater estimated baseflow, a higher minimum precipitation threshold for stream response and maximum discharge increases, better maximum discharge control for small precipitation events, and reduced runoff volume during an extreme (1000-year) precipitation event compared to centralized BMPs. For all catchments, greater forest land cover and less impervious cover appeared to be more important drivers than stormwater BMP spatial pattern, and caused lower total, stormflow, and baseflow runoff volume; lower maximum discharge during typical precipitation events; and lower runoff volume during an extreme precipitation event. Analysis of hydrologic field data in this study suggests that both the spatial distribution of stormwater BMPs and land cover are important for management of urban stormwater runoff. In particular, catchment-wide application of distributed BMPs improved stream hydrology compared to centralized BMPs, but not enough to fully replicate forested
Loperfido, J. V.; Noe, Gregory B.; Jarnagin, S. Taylor; Hogan, Dianna M.
Urban stormwater runoff remains an important issue that causes local and regional-scale water quantity and quality issues. Stormwater best management practices (BMPs) have been widely used to mitigate runoff issues, traditionally in a centralized manner; however, problems associated with urban hydrology have remained. An emerging trend is implementation of BMPs in a distributed manner (multi-BMP treatment trains located on the landscape and integrated with urban design), but little catchment-scale performance of these systems have been reported to date. Here, stream hydrologic data (March, 2011-September, 2012) are evaluated in four catchments located in the Chesapeake Bay watershed: one utilizing distributed stormwater BMPs, two utilizing centralized stormwater BMPs, and a forested catchment serving as a reference. Among urban catchments with similar land cover, geology and BMP design standards (i.e. 100-year event), but contrasting placement of stormwater BMPs, distributed BMPs resulted in: significantly greater estimated baseflow, a higher minimum precipitation threshold for stream response and maximum discharge increases, better maximum discharge control for small precipitation events, and reduced runoff volume during an extreme (1000-year) precipitation event compared to centralized BMPs. For all catchments, greater forest land cover and less impervious cover appeared to be more important drivers than stormwater BMP spatial pattern, and caused lower total, stormflow, and baseflow runoff volume; lower maximum discharge during typical precipitation events; and lower runoff volume during an extreme precipitation event. Analysis of hydrologic field data in this study suggests that both the spatial distribution of stormwater BMPs and land cover are important for management of urban stormwater runoff. In particular, catchment-wide application of distributed BMPs improved stream hydrology compared to centralized BMPs, but not enough to fully replicate forested
Ertsen, Maurits; Strohschein, Paul; Onencan, Abby; van de Giesen, Nick
Water conservation is a high priority in the drier areas of sub-Saharan Africa. Storage of water from the rainy season to the dry season, or even from wet years to dry years is highly important. Small multi-purpose sub-surface water reservoirs recharged through infiltration are used to provide water for humans, livestock and crops in the Kitui region in Kenya. The groundwater dams obstruct the natural flow of water in wet seasons or periods, and provide storage of water during dry seasons or periods. This paper links the hydrology of the sand-storage dams to human agency. When is a dam a success in hydrological terms? When it provides water every year? Every two years? How many months? What happens in very dry years? Obviously, water use will decrease the water volume and thus the water level upstream of the dam, but to what extent typically depends on the amounts used compared to the size of the dam and the water use itself. Longer-term effects on groundwater levels to be expected depend strongly on the way the water is used. Household water use and river banks infiltration increasing seasonal storage can go hand in hand. However, when water in dams is used for higher water demanding activities such as (motorized) irrigation, the infiltration effect into banks may be minimal. A dam can also be "too effective" and decrease water availability for water users further downstream. It is unlikely, however, that an individual farmer will effect on the downstream users of the resources he/she is tapping, but a network of dams as in Kitui may have considerable effect. Measurements indicate that only about 2% to 3% of the total yearly runoff within the catchment directly associated with a single dam is stored in its reservoir. Therefore only this small percentage of the total flow of a seasonal river with dams is blocked. The paper will detail these general concepts with a case study of the Kiindu catchment. The hydrology of the Kiindu catchment is dependent on different
Seuntjens, P.; Desmet, N.; Holvoet, K.; van Griensven, A.; van Hoey, S.; Tang, X. Y.; Nopens, I.
Micropollutants, such as pesticides, personal care products, veterinary and human pharmaceuticals, pose a possible threat to human and ecological health. Humans and ecosystems may be exposed to these chemicals via the water system. Catchment models can be used to optimise management in view of risk reduction of the chemicals. Along the trajectory of science to practice a number of catchment models are available that simulate the fate and transport of micropollutants. They range from physically-based fully-coupled soil, groundwater, and surface water models, over empirical management models, to purely statistical database-driven models. For assessing effects on ecosystems, models need to be able to predict the observed highly dynamic behaviour of pesticide concentrations in the surface water, since adverse effects will be determined by the number, intensity and frequency of ecological threshold exceedances. For assessing effects on humans, models need to predict the dilution between areas where the pesticide is released and the location of the drinking water intake, sometimes tens or hundreds of kilometres further downstream. We adapted management models to simulate dynamic pesticide behaviour and fate at the catchment scale. The models were also used to illustrate the effects of specific management options on risk reduction and to derive the dominant sources of pollutants in a catchment area. The results show that the concentrations of pesticides in river systems are attributed to (1) fast flow over and in soils or pavements, and to (2) point sources. Therefore, future models for improved estimation of chemical fate at the catchment scale need a combination of stochastic source characterisation, higher spatial resolution and reduced complexity of the mathematical description of fast flow processes. This will be illustrated by recent developments in model simplification coupled to increased spatial detail.
Taccone, Florent; Antoine, Germain; Delestre, Olivier; Goutal, Nicole
Water equations. The numerical scheme developed by Chen and Noelle (2015) appears to be the best compromise between robustness and accuracy. The sediment transport module SISYPHE of TELEMAC-MASCARET is also used for simulating suspended sediment transport and erosion in this configuration. Then, an application to a real, well-documented watershed is performed. With a total area of 86.4 ha, the Laval watershed is located in the Southern French Alps. It takes part of the Draix-Bleone Observatory, on which 30 years of collected data are available. On this site, several rainfall events have been simulated using high performance clusters and parallelized computation methods. The results show a good robustness and accuracy of the chosen numerical schemes for hydraulic and sediment transport. Furthermore, a good agreement with measured data is obtain if an infiltration model is added to the Shallow Water equations. This study gives promising perspectives for simulating sediment transfers at the catchment scale with a physically based approach. G. Chen et S. Noelle: A new hydrostatic reconstruction scheme motivated by the wet-dry front. 2015. G. Kirstetter et al: Modeling rain-driven overland fow: empirical versus analytical friction terms in the shallow water approximation. Journal of Hydrology, 2015.
Peche, Aaron; Fuchs, Lothar; Spönemann, Peter; Graf, Thomas; Neuweiler, Insa
Keywords: pipe leakage, urban hydrogeology, catchment scale, OpenGeoSys, HYSTEM-EXTRAN Wastewater leakage from subsurface sewer pipe defects leads to contamination of the surrounding soil and groundwater (Ellis, 2002; Wolf et al., 2004). Leakage rates at pipe defects have to be known in order to quantify contaminant input. Due to inaccessibility of subsurface pipe defects, direct (in-situ) measurements of leakage rates are tedious and associated with a high degree of uncertainty (Wolf, 2006). Proposed catchment-scale models simplify leakage rates by neglecting unsaturated zone flow or by reducing spatial dimensions (Karpf & Krebs, 2013, Boukhemacha et al., 2015). In the present study, we present a physically based 3-dimensional numerical model incorporating flow in the pipe network, in the saturated zone and in the unsaturated zone to quantify leakage rates on the catchment scale. The model consists of the pipe network flow model HYSTEM-EXTAN (itwh, 2002), which is coupled to the subsurface flow model OpenGeoSys (Kolditz et al., 2012). We also present the newly developed coupling scheme between the two flow models. Leakage functions specific to a pipe defect are derived from simulations of pipe leakage using spatially refined grids around pipe defects. In order to minimize computational effort, these leakage functions are built into the presented numerical model using unrefined grids around pipe defects. The resulting coupled model is capable of efficiently simulating spatially distributed pipe leakage coupled with subsurficial water flow in a 3-dimensional environment. References: Boukhemacha, M. A., Gogu, C. R., Serpescu, I., Gaitanaru, D., & Bica, I. (2015). A hydrogeological conceptual approach to study urban groundwater flow in Bucharest city, Romania. Hydrogeology Journal, 23(3), 437-450. doi:10.1007/s10040-014-1220-3. Ellis, J. B., & Revitt, D. M. (2002). Sewer losses and interactions with groundwater quality. Water Science and Technology, 45(3), 195
Mouri, Goro; Oki, Taikan
Water shortages and water pollution are a global problem. Increases in population can have further acute effects on water cycles and on the availability of water resources. Thus, wastewater management plays an important role in mitigating negative impacts on natural ecosystems and human environments and is an important area of research. In this study, we modelled catchment-scale hydrology, including water balances, rainfall, contamination, and urban wastewater treatment. The entire water resource system of a basin, including a forest catchment and an urban city area, was evaluated synthetically from a spatial distribution perspective with respect to water quantity and quality; the Life Cycle Assessment (LCA) technique was applied to optimize wastewater treatment management with the aim of improving water quality and reducing CO₂ emissions. A numerical model was developed to predict the water cycle and contamination in the catchment and city; the effect of a wastewater treatment system on the urban region was evaluated; pollution loads were evaluated quantitatively; and the effects of excluding rainwater from the treatment system during flooding and of urban rainwater control on water quality were examined. Analysis indicated that controlling the amount of rainwater inflow to a wastewater treatment plant (WWTP) in an urban area with a combined sewer system has a large impact on reducing CO₂ emissions because of the load reduction on the urban sewage system.
von Ruette, J.; Lehmann, P.; Or, D.
Rainfall-induced shallow landslides may occur abruptly without distinct precursors and could span a wide range of soil mass released during a triggering event. We present a rainfall-induced landslide-triggering model for steep catchments with surfaces represented as an assembly of hydrologically and mechanically interconnected soil columns. The abruptness of failure was captured by defining local strength thresholds for mechanical bonds linking soil and bedrock and adjacent columns, whereby a failure of a single bond may initiate a chain reaction of subsequent failures, culminating in local mass release (a landslide). The catchment-scale hydromechanical landslide-triggering model (CHLT) was applied to results from two event-based landslide inventories triggered by two rainfall events in 2002 and 2005 in two nearby catchments located in the Prealps in Switzerland. Rainfall radar data, surface elevation and vegetation maps, and a soil production model for soil depth distribution were used for hydromechanical modeling of failure patterns for the two rainfall events at spatial and temporal resolutions of 2.5 m and 0.02 h, respectively. The CHLT model enabled systematic evaluation of the effects of soil type, mechanical reinforcement (soil cohesion and lateral root strength), and initial soil water content on landslide characteristics. We compared various landslide metrics and spatial distribution of simulated landslides in subcatchments with observed inventory data. Model parameters were optimized for the short but intense rainfall event in 2002, and the calibrated model was then applied for the 2005 rainfall, yielding reasonable predictions of landslide events and volumes and statistically reproducing localized landslide patterns similar to inventory data. The model provides a means for identifying local hot spots and offers insights into the dynamics of locally resolved landslide hazards in mountainous regions.
Yeo, I. Y.
Wetlands are valuable landscape features that provide important ecosystem functions and services. The ecosystem processes in wetlands are highly dependent on the hydrology. However, hydroperiod (i.e., change dynamics in inundation extent) is highly variable spatially and temporarily, and extremely difficult to predict owing to the complexity in hydrological processes within wetlands and its interaction with surrounding areas. This study reports the challenges and progress in assessing the catchment scale benefits of wetlands to regulate hydrological regime and water quality improvement in agricultural watershed. A process-based watershed model, Soil and Water Assessment Tool (SWAT) was improved to simulate the cumulative impacts of wetlands on downstream. Newly developed remote sensing products from LiDAR intensity and time series Landsat records, which show the inter-annual changes in fraction inundation, were utilized to describe the change status of inundated areas within forested wetlands, develop spatially varying wetland parameters, and evaluate the predicted inundated areas at the landscape level. We outline the challenges on developing the time series inundation mapping products at a high spatial and temporal resolution and reconciling the catchment scale model with the moderate remote sensing products. We then highlight the importance of integrating spatialized information to model calibration and evaluation to address the issues of equi-finality and prediction uncertainty. This integrated approach was applied to the upper region of Choptank River Watershed, the agricultural watershed in the Coastal Plain of Chesapeake Bay Watershed (in US). In the Mid- Atlantic US, the provision of pollution regulation services provided by wetlands has been emphasized due to declining water quality within the Chesapeake Bay and watersheds, and the preservation and restoration of wetlands has become the top priority to manage nonpoint source water pollution.
Greene, S; Taylor, D; McElarney, Y R; Foy, R H; Jordan, P
Functional relationships between phosphorus (P) discharge and concentration mechanisms were explored using a load apportionment model (LAM) developed for use in a freshwater catchment in Ireland with fourteen years of data (1995-2008). The aim of model conceptualisation was to infer changes in point and diffuse sources from catchment P loading during P mitigation, based upon a dataset comprising geospatial and water quality data from a 256km(2) lake catchment in an intensively farmed drumlin region of the midlands of Ireland. The model was calibrated using river total P (TP), molybdate reactive P (MRP) and runoff data from seven subcatchments. Temporal and spatial heterogeneity of P sources existed within and between subcatchments; these were attributed to differences in agricultural intensity, soil type and anthropogenically-sourced effluent P loading. Catchment rivers were sensitive to flow regime, which can result in eutrophication of rivers during summer and lake enrichment from frequent flood events. For one sewage impacted river, the LAM estimated that point sourced P contributed up to of 90% of annual MRP load delivered during a hydrological year and in this river point P sources dominated flows up to 92% of days. In the other rivers, despite diffuse P forming a majority of the annual P exports, point sources of P dominated flows for up to 64% of a hydrological year. The calibrated model demonstrated that lower P export rates followed specific P mitigation measures. The LAM estimated up to 80% decreases in point MRP load after enhanced P removal at waste water treatments plants in urban subcatchments and the implementation of septic tank and agricultural bye-laws in rural subcatchments. The LAM approach provides a way to assess the long-term effectiveness of further measures to reduce P loadings in EU (International) River Basin Districts and subcatchments. Copyright © 2011 Elsevier B.V. All rights reserved.
Lerner, R. N.; Lerner, D. N.; Surridge, B.; Paetzold, A.; Harris, B.; Anderson, C. W.
In Europe, the Water Framework Directive (WFD) is providing a powerful regulatory driver to adopt integrated catchment management, and so pressurizing researchers to build suitable supporting tools. The WFD requires agencies to drive towards `good ecological quality' by 2015. After the initial step of characterising water bodies and the pressures on them, the next substantive step is the preparation of river basin management plans and proposed programmes of measures by 2009. Ecological quality is a complex concept and poorly defined, unless it is taken as a simple measure such as the abundance of a particular species of organism. There is clearly substantial work to do to build a practical but sound definition of ecological quality; practical in the sense of being easy to measure and explain to stakeholders, and sound in the sense that it reflects ecological complexity within catchments, the variability between catchments, and the conflicts demands for goods and services that human society places upon the ecological system. However ecological quality is defined, it will be driven by four interacting groups of factors. These represent the physical, chemical, ecological and socio-economic environments within and encompassing the catchment. Some of these groupings are better understood than others, for example hydrological processes and the transport of solutes are reasonably understood, even though they remain research areas in their own right. There are much larger gaps in our understanding at the interfaces, i.e. predicting how, for example, hydrological processes such as flow and river morphology influence ecological quality. Overall, it is clear we are not yet in a position to build deterministic models of the overall ecological behaviour of catchment. But we need predictive tools to support catchment management agencies in preparing robust plans. This poster describes our current exploration of soft modelling options to build a comprehensive macro
Stegen, Ronald; Gassmann, Matthias
The use of a broad variation of agrochemicals is essential for the modern industrialized agriculture. During the last decades, the awareness of the side effects of their use has grown and with it the requirement to reproduce, understand and predict the behaviour of these agrochemicals in the environment, in order to optimize their use and minimize the side effects. The modern modelling has made great progress in understanding and predicting these chemicals with digital methods. While the behaviour of the applied chemicals is often investigated and modelled, most studies only simulate parent chemicals, considering total annihilation of the substance. However, due to a diversity of chemical, physical and biological processes, the substances are rather transformed into new chemicals, which themselves are transformed until, at the end of the chain, the substance is completely mineralized. During this process, the fate of each transformation product is determined by its own environmental characteristics and the pathway and results of transformation can differ largely by substance and environmental influences, that can occur in different compartments of the same site. Simulating transformation products introduces additional model uncertainties. Thus, the calibration effort increases compared to simulations of the transport and degradation of the primary substance alone. The simulation of the necessary physical processes needs a lot of calculation time. Due to that, few physically-based models offer the possibility to simulate transformation products at all, mostly at the field scale. The few models available for the catchment scale are not optimized for this duty, i.e. they are only able to simulate a single parent compound and up to two transformation products. Thus, for simulations of large physico-chemical parameter spaces, the enormous calculation time of the underlying hydrological model diminishes the overall performance. In this study, the structure of the model
Jencso, Kelsey G.; McGlynn, Brian L.; Gooseff, Michael N.; Wondzell, Steven M.; Bencala, Kenneth E.; Marshall, Lucy A.
The relationship between catchment structure and runoff characteristics is poorly understood. In steep headwater catchments with shallow soils the accumulation of hillslope area (upslope accumulated area (UAA)) is a hypothesized first‐order control on the distribution of soil water and groundwater. Hillslope‐riparian water table connectivity represents the linkage between the dominant catchment landscape elements (hillslopes and riparian zones) and the channel network. Hydrologic connectivity between hillslope‐riparian‐stream (HRS) landscape elements is heterogeneous in space and often temporally transient. We sought to test the relationship between UAA and the existence and longevity of HRS shallow groundwater connectivity. We quantified water table connectivity based on 84 recording wells distributed across 24 HRS transects within the Tenderfoot Creek Experimental Forest (U.S. Forest Service), northern Rocky Mountains, Montana. Correlations were observed between the longevity of HRS water table connectivity and the size of each transect's UAA (r2 = 0.91). We applied this relationship to the entire stream network to quantify landscape‐scale connectivity through time and ascertain its relationship to catchment‐scale runoff dynamics. We found that the shape of the estimated annual landscape connectivity duration curve was highly related to the catchment flow duration curve (r2 = 0.95). This research suggests internal catchment landscape structure (topography and topology) as a first‐order control on runoff source area and whole catchment response characteristics.
Barnes, Mhari; Quinn, Paul; Bathurst, James; Birkinshaw, Stephen
After the 2013-14 floods in the UK there were calls to 'forest the uplands' as a solution to reducing flood risk across the nation. At present, 1 in 6 homes in Britain are at risk of flooding and current EU legislation demands a sustainable, 'nature-based solution'. However, the role of forests as a natural flood management technique remains highly controversial, due to a distinct lack of robust evidence into its effectiveness in reducing flood risk during extreme events. SHETRAN, physically-based spatially-distributed hydrological models of the Irthing catchment and Wark forest sub-catchments (northern England) have been developed in order to test the hypothesis of the effect trees have on flood magnitude. The advanced physically-based models have been designed to model scale-related responses from 1, through 10, to 100km2, a first study of the extent to which afforestation and woody debris runoff attenuation features (RAFs) may help to mitigate floods at the full catchment scale (100-1000 km2) and on a national basis. Furthermore, there is a need to analyse the extent to which land management practices, and the installation of nature-based RAFs, such as woody debris dams, in headwater catchments can attenuate flood-wave movement, and potentially reduce downstream flood risk. The impacts of riparian planting and the benefits of adding large woody debris of several designs and on differing sizes of channels has also been simulated using advanced hydrodynamic (HiPIMS) and hydrological modelling (SHETRAN). With the aim of determining the effect forestry may have on flood frequency, 1000 years of generated rainfall data representative of current conditions has been used to determine the difference between current land-cover, different distributions of forest cover and the defining scenarios - complete forest removal and complete afforestation of the catchment. The simulations show the percentage of forestry required to have a significant impact on mitigating
Liao, Wenjie; van der Werf, Hayo M G; Salmon-Monviola, Jordy
One of the major challenges in environmental life cycle assessment (LCA) of crop production is the nonlinearity between nitrogen (N) fertilizer inputs and on-site N emissions resulting from complex biogeochemical processes. A few studies have addressed this nonlinearity by combining process-based N simulation models with LCA, but none accounted for nitrate (NO3(-)) flows across fields. In this study, we present a new method, TNT2-LCA, that couples the topography-based simulation of nitrogen transfer and transformation (TNT2) model with LCA, and compare the new method with a current LCA method based on a French life cycle inventory database. Application of the two methods to a case study of crop production in a catchment in France showed that, compared to the current method, TNT2-LCA allows delineation of more appropriate temporal limits when developing data for on-site N emissions associated with specific crops in this catchment. It also improves estimates of NO3(-) emissions by better consideration of agricultural practices, soil-climatic conditions, and spatial interactions of NO3(-) flows across fields, and by providing predicted crop yield. The new method presented in this study provides improved LCA of crop production at the catchment scale.
Leterme, Bertrand; Di Ciacca, Antoine; Laloy, Eric; Jacques, Diederik
Accurate estimation of groundwater recharge is a challenging task as only a few devices (if any) can measure it directly. In this study, we discuss how groundwater recharge can be calculated at different temporal and spatial scales in the Kleine Nete catchment (Belgium). A small monitoring network is being installed, that is aimed to monitor the changes in dominant processes and to address data availability as one goes from the point to the catchment scale. At the point scale, groundwater recharge is estimated using inversion of soil moisture and/or water potential data and stable isotope concentrations (Koeniger et al. 2015). At the plot scale, it is proposed to monitor the discharge of a small drainage ditch in order to calculate the field groundwater recharge. Electrical conductivity measurements are necessary to separate shallow from deeper groundwater contribution to the ditch discharge (see Di Ciacca et al. poster in session HS8.3.4). At this scale, two or three-dimensional process-based vadose zone models will be used to model subsurface flow. At the catchment scale though, using a mechanistic, process-based model to estimate groundwater recharge is debatable (because of, e.g., the presence of numerous drainage ditches, mixed land use pixels, etc.). We therefore investigate to which extent various types of surrogate models can be used to make the necessary upscaling from the plot scale to the scale of the whole Kleine Nete catchment. Ref. Koeniger P, Gaj M, Beyer M, Himmelsbach T (2015) Review on soil water isotope based groundwater recharge estimations. Hydrological Processes, DOI: 10.1002/hyp.10775
Over the last five years, Structure-from-Motion photogrammetry has dramatically democratized the availability of high quality topographic data. This approach involves the use of a non-linear bundle adjustment to estimate simultaneously camera position, pose, distortion and 3D model coordinates. In contrast to traditional aerial photogrammetry, the bundle adjustment is typically solved without external constraints and instead ground control is used a posteriori to transform the modelled coordinates to an established datum using a similarity transformation. The limited data requirements, coupled with the ability to self-calibrate compact cameras, has led to a burgeoning of applications using low-cost imagery acquired terrestrially or from low-altitude platforms. To date, most applications have focused on relatively small spatial scales where relaxed logistics permit the use of dense ground control and high resolution, close-range photography. It is less clear whether this low-cost approach can be successfully upscaled to tackle larger, watershed-scale projects extending over 102-3 km2 where it could offer a competitive alternative to landscape modelling with airborne lidar. At such scales, compromises over the density of ground control, the speed and height of sensor platform and related image properties are inevitable. In this presentation we provide a systematic assessment of large-scale SfM terrain products derived for over 80 km2 of the braided Dart River and its catchment in the Southern Alps of NZ. Reference data in the form of airborne and terrestrial lidar are used to quantify the quality of 3D reconstructions derived from helicopter photography and used to establish baseline uncertainty models for geomorphic change detection. Results indicate that camera network design is a key determinant of model quality, and that standard aerial networks based on strips of nadir photography can lead to unstable camera calibration and systematic errors that are difficult
Brasington, James; James, Joe; Cook, Simon; Cox, Simon; Lotsari, Eliisa; McColl, Sam; Lehane, Niall; Williams, Richard; Vericat, Damia
In recent years, 3D terrain reconstructions based on Structure-from-Motion photogrammetry have dramatically democratized the availability of high quality topographic data. This approach involves the use of a non-linear bundle adjustment to estimate simultaneously camera position, pose, distortion and 3D model coordinates. In contrast to traditional aerial photogrammetry, the bundle adjustment is typically solved without external constraints and instead ground control is used a posteriori to transform the modelled coordinates to an established datum using a similarity transformation. The limited data requirements, coupled with the ability to self-calibrate compact cameras, has led to a burgeoning of applications using low-cost imagery acquired terrestrially or from low-altitude platforms. To date, most applications have focused on relatively small spatial scales (0.1-5 Ha), where relaxed logistics permit the use of dense ground control networks and high resolution, close-range photography. It is less clear whether this low-cost approach can be successfully upscaled to tackle larger, watershed-scale projects extending over 102-3 km2 where it could offer a competitive alternative to established landscape modelling with airborne lidar. At such scales, compromises over the density of ground control, the speed and height of sensor platform and related image properties are inevitable. In this presentation we provide a systematic assessment of the quality of large-scale SfM terrain products derived for over 80 km2 of the braided Dart River and its catchment in the Southern Alps of NZ. Reference data in the form of airborne and terrestrial lidar are used to quantify the quality of 3D reconstructions derived from helicopter photography and used to establish baseline uncertainty models for geomorphic change detection. Results indicate that camera network design is a key determinant of model quality, and that standard aerial photogrammetric networks based on strips of nadir
Hüffmeyer, N.; Berlekamp, J.; Klasmeier, J.
1. Introduction The European Water Framework Directive demands the good ecological and chemical state of surface waters . This implies the reduction of unwanted metal concentrations in surface waters. To define reasonable environmental target values and to develop promising mitigation strategies a detailed exposure assessment is required. This includes the identification of emission sources and the evaluation of their effect on local and regional surface water concentrations. Point source emissions via municipal or industrial wastewater that collect metal loads from a wide variety of applications and products are important anthropogenic pathways into receiving waters. Natural background and historical influences from ore-mining activities may be another important factor. Non-point emissions occur via surface runoff and erosion from drained land area. Besides deposition metals can be deposited by fertilizer application or the use of metal products such as wires or metal fences. Surface water concentrations vary according to the emission strength of sources located nearby and upstream of the considered location. A direct link between specific emission sources and pathways on the one hand and observed concentrations can hardly be established by monitoring alone. Geo-referenced models such as GREAT-ER (Geo-referenced Regional Exposure Assessment Tool for European Rivers) deliver spatially resolved concentrations in a whole river basin and allow for evaluating the causal relationship between specific emissions and resulting concentrations. This study summarizes the results of investigations for the metals zinc and copper in three German catchments. 2. The model GREAT-ER The geo-referenced model GREAT-ER has originally been developed to simulate and assess chemical burden of European river systems from multiple emission sources . Emission loads from private households and rainwater runoff are individually estimated based on average consumption figures, runoff rates
López-Vicente, Manuel, , Dr.; Palazón, M. Sc. Leticia; Quijano, M. Sc. Laura; Gaspar, Leticia, , Dr.; Navas, Ana, , Dr.
weather station (WS) from the Caseda and Uncastillo WS. The effective rainfall that reaches the soils (after canopy interception and slope correction) was 85% on average from the total rainfall depth (556 mm yr-1) and the average initial runoff, before overland flow processes, was 320 mm yr-1. The simulated effective runoff (CQeff) ranged from 0 until 29,960 mm yr-1 and the corresponding map showed the typical spatial pattern of overland flow pathways though numerous disruptions appeared along the hillslopes and the main streams due to the presence of LLEs. The total depth of annual runoff corresponds to 37.8% of the total effective rainfall (TER) and 32.0% of the total rainfall depth (TR). The remaining volume of water, the soil water content (Waa) associated with the runoff and rainfall events, meant 62.2% and 52.7% of the TER and TR, respectively. The map of the Waa presented a different spatial pattern where the land uses play a more important role than the processes of cumulative overland flow. Significant variations in the monthly values of CQeff and Waa were described. This study proves the ability of the DR2-2013© SAGA v1.1 model to simulate the hydrological response of the soils at catchment scale.
Barnes, M. S.; Bathurst, J. C.; Quinn, P. F.; Birkinshaw, S.
After the 2013-14, and the more recent 2015-16, winter floods in the UK there were calls to 'forest the uplands' as a solution to reducing flood risk across the nation. However, the role of forests as a natural flood management practice remains highly controversial, due to a distinct lack of robust evidence into its effectiveness in reducing flood risk during extreme events. This project aims to improve the understanding of the impacts of upland afforestation on flood risk at the sub-catchment and full catchment scales. This will be achieved through an integrated fieldwork and modelling approach, with the use of a series of process based hydrological models to scale up and examine the effects forestry can have on flooding. Furthermore, there is a need to analyse the extent to which land management practices, catchment system engineering and the installation of runoff attenuation features (RAFs), such as engineered log jams, in headwater catchments can attenuate flood-wave movement, and potentially reduce downstream flood risk. Additionally, the proportion of a catchment or riparian reach that would need to be forested in order to achieve a significant impact on reducing downstream flooding will be defined. The consequential impacts of a corresponding reduction in agriculturally productive farmland and the potential decline of water resource availability will also be considered in order to safeguard the UK's food security and satisfy the global demand on water resources.
Chadalawada, Jayashree; Babovic, Vladan
One of the recent challenges for the hydrologic research community is the need for the development of coupled systems that involves the integration of hydrologic, atmospheric and socio-economic relationships. This poses a requirement for novel modelling frameworks that can accurately represent complex systems, given, the limited understanding of underlying processes, increasing volume of data and high levels of uncertainity. Each of the existing hydrological models vary in terms of conceptualization and process representation and is the best suited to capture the environmental dynamics of a particular hydrological system. Data driven approaches can be used in the integration of alternative process hypotheses in order to achieve a unified theory at catchment scale. The key steps in the implementation of integrated modelling framework that is influenced by prior understanding and data, include, choice of the technique for the induction of knowledge from data, identification of alternative structural hypotheses, definition of rules, constraints for meaningful, intelligent combination of model component hypotheses and definition of evaluation metrics. This study aims at defining a Genetic Programming based modelling framework that test different conceptual model constructs based on wide range of objective functions and evolves accurate and parsimonious models that capture dominant hydrological processes at catchment scale. In this paper, GP initializes the evolutionary process using the modelling decisions inspired from the Superflex framework [Fenicia et al., 2011] and automatically combines them into model structures that are scrutinized against observed data using statistical, hydrological and flow duration curve based performance metrics. The collaboration between data driven and physical, conceptual modelling paradigms improves the ability to model and manage hydrologic systems. Fenicia, F., D. Kavetski, and H. H. Savenije (2011), Elements of a flexible approach
Bertuzzo, E.; Thomet, M.; Botter, G.; Rinaldo, A.
This paper proposes and tests a model which couples the description of hydrologic flow and transport of herbicides at catchment scales. The model accounts for streamflow components' age to characterize short and long term fluctuations of herbicide flux concentrations in stream waters, whose peaks exceeding a toxic threshold are key to exposure risk of aquatic ecosystems. The model is based on a travel time formulation of transport embedding a source zone that describes near surface herbicide dynamics. To this aim we generalize a recently proposed scheme for the analytical derivation of travel time distributions to the case of solutes that can be partially taken up by transpiration and undergo chemical degradation. The framework developed is evaluated by comparing modeled hydrographs and atrazine chemographs with those measured in the Aabach agricultural catchment (Switzerland). The model proves reliable in defining complex transport features shaped by the interplay of long term processes, related to the persistence of solute components in soils, and short term dynamics related to storm inter-arrivals. The effects of stochasticity in rainfall patterns and application dates on concentrations and loads in runoff are assessed via Monte Carlo simulations, highlighting the crucial role played by the first rainfall event occurring after herbicide application. A probabilistic framework for critical determinants of exposure risk to aquatic communities is defined. Modeling of herbicides circulation at catchment scale thus emerges as essential tools for ecological risk assessment.
Rose, Steve; Worrall, Peter; Rosolova, Zdenka; Hammond, Gene
Rural land management is known to affect both the generation and propagation of flooding at the local scale, but there is still a general lack of good evidence that this impact is still significant at the larger catchment scale given the complexity of physical interactions and climatic variability taking place at this level. The National Trust, in partnership with the Environment Agency, are managing an innovative project on the Holnicote Estate in south west England to demonstrate the benefits of using good rural land management practices to reduce flood risk at the both the catchment and sub-catchment scales. The Holnicote Estate is owned by the National Trust and comprises about 5,000 hectares of land, from the uplands of Exmoor to the sea, incorporating most of the catchments of the river Horner and Aller Water. There are nearly 100 houses across three villages that are at risk from flooding which could potentially benefit from changes in land management practices in the surrounding catchment providing a more sustainable flood attenuation function. In addition to the contribution being made to flood risk management there are a range of other ecosystems services that will be enhanced through these targeted land management changes. Alterations in land management will create new opportunities for wildlife and habitats and help to improve the local surface water quality. Such improvements will not only create additional wildlife resources locally but also serve the landscape response to climate change effects by creating and enhancing wildlife networks within the region. Land management changes will also restore and sustain landscape heritage resources and provide opportunities for amenity, recreation and tourism. The project delivery team is working with the National Trust from source to sea across the entire Holnicote Estate, to identify and subsequently implement suitable land management techniques to manage local flood risk within the catchments. These
Klatt, S.; Butterbach-Bahl, K.; Kiese, R.; Haas, E.; Kraus, D.; Molina-Herrera, S. W.; Kraft, P.
The continuous growth of the human population demands an equally growing supply for fresh water and food. As a result, available land for efficient agriculture is constantly diminishing which forces farmers to cultivate inferior croplands and intensify agricultural practices, e.g., increase the use of synthetic fertilizers. This intensification of marginal areas in particular will cause a dangerous rise in nitrate discharge into open waters or even drinking water resources. In order to reduce the amount of nitrate lost by surface runoff or lateral subsurface transport, bufferstrips have proved to be a valuable means. Current laws, however, promote rather static designs (i.e., width and usage) even though a multitude of factors, e.g., soil type, slope, vegetation and the nearby agricultural management, determines its effectiveness. We propose a spatially explicit modeling approach enabling to assess the effects of those factors on nitrate discharge from arable lands using the fully distributed hydrology model CMF coupled to the complex biogeochemical model LandscapeDNDC. Such a modeling scheme allows to observe the displacement of dissolved nutrients in both vertical and horizontal directions and serves to estimate both their uptake by the vegetated bufferstrip and loss to the environment. First results indicate a significant reduction of nitrate loss in the presence of a bufferstrip (2.5 m). We show effects induced by various buffer strip widths and plant cover on the nitrate retention.
Cole, A.; Boutt, D. F.
Isotopic analyses of d18O and d2H of water transiting the hydrologic cycle have allowed hydrologists to better understand the portioning of water between the different components of the water cycle. Isoscapes on a large spatial scale have been created to show isotopic variation in waters as a function of elevation, temperature, distance to coast and precipitation. This has not been done on a 10,000 sq mi area, sub-regional scale or for that matter exhaustively sampled the important components of the terrestrial hydrologic cycle (groundwater, surface water and soil waters). We present the spatial and temporal isotopic results of an ongoing study across Massachusetts, USA, to establish an isotopic baseline for the region. Our current database consists of water samples from 50 precipitation sites, 333 ground water sites and 421 surface water sites. The isotopic signature of d18O and d2H of the samples are measured by a wavelength scanned cavity ring-down spectrometry on un-acidified water samples by a Picarro Cavity Ring Down Spectrometer (L2120-I) analyzer. Our results show that groundwater ranges from -11 to -1 ‰ δ18O across Massachusetts. Wells show a correlation with elevation; at higher elevations groundwater is more depleted in the heavy isotopes than compared with wells located at a lower elevation. Surface, groundwater and precipitation depict a seasonal evaporative enrichment, with waters being lighter during the months and heavier during the summer months. Based on Massachusetts location relative to the coast, there is a large variability in the mean d18O of precipitation with rain being heavy near the coast and lighter with increasing distance from the coast. HYSPLIT trajectory models will be used to determine how source affects isotopic composition. Within Massachusetts the isotopic composition of groundwater in till, glacial fluvial and bedrock aquifers are distinct which indicates the potential for surface and groundwater interaction. Our data also
Rivers, Mark; Clarendon, Simon; Coles, Neil
Natural Resource Management and Agri-industry development groups in Australia have invested considerable resources into the investigation of the economic, social and, particularly, environmental impacts of varying farming activities in a "catchment context". This research has resulted in the development of a much-improved understanding of the likely impacts of changed management practices at the farm-scale as well as the development of a number of conceptual models which place farming within this broader catchment context. The project discussed in this paper transformed a conceptual model of dairy farm phosphorus (P) management and transport processes into a more temporally and spatially dynamic model. This was then loaded with catchment-specific data and used as a "policy support tool" to allow the Australian dairy industry to examine the potential farm and catchment-scale impacts of varying dairy farm management practices within some key dairy farming regions. Models were developed, validated and calibrated using "STELLA©" dynamic modelling software for three catchments in which dairy is perceived as a significant land use. The models describe P movement and cycling within and through dairy farms in great detail and also estimate P transport through major source, sink and flow sectors of the catchments. A series of scenarios were executed for all three catchments which examined three main "groups" of tests: changes to farm P input rates; implementation of perceived environmental "Best Management Practices" (BMPs), and; changes to land use mosaics. Modifications to actual P input rates into dairy farms (not surprisingly) had a major effect on nutrient transport within and from the farms with a significant rise in nutrient loss rates at all scales with increasing fertiliser use. More surprisingly, however, even extensive environmental BMP implementation did not have marked effects on off-farm nutrient loss rates. On and off-farm riparian management implemented
Kellie Vache; Lutz Breuer; Julia Jones; Phil Sollins
We present a systems modeling approach to the development of a place-based ecohydrological model. The conceptual model is calibrated to a variety of existing observations, taken in watershed 10 (WS10) at the HJ Andrews Experimental Forest (HJA) in Oregon, USA, a long term ecological research (LTER) site with a long history of catchment-...
Refsgaard, A; Jacobsen, T; Jacobsen, B; Ørum, J-E
The EU Water Framework Directive (WFD) requires an integrated approach to river basin management in order to meet environmental and ecological objectives. This paper presents concepts and full-scale application of an integrated modelling framework. The Ringkoebing Fjord basin is characterized by intensive agricultural production and leakage of nitrate constitute a major pollution problem with respect groundwater aquifers (drinking water), fresh surface water systems (water quality of lakes) and coastal receiving waters (eutrophication). The case study presented illustrates an advanced modelling approach applied in river basin management. Point sources (e.g. sewage treatment plant discharges) and distributed diffuse sources (nitrate leakage) are included to provide a modelling tool capable of simulating pollution transport from source to recipient to analyse the effects of specific, localized basin water management plans. The paper also includes a land rent modelling approach which can be used to choose the most cost-effective measures and the location of these measures. As a forerunner to the use of basin-scale models in WFD basin water management plans this project demonstrates the potential and limitations of comprehensive, integrated modelling tools.
Pullan, S P; Whelan, M J; Rettino, J; Filby, K; Eyre, S; Holman, I P
This paper describes the development and application of IMPT (Integrated Model for Pesticide Transport), a parameter-efficient tool for predicting diffuse-source pesticide concentrations in surface waters used for drinking water supply. The model was applied to a small UK headwater catchment with high frequency (8h) pesticide monitoring data and to five larger catchments (479-1653km(2)) with sampling approximately every 14days. Model performance was good for predictions of both flow (Nash Sutcliffe Efficiency generally >0.59 and PBIAS <10%) and pesticide concentrations, although low sampling frequency in the larger catchments is likely to mask the true episodic nature of exposure. The computational efficiency of the model, along with the fact that most of its parameters can be derived from existing national soil property data mean that it can be used to rapidly predict pesticide exposure in multiple surface water resources to support operational and strategic risk assessments. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
Oliver, David M; Bartie, Phil J; Louise Heathwaite, A; Reaney, Sim M; Parnell, Jared A Q; Quilliam, Richard S
Effective management of diffuse microbial water pollution from agriculture requires a fundamental understanding of how spatial patterns of microbial pollutants, e.g. E. coli, vary over time at the landscape scale. The aim of this study was to apply the Visualising Pathogen &Environmental Risk (ViPER) model, developed to predict E. coli burden on agricultural land, in a spatially distributed manner to two contrasting catchments in order to map and understand changes in E. coli burden contributed to land from grazing livestock. The model was applied to the River Ayr and Lunan Water catchments, with significant correlations observed between area of improved grassland and the maximum total E. coli per 1km 2 grid cell (Ayr: r=0.57; p<0.001, Lunan: r=0.32; p<0.001). There was a significant difference in the predicted maximum E. coli burden between seasons in both catchments, with summer and autumn predicted to accrue higher E. coli contributions relative to spring and winter (P<0.001), driven largely by livestock presence. The ViPER model thus describes, at the landscape scale, spatial nuances in the vulnerability of E. coli loading to land as driven by stocking density and livestock grazing regimes. Resulting risk maps therefore provide the underpinning evidence to inform spatially-targeted decision-making with respect to managing sources of E. coli in agricultural environments. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.
Selle, Benny; Schwientek, Marc; Osenbrück, Karsten
The understanding of flow paths and travel times of water and solutes in catchments can be substantially improved by a combination of bottom-up and top-down modelling approaches. This hypothesis was tested for the 180 km² Ammer catchment in south-western Germany in which the landuse is dominated by agricultural and urban areas. The Ammer River with a mean discharge of 1 m³/s is mainly fed by springs from karstified and fractured aquifers. A limestone aquifer is extensively used for groundwater production. As a first step, we analysed measured concentrations of major ions, selected organic micro-pollutants and environmental tracers for surface water, springs and deep groundwater from wells using typical top-down approaches such as principal component analysis and lumped parameter models. From these approaches, we gained an initial understanding of water and solute fluxes in the catchment. The initial hypotheses on subsurface flow paths and travel times were subsequently tested using a numerical, 3-D groundwater model as a typical bottom-up approach. Our synthesis of top-down and bottom-up approaches provided us with a reliable picture of the dominant processes governing water and solute fluxes in the Ammer catchment. Several spring waters indicated mixing with wastewater. These contaminations were indentified to be caused by either recharge of surface water or leaky sewer systems. Deep percolation below the plant root zone polluted with agrochemicals was found to affect most springs and surface waters resulting in nitrate concentrations of approximately 30 mg/l. This process also influenced some of the drinking-water wells, although water quality for most of these wells is still relatively high due to some attenuation of pollutants but - above all - due to a significant proportion of groundwater with ages > 50 years. However, water quality will likely decrease if contaminants break through and/or conditions for microbiological attenuation process will deteriorate
Shafii, Mahyar; Basu, Nandita; Schiff, Sherry; Van Cappellen, Philippe
Dramatic increase in nitrogen circulating in the biosphere due to anthropogenic activities has resulted in impairment of water quality in groundwater and surface water causing eutrophication in coastal regions. Understanding the fate and transport of nitrogen from landscape to coastal areas requires exploring the drivers of nitrogen processes in both time and space, as well as the identification of appropriate flow pathways. Conceptual models can be used as diagnostic tools to provide insights into such controls. However, diagnostic evaluation of coupled hydrological-biogeochemical models is challenging. This research proposes a top-down methodology utilizing hydrochemical signatures to develop conceptual models for simulating the integrated streamflow and nitrate responses while taking into account dominant controls on nitrate variability (e.g., climate, soil water content, etc.). Our main objective is to seek appropriate model complexity that sufficiently reproduces multiple hydrological and nitrate signatures. Having developed a suitable conceptual model for a given watershed, we employ it in sensitivity studies to demonstrate the dominant process controls that contribute to the nitrate response at scales of interest. We apply the proposed approach to nitrate simulation in a range of small to large sub-watersheds in the Grand River Watershed (GRW) located in Ontario. Such multi-basin modeling experiment will enable us to address process scaling and investigate the consequences of lumping processes in terms of models' predictive capability. The proposed methodology can be applied to the development of large-scale models that can help decision-making associated with nutrients management at regional scale.
Zhao, Jie; Xu, Zongxue; Singh, Vijay P.
The root zone storage capacity (Sr) greatly influences runoff generation, soil water movement, and vegetation growth and is hence an important variable for ecological and hydrological modelling. However, due to the great heterogeneity in soil texture and structure, there seems to be no effective approach to monitor or estimate Sr at the catchment scale presently. To fill the gap, in this study the Mass Curve Technique (MCT) was improved by incorporating a snowmelt module for the estimation of Sr at the catchment scale in different climatic regions. The "range of perturbation" method was also used to generate different scenarios for determining the sensitivity of the improved MCT-derived Sr to its influencing factors after the evaluation of plausibility of Sr derived from the improved MCT. Results can be showed as: (i) Sr estimates of different catchments varied greatly from ∼10 mm to ∼200 mm with the changes of climatic conditions and underlying surface characteristics. (ii) The improved MCT is a simple but powerful tool for the Sr estimation in different climatic regions of China, and incorporation of more catchments into Sr comparisons can further improve our knowledge on the variability of Sr. (iii) Variation of Sr values is an integrated consequence of variations in rainfall, snowmelt water and evapotranspiration. Sr values are most sensitive to variations in evapotranspiration of ecosystems. Besides, Sr values with a longer return period are more stable than those with a shorter return period when affected by fluctuations in its influencing factors.
Harpold, A. A.; Brooks, P. D.; Biederman, J. A.; Swetnam, T.
Difficulty estimating snowpack variability across complex forested terrain currently hinders the prediction of water resources in the semi-arid Southwestern U.S. Catchment-scale estimates of snowpack variability are necessary for addressing ecological, hydrological, and water resources issues, but are often interpolated from a small number of point-scale observations. In this study, we used LiDAR-derived distributed datasets to investigate how elevation, aspect, topography, and vegetation interact to control catchment-scale snowpack variability. The study area is the Redondo massif in the Valles Caldera National Preserve, NM, a resurgent dome that varies from 2500 to 3430 m and drains from all aspects. Mean LiDAR-derived snow depths from four catchments (2.2 to 3.4 km^2) draining different aspects of the Redondo massif varied by 30%, despite similar mean elevations and mixed conifer forest cover. To better quantify this variability in snow depths we performed a multiple linear regression (MLR) at a 7.3 by 7.3 km study area (5 x 106 snow depth measurements) comprising the four catchments. The MLR showed that elevation explained 45% of the variability in snow depths across the study area, aspect explained 18% (dominated by N-S aspect), and vegetation 2% (canopy density and height). This linear relationship was not transferable to the catchment-scale however, where additional MLR analyses showed the influence of aspect and elevation differed between the catchments. The strong influence of North-South aspect in most catchments indicated that the solar radiation is an important control on snow depth variability. To explore the role of solar radiation, a model was used to generate winter solar forcing index (SFI) values based on the local and remote topography. The SFI was able to explain a large amount of snow depth variability in areas with similar elevation and aspect. Finally, the SFI was modified to include the effects of shading from vegetation (in and out of
We increasingly build and apply hydrologic models that simulate systems beyond the catchment scale. Such models run at regional, national or even continental scales. They therefore offer opportunities for new scientific insights, for example by enabling comparative hydrology or connectivity studies, and for water management, where we might better understand changes to water resources from larger scale activities like agriculture or from hazards such as droughts. However, these models also require us to rethink how we build and evaluate them given that some of the unsolved problems from the catchment scale have not gone away. So what role should such models play in scientific advancement in hydrology? What problems do we still have to resolve before they can fulfill their role? What opportunities for solving these problems are there, but have not yet been utilized? I will provide some thoughts on these issues in the context of the IAHS Panta Rhei initiative and the scientific challenges it has set out for hydrology (Montanari et al., 2013, Hydrological Sciences Journal; McMillan et al., 2016, Hydrological Sciences Journal).
This chapter provides a brief overview of forest hydrology modelling approaches for answering important global research and management questions. Many hundreds of hydrological models have been applied globally across multiple decades to represent and predict forest hydrological p...
Huang, Yumei; Quinn, Paul; Liang, Qiuhua; Adams, Russell
When modelling the flow pathways for nutrient transport, the lack of good data and limitation of data resolution become the key cause of low quality output in various hydrologic models. The scale of catchment being studied would present the main issues of the sensitivity and uncertainty expected on the hydrologic modelling. Equally, the time step chosen is also important to nutrient dynamics. This study aims to evaluate the benefits of using both monthly and daily data in hydrologic models, and to address the issues of catchment scale when using the two hydrologic models, the Soil and Water Assessment Tool (SWAT), and Catchment Runoff Attenuation Flux Tool (CRAFT), by comparing the difference between SWAT and CRAFT in flow pathways and sediment transport. The models are different in terms of complexity, therefore the poster will discuss the strengths and weakness of the models. Also we can show the problems of calibration and how the models can be used to support catchment modelling.
Lutz, S. R.; van Meerveld, H. J.; Waterloo, M. J.; Broers, H. P.; van Breukelen, B. M.
Concentration measurements are indispensable for the assessment of subsurface and surface water pollution by agrochemicals such as pesticides. However, monitoring data is often ambiguous and easily misinterpreted as a decrease in concentration could be caused by transformation, dilution or changes in the application of the pesticide. In this context, compound specific isotope analysis (CSIA) has recently emerged as a complementary monitoring technique. It is based on the measurement of the isotopic composition (e.g. δ13C and δ2H) of the contaminant. Since transformation processes are likely accompanied by isotope fractionation, thus a change in this composition, CSIA offers the opportunity to gain additional knowledge about transport and degradation processes as well as to track pollutants back to their sources. Isotopic techniques have not yet been applied in a comprehensive way in the analysis of catchment-wide organic pollution. We therefore incorporated fractionation processes associated with the fate of pesticides into the numerical flow and solute transport model HydroGeoSphere in order to assess the feasibility of CSIA within the context of catchment monitoring. The model was set up for a hypothetical hillslope transect which drains into a river. Reactive solute transport was driven by two pesticides applications within one year and actual data for rainfall and potential evapotranspiration from a meteorological station in the Netherlands. Degradation of the pesticide was assumed to take place at a higher rate under the prevailing oxic conditions in the topsoil than in deeper, anoxic subsurface layers. In terms of CSIA, these two degradation pathways were associated with different strengths of isotope fractionation for both hydrogen and carbon atoms. By simulating changes in δ13C and δ2H, the share of the oxic and the anoxic reaction on the overall degradation could be assessed. Model results suggest that CSIA is suitable for assessing degradation of
Hoogewoud, J. C.; de Lange, W. J.; Veldhuizen, A.; Prinsen, G.
Netherlands Hydrological Modeling Instrument A decision support system for water basin management. J.C. Hoogewoud , W.J. de Lange ,A. Veldhuizen , G. Prinsen , The Netherlands Hydrological modeling Instrument (NHI) is the center point of a framework of models, to coherently model the hydrological system and the multitude of functions it supports. Dutch hydrological institutes Deltares, Alterra, Netherlands Environmental Assessment Agency, RWS Waterdienst, STOWA and Vewin are cooperating in enhancing the NHI for adequate decision support. The instrument is used by three different ministries involved in national water policy matters, for instance the WFD, drought management, manure policy and climate change issues. The basis of the modeling instrument is a state-of-the-art on-line coupling of the groundwater system (MODFLOW), the unsaturated zone (metaSWAP) and the surface water system (MOZART-DM). It brings together hydro(geo)logical processes from the column to the basin scale, ranging from 250x250m plots to the river Rhine and includes salt water flow. The NHI is validated with an eight year run (1998-2006) with dry and wet periods. For this run different parts of the hydrology have been compared with measurements. For instance, water demands in dry periods (e.g. for irrigation), discharges at outlets, groundwater levels and evaporation. A validation alone is not enough to get support from stakeholders. Involvement from stakeholders in the modeling process is needed. There fore to gain sufficient support and trust in the instrument on different (policy) levels a couple of actions have been taken: 1. a transparent evaluation of modeling-results has been set up 2. an extensive program is running to cooperate with regional waterboards and suppliers of drinking water in improving the NHI 3. sharing (hydrological) data via newly setup Modeling Database for local and national models 4. Enhancing the NHI with "local" information. The NHI is and has been used for many
Anghileri, D.; Kaelin, A.; Peleg, N.; Fatichi, S.; Molnar, P.; Roques, C.; Longuevergne, L.; Burlando, P.
Hydrological modeling in poorly gauged basins can benefit from the use of remote sensing datasets although there are challenges associated with the mismatch in spatial and temporal scales between catchment scale hydrological models and remote sensing products. We model the hydrological processes and long-term water budget of the Lake Turkana catchment, a transboundary basin between Kenya and Ethiopia, by integrating several remote sensing products into a spatially distributed and physically explicit model, Topkapi-ETH. Lake Turkana is the world largest desert lake draining a catchment of 145'500 km2. It has three main contributing rivers: the Omo river, which contributes most of the annual lake inflow, the Turkwel river, and the Kerio rivers, which contribute the remaining part. The lake levels have shown great variations in the last decades due to long-term climate fluctuations and the regulation of three reservoirs, Gibe I, II, and III, which significantly alter the hydrological seasonality. Another large reservoir is planned and may be built in the next decade, generating concerns about the fate of Lake Turkana in the long run because of this additional anthropogenic pressure and increasing evaporation driven by climate change. We consider different remote sensing datasets, i.e., TRMM-V7 for precipitation, MERRA-2 for temperature, as inputs to the spatially distributed hydrological model. We validate the simulation results with other remote sensing datasets, i.e., GRACE for total water storage anomalies, GLDAS-NOAH for soil moisture, ERA-Interim/Land for surface runoff, and TOPEX/Poseidon for satellite altimetry data. Results highlight how different remote sensing products can be integrated into a hydrological modeling framework accounting for their relative uncertainties. We also carried out simulations with the artificial reservoirs planned in the north part of the catchment and without any reservoirs, to assess their impacts on the catchment hydrological
Fan, Linfeng; Lehmann, Peter; Or, Dani
Spatial variations in soil properties affect key hydrological processes, yet their role in soil mechanical response to hydro-mechanical loading is rarely considered. This study aims to fill this gap by systematically quantifying effects of spatial variations in soil type and initial water content on rapid rainfall-induced shallow landslide predictions at the hillslope- and catchment-scales. We employed a physically-based landslide triggering model that considers mechanical interactions among soil columns governed by strength thresholds. At the hillslope scale, we found that the emergence of weak regions induced by spatial variations of soil type and initial water content resulted in early triggering of landslides with smaller volumes of released mass relative to a homogeneous slope. At the catchment scale, initial water content was linked to a topographic wetness index, whereas soil type varied deterministically with soil depth considering spatially correlated stochastic components. Results indicate that a strong spatial organization of initial water content delays landslide triggering, whereas spatially linked soil type with soil depth promoted landslide initiation. Increasing the standard deviation and correlation length of the stochastic component of soil type increases landslide volume and hastens onset of landslides. The study illustrates that for similar external boundary conditions and mean soil properties, landslide characteristics vary significantly with soil variability, hence it must be considered for improved landslide model predictions.
Peña, Luis E.; Barrios, Miguel; Francés, Félix
Changes in land use within a catchment are among the causes of non-stationarity in the flood regime, as they modify the upper soil physical structure and its runoff production capacity. This paper analyzes the relation between the variation of the upper soil hydraulic properties due to changes in land use and its effect on the magnitude of peak flows: (1) incorporating fractal scaling properties to relate the effect of the static storage capacity (the sum of capillary water storage capacity in the root zone, canopy interception and surface puddles) and the upper soil vertical saturated hydraulic conductivity on the flood regime; (2) describing the effect of the spatial organization of the upper soil hydraulic properties at catchment scale; (3) examining the scale properties in the parameters of the Generalized Extreme Value (GEV) probability distribution function, in relation to the upper soil hydraulic properties. This study considered the historical changes of land use in the Combeima River catchment in South America, between 1991 and 2007, using distributed hydrological modeling of daily discharges to describe the hydrological response. Through simulation of land cover scenarios, it was demonstrated that it is possible to quantify the magnitude of peak flows in scenarios of land cover changes through its Wide-Sense Simple Scaling with the upper soil hydraulic properties.
Booij, Martijn J.; Oldhoff, Ruben J. J.; Rustanto, Andry
In order to accurately model the hydrological processes in a catchment, information on the soil hydraulic properties is of great importance. These data can be obtained by conducting field work, which is costly and time consuming, or by using pedotransfer functions (PTFs). A PTF is an empirical relationship between easily obtainable soil characteristics and a soil hydraulic parameter. In this study, PTFs for the saturated hydraulic conductivity (Ks) and the available water content (AWC) are investigated. PTFs are area-specific, since for instance tropical soils often have a different composition and hydraulic behaviour compared to temperate soils. Application of temperate soil PTFs on tropical soils might result in poor performance, which is a problem as few tropical soil PTFs are available. The objective of this study is to determine whether Ks and AWC can be accurately approximated using PTFs, by analysing their performance at both the local scale and the catchment scale. Four published PTFs for Ks and AWC are validated on a data set of 91 soil samples collected in the Upper Bengawan Solo catchment on Java, Indonesia. The AWC is predicted very poorly, with Nash-Sutcliffe Efficiency (NSE) values below zero for all selected PTFs. For Ks PTFs better results were found. The Wösten and Rosetta-3 PTFs predict the Ks moderately accurate, with NSE values of 0.28 and 0.39, respectively. New PTFs for both AWC and Ks were developed using multiple linear regression and NSE values of 0.37 (AWC) and 0.55 (Ks) were obtained. Although these values are not very high, they are significantly higher than for the published PTFs. The hydrological SWAT model was set up for the Keduang, a sub-catchment of the Upper Bengawan Solo River, to simulate monthly catchment streamflow. Eleven cases were defined to validate the PTFs at the catchment scale. For the Ks-PTF cases NSE values of around 0.84 were obtained for the validation period. The use of AWC PTFs resulted in slightly lower NSE
Bouchoms, Samuel; Van Oost, Kristof; Vanacker, Veerle
Over the past 20 years, there has been increasing evidence of the strong impact of human activities on the landscape, specifically on soil erosion due to the removal of natural vegetation cover for agricultural and urban purposes. The results question the widespread hypothesis of a steady state landscape since it appears that the balance between soil production and erosion may be broken altering the interactions between chemical, physical and biological processes in both soil and landscape system. Yet, the relationship between this accelerated erosion and the carbon dynamics at the landscape scale remains an important area of investigation. Recent attempts to combine geomorphic models, soil redistribution and carbon dynamic has proved themselves valuable in term of supporting the importance of lateral fluxes as a crucial control of carbon dynamic at the landscape scale. We use the SPEROS LT model, a modified version of SPEROS-C which includes dynamic land use and soil physical properties, to assess the impact of historical land use conversion on sediment and carbon fluxes in the Dijle catchment. This particular location has experienced a significant human impact since the Roman period, undergoing heavy deforestation and expansion of agricultural lands followed by a period of abandonment. The last 400 to 500 years saw a dramatic increase in the intensity of land use conversion associated to population growth leading to forest cleaning and urbanization. Our main objective is to validate the combined geomorphic and soil carbon turnover process descriptions of the model. Historical land use proportions are based on existing literature estimations and spatial assignation of the land conversion relies on simple allocation rules based on criteria such as slope or soil texture. Land use scenarios are constructed for the last 2000 years. We confront the model results with observations and perform a sensitivity analysis. The results indicate that the general trends in
Ferrant, Sylvain; Kerr, Yann; Al-Bitar, Ahmad; Le Page, Michel; Selles, Adrien; Mermoz, Stephane; Bouvet, Alexandre; Marechal, Jean-Christophe; Tomer, Sat; Sekhar, Muddu; Dedieu, Gerard; Le Toan, Thuy; Bustillo, Vincent
In the context of global changes and population growth, agricultural activities are a growing factor influencing water resources availability in term of quantity and quality. Water management strategies have to be analyzed at a regional catchment scales. Yet, agricultural practices, crop water and nutrient consumption that drive the main water and nutrient fluxes at the catchment scale have to be monitored at a high spatial (crop extension) and temporal resolution (crop growth period). This proceeding describes some advances in the framework of a co-funded ESA Living Planet Fellowship project, called ―agro-hydrology from space‖, which aims at demonstrating the improvement brought by synergetic observations of Sentinel-1 (S1) and Sentinel-2 (S2) satellite mission in agro- hydrological studies. Geo-information time-series of vegetation and water index with multi-spectral optical detection S2 together with surface roughness time series with C-band radar detection S1 are used to re-set soil water holding capacity parameters (depth, porosity) and agricultural practices (sowing date, irrigated area extent) of a crop model coupled with a hydrological model in two contrasted water management issues: stream water nitrate pollution in Gascogne region in south-west of France and groundwater depletion and shortages for irrigation in Deccan Plateau, in south-India.
Wheater, H. S.; Jackson, B.; Bulygina, N.; Ballard, C.; McIntyre, N.; Marshall, M.; Frogbrook, Z.; Solloway, I.; Reynolds, B.
Recent UK floods have focused attention on the effects of agricultural intensification on flood risk. However, quantification of these effects raises important methodological issues. Catchment-scale data have proved inadequate to support analysis of impacts of land management change, due to climate variability, uncertainty in input and output data, spatial heterogeneity in land use and lack of data to quantify historical changes in management practices. Manipulation experiments to quantify the impacts of land management change have necessarily been limited and small scale, and in the UK mainly focused on the lowlands and arable agriculture. There is a need to develop methods to extrapolate from small scale observations to predict catchment-scale response, and to quantify impacts for upland areas. With assistance from a cooperative of Welsh farmers, a multi-scale experimental programme has been established at Pontbren, in mid-Wales, an area of intensive sheep production. The data have been used to support development of a multi-scale modelling methodology to assess impacts of agricultural intensification and the potential for mitigation of flood risk through land use management. Data are available from replicated experimental plots under different land management treatments, from instrumented field and hillslope sites, including tree shelter belts, and from first and second order catchments. Measurements include climate variables, soil water states and hydraulic properties at multiple depths and locations, tree interception, overland flow and drainflow, groundwater levels, and streamflow from multiple locations. Fine resolution physics-based models have been developed to represent soil and runoff processes, conditioned using experimental data. The detailed models are used to calibrate simpler 'meta- models' to represent individual hydrological elements, which are then combined in a semi-distributed catchment-scale model. The methodology is illustrated using field
Hellwig, Jost; Stahl, Kerstin
Gridded meteorological datasets provide the basis to study drought at a range of scales, including catchment scale drought studies in hydrology. They are readily available to study past weather conditions and often serve real time monitoring as well. As these datasets differ in spatial/temporal coverage and spatial/temporal resolution, for most studies there is a tradeoff between these features. Our investigation examines whether biases occur when studying drought on catchment scale with low resolution input data. For that, a comparison among the datasets HYRAS (covering Central Europe, 1x1 km grid, daily data, 1951 - 2005), E-OBS (Europe, 0.25° grid, daily data, 1950-2015) and GPCC (whole world, 0.5° grid, monthly data, 1901 - 2013) is carried out. Generally, biases in precipitation increase with decreasing resolution. Most important variations are found during summer. In low mountain range of Central Europe the datasets of sparse resolution (E-OBS, GPCC) overestimate dry days and underestimate total precipitation since they are not able to describe high spatial variability. However, relative measures like the correlation coefficient reveal good consistencies of dry and wet periods, both for absolute precipitation values and standardized indices like the Standardized Precipitation Index (SPI) or Standardized Precipitation Evaporation Index (SPEI). Particularly the most severe droughts derived from the different datasets match very well. These results indicate that absolute values of sparse resolution datasets applied to catchment scale might be critical to use for an assessment of the hydrological drought at catchment scale, whereas relative measures for determining periods of drought are more trustworthy. Therefore, studies on drought, that downscale meteorological data, should carefully consider their data needs and focus on relative measures for dry periods if sufficient for the task.
von Ruette, J.; Lehmann, P.; Or, D.
The occurrence of shallow landslides is often associated with intense and prolonged rainfall events, where infiltrating water reduces soil strength and may lead to abrupt mass release. Despite general understanding of the role of rainfall water in slope stability, the prediction of rainfall-induced landslides remains a challenge due to natural heterogeneity that affect hydrologic loading patterns and the largely unobservable internal progressive failures. An often overlooked and potentially important factor is the role of rainfall variability in space and time on landslide triggering that is often obscured by coarse information (e.g., hourly radar data at spatial resolution of a few kilometers). To quantify potential effects of rainfall variability on failure dynamics, spatial patterns, landslide numbers and volumes, we employed a physically based "Catchment-scale Hydromechanical Landslide Triggering" (CHLT) model for a study area where a summer storm in 2002 triggered 51 shallow landslides. In numerical experiments based on the CHLT model, we applied the measured rainfall amount of 53 mm in different artificial spatiotemporal rainfall patterns, resulting in between 30 and 100 landslides and total released soil volumes between 3000 and 60,000 m3 for the various scenarios. Results indicate that low intensity rainfall below soil's infiltration capacity resulted in the largest mechanical perturbation. This study illustrates how small-scale rainfall variability that is often overlooked by present operational rainfall data may play a key role in shaping landslide patterns.
Wilby, Robert; Greenfield, Brian; Glenny, Cathy
A coupled atmospheric-hydrological model is presented. Sequences of daily rainfall occurrence for the 20 year period 1971-1990 at sites in the British Isles are related to the Lamb's Weather Types (LWT) by using conditional probabilities. Time series of circulation patterns and hence rainfall were then generated using a Markov representation of matrices of transition probabilities between weather types. The resultant precipitation data were used as input to a semidistributed catchment model to simulate daily flows. The combined model successfully reproduced aspects of the daily weather, precipitation and flow regimes. A range of synoptic scenarios were further investigated with particular reference to low flows in the River Coln, UK. The modelling approach represents a means of translating general circulation model (GCM) climate change predictions at the macro-scale into hydrological concerns at the catchment scale.
Stormwater runoff from extensive impervious surfaces in urban and suburban areas has led to human safety risks and stream ecosystem impairment, triggering an interest in catchment-scale retrofit stormwater management. Such stormwater management is of multidisciplinary relevance, ...
Guse, Björn; Kail, Jochem; Radinger, Johannes; Schröder, Maria; Kiesel, Jens; Hering, Daniel; Wolter, Christian; Fohrer, Nicola
Climate and land use changes affect the hydro- and biosphere at different spatial scales. These changes alter hydrological processes at the catchment scale, which impact hydrodynamics and habitat conditions for biota at the river reach scale. In order to investigate the impact of large-scale changes on biota, a cascade of models at different scales is required. Using scenario simulations, the impact of climate and land use change can be compared along the model cascade. Such a cascade of consecutively coupled models was applied in this study. Discharge and water quality are predicted with a hydrological model at the catchment scale. The hydraulic flow conditions are predicted by hydrodynamic models. The habitat suitability under these hydraulic and water quality conditions is assessed based on habitat models for fish and macroinvertebrates. This modelling cascade was applied to predict and compare the impacts of climate- and land use changes at different scales to finally assess their effects on fish and macroinvertebrates. Model simulations revealed that magnitude and direction of change differed along the modelling cascade. Whilst the hydrological model predicted a relevant decrease of discharge due to climate change, the hydraulic conditions changed less. Generally, the habitat suitability for fish decreased but this was strongly species-specific and suitability even increased for some species. In contrast to climate change, the effect of land use change on discharge was negligible. However, land use change had a stronger impact on the modelled nitrate concentrations affecting the abundances of macroinvertebrates. The scenario simulations for the two organism groups illustrated that direction and intensity of changes in habitat suitability are highly species-dependent. Thus, a joined model analysis of different organism groups combined with the results of hydrological and hydrodynamic models is recommended to assess the impact of climate and land use changes on
Golden, Heather E.; Hoghooghi, Nahal
Urbanizing environments alter the hydrological cycle by redirecting stream networks for stormwater and wastewater transmission and increasing impermeable surfaces. These changes thereby accelerate the runoff of water and its constituents following precipitation events, alter evapotranspiration processes, and indirectly modify surface precipitation patterns. Green infrastructure, or low-impact development (LID), can be used as a standalone practice or in concert with gray infrastructure (traditional stormwater management approaches) for cost-efficient, decentralized stormwater management. The growth in LID over the past several decades has resulted in a concomitant increase in research evaluating LID efficiency and effectiveness, but mostly at localized scales. There is a clear research need to quantify how LID practices affect water quantity (i.e., runoff and discharge) and quality at the scale of catchments. In this overview, we present the state of the science of LID research at the local scale, considerations for scaling this research to catchments, recent advances and findings in scaling the effects of LID practices on water quality and quantity at catchment scales, and the use of models as novel tools for these scaling efforts. PMID:29682288
Golden, Heather E; Hoghooghi, Nahal
Urbanizing environments alter the hydrological cycle by redirecting stream networks for stormwater and wastewater transmission and increasing impermeable surfaces. These changes thereby accelerate the runoff of water and its constituents following precipitation events, alter evapotranspiration processes, and indirectly modify surface precipitation patterns. Green infrastructure, or low-impact development (LID), can be used as a standalone practice or in concert with gray infrastructure (traditional stormwater management approaches) for cost-efficient, decentralized stormwater management. The growth in LID over the past several decades has resulted in a concomitant increase in research evaluating LID efficiency and effectiveness, but mostly at localized scales. There is a clear research need to quantify how LID practices affect water quantity (i.e., runoff and discharge) and quality at the scale of catchments. In this overview, we present the state of the science of LID research at the local scale, considerations for scaling this research to catchments, recent advances and findings in scaling the effects of LID practices on water quality and quantity at catchment scales, and the use of models as novel tools for these scaling efforts.
Bhatt, Divya; Jain, Ashu
developed in this study. The ANN models developed consistently outperformed the conceptual model developed in this study. The results obtained in this study indicate that the ANNs can be extremely useful tools for modeling the complex rainfall-runoff process in real catchments. The ANNs should be adopted in real catchments for hydrological modeling and forecasting. It is hoped that more research will be carried out to compare the performance of ANN model with the conceptual models actually in use at catchment scales. It is hoped that such efforts may go a long way in making the ANNs more acceptable by the policy makers, water resources decision makers, and traditional hydrologists.
H.E. Golden; G.R. Evenson; S. Tian; Devendra Amatya; Ge Sun
Characterizing and quantifying interactions among components of the forest hydrological cycle is complex and usually requires a combination of field monitoring and modelling approaches (Weiler and McDonnell, 2004; National Research Council, 2008). Models are important tools for testing hypotheses, understanding hydrological processes and synthesizing experimental data...
Guardiola-Claramonte, M.; Troch, P.
Montane mainland South East Asia comprises areas of great biological and cultural diversity. Over the last decades the region has overcome an important conversion from traditional agriculture to cash crop agriculture driven by regional and global markets. Our study aims at understanding the hydrological implications of these land use changes at the catchment scale. In 2004, networks of hydro-meteorological stations observing water and energy fluxes were installed in two 70 km2 catchments in Northern Thailand (Chiang Mai Province) and Southern China (Yunnan Province). In addition, a detailed soil surveying campaign was done at the moment of instrument installation. Land use is monitored periodically using satellite data. The Thai catchment is switching from small agricultural fields to large extensions of cash crops. The Chinese catchment is replacing the traditional forest for rubber plantations. A first comparative study based on catchments' geomorphologic characteristics, field observations and rainfall-runoff response revealed the dominant hydrologic processes in the catchments. Land use information is then translated into three different Hydrologic Response Units (HRU): rice paddies, pervious and impervious surfaces. The pervious HRU include different land uses such as different stages of forest development, rubber plantations, and agricultural fields; the impervious ones are urban areas, roads and outcrops. For each HRU a water and energy balance model is developed incorporating field observed hydrologic processes, measured field parameters, and literature-based vegetation and soil parameters to better describe the root zone, surface and subsurface flow characteristics without the need of further calibration. The HRU water and energy balance models are applied to single hillslopes and their integrated hydrologic response are compared for different land covers. Finally, the response of individual hillslopes is routed through the channel network to represent
Ajami, H.; Sharma, A.; Lakshmi, V.
Application of semi-distributed hydrologic modeling frameworks is a viable alternative to fully distributed hyper-resolution hydrologic models due to computational efficiency and resolving fine-scale spatial structure of hydrologic fluxes and states. However, fidelity of semi-distributed model simulations is impacted by (1) formulation of hydrologic response units (HRUs), and (2) aggregation of catchment properties for formulating simulation elements. Here, we evaluate the performance of a recently developed Soil Moisture and Runoff simulation Toolkit (SMART) for large catchment scale simulations. In SMART, topologically connected HRUs are delineated using thresholds obtained from topographic and geomorphic analysis of a catchment, and simulation elements are equivalent cross sections (ECS) representative of a hillslope in first order sub-basins. Earlier investigations have shown that formulation of ECSs at the scale of a first order sub-basin reduces computational time significantly without compromising simulation accuracy. However, the implementation of this approach has not been fully explored for catchment scale simulations. To assess SMART performance, we set-up the model over the Little Washita watershed in Oklahoma. Model evaluations using in-situ soil moisture observations show satisfactory model performance. In addition, we evaluated the performance of a number of soil moisture disaggregation schemes recently developed to provide spatially explicit soil moisture outputs at fine scale resolution. Our results illustrate that the statistical disaggregation scheme performs significantly better than the methods based on topographic data. Future work is focused on assessing the performance of SMART using remotely sensed soil moisture observations using spatially based model evaluation metrics.
Viaud, Valérie; Merot, Philippe; Baudry, Jacques
Non-point-source pollution of surface and groundwater is a prominent environmental issue in rural catchments, with major consequences on water supply and aquatic ecosystem quality. Among surface-water protection measures, environmental or landscape management policies support the implementation and the management of buffer zones. Although a great number of studies have focused on buffer zones, quantification of the buffer effect is still a recurring question. The purpose of this article is a critical review of the assessment of buffer-zone functioning. Our objective is to provide land planners and managers with a set of variables to assess the limits and possibilities for quantifying buffer impact at the catchment scale. We first consider the scale of the local landscape feature. The most commonly used empirical method for assessing buffers is to calculate water/nutrient budgets from inflow-outflow monitoring at the level of landscape structures. We show that several other parameters apart from mean depletion of flux can be used to describe buffer functions. Such parameters include variability, with major implication for water management. We develop a theoretical framework to clarify the assessment of the buffer effect and propose a systematic analysis taking account of temporal variability. Second, we review the current assessment of buffer effects at the catchment scale according to the theoretical framework established at the local scale. Finally, we stress the limits of direct empirical assessment at the catchment scale and, in particular, we emphasize the hierarchy in hydrological processes involved at the catchment scale: The landscape feature function is constrained by other factors (climate and geology) that are of importance at a broader spatial and temporal scale.
Rogger, M.; Agnoletti, M.; Alaoui, A.; Bathurst, J. C.; Bodner, G.; Borga, M.; Chaplot, V.; Gallart, F.; Glatzel, G.; Hall, J.; Holden, J.; Holko, L.; Horn, R.; Kiss, A.; Kohnová, S.; Leitinger, G.; Lennartz, B.; Parajka, J.; Perdigão, R.; Peth, S.; Plavcová, L.; Quinton, J. N.; Robinson, M.; Salinas, J. L.; Santoro, A.; Szolgay, J.; Tron, S.; van den Akker, J. J. H.; Viglione, A.; Blöschl, G.
Research gaps in understanding flood changes at the catchment scale caused by changes in forest management, agricultural practices, artificial drainage, and terracing are identified. Potential strategies in addressing these gaps are proposed, such as complex systems approaches to link processes across time scales, long-term experiments on physical-chemical-biological process interactions, and a focus on connectivity and patterns across spatial scales. It is suggested that these strategies will stimulate new research that coherently addresses the issues across hydrology, soil and agricultural sciences, forest engineering, forest ecology, and geomorphology.
Agnoletti, M.; Alaoui, A.; Bathurst, J. C.; Bodner, G.; Borga, M.; Chaplot, V.; Gallart, F.; Glatzel, G.; Hall, J.; Holden, J.; Holko, L.; Horn, R.; Kiss, A.; Kohnová, S.; Leitinger, G.; Lennartz, B.; Parajka, J.; Perdigão, R.; Peth, S.; Plavcová, L.; Quinton, J. N.; Robinson, M.; Salinas, J. L.; Santoro, A.; Szolgay, J.; Tron, S.; van den Akker, J. J. H.; Viglione, A.; Blöschl, G.
Abstract Research gaps in understanding flood changes at the catchment scale caused by changes in forest management, agricultural practices, artificial drainage, and terracing are identified. Potential strategies in addressing these gaps are proposed, such as complex systems approaches to link processes across time scales, long‐term experiments on physical‐chemical‐biological process interactions, and a focus on connectivity and patterns across spatial scales. It is suggested that these strategies will stimulate new research that coherently addresses the issues across hydrology, soil and agricultural sciences, forest engineering, forest ecology, and geomorphology. PMID:28919651
Soltani, S. S.; Cvetkovic, V.; Destouni, G.
The distribution of catchment-scale water travel times is strongly influenced by morphological dispersion and is partitioned between hillslope and larger, regional scales. We explore whether hillslope travel times are predictable using a simple semi-analytical "kinematic pathway approach" (KPA) that accounts for dispersion on two levels of morphological and macro-dispersion. The study gives new insights to shallow (hillslope) and deep (regional) groundwater travel times by comparing numerical simulations of travel time distributions, referred to as "dynamic model", with corresponding KPA computations for three different real catchment case studies in Sweden. KPA uses basic structural and hydrological data to compute transient water travel time (forward mode) and age (backward mode) distributions at the catchment outlet. Longitudinal and morphological dispersion components are reflected in KPA computations by assuming an effective Peclet number and topographically driven pathway length distributions, respectively. Numerical simulations of advective travel times are obtained by means of particle tracking using the fully-integrated flow model MIKE SHE. The comparison of computed cumulative distribution functions of travel times shows significant influence of morphological dispersion and groundwater recharge rate on the compatibility of the "kinematic pathway" and "dynamic" models. Zones of high recharge rate in "dynamic" models are associated with topographically driven groundwater flow paths to adjacent discharge zones, e.g. rivers and lakes, through relatively shallow pathway compartments. These zones exhibit more compatible behavior between "dynamic" and "kinematic pathway" models than the zones of low recharge rate. Interestingly, the travel time distributions of hillslope compartments remain almost unchanged with increasing recharge rates in the "dynamic" models. This robust "dynamic" model behavior suggests that flow path lengths and travel times in shallow
Making hydrological models more realistic requires both better physical understanding of their underlying processes, and more rigorous tests of the hypotheses that they embody. In the current model-testing paradigm, multiple interdependent hypotheses are combined to generate model predictions, which are then compared with observational time series that reflect multiple interdependent forcings. This approach is problematic in several respects. If the modeled time series does not match the observations, which of the model's many embedded hypotheses is falsified? Conversely, even if the model matches the data, how many of its underlying hypotheses could still be wrong, perhaps in offsetting ways? The essence of the problem is that if model simulations depend on many interacting hypotheses, and if observational data reflect many different environmental forcings, then comparisons of simulations against data will rarely be diagnostic tests of specific hypotheses in the model. For this reason, I have long argued for a different approach to hypothesis testing, in which key signatures of behavior are extracted from both model and data before they are compared (Kirchner et al., 1996; Kirchner, 2006). This approach allows one to isolate the model/data comparison as much as possible from potentially confounding factors in both the model and the data. One key signature of catchment behavior, which has challenged many hydrologic models, is the contrast between the relatively short timescales of hydrologic response to precipitation events, reflecting the celerity of hydraulic potentials, and the much longer timescales of water transport through the landscape, reflecting the velocity of water movement as tracked by passive tracers (Kirchner, 2003). Here I show how both the velocity and celerity of transport at the catchment scale can be quantified from hydrologic and isotopic time series. The conventional formula used for hydrograph separation can be converted into an equivalent
Troch, P. A. A.; Dwivedi, R.; Liu, T.; Meira, A.; Roy, T.; Valdés-Pineda, R.; Durcik, M.; Arciniega, S.; Brena-Naranjo, J. A.
Precipitation undergoes a two-step partitioning when it falls on the land surface. At the land surface and in the shallow subsurface, rainfall or snowmelt can either runoff as infiltration/saturation excess or quick subsurface flow. The rest will be stored temporarily in the root zone. From the root zone, water can leave the catchment as evapotranspiration or percolate further and recharge deep storage (e.g. fractured bedrock aquifer). Quantifying the average amount of water that recharges deep storage and sustains low flows is extremely challenging, as we lack reliable methods to quantify this flux at the catchment scale. It was recently shown, however, that for semi-arid catchments in Mexico, an index of vegetation water use efficiency, i.e. the Horton index (HI), could predict deep storage dynamics. Here we test this finding using 247 MOPEX catchments across the conterminous US, including energy-limited catchments. Our results show that the observed HI is indeed a reliable predictor of deep storage dynamics in space and time. We further investigate whether the HI can also predict average recharge rates across the conterminous US. We find that the HI can reliably predict the average recharge rate, estimated from the 50th percentile flow of the flow duration curve. Our results compare favorably with estimates of average recharge rates from the US Geological Survey. Previous research has shown that HI can be reliably estimated based on aridity index, mean slope and mean elevation of a catchment (Voepel et al., 2011). We recalibrated Voepel's model and used it to predict the HI for our 247 catchments. We then used these predicted values of the HI to estimate average recharge rates for our catchments, and compared them with those estimated from observed HI. We find that the accuracies of our predictions based on observed and predicted HI are similar. This provides an estimation method of catchment-scale average recharge rates based on easily derived catchment
Alex Abdelnour; Marc Stieglitz; Feifei Pan; Robert McKane
Forest harvest effects on streamflow generation have been well described experimentally, but a clear understanding of process-level hydrological controls can be difficult to ascertain from data alone. We apply a new model, Visualizing Ecosystems for Land Management Assessments (VELMA), to elucidate how hillslope and catchment-scale processes control stream discharge in...
Thirel, Guillaume; Delaigue, Olivier; Coron, Laurent; Andréassian, Vazken; Brigode, Pierre
Lumped hydrological models are useful and convenient tools for research, engineering and educational purposes. They propose catchment-scale representations of the precipitation-discharge relationship. Thanks to their limited data requirements, they can be easily implemented and run. With such models, it is possible to simulate a number of hydrological key processes over the catchment with limited structural and parametric complexity, typically evapotranspiration, runoff, underground losses, etc. The Hydrology Group at Irstea (Antony) has been developing a suite of rainfall-runoff models over the past 30 years. This resulted in a suite of models running at different time steps (from hourly to annual) applicable for various issues including water balance estimation, forecasting, simulation of impacts and scenario testing. Recently, Irstea has developed an easy-to-use R-package (R Core Team, 2016), called airGR (Coron et al., 2016, 2017), to make these models widely available. Although its initial target public was hydrological modellers, the package is already used for educational purposes. Indeed, simple models allow for rapidly visualising the effects of parameterizations and model components on flows hydrographs. In order to avoid the difficulties that students may have when manipulating R and datasets, we developed (Delaigue and Coron, 2016): - Three simplified functions to prepare data, calibrate a model and run a simulation - Simplified and dynamic plot functions - A shiny (Chang et al., 2016) interface that connects this R-package to a browser-based visualisation tool. On this interface, the students can use different hydrological models (including the possibility to use a snow-accounting model), manually modify their parameters and automatically calibrate their parameters with diverse objective functions. One of the visualisation tabs of the interface includes observed precipitation and temperature, simulated snowpack (if any), observed and simulated
Fatichi, Simone; Ivanov, Valeriy Y.; Caporali, Enrica
A blueprint methodology for studying climate change impacts, as inferred from climate models, on eco-hydrological dynamics at the plot and small catchment scale is presented. Input hydro-meteorological variables for hydrological and eco-hydrological models for present and future climates are reproduced using a stochastic downscaling technique and a weather generator, "AWE-GEN". The generated time series of meteorological variables for the present climate and an ensemble of possible future climates serve as input to a newly developed physically-based eco-hydrological model "Tethys-Chloris". An application of the proposed methodology is realized reproducing the current (1961-2000) and multiple future (2081-2100) climates for the location of Tucson (Arizona). A general reduction of precipitation and a significant increase of air temperature are inferred. The eco-hydrological model is successively applied to detect changes in water recharge and vegetation dynamics for a desert shrub ecosystem, typical of the semi-arid climate of south Arizona. Results for the future climate account for uncertainties in the downscaling and are produced in terms of probability density functions. A comparison of control and future scenarios is discussed in terms of changes in the hydrological balance components, energy fluxes, and indices of vegetation productivity. An appreciable effect of climate change can be observed in metrics of vegetation performance. The negative impact on vegetation due to amplification of water stress in a warmer and dryer climate is offset by a positive effect of carbon dioxide augment. This implies a positive shift in plant capabilities to exploit water. Consequently, the plant water use efficiency and rain use efficiency are expected to increase. Interesting differences in the long-term vegetation productivity are also observed for the ensemble of future climates. The reduction of precipitation and the substantial maintenance of vegetation cover ultimately
Ye, Sheng; Li, Hongyi; Huang, Maoyi
Subsurface stormflow is an important component of the rainfall–runoff response, especially in steep terrain. Its contribution to total runoff is, however, poorly represented in the current generation of land surface models. The lack of physical basis of these common parameterizations precludes a priori estimation of the stormflow (i.e. without calibration), which is a major drawback for prediction in ungauged basins, or for use in global land surface models. This paper is aimed at deriving regionalized parameterizations of the storage–discharge relationship relating to subsurface stormflow from a top–down empirical data analysis of streamflow recession curves extracted from 50 eastern United Statesmore » catchments. Detailed regression analyses were performed between parameters of the empirical storage–discharge relationships and the controlling climate, soil and topographic characteristics. The regression analyses performed on empirical recession curves at catchment scale indicated that the coefficient of the power-law form storage–discharge relationship is closely related to the catchment hydrologic characteristics, which is consistent with the hydraulic theory derived mainly at the hillslope scale. As for the exponent, besides the role of field scale soil hydraulic properties as suggested by hydraulic theory, it is found to be more strongly affected by climate (aridity) at the catchment scale. At a fundamental level these results point to the need for more detailed exploration of the co-dependence of soil, vegetation and topography with climate.« less
Willem J. van Verseveld; Jeffrey J. McDonnell; Kate Lajtha
This paper mechanistically assesses the flushing mechanism of DOC, DON, and DIN at the hillslope and catchment scales during two storm events, in a small catchment (WS10), H.J. Andrews Experimental Forest in the western Cascade Mountains of Oregon. Using a combination of natural tracer and hydrometric data, and end-member mixing analysis, we were able to describe the...
Su, Simon; Cruz-Neira, Carolina; Habib, Emad; Gerndt, Andreas
The Virtual Hydrology Observatory will provide students with the ability to observe the integrated hydrology simulation with an instructional interface by using a desktop based or immersive virtual reality setup. It is the goal of the virtual hydrology observatory application to facilitate the introduction of field experience and observational skills into hydrology courses through innovative virtual techniques that mimic activities during actual field visits. The simulation part of the application is developed from the integrated atmospheric forecast model: Weather Research and Forecasting (WRF), and the hydrology model: Gridded Surface/Subsurface Hydrologic Analysis (GSSHA). Both the output from WRF and GSSHA models are then used to generate the final visualization components of the Virtual Hydrology Observatory. The various visualization data processing techniques provided by VTK are 2D Delaunay triangulation and data optimization. Once all the visualization components are generated, they are integrated into the simulation data using VRFlowVis and VR Juggler software toolkit. VR Juggler is used primarily to provide the Virtual Hydrology Observatory application with fully immersive and real time 3D interaction experience; while VRFlowVis provides the integration framework for the hydrologic simulation data, graphical objects and user interaction. A six-sided CAVETM like system is used to run the Virtual Hydrology Observatory to provide the students with a fully immersive experience.
Kim, Jongho; Ivanov, Valeriy Y.; Katopodes, Nikolaos D.
A novel two-dimensional, physically based model of soil erosion and sediment transport coupled to models of hydrological and overland flow processes has been developed. The Hairsine-Rose formulation of erosion and deposition processes is used to account for size-selective sediment transport and differentiate bed material into original and deposited soil layers. The formulation is integrated within the framework of the hydrologic and hydrodynamic model tRIBS-OFM, Triangulated irregular network-based, Real-time Integrated Basin Simulator-Overland Flow Model. The integrated model explicitly couples the hydrodynamic formulation with the advection-dominated transport equations for sediment of multiple particle sizes. To solve the system of equations including both the Saint-Venant and the Hairsine-Rose equations, the finite volume method is employed based on Roe's approximate Riemann solver on an unstructured grid. The formulation yields space-time dynamics of flow, erosion, and sediment transport at fine scale. The integrated model has been successfully verified with analytical solutions and empirical data for two benchmark cases. Sensitivity tests to grid resolution and the number of used particle sizes have been carried out. The model has been validated at the catchment scale for the Lucky Hills watershed located in southeastern Arizona, USA, using 10 events for which catchment-scale streamflow and sediment yield data were available. Since the model is based on physical laws and explicitly uses multiple types of watershed information, satisfactory results were obtained. The spatial output has been analyzed and the driving role of topography in erosion processes has been discussed. It is expected that the integrated formulation of the model has the promise to reduce uncertainties associated with typical parameterizations of flow and erosion processes. A potential for more credible modeling of earth-surface processes is thus anticipated.
Drew, C. Ashton; Eddy, Michele; Kwak, Thomas J.; Cope, W. Gregory; Augspurger, Tom
The ability to model freshwater stream habitat and species distributions is limited by the spatially sparse flow data available from long-term gauging stations. Flow data beyond the immediate vicinity of gauging stations would enhance our ability to explore and characterize hydrologic habitat suitability. The southeastern USA supports high aquatic biodiversity, but threats, such as landuse alteration, climate change, conflicting water-resource demands, and pollution, have led to the imperilment and legal protection of many species. The ability to distinguish suitable from unsuitable habitat conditions, including hydrologic suitability, is a key criterion for successful conservation and restoration of aquatic species. We used the example of the critically endangered Tar River Spinymussel (Parvaspina steinstansana) and associated species to demonstrate the value of modeled flow data (WaterFALL™) to generate novel insights into population structure and testable hypotheses regarding hydrologic suitability. With ordination models, we: 1) identified all catchments with potentially suitable hydrology, 2) identified 2 distinct hydrologic environments occupied by the Tar River Spinymussel, and 3) estimated greater hydrological habitat niche breadth of assumed surrogate species associates at the catchment scale. Our findings provide the first demonstrated application of complete, continuous, regional modeled hydrologic data to freshwater mussel distribution and management. This research highlights the utility of modeling and data-mining methods to facilitate further exploration and application of such modeled environmental conditions to inform aquatic species management. We conclude that such an approach can support landscape-scale management decisions that require spatial information at fine resolution (e.g., enhanced National Hydrology Dataset catchments) and broad extent (e.g., multiple river basins).
Yilmaz, Koray K.; Vrugt, Jasper A.; Gupta, Hoshin V.; Sorooshian, Soroosh
Hydrologic models use relatively simple mathematical equations to conceptualize and aggregate the complex, spatially distributed, and highly interrelated water, energy, and vegetation processes in a watershed. A consequence of process aggregation is that the model parameters often do not represent directly measurable entities and must, therefore, be estimated using measurements of the system inputs and outputs. During this process, known as model calibration, the parameters are adjusted so that the behavior of the model approximates, as closely and consistently as possible, the observed response of the hydrologic system over some historical period of time. This Chapter reviews the current state-of-the-art of model calibration in watershed hydrology with special emphasis on our own contributions in the last few decades. We discuss the historical background that has led to current perspectives, and review different approaches for manual and automatic single- and multi-objective parameter estimation. In particular, we highlight the recent developments in the calibration of distributed hydrologic models using parameter dimensionality reduction sampling, parameter regularization and parallel computing.
Sillanpää, Nora; Koivusalo, Harri
Despite the crucial role of snow in the hydrological cycle in cold climate conditions, monitoring studies of urban snow quality often lack discussions about the relevance of snow in the catchment-scale runoff management. In this study, measurements of snow quality were conducted at two residential catchments in Espoo, Finland, simultaneously with continuous runoff measurements. The results of the snow quality were used to produce catchment-scale estimates of areal snow mass loads (SML). Based on the results, urbanization reduced areal snow water equivalent but increased pollutant accumulation in snow: SMLs in a medium-density residential catchment were two- to four-fold higher in comparison with a low-density residential catchment. The main sources of pollutants were related to vehicular traffic and road maintenance, but also pet excrement increased concentrations to a high level. Ploughed snow can contain 50% of the areal pollutant mass stored in snow despite its small surface area within a catchment.
This chapter provides a brief overview of forest hydrology modelling approaches for answering important global research and management questions. Many hundreds of hydrological models have been applied globally across multiple decades to represent and predict forest hydrological processes. The focus of this chapter is on process-based models and approaches, specifically 'forest hydrology models'; that is, physically based simulation tools that quantify compartments of the forest hydrological cycle. Physically based models can be considered those that describe the conservation of mass, momentum and/or energy. The purpose of this chapter is to provide a brief overview of forest hydrology modeling approaches for answering important global research and management questions. The focus of this chapter is on process-based models and approaches, specifically “forest hydrology models”, i.e., physically-based simulation tools that quantify compartments of the forest hydrological cycle.
Smith, M. W.; Macklin, M. G.; Thomas, C. J.
Malaria risk is linked inextricably to the hydrological and geomorphological processes that form vector breeding sites. Yet environmental controls of malaria transmission are often represented by temperature and rainfall amounts, ignoring hydrological and geomorphological influences altogether. Continental-scale studies incorporate hydrology implicitly through simple minimum rainfall thresholds, while community-scale coupled hydrological and entomological models do not represent the actual diversity of the mosquito vector breeding sites. The greatest range of malaria transmission responses to environmental factors is observed at the catchment scale where seemingly contradictory associations between rainfall and malaria risk can be explained by hydrological and geomorphological processes that govern surface water body formation and persistence. This paper extends recent efforts to incorporate ecological factors into malaria-risk models, proposing that the same detailed representation be afforded to hydrological and, at longer timescales relevant for predictions of climate change impacts, geomorphological processes. We review existing representations of environmental controls of malaria and identify a range of hydrologically distinct vector breeding sites from existing literature. We illustrate the potential complexity of interactions among hydrology, geomorphology and vector breeding sites by classifying a range of water bodies observed in a catchment in East Africa. Crucially, the mechanisms driving surface water body formation and destruction must be considered explicitly if we are to produce dynamic spatial models of malaria risk at catchment scales.
Fan, Linfeng; Lehmann, Peter; McArdell, Brian; Or, Dani
Debris flows and landslides induced by heavy rainfall represent an ubiquitous and destructive natural hazard in steep mountainous regions. For debris flows initiated by shallow landslides, the prediction of the resulting pathways and associated hazard is often hindered by uncertainty in determining initiation locations, volumes and mechanical state of the mobilized debris (and by model parameterization). We propose a framework for linking a simplified physically-based debris flow runout model with a novel Landslide Hydro-mechanical Triggering (LHT) model to obtain a coupled landslide-debris flow susceptibility and hazard assessment. We first compared the simplified debris flow model of Perla (1980) with a state-of-the art continuum-based model (RAMMS) and with an empirical model of Rickenmann (1999) at the catchment scale. The results indicate that predicted runout distances by the Perla model are in reasonable agreement with inventory measurements and with the other models. Predictions of localized shallow landslides by LHT model provides information on water content of released mass. To incorporate effects of water content and flow viscosity as provided by LHT on debris flow runout, we adapted the Perla model. The proposed integral link between landslide triggering susceptibility quantified by LHT and subsequent debris flow runout hazard calculation using the adapted Perla model provides a spatially and temporally resolved framework for real-time hazard assessment at the catchment scale or along critical infrastructure (roads, railroad lines).
Pattison, Ian; Lane, Stuart; Hardy, Richard; Reaney, Sim
workshop, whereby a map of the catchment was laid out and locations where each scenario could feasibly be implemented were drawn on. This was combined with an analysis of historical maps to identify past land covers and a catchment walkover survey to put modelling work in the real world context. The land management scenarios were tested using hydrological and hydraulic models. Landscape scale changes, such as the effects of compaction and afforestation were tested using a catchment scale hydrological mode, CRUM2D. Channel scale changes, such as re-meandering and floodplain storage were tested using the 1D hydraulic model, iSIS, by altering channel cross sections and creating spills between the channel and floodplain. It is expected that the channel modification and floodplain storage scenarios will have the greatest impact on flooding both at the local and catchment scales. The landscape scale changes are more diffuse and therefore their impact is expected to be less significant. Although, early analysis indicates that the spatial location of changes strongly influences their effect on flooding.
Rinderer, M.; McGlynn, B. L.; van Meerveld, I. H. J.
Groundwater measurements can help us to improve our understanding of runoff generation at the catchment-scale but typically only provide point-scale data. These measurements, therefore, need to be interpolated or upscaled in order to obtain information about catchment scale groundwater dynamics. Our approach used data from 51 spatially distributed groundwater monitoring sites in a Swiss pre-alpine catchment and time series clustering to define six groundwater response clusters. Each of the clusters was characterized by distinctly different site characteristics (i.e., Topographic Wetness Index and curvature), which allowed us to assign all unmonitored locations to one of these clusters. Time series modeling and the definition of response thresholds (i.e., the depth of more transmissive soil layers) allowed us to derive maps of the spatial distribution of active (i.e., responding) locations across the catchment at 15 min time intervals. Connectivity between all active locations and the stream network was determined using a graph theory approach. The extent of the active and connected areas differed during events and suggests that not all active locations directly contributed to streamflow. Gate keeper sites prevented connectivity of upslope locations to the channel network. Streamflow dynamics at the catchment outlet were correlated to catchment average connectivity dynamics. In a sensitivity analysis we tested six different groundwater levels for a site to be considered "active", which showed that the definition of the threshold did not significantly influence the conclusions drawn from our analysis. This study is the first one to derive patterns of groundwater dynamics based on empirical data (rather than interpolation) and provides insight into the spatio-temporal evolution of the active and connected runoff source areas at the catchment-scale that is critical to understanding the dynamics of water quantity and quality in streams.
Pattison, Ian; Lane, Stuart; Hardy, Richard; Reaney, Sim
The recent increase in flood frequency and magnitude has been hypothesised to have been caused by either climate change or land management. Field scale studies have found that changing land management practices does affect local runoff and streamflow, but upscaling these effects to the catchment scale continues to be problematic, both conceptually and more importantly methodologically. The impact on downstream flood risk is highly dependent upon where the changes are in the catchment, indicating that some areas of the catchment are more important in determining downstream flood risk than others. This is a major flaw in the traditional approach to studying the effect of land use on downstream flood risk: catchment scale hydrological models, which treat every cell in the model equally. We are proposing an alternative ideological approach for doing flood management research, which is underpinned by downscaling the downstream effect (problem i.e. flooding) to the upstream causes (contributing sub-catchments). It is hoped that this approach could have several benefits over the traditional upscaling approach. Firstly, it provides an efficient method to prioritise areas for land use management changes to be implemented to reduce downstream flood risk. Secondly, targets for sub-catchment hydrograph change can be determined which will deliver the required downstream effect. Thirdly, it may be possible to detect the effect of land use changes in upstream areas on downstream flood risk, by weighting the areas of most importance in hydrological models. Two methods for doing this downscaling are proposed; 1) data-based statistical analysis; and 2) hydraulic modelling-based downscaling. These will be outlined using the case study of the River Eden, Cumbria, NW England. The data-based methodology uses the timing and magnitude of floods for each sub-catchment. Principal components analysis (PCA) is used to simplify sub-catchment interactions and optimising stepwise regression is
Evans, Cristina M.; Dritschel, David G.; Singer, Michael B.
Soil-moisture patterns in floodplains are highly dynamic, owing to the complex relationships between soil properties, climatic conditions at the surface, and the position of the water table. Given this complexity, along with climate change scenarios in many regions, there is a need for a model to investigate the implications of different conditions on water availability to riparian vegetation. We present a model, HaughFlow, which is able to predict coupled water movement in the vadose and phreatic zones of hydraulically connected floodplains. Model output was calibrated and evaluated at six sites in Australia to identify key patterns in subsurface hydrology. This study identifies the importance of the capillary fringe in vadose zone hydrology due to its water storage capacity and creation of conductive pathways. Following peaks in water table elevation, water can be stored in the capillary fringe for up to months (depending on the soil properties). This water can provide a critical resource for vegetation that is unable to access the water table. When water table peaks coincide with heavy rainfall events, the capillary fringe can support saturation of the entire soil profile. HaughFlow is used to investigate the water availability to riparian vegetation, producing daily output of water content in the soil over decadal time periods within different depth ranges. These outputs can be summarized to support scientific investigations of plant-water relations, as well as in management applications.
Paniconi, Claudio; Putti, Mario
Integrated, process-based numerical models in hydrology are rapidly evolving, spurred by novel theories in mathematical physics, advances in computational methods, insights from laboratory and field experiments, and the need to better understand and predict the potential impacts of population, land use, and climate change on our water resources. At the catchment scale, these simulation models are commonly based on conservation principles for surface and subsurface water flow and solute transport (e.g., the Richards, shallow water, and advection-dispersion equations), and they require robust numerical techniques for their resolution. Traditional (and still open) challenges in developing reliable and efficient models are associated with heterogeneity and variability in parameters and state variables; nonlinearities and scale effects in process dynamics; and complex or poorly known boundary conditions and initial system states. As catchment modeling enters a highly interdisciplinary era, new challenges arise from the need to maintain physical and numerical consistency in the description of multiple processes that interact over a range of scales and across different compartments of an overall system. This paper first gives an historical overview (past 50 years) of some of the key developments in physically based hydrological modeling, emphasizing how the interplay between theory, experiments, and modeling has contributed to advancing the state of the art. The second part of the paper examines some outstanding problems in integrated catchment modeling from the perspective of recent developments in mathematical and computational science.
Peoples, Brandon K.; Midway, Stephen R.; DeWeber, Jefferson T.; Wagner, Tyler
Understanding the drivers of biological invasions is critical for preserving aquatic biodiversity. Stream fishes make excellent model taxa for examining mechanisms driving species introduction success because their distributions are naturally limited by catchment boundaries. In this study, we compared the relative importance of catchment-scale abiotic and biotic predictors of native and nonindigenous minnow (Cyprinidae) richness in 170 catchments throughout the eastern United States. We compared historic and contemporary cyprinid distributional data to determine catchment-wise native/nonindigenous status for 152 species. Catchment-scale model predictor variables described natural (elevation, precipitation, flow accumulation) and anthropogenic (developed land cover, number of dams) abiotic features, as well as native congener richness. Native congener richness may represent either biotic resistance via interspecific competition, or trait preadaptation according to Darwin's naturalisation hypothesis. We used generalised linear mixed models to examine evidence supporting the relative roles of abiotic and biotic predictors of cyprinid introduction success. Native congener richness was positively correlated with nonindigenous cyprinid richness and was the most important variable predicting nonindigenous cyprinid richness. Mean elevation had a weak positive effect, and effects of other abiotic factors were insignificant and less important. Our results suggest that at this spatial scale, trait preadaptation may be more important than intrageneric competition for determining richness of nonindigenous fishes.
van Breda, Phelia; De Clercq, Willem; Vlok, Pieter; Querner, Erik
Hydrological modelling lends itself to other disciplines very well, normally as a process based system that acts as a catalogue of events taking place. These hydrological models are spatial-temporal in their design and are generally well suited for what-if situations in other disciplines. Scaling should therefore be a function of the purpose of the modelling. Process is always linked with scale or support but the temporal resolution can affect the results if the spatial scale is not suitable. The use of hydrological response units tends to lump area around physical features but disregards farm boundaries. Farm boundaries are often the more crucial uppermost resolution needed to gain more value from hydrological modelling. In the Letaba Catchment of South Africa, we find a generous portion of landuses, different models of ownership, different farming systems ranging from large commercial farms to small subsistence farming. All of these have the same basic right to water but water distribution in the catchment is somewhat of a problem. Since water quantity is also a problem, the water supply systems need to take into account that valuable production areas not be left without water. Clearly hydrological modelling should therefore be sensitive to specific landuse. As a measure of productivity, a system of small farmer production evaluation was designed. This activity presents a dynamic system outside hydrological modelling that is generally not being considered inside hydrological modelling but depends on hydrological modelling. For sustainable development, a number of important concepts needed to be aligned with activities in this region, and the regulatory actions also need to be adhered to. This study aimed at aligning the activities in a region to the vision and objectives of the regulatory authorities. South Africa's system of socio-economic development planning is complex and mostly ineffective. There are many regulatory authorities involved, often with unclear
Giudici, Federico; Anghileri, Daniela; Castelletti, Andrea; Burlando, Paolo
Recent years have seen a significant increase of the human influence on the natural systems both at the global and local scale. Accurately modeling the human component and its interaction with the natural environment is key to characterize the real system dynamics and anticipate future potential changes to the hydrological regimes. Modern distributed, physically-based hydrological models are able to describe hydrological processes with high level of detail and high spatiotemporal resolution. Yet, they lack in sophistication for the behavior component and human decisions are usually described by very simplistic rules, which might underperform in reproducing the catchment dynamics. In the case of water reservoir operators, these simplistic rules usually consist of target-level rule curves, which represent the average historical level trajectory. Whilst these rules can reasonably reproduce the average seasonal water volume shifts due to the reservoirs' operation, they cannot properly represent peculiar conditions, which influence the actual reservoirs' operation, e.g., variations in energy price or water demand, dry or wet meteorological conditions. Moreover, target-level rule curves are not suitable to explore the water system response to climate and socio economic changing contexts, because they assume a business-as-usual operation. In this work, we quantitatively assess how the inclusion of adaptive reservoirs' operating rules into physically-based hydrological models contribute to the proper representation of the hydrological regime at the catchment scale. In particular, we contrast target-level rule curves and detailed optimization-based behavioral models. We, first, perform the comparison on past observational records, showing that target-level rule curves underperform in representing the hydrological regime over multiple time scales (e.g., weekly, seasonal, inter-annual). Then, we compare how future hydrological changes are affected by the two modeling
Faunt, C.; Belitz, K.; Hanson, R. T.
Historically, California’s Central Valley has been one of the most productive agricultural regions in the world. The Central Valley also is rapidly becoming an important area for California’s expanding urban population. In response to this competition for water, a number of water-related issues have gained prominence: conjunctive use, artificial recharge, hydrologic implications of land-use change, subsidence, and effects of climate variability. To provide information to stakeholders addressing these issues, the USGS made a detailed assessment of the Central Valley aquifer system that includes the present status of water resources and how these resources have changed over time. The principal product of this assessment is a tool, referred to as the Central Valley Hydrologic Model (CVHM), that simulates surface-water flows, groundwater flows, and land subsidence in response to stresses from human uses and from climate variability throughout the entire Central Valley. The CVHM utilizes MODFLOW combined with a new tool called “Farm Process” to simulate groundwater and surface-water flow, irrigated agriculture, land subsidence, and other key processes in the Central Valley on a monthly basis. This model was discretized horizontally into 20,000 1-mi2 cells and vertically into 10 layers ranging in thickness from 50 feet at the land surface to 750 feet at depth. A texture model constructed by using data from more than 8,500 drillers’ logs was used to estimate hydraulic properties. Unmetered pumpage and surface-water deliveries for 21 water-balance regions were simulated with the Farm Process. Model results indicate that human activities, predominately surface-water deliveries and groundwater pumping for irrigated agriculture, have dramatically influenced the hydrology of the Central Valley. These human activities have increased flow though the aquifer system by about a factor of six compared to pre-development conditions. The simulated hydrology reflects spatial
Jenkins, Aaron Peter; Jupiter, Stacy; Mueller, Ute; Jenney, Adam; Vosaki, Gandercillar; Rosa, Varanisese; Naucukidi, Alanieta; Mulholland, Kim; Strugnell, Richard; Kama, Mike; Horwitz, Pierre
The impact of environmental change on transmission patterns of waterborne enteric diseases is a major public health concern. This study concerns the burden and spatial nature of enteric fever, attributable to Salmonella Typhi infection in the Central Division, Republic of Fiji at a sub-catchment scale over 30-months (2013-2015). Quantitative spatial analysis suggested relationships between environmental conditions of sub-catchments and incidence and recurrence of typhoid fever. Average incidence per inhabited sub-catchment for the Central Division was high at 205.9/100,000, with cases recurring in each calendar year in 26% of sub-catchments. Although the numbers of cases were highest within dense, urban coastal sub-catchments, the incidence was highest in low-density mountainous rural areas. Significant environmental determinants at this scale suggest increased risk of exposure where sediment yields increase following runoff. The study suggests that populations living on large systems that broaden into meandering mid-reaches and floodplains with alluvial deposition are at a greater risk compared to small populations living near small, erosional, high-energy headwaters and small streams unconnected to large hydrological networks. This study suggests that anthropogenic alteration of land cover and hydrology (particularly via fragmentation of riparian forest and connectivity between road and river networks) facilitates increased transmission of typhoid fever and that environmental transmission of typhoid fever is important in Fiji.
The purpose of this report is to present a set of findings and examples for subdivision of watersheds for hydrologic modeling. Three approaches were used to examine the impact of watershed subdivision on modeled hydrologic response: (1) An equal-area...
Dozier, J.; Estes, J. E.; Simonett, D. S.; Davis, R.; Frew, J.; Marks, D.; Schiffman, K.; Souza, M.; Witebsky, E.
An energy balance snowmelt model for rugged terrain was devised and coupled to a flow model. A literature review of remote sensing applications to hydrologic modeling was included along with a software development outline.
Tarboton, D. G.; Horsburgh, J. S.; Zaslavsky, I.; Maidment, D. R.; Valentine, D.; Jennings, B.
The CUAHSI Hydrologic Information System project is developing information technology infrastructure to support hydrologic science. Hydrologic information science involves the description of hydrologic environments in a consistent way, using data models for information integration. This includes a hydrologic observations data model for the storage and retrieval of hydrologic observations in a relational database designed to facilitate data retrieval for integrated analysis of information collected by multiple investigators. It is intended to provide a standard format to facilitate the effective sharing of information between investigators and to facilitate analysis of information within a single study area or hydrologic observatory, or across hydrologic observatories and regions. The observations data model is designed to store hydrologic observations and sufficient ancillary information (metadata) about the observations to allow them to be unambiguously interpreted and used and provide traceable heritage from raw measurements to usable information. The design is based on the premise that a relational database at the single observation level is most effective for providing querying capability and cross dimension data retrieval and analysis. This premise is being tested through the implementation of a prototype hydrologic observations database, and the development of web services for the retrieval of data from and ingestion of data into the database. These web services hosted by the San Diego Supercomputer center make data in the database accessible both through a Hydrologic Data Access System portal and directly from applications software such as Excel, Matlab and ArcGIS that have Standard Object Access Protocol (SOAP) capability. This paper will (1) describe the data model; (2) demonstrate the capability for representing diverse data in the same database; (3) demonstrate the use of the database from applications software for the performance of hydrologic analysis
Conan, C.; Bouraoui, F.; de Marsily, G.; Bidoglio, G.
Increased anthropogenic activities such as agriculture, irrigation, industry, mining, ur- ban water supply and sewage treatment, have created significant environmental prob- lems. To ensure sustainable development of water resources, water managers need new strategies and suitable tools. In particular it is often compulsory that surface wa- ter and groundwater be managed simultaneously both in terms of quantity and quality at catchment scales. To this purpose, a model coupling SWAT (Soil and Water As- sessment Tool) and MODFLOW (Modular 3-D Flow model) was developed. SWAT is a quasi-distributed watershed model with a GIS interface that outlines the sub-basins and stream networks from a Digital Elevation Model (DEM) and calculates daily wa- ter balances from meteorological data, soil and land-use characteristics. The particular advantage of this model, compared to other fully distributed physically based mod- els, is that it requires a small amount of readily available input data. MODFLOW is a fully distributed model that calculates groundwater flow from aquifer characteris- tics. We have adapted this new coupled model SWAT-MODFLOW to a Mediterranean catchment, the Guadiana basin, and present the first results of this work. Only wa- ter quantity results are available at this stage. The validation consisted in comparing measured and predicted daily flow at the catchment and sub-catchment outlets for the period 1970-1995. The model accurately reproduced the decrease of the piezometric level, due to increased water abstraction, and the exchanges between surface water and ground-water. The sensitivity of the model to irrigation practices was evaluated. The usefulness of this model as a management tool has been illustrated through the analysis of alternative scenarios of agricultural practices and climate change.
Jan Seibert; Jeffrey J. McDonnell; Richard D. Woodsmith
Wildfire is an important disturbance affecting hydrological processes through alteration of vegetation cover and soil characteristics. The effects of fire on hydrological systems at the catchment scale are not well known, largely because site specific data from both before and after wildfire are rare. In this study a modelling approach was employed for change detection...
Queyrel, Wilfried; Florence, Habets; Hélène, Blanchoud; Céline, Schott; Laurine, Nicola
Pesticide applications lead to contamination risks of environmental compartments causing harmful effects on water resource used for drinking water. Pesticide fate modeling is assumed to be a relevant approach to study pesticide dissipation at the catchment scale. Simulations of five herbicides (atrazine, simazine, isoproturon, chlortoluron, metolachor) and one metabolite (DEA) were carried out with the crop model STICS over a 23-year period (1990-2012). The model application was performed using real agricultural practices over a small rural catchment (104 km²) located at 60km east from Paris (France). Model applications were established for two crops: wheat and maize. The objectives of the study were i) to highlight the main processes implied in pesticide fate and transfer at long-term; ii) to assess the influence of dynamics of the remaining mass of pesticide in soil on transfer; iii) to determine the most sensitive parameters related to pesticide losses by leaching over a 23-year period. The simulated data related to crop yield, water transfer, nitrates and pesticide concentrations were first compared to observations over the 23-year period, when measurements were available at the catchment scale. Then, the evaluation of the main processes related to pesticide fate and transfer was performed using long-term simulations at a yearly time step and monthly average variations. Analyses of the monthly average variations were oriented on the impact of pesticide application, water transfer and pesticide transformation on pesticide leaching. The evolution of the remaining mass of pesticide in soil, including the mobile phase (the liquid phase) and non-mobile (adsorbed at equilibrium and non-equilibrium), was studied to evaluate the impact of pesticide stored in soil on the fraction available for leaching. Finally, a sensitivity test was performed to evaluate the more sensitive parameters regarding the remaining mass of pesticide in soil and leaching. The findings of the
Baroni, G.; Gräff, T.; Reinstorf, F.; Oswald, S. E.
Nowadays uncertainty and sensitivity analysis are considered basic tools for the assessment of hydrological models and the evaluation of the most important sources of uncertainty. In this context, in the last decades several methods have been developed and applied in different hydrological conditions. However, in most of the cases, the studies have been done by investigating mainly the influence of the parameter uncertainty on the simulated outputs and few approaches tried to consider also other sources of uncertainty i.e. input and model structure. Moreover, several constrains arise when spatially distributed parameters are involved. To overcome these limitations a general probabilistic framework based on Monte Carlo simulations and the Sobol method has been proposed. In this study, the general probabilistic framework was applied at field scale using a 1D physical-based hydrological model (SWAP). Furthermore, the framework was extended at catchment scale in combination with a spatially distributed hydrological model (SHETRAN). The models are applied in two different experimental sites in Germany: a relatively flat cropped field close to Potsdam (Brandenburg) and a small mountainous catchment with agricultural land use (Schaefertal, Harz Mountains). For both cases, input and parameters are considered as major sources of uncertainty. Evaluation of the models was based on soil moisture detected at plot scale in different depths and, for the catchment site, also with daily discharge values. The study shows how the framework can take into account all the various sources of uncertainty i.e. input data, parameters (either in scalar or spatially distributed form) and model structures. The framework can be used in a loop in order to optimize further monitoring activities used to improve the performance of the model. In the particular applications, the results show how the sources of uncertainty are specific for each process considered. The influence of the input data as
Haddeland, I.; Lettenmaier, D. P.
This study focused on the hydrologic response, including vegetation water use, of two test regions within the Boreal-Ecosystem-Atmosphere Study (BOREAS) region in the Canadian boreal forest, one north of Prince Albert, Saskatchewan, and the other near Thompson, Manitoba. Fluxes of moisture and heat were studied using a spatially distributed hydrology soil-vegetation-model (DHSVM).
Barros, A. P.; Prat, O. P.; Sun, X.; Shrestha, P.; Miller, D.
The classic conceptual model of orographic rainfall depicts strong stationary horizontal gradients in rainfall accumulations and landcover contrasts across topographic divides (i.e. the rainshadow) at the broad scale of mountain ranges, or isolated orographic features. Whereas this model is sufficient to fingerprint the land-modulation of precipitation at the macroscale in climate studies, and can be useful to force geological models of land evolution for example, it fails to describe the active 4D space-time gradients that are critical at the fundamental scale of mountain hydrometeorology and hydrology, that is the headwater catchment. That is, the scale at which flash-floods are generated and landslides are triggered. Our work surveying the spatial and temporal habits of clouds and rainfall for some of the world's major mountain ranges from remotely-sensed data shows a close alignment of spatial scaling behavior with landform down to the mountain fold scale, that is the ridge-valley. Likewise, we find that diurnal and seasonal cycles are organized and constrained by topography from the macro- to the meso- to the alpha-scale of individual basins varying with synoptic weather conditions. At the catchment scale, the diurnal cycle exhibits an oscillatory behavior with storm features moving up and down from the ridge crests to the valley floor and back and forth from head to mouth along the valley with strong variations in rainfall intensity and duration. Direct observations to provide quantitative estimates of precipitation at this scale are beyond the capability of satellite-based observations present and anticipated in the next 10-20 years. This limitation can be addressed by assimilating the space-time modes of variability of rainfall into satellite-observations at coarser scale using multiscale blending algorithms. The challenge is to characterize the modes of space-time variability of precipitation in a systematic, and quantitative fashion that can be
Marshall, Susan; Roads, John O.; Glatzmaier, Gary
A snow hydrology has been implemented in an atmospheric general circulation model (GCM). The snow hydrology consists of parameterizations of snowfall and snow cover fraction, a prognostic calculation of snow temperature, and a model of the snow mass and hydrologic budgets. Previously, only snow albedo had been included by a specified snow line. A 3-year GCM simulation with this now more complete surface hydrology is compared to a previous GCM control run with the specified snow line, as well as with observations. In particular, the authors discuss comparisons of the atmospheric and surface hydrologic budgets and the surface energy budget for U.S. and Canadian areas. The new snow hydrology changes the annual cycle of the surface moisture and energy budgets in the model. There is a noticeable shift in the runoff maximum from winter in the control run to spring in the snow hydrology run. A substantial amount of GCM winter precipitation is now stored in the seasonal snowpack. Snow cover also acts as an important insulating layer between the atmosphere and the ground. Wintertime soil temperatures are much higher in the snow hydrology experiment than in the control experiment. Seasonal snow cover is important for dampening large fluctuations in GCM continental skin temperature during the Northern Hemisphere winter. Snow depths and snow extent show good agreement with observations over North America. The geographic distribution of maximum depths is not as well simulated by the model due, in part, to the coarse resolution of the model. The patterns of runoff are qualitatively and quantitatively similar to observed patterns of streamflow averaged over the continental United States. The seasonal cycles of precipitation and evaporation are also reasonably well simulated by the model, although their magnitudes are larger than is observed. This is due, in part, to a cold bias in this model, which results in a dry model atmosphere and enhances the hydrologic cycle everywhere.
Rasmussen, J.; Madsen, H.; Jensen, K. H.; Refsgaard, J. C.
The use of bias-aware Kalman filters for estimating and correcting observation bias in groundwater head observations is evaluated using both synthetic and real observations. In the synthetic test, groundwater head observations with a constant bias and unbiased stream discharge observations are assimilated in a catchment scale integrated hydrological model with the aim of updating stream discharge and groundwater head, as well as several model parameters relating to both stream flow and groundwater modeling. The Colored Noise Kalman filter (ColKF) and the Separate bias Kalman filter (SepKF) are tested and evaluated for correcting the observation biases. The study found that both methods were able to estimate most of the biases and that using any of the two bias estimation methods resulted in significant improvements over using a bias-unaware Kalman Filter. While the convergence of the ColKF was significantly faster than the convergence of the SepKF, a much larger ensemble size was required as the estimation of biases would otherwise fail. Real observations of groundwater head and stream discharge were also assimilated, resulting in improved stream flow modeling in terms of an increased Nash-Sutcliffe coefficient while no clear improvement in groundwater head modeling was observed. Both the ColKF and the SepKF tended to underestimate the biases, which resulted in drifting model behavior and sub-optimal parameter estimation, but both methods provided better state updating and parameter estimation than using a bias-unaware filter.
Rasmussen, Jørn; Madsen, Henrik; Høgh Jensen, Karsten; Refsgaard, Jens Christian
The use of bias-aware Kalman filters for estimating and correcting observation bias in groundwater head observations is evaluated using both synthetic and real observations. In the synthetic test, groundwater head observations with a constant bias and unbiased stream discharge observations are assimilated in a catchment-scale integrated hydrological model with the aim of updating stream discharge and groundwater head, as well as several model parameters relating to both streamflow and groundwater modelling. The coloured noise Kalman filter (ColKF) and the separate-bias Kalman filter (SepKF) are tested and evaluated for correcting the observation biases. The study found that both methods were able to estimate most of the biases and that using any of the two bias estimation methods resulted in significant improvements over using a bias-unaware Kalman filter. While the convergence of the ColKF was significantly faster than the convergence of the SepKF, a much larger ensemble size was required as the estimation of biases would otherwise fail. Real observations of groundwater head and stream discharge were also assimilated, resulting in improved streamflow modelling in terms of an increased Nash-Sutcliffe coefficient while no clear improvement in groundwater head modelling was observed. Both the ColKF and the SepKF tended to underestimate the biases, which resulted in drifting model behaviour and sub-optimal parameter estimation, but both methods provided better state updating and parameter estimation than using a bias-unaware filter.
Volkmann, T. H. M.; Van Haren, J. L. M.; Kim, M.; Harman, C. J.; Pangle, L.; Meredith, L. K.; Troch, P. A.
Stable isotope analysis is a powerful tool for tracking flow pathways, residence times, and the partitioning of water resources through catchments. However, the capacity of stable isotopes to characterize catchment hydrological dynamics has not been fully exploited as commonly used methodologies constrain the frequency and extent at which isotopic data is available across hydrologically-relevant compartments (e.g. soil, plants, atmosphere, streams). Here, building upon significant recent developments in laser spectroscopy and sampling techniques, we present a fully automated monitoring network for tracing water isotopes through the three model catchments of the Landscape Evolution Observatory (LEO) at the Biosphere 2, University of Arizona. The network implements state-of-the-art techniques for monitoring in great spatiotemporal detail the stable isotope composition of water in the subsurface soil, the discharge outflow, and the atmosphere above the bare soil surface of each of the 330-m2 catchments. The extensive valving and probing systems facilitate repeated isotope measurements from a total of more than five-hundred locations across the LEO domain, complementing an already dense array of hydrometric and other sensors installed on, within, and above each catchment. The isotope monitoring network is operational and was leveraged during several months of experimentation with deuterium-labelled rain pulse applications. Data obtained during the experiments demonstrate the capacity of the monitoring network to resolve sub-meter to whole-catchment scale flow and transport dynamics in continuous time. Over the years to come, the isotope monitoring network is expected to serve as an essential tool for collaborative interdisciplinary Earth science at LEO, allowing us to disentangle changes in hydrological behavior as the model catchments evolve in time through weathering and colonization by plant communities.
Dung, B. X.; Gomi, T.; Onda, Y.; Kato, H.; Hiraoka, M.
We conducted field observation in nested headwater catchments draining Japanese cypress (Chamaecyparis obtusa) and cedar (Cryptomeria japonica) forests at Tochigi prefectures for examining the effects of forest thinning on runoff generation at different catchment scales. 50% of the stems was removed with line thinning in catchment K2 (treatment catchment), while catchment K3 remained untreated as a control. We also monitored nested catchments within K2-1 (17.1 ha) as K2-2 (10.2 ha), K2-3 (3.7 ha) and K2-4 (5.1 ha), and within K3-1 (8.9 ha) as K3-2 (3.0 ha). Runoff from the catchments was monitored during the pre-thinning (from April, 2010 to May 2011), and the post-thinning periods (from June 2011 to July 2012). Paired-catchment and hydrograph separation analysis were used to evaluate the effects of forest thinning on runoff generation at different catchment scales. We developed the pre-thinning calibration equation for predicting post-thinning responses. Paired-catchment analysis revealed that annual catchment runoff increased 648 mm in K2-1, 414 mm in K2-2, 517 mm in K2-3 and 487 mm in K2-4 after the thinning. Both quick and delayed runoff components only increased significantly in the larger catchments of K2-1 and K2-2, while only delayed runoff components of smaller catchments (K2-3 and K2-4) increased significantly during the post-thinning period. Increases of quick runoff in large catchments could be associated with quick runoff response to soil surface compaction by line thinning and skid trail installation. Increases of delayed runoff in small catchment may be associated with increase in net precipitation and decrease in evapotranspiration. Our finding showed that changes in internal hydrological flow pathways and associated changes in runoff components due to forest harvesting differ depending on the catchment sizes.
Rahman, Mostaquimur; Rosolem, Rafael
Modelling and monitoring of hydrological processes in the unsaturated zone of chalk, a porous medium with fractures, is important to optimize water resource assessment and management practices in the United Kingdom (UK). However, incorporating the processes governing water movement through a chalk unsaturated zone in a numerical model is complicated mainly due to the fractured nature of chalk that creates high-velocity preferential flow paths in the subsurface. In general, flow through a chalk unsaturated zone is simulated using the dual-porosity concept, which often involves calibration of a relatively large number of model parameters, potentially undermining applications to large regions. In this study, a simplified parameterization, namely the Bulk Conductivity (BC) model, is proposed for simulating hydrology in a chalk unsaturated zone. This new parameterization introduces only two additional parameters (namely the macroporosity factor and the soil wetness threshold parameter for fracture flow activation) and uses the saturated hydraulic conductivity from the chalk matrix. The BC model is implemented in the Joint UK Land Environment Simulator (JULES) and applied to a study area encompassing the Kennet catchment in the southern UK. This parameterization is further calibrated at the point scale using soil moisture profile observations. The performance of the calibrated BC model in JULES is assessed and compared against the performance of both the default JULES parameterization and the uncalibrated version of the BC model implemented in JULES. Finally, the model performance at the catchment scale is evaluated against independent data sets (e.g. runoff and latent heat flux). The results demonstrate that the inclusion of the BC model in JULES improves simulated land surface mass and energy fluxes over the chalk-dominated Kennet catchment. Therefore, the simple approach described in this study may be used to incorporate the flow processes through a chalk unsaturated
Archfield, Stacey A.; Clark, Martyn; Arheimer, Berit; Hay, Lauren E.; McMillan, Hilary; Kiang, Julie E.; Seibert, Jan; Hakala, Kirsti; Bock, Andrew R.; Wagener, Thorsten; Farmer, William H.; Andreassian, Vazken; Attinger, Sabine; Viglione, Alberto; Knight, Rodney; Markstrom, Steven; Over, Thomas M.
In the past, hydrologic modeling of surface water resources has mainly focused on simulating the hydrologic cycle at local to regional catchment modeling domains. There now exists a level of maturity among the catchment, global water security, and land surface modeling communities such that these communities are converging toward continental domain hydrologic models. This commentary, written from a catchment hydrology community perspective, provides a review of progress in each community toward this achievement, identifies common challenges the communities face, and details immediate and specific areas in which these communities can mutually benefit one another from the convergence of their research perspectives. Those include: (1) creating new incentives and infrastructure to report and share model inputs, outputs, and parameters in data services and open access, machine-independent formats for model replication or reanalysis; (2) ensuring that hydrologic models have: sufficient complexity to represent the dominant physical processes and adequate representation of anthropogenic impacts on the terrestrial water cycle, a process-based approach to model parameter estimation, and appropriate parameterizations to represent large-scale fluxes and scaling behavior; (3) maintaining a balance between model complexity and data availability as well as uncertainties; and (4) quantifying and communicating significant advancements toward these modeling goals.
Dierauer, J. R.; Allen, D. M.
Climate change is expected to lead to an increase in extremes, including daily maximum temperatures, heat waves, and meteorological droughts, which will likely result in shifts in the hydrological drought regime (i.e. the frequency, timing, duration, and severity of drought events). While many studies have used hydrologic models to simulate climate change impacts on water resources, only a small portion of these studies have analyzed impacts on low flows and/or hydrological drought. This study is the first to use a fully coupled groundwater-surface water (gw-sw) model to study climate change impacts on hydrological drought. Generic catchment-scale gw-sw models were created for each of the six major eco-regions in British Columbia using the MIKE-SHE/MIKE-11 modelling code. Daily precipitation and temperature time series downscaled using bias-correction spatial disaggregation for the simulated period of 1950-2100 were obtained from the Pacific Climate Institute Consortium (PCIC). Streamflow and groundwater drought events were identified from the simulated time series for each catchment model using the moving window quantile threshold. The frequency, timing, duration, and severity of drought events were compared between the reference period (1961-2000) and two future time periods (2031-2060, 2071-2100). Results show how hydrological drought regimes across the different British Columbia eco-regions will be impacted by climate change.
Lin, H.; Baldwin, D. C.; Smithwick, E. A. H.
Predicting root zone (0-100 cm) soil moisture (RZSM) content at a catchment-scale is essential for drought and flood predictions, irrigation planning, weather forecasting, and many other applications. Satellites, such as the NASA Soil Moisture Active Passive (SMAP), can estimate near-surface (0-5 cm) soil moisture content globally at coarse spatial resolutions. We develop a hierarchical Ensemble Kalman Filter (EnKF) data assimilation modeling system to downscale satellite-based near-surface soil moisture and to estimate RZSM content across the Shale Hills Critical Zone Observatory at a 1-m resolution in combination with ground-based soil moisture sensor data. In this example, a simple infiltration model within the EnKF-model has been parameterized for 6 soil-terrain units to forecast daily RZSM content in the catchment from 2009 - 2012 based on AMSRE. LiDAR-derived terrain variables define intra-unit RZSM variability using a novel covariance localization technique. This method also allows the mapping of uncertainty with our RZSM estimates for each time-step. A catchment-wide satellite-to-surface downscaling parameter, which nudges the satellite measurement closer to in situ near-surface data, is also calculated for each time-step. We find significant differences in predicted root zone moisture storage for different terrain units across the experimental time-period. Root mean square error from a cross-validation analysis of RZSM predictions using an independent dataset of catchment-wide in situ Time-Domain Reflectometry (TDR) measurements ranges from 0.060-0.096 cm3 cm-3, and the RZSM predictions are significantly (p < 0.05) correlated with TDR measurements [r = 0.47-0.68]. The predictive skill of this data assimilation system is similar to the Penn State Integrated Hydrologic Modeling (PIHM) system. Uncertainty estimates are significantly (p < 0.05) correlated to cross validation error during wet and dry conditions, but more so in dry summer seasons. Developing an
Sulis, M.; Paniconi, C.; Marrocu, M.; Huard, D.; Chaumont, D.
General circulation models (GCMs) are the primary instruments for obtaining projections of future global climate change. Outputs from GCMs, aided by dynamical and/or statistical downscaling techniques, have long been used to simulate changes in regional climate systems over wide spatiotemporal scales. Numerous studies have acknowledged the disagreements between the various GCMs and between the different downscaling methods designed to compensate for the mismatch between climate model output and the spatial scale at which hydrological models are applied. Very little is known, however, about the importance of these differences once they have been input or assimilated by a nonlinear hydrological model. This issue is investigated here at the catchment scale using a process-based model of integrated surface and subsurface hydrologic response driven by outputs from 12 members of a multimodel climate ensemble. The data set consists of daily values of precipitation and min/max temperatures obtained by combining four regional climate models and five GCMs. The regional scenarios were downscaled using a quantile scaling bias-correction technique. The hydrologic response was simulated for the 690 km2des Anglais catchment in southwestern Quebec, Canada. The results show that different hydrological components (river discharge, aquifer recharge, and soil moisture storage) respond differently to precipitation and temperature anomalies in the multimodel climate output, with greater variability for annual discharge compared to recharge and soil moisture storage. We also find that runoff generation and extreme event-driven peak hydrograph flows are highly sensitive to any uncertainty in climate data. Finally, the results show the significant impact of changing sequences of rainy days on groundwater recharge fluxes and the influence of longer dry spells in modifying soil moisture spatial variability.
Ali, Melkamu; Ye, Sheng; Li, Hongyi
Subsurface stormflow is an important component of the rainfall-runoff response, especially in steep forested regions. However; its contribution is poorly represented in current generation of land surface hydrological models (LSMs) and catchment-scale rainfall-runoff models. The lack of physical basis of common parameterizations precludes a priori estimation (i.e. without calibration), which is a major drawback for prediction in ungauged basins, or for use in global models. This paper is aimed at deriving physically based parameterizations of the storage-discharge relationship relating to subsurface flow. These parameterizations are derived through a two-step up-scaling procedure: firstly, through simulations with a physically based (Darcian) subsurfacemore » flow model for idealized three dimensional rectangular hillslopes, accounting for within-hillslope random heterogeneity of soil hydraulic properties, and secondly, through subsequent up-scaling to the catchment scale by accounting for between-hillslope and within-catchment heterogeneity of topographic features (e.g., slope). These theoretical simulation results produced parameterizations of the storage-discharge relationship in terms of soil hydraulic properties, topographic slope and their heterogeneities, which were consistent with results of previous studies. Yet, regionalization of the resulting storage-discharge relations across 50 actual catchments in eastern United States, and a comparison of the regionalized results with equivalent empirical results obtained on the basis of analysis of observed streamflow recession curves, revealed a systematic inconsistency. It was found that the difference between the theoretical and empirically derived results could be explained, to first order, by climate in the form of climatic aridity index. This suggests a possible codependence of climate, soils, vegetation and topographic properties, and suggests that subsurface flow parameterization needed for ungauged
Rivera Villarreyes, C.; Baroni, G.; Oswald, S. E.
Soil water content at the plot or hill-slope scale is an important link between local vadose zone hydrology and catchment hydrology. One largest initiative to cover the measuring gap of soil moisture between point scale and remote sensing observations is the COSMOS network (Zreda et al., 2012). Here, cosmic-ray neutron sensing, which may be more precisely named ground albedo neutron sensing (GANS), is applied. The measuring principle is based on the crucial role of hydrogen as neutron moderator compared to others landscape materials. Soil water content contained in a footprint of ca. 600 m diameter and a depth ranging down to a few decimeters is inversely correlated to the neutron flux at the air-ground interface. This approach is now implemented, e.g. in USA (Zreda et al., 2012) and Germany (Rivera Villarreyes et al., 2011), based on its simple installation and integral measurement of soil moisture at the small catchment scale. The present study performed Ground Albedo Neutron Sensing on farmland at two locations in Germany under different vegetative situations (cropped and bare field) and different seasonal conditions (summer, autumn and winter). Ground albedo neutrons were measured at (i) a farmland close to Potsdam and Berlin cropped with corn in 2010, sunflower in 2011 and winter rye in 2012, and (ii) a mountainous farmland catchment (Schaefertal, Harz Mountains) since middle 2011. In order to test this methodology, classical soil moisture devices and meteorological data were used for comparison. Moreover, several calibration approaches, role of vegetation cover and transferability of calibration parameters to different times and locations were also evaluated. Observations suggest that GANS can overcome the lack of data for hydrological processes at the intermediate scale. Soil moisture from GANS compared quantitatively with mean values derived from a network of classical devices under vegetated and non- vegetated conditions. The GANS approach responded well
de Marsily, G.
This discussion article addresses the nature of models used in hydrology. It proposes a minimalist classification of models into two categories: models built on data from observations of the processes involved, and those for which there are no observation data on any of these processes, at the scale of interest. (LZ)
Hörmann, G.; Schmalz, B.; Fohrer, N.
The department of hydrology and water resources management is part of the Ecology Center of Kiel University, an interdisciplinary research organization. We teach hydrology for geographers, biologists, agricultural engineers and ecologists. Hydrological modeling is part of the curriculum since 1988. It has moved from the subject for specialists to a basic component of all hydrological courses. During the first year, we focussed on in-depth teaching of theory and practice of one big model, but the students found it hard to follow and beyond practical problems. During the last years we switched to a broader, but more shallow policy. Modeling is now part of nearly all courses, but remains limited to mostly 2-4 days of teaching. We now present only very basic theory and leave it to the students to discover the details during the practical work with pre-installed data sets. The poster shows how the models SWAT, Hydrus, Coupmodel, SIMPEL and PC-Raster are embedded in the hydrological curriculum and what kind of problems we experienced in teaching.
Van De Giesen, N.; Schoups, G.; Weijs, S. V.
The Data Processing Inequality implies that hydrological modeling can only reduce, and never increase, the amount of information available in the original data used to formulate and calibrate hydrological models: I(X;Z(Y)) ≤ I(X;Y). Still, hydrologists around the world seem quite content building models for "their" watersheds to move our discipline forward. Hydrological models tend to have a hybrid character with respect to underlying physics. Most models make use of some well established physical principles, such as mass and energy balances. One could argue that such principles are based on many observations, and therefore add data. These physical principles, however, are applied to hydrological models that often contain concepts that have no direct counterpart in the observable physical universe, such as "buckets" or "reservoirs" that fill up and empty out over time. These not-so-physical concepts are more like the Artificial Neural Networks and Support Vector Machines of the Artificial Intelligence (AI) community. Within AI, one quickly came to the realization that by increasing model complexity, one could basically fit any dataset but that complexity should be controlled in order to be able to predict unseen events. The more data are available to train or calibrate the model, the more complex it can be. Many complexity control approaches exist in AI, with Solomonoff inductive inference being one of the first formal approaches, the Akaike Information Criterion the most popular, and Statistical Learning Theory arguably being the most comprehensive practical approach. In hydrology, complexity control has hardly been used so far. There are a number of reasons for that lack of interest, the more valid ones of which will be presented during the presentation. For starters, there are no readily available complexity measures for our models. Second, some unrealistic simplifications of the underlying complex physics tend to have a smoothing effect on possible model
R. W. Malone; G. Yagow; C. Baffaut; M.W Gitau; Z. Qi; Devendra Amatya; P.B. Parajuli; J.V. Bonta; T.R. Green
Â Imparting knowledge of the physical processes of a system to a model and determining a set of parameter values for a hydrologic or water quality model application (i.e., parameterization) are important and difficult tasks. An exponential...
Imparting knowledge of the physical processes of a system to a model and determining a set of parameter values for a hydrologic or water quality model application (i.e., parameterization) is an important and difficult task. An exponential increase in literature has been devoted to the use and develo...
Hydrological models are used to assess many water resources problems from agricultural use and water quality to engineering issues. The success of these models are dependent on correct parameterization; the most sensitive being the rainfall input time series. These records can come from land-based ...
McMillan, H. K.; Booker, D. J.; Cattoën, C.
Nationwide predictions of flow time-series are valuable for development of policies relating to environmental flows, calculating reliability of supply to water users, or assessing risk of floods or droughts. This breadth of model utility is possible because various hydrological signatures can be derived from simulated flow time-series. However, producing national hydrological simulations can be challenging due to strong environmental diversity across catchments and a lack of data available to aid model parameterisation. A comprehensive and consistent suite of test procedures to quantify spatial and temporal patterns in performance across various parts of the hydrograph is described and applied to quantify the performance of an uncalibrated national rainfall-runoff model of New Zealand. Flow time-series observed at 485 gauging stations were used to calculate Nash-Sutcliffe efficiency and percent bias when simulating between-site differences in daily series, between-year differences in annual series, and between-site differences in hydrological signatures. The procedures were used to assess the benefit of applying a correction to the modelled flow duration curve based on an independent statistical analysis. They were used to aid understanding of climatological, hydrological and model-based causes of differences in predictive performance by assessing multiple hypotheses that describe where and when the model was expected to perform best. As the procedures produce quantitative measures of performance, they provide an objective basis for model assessment that could be applied when comparing observed daily flow series with competing simulated flow series from any region-wide or nationwide hydrological model. Model performance varied in space and time with better scores in larger and medium-wet catchments, and in catchments with smaller seasonal variations. Surprisingly, model performance was not sensitive to aquifer fraction or rain gauge density.
Di Baldassarre, Giuliano; Martinez, Fabian; Kalantari, Zahra; Viglione, Alberto
Hydrological studies have investigated human impacts on hydrological extremes, i.e. droughts and floods, while social studies have explored human responses and adaptation to them. Yet, there is still little understanding about the dynamics resulting from two-way feedbacks, i.e. both impacts and responses. Traditional risk assessment methods therefore fail to assess future dynamics, and thus risk reduction strategies built on these methods can lead to unintended consequences in the medium-long term. Here we review the dynamics resulting from the reciprocal links between society and hydrological extremes, and describe initial efforts to model floods and droughts in the Anthropocene. In particular, we first discuss the need for a novel approach to explicitly account for human interactions with both hydrological extremes, and then present a stylized model simulating the reciprocal effects between droughts, foods and reservoir operation rules. Unprecedented opportunities offered by the growing availability of global data and worldwide archives to uncover the mutual shaping of hydrological extremes and society across places and scales are also discussed.
Silberstein, Richard P.
As the pressures of industry, agriculture and mining on groundwater resources increase there is a burgeoning un-met need to be able to capture these multiple, direct and indirect stresses in a formal framework that will enable better assessment of impact scenarios. While there are many catchment hydrological models and there are some models that represent ecological states and change (e.g. FLAMES, Liedloff and Cook, 2007), these have not been linked in any deterministic or substantive way. Without such coupled eco-hydrological models quantitative assessments of impacts from water use intensification on water dependent ecosystems under changing climate are difficult, if not impossible. The concept would include facility for direct and indirect water related stresses that may develop around mining and well operations, climate stresses, such as rainfall and temperature, biological stresses, such as diseases and invasive species, and competition such as encroachment from other competing land uses. Indirect water impacts could be, for example, a change in groundwater conditions has an impact on stream flow regime, and hence aquatic ecosystems. This paper reviews previous work examining models combining ecology and hydrology with a view to developing a conceptual framework linking a biophysically defensable model that combines ecosystem function with hydrology. The objective is to develop a model capable of representing the cumulative impact of multiple stresses on water resources and associated ecosystem function.
Viola, Francesco; Caracciolo, Domenico; Pumo, Dario; Francipane, Antonio; Valerio Noto, Leonardo
Natural changes and human modifications in hydrological systems coevolve and interact in a coupled and interlinked way. If, on one hand, climatic changes are stochastic, non-steady, and affect the hydrological systems, on the other hand, human-induced changes due to over-exploitation of soils and water resources modifies the natural landscape, water fluxes and its partitioning. Indeed, the traditional assumption of static systems in hydrological analysis, which has been adopted for long time, fails whenever transient climatic conditions and/or land use changes occur. Time series analysis is a way to explore environmental changes together with societal changes; unfortunately, the not distinguishability between causes restrict the scope of this method. In order to overcome this limitation, it is possible to couple time series analysis with an opportune hydrological model, such as a conceptual hydrological model, which offers a schematization of complex dynamics acting within a basin. Assuming that model parameters represent morphological basin characteristics and that calibration is a way to detect hydrological signature at a specific moment, it is possible to argue that calibrating the model over different time windows could be a method for detecting potential hydrological changes. In order to test the capabilities of a conceptual model in detecting hydrological changes, this work presents different "in silico" experiments. A synthetic-basin is forced with an ensemble of possible future scenarios generated with a stochastic weather generator able to simulate steady and non-steady climatic conditions. The experiments refer to Mediterranean climate, which is characterized by marked seasonality, and consider the outcomes of the IPCC 5th report for describing climate evolution in the next century. In particular, in order to generate future climate change scenarios, a stochastic downscaling in space and time is carried out using realizations of an ensemble of General
Le Vine, Nataliya; Butler, Adrian; McIntyre, Neil; Jackson, Christopher
Land Surface Models (LSMs) are key elements in guiding adaptation to the changing water cycle and the starting points to develop a global hyper-resolution model of the terrestrial water, energy and biogeochemical cycles. However, before this potential is realised, there are some fundamental limitations of LSMs related to how meaningfully hydrological fluxes and stores are represented. An important limitation is the simplistic or non-existent representation of the deep subsurface in LSMs; and another is the lack of connection of LSM parameterisations to relevant hydrological information. In this context, the paper uses a case study of the JULES (Joint UK Land Environmental Simulator) LSM applied to the Kennet region in Southern England. The paper explores the assumptions behind JULES hydrology, adapts the model structure and optimises the coupling with the ZOOMQ3D regional groundwater model. The analysis illustrates how three types of information can be used to improve the model's hydrology: a) observations, b) regionalized information, and c) information from an independent physics-based model. It is found that: 1) coupling to the groundwater model allows realistic simulation of streamflows; 2) a simple dynamic lower boundary improves upon JULES' stationary unit gradient condition; 3) a 1D vertical flow in the unsaturated zone is sufficient; however there is benefit in introducing a simple dual soil moisture retention curve; 4) regionalized information can be used to describe soil spatial heterogeneity. It is concluded that relatively simple refinements to the hydrology of JULES and its parameterisation method can provide a substantial step forward in realising its potential as a high-resolution multi-purpose model.
Sear, D.; Newson, M.; Hill, C.; Branson, J.; Old, J.
Fluvial geomorphology is increasingly used by those responsible for conserving river ecosystems; survey techniques are used to derive conceptual models of the processes and forms that characterise particular systems and locations, with a view to making statements of `condition' or `status' and providing fundamental strategies for rehabilitation/restoration. However, there are important scale-related problems in developing catchments scale restoration plans that inevitably are implemented on a reach- by-reach basis. This paper reports on a watershed scale methodology for setting geomorphological and physical habitat reference conditions based on a science-based conceptual model of cachment:channel function. Using a case study from the River Nar, a gravel-bed groundwater dominated river in the UK with important conservation status, the paper describes the sequences of the methodology; from analysis of available evidence, process of field data capture and development of a conceptual model of catchment-wide fluvial dynamics. Reference conditions were derived from the conceptual model and gathered from the literature for the two main river types found on the river Nar, and compared with the current situation in 76 sub-reaches from source to mouth. Multi-Criteria Analysis (MCA) was used to score the extent of channel departures from `natural' and to suggest the basis for a progressive restoration strategy for the whole river system. MCA is shown to be a flexible method for setting and communicating decisions that are amenable to stakeholder and public consultation.
Trigalet, Sylvain; Chartin, Caroline; Van Oost, Kristof; van Wesemael, Bas
Understanding the soil organic carbon (SOC) distribution a few decades after conversion to cropland and plantations in a hilly catchment in southern Brazil is challenging due to scale-dependent controlling factors. Firstly, SOC, bulk density (BD) and texture were measured by depth intervals along 18 soil profiles located in three topographical positions (sloping plateau, central back slope and concave foot slope) in cropland and forest with contrasting slopes. SOC stocks in concave footslope position were not significantly different between fields on steep (11.1 kg C m-2) and gentle slopes (12.8 kg C m-2). However, in eroding profiles, SOC stocks are twice as high in fields on gentle slopes (17.6/12.6 kg C m-2) compared to steep slopes (8.3/7.1 kg C m-2). SOC stocks on steep slope on cropland (8.8 kg C m-2) are three times lower than SOC stocks on steep slope under undisturbed forest (23.7 kg C m-2). On gentle slopes, the effect of deforestation on SOC stocks was not so drastic (14.3 and 14.4 kg C m-2). Therefore, contrasting topography generates different patterns of SOC redistribution in the catchment. The effect of conversion to cropland is probably due to soil redistribution by water and tillage erosion aggravated by the steep terrain. Secondly, in order to assess the heterogeneity of SOC distribution at catchment scale, samples were collected at 10-20; 40-50 and 75-85 cm in 167 soil profiles sampled with an auger. SOC concentrations (gC kg-1 ) in numerous bulk soil samples (n = 378) were predicted by VIS-NIR spectroscopy and partial least-square regression models. SOC stocks were assessed by a mass preserving spline tool by interpolating SOC mass at the three non-contiguous depth intervals. Samples of calibration-validation dataset (n = 95) were used for physical SOC fractionation allowing the measurement of carbon associated with < 20 μm fraction. Multivariate linear regression models and Pearson correlation coefficients were used to assess the influence of
Arenas, M. C.; Duque, N.; Arboleda, P.; Guadagnini, A.; Riva, M.; Donado-Garzon, L. D.
Hydrological distributed modeling is key point for a comprehensive assessment of the feedback between the dynamics of the hydrological cycle, climate conditions and land use. Such modeling results are markedly relevant in the fields of water resources management, natural hazards and oil and gas industry. Here, we employ TopModel (TOPography based hydrological MODEL) for the hydrological modeling of an area in the Middle Magdalena Valley (MMV), a tropical basin located in Colombia. This study is located over the intertropical convergence zone and is characterized by special meteorological conditions, with fast water fluxes over the year. It has been subject to significant land use changes, as a result of intense economical activities, i.e., and agriculture, energy and oil & gas production. The model employees a record of 12 years of daily precipitation and evapotranspiration data as inputs. Streamflow data monitored across the same time frame are used for model calibration. The latter is performed by considering data from 2000 to 2008. Model validation then relies on observations from 2009 to 2012. The robustness of our analyses is based on the Nash-Sutcliffe coefficient (values of this metric being 0.62 and 0.53, respectively for model calibration and validation). Our results reveal high water storage capacity in the soil, and a marked subsurface runoff, consistent with the characteristics of the soil types in the regions. A significant influence on runoff response of the basin to topographical factors represented in the model is evidenced. Our calibrated model provides relevant indications about recharge in the region, which is important to quantify the interaction between surface water and groundwater, specially during the dry season, which is more relevant in climate-change and climate-variability scenarios.
It is always stressed that hydrological modelling is very important, to prevent floods, to mitigate droughts, to ensure food production or nature conservation. All very true, but I believe that focussing so much on the application of our knowledge (which I call `the engineering approach'), does not stimulate thorough system understanding (which I call `the scientific approach'). In many studies, science and engineering approaches are mixed, which results in large uncertainty e.g. due to a lack of system understanding. To what extent engineering and science approached are mixed depends on the Philosophy of Science of the researcher; verificationism seems to be closer related to engineering, than falsificationism or Bayesianism. In order to grow our scientific knowledge, which means increasing our understanding of the system, we need to be more critical towards the models that we use, but also recognize all the processes that influence the hydrological cycle. In an era called 'The Anthropocene' the influence of humans on the water system can no longer be neglected, and if we choose a scientific approach we have to account for human-induced processes. Summarizing, I believe that we have to account for human impact on the hydrological system, but we have to resist the temptation to directly quantify the hydrological impact on the human system.
Bogner, Christina; Hauhs, Michael; Lange, Holger
the catchment scale using tracer experiments. Rather, the series demonstrate the utter importance of the initial and boundary conditions which largely determine the response of the system to inert tracer pulses.
Brierley, Gary; Fryirs, Kirstie
Three geomorphic considerations that underpin the design and implementation of realistic and strategic river conservation and rehabilitation programs that work with the nature are outlined. First, the importance of appreciating the inherent diversity of river forms and processes is discussed. Second, river dynamics are appraised, framing the contemporary behavioral regime of a reach in relation to system evolution to explain changes to river character and behavior over time. Third, the trajectory of a reach is framed in relation to downstream patterns of river types, analyzing landscape connectivity at the catchment scale to interpret geomorphic river recovery potential. The application of these principles is demonstrated using extensive catchment-scale analyses of geomorphic river responses to human disturbance in the Bega and Upper Hunter catchments in southeastern Australia. Differing implications for reach- and catchment-scale rehabilitation planning prompt the imperative that management practices work with nature rather than strive to 'fight the site.'
Lanthier, M.; Arsenault, R.; Brissette, F.
Hydrologic modelling, by nature, is a simplification of the real-world hydrologic system. Therefore ensemble hydrological predictions thus obtained do not present the full range of possible streamflow outcomes, thereby producing ensembles which demonstrate errors in variance such as under-dispersion. Past studies show that lumped models used in prediction mode can return satisfactory results, especially when there is not enough information available on the watershed to run a distributed model. But all lumped models greatly simplify the complex processes of the hydrologic cycle. To generate more spread in the hydrologic ensemble predictions, multi-model ensembles have been considered. In this study, the aim is to propose and analyse a method that gives an ensemble streamflow prediction that properly represents the forecast probabilities and reduced ensemble bias. To achieve this, three simple lumped models are used to generate an ensemble. These will also be combined using multi-model averaging techniques, which generally generate a more accurate hydrogram than the best of the individual models in simulation mode. This new predictive combined hydrogram is added to the ensemble, thus creating a large ensemble which may improve the variability while also improving the ensemble mean bias. The quality of the predictions is then assessed on different periods: 2 weeks, 1 month, 3 months and 6 months using a PIT Histogram of the percentiles of the real observation volumes with respect to the volumes of the ensemble members. Initially, the models were run using historical weather data to generate synthetic flows. This worked for individual models, but not for the multi-model and for the large ensemble. Consequently, by performing data assimilation at each prediction period and thus adjusting the initial states of the models, the PIT Histogram could be constructed using the observed flows while allowing the use of the multi-model predictions. The under-dispersion has been
Globally river sediment associated contaminants, most notably heavy metals, radionuclides, Polychlorinated Biphenyls (PCBs), Organochlorine pesticides (OCs) and phosphorous, constitute one the most significant long-term risks to ecosystems and human health. These can impact both urban and rural areas and, because of their prolonged environmental residence times, are major sources of secondary pollution if contaminated soil and sediment are disturbed by human activity or by natural processes such as water or wind erosion. River catchments are also the primary source of sediment-associated contaminants to the coastal zone, and to the ocean, and an understanding of the factors that control contaminated sediment fluxes and delivery in river systems is essential for effective environmental management and protection. In this paper the catchment-scale controls of sediment-associated contaminant dispersal are reviewed, including climate-related variations in flooding regime, land-use change, channel engineering, restoration and flood defence. Drawing on case studies from metal mining impacted catchments in Bolivia (Río Pilcomayo), Spain (Río Guadiamar), Romania (River Tisa) and the UK (River Swale) some improved methodologies for identifying, tracing, modelling and managing contaminated river sediments are proposed that could have more general application in similarly affected river systems worldwide.
Ma, Yukun; McGree, James; Liu, An; Deilami, Kaveh; Egodawatta, Prasanna; Goonetilleke, Ashantha
Heavy metals (HMs) and polycyclic aromatic hydrocarbons (PAHs) are among the most toxic chemical pollutants present in urban stormwater. Consequently, urban stormwater reuse is constrained due to the human health risk posed by these pollutants. This study developed a scientifically robust approach to assess the risk to human health posed by HMs and PAHs in urban stormwater in order to enhance its reuse. Accordingly, an innovative methodology was created consisting of four stages: quantification of traffic and land use parameters; estimation of pollutant concentrations for model development; risk assessment, and risk map presentation. This methodology will contribute to catchment scale assessment of the risk associated with urban stormwater and for risk mitigation. The risk map developed provides a simple and efficient approach to identify the critical areas within a large catchment. The study also found that heavy molecular weight PAHs (PAHs with 5-6 benzene rings) in urban stormwater pose higher risk to human health compared to light molecular PAHs (PAHs with 2-4 benzene rings). These outcomes will facilitate the development of practical approaches for applying appropriate mitigation measures for the safe management of urban stormwater pollution and for the identification of enhanced reuse opportunities. Copyright © 2017 Elsevier Inc. All rights reserved.
Assessing the performance of Low Impact Development (LID) practices at a catchment scale is important in managing urban watersheds. Few modeling tools exist that are capable of explicitly representing the hydrological mechanisms of LIDs while considering the diverse land uses of urban watersheds. ...
In traditional watershed delineation and topographic modeling, surface depressions are generally treated as spurious features and simply removed from a digital elevation model (DEM) to enforce flow continuity of water across the topographic surface to the watershed outlets. In reality, however, many depressions in the DEM are actual wetland landscape features with seasonal to permanent inundation patterning characterized by nested hierarchical structures and dynamic filling–spilling–merging surface-water hydrological processes. Differentiating and appropriately processing such ecohydrologically meaningful features remains a major technical terrain-processing challenge, particularly as high-resolution spatial data are increasingly used to support modeling and geographic analysis needs. The objectives of this study were to delineate hierarchical wetland catchments and model their hydrologic connectivity using high-resolution lidar data and aerial imagery. The graph-theory-based contour tree method was used to delineate the hierarchical wetland catchments and characterize their geometric and topological properties. Potential hydrologic connectivity between wetlands and streams were simulated using the least-cost-path algorithm. The resulting flow network delineated potential flow paths connecting wetland depressions to each other or to the river network on scales finer than those available through the National Hydrography Dataset. The results demonstrated that
Savenije, Hubert H. G.; Hrachowitz, Markus
Catchment-scale hydrological models frequently miss essential characteristics of what determines the functioning of catchments. The most important active agent in catchments is the ecosystem. It manipulates and partitions moisture in a way that supports the essential functions of survival and productivity: infiltration of water, retention of moisture, mobilization and retention of nutrients, and drainage. Ecosystems do this in the most efficient way, establishing a continuous, ever-evolving feedback loop with the landscape and climatic drivers. In brief, hydrological systems are alive and have a strong capacity to adjust themselves to prevailing and changing environmental conditions. Although most models take Newtonian theory at heart, as best they can, what they generally miss is Darwinian theory on how an ecosystem evolves and adjusts its environment to maintain crucial hydrological functions. In addition, catchments, such as many other natural systems, do not only evolve over time, but develop features of spatial organization, including surface or sub-surface drainage patterns, as a by-product of this evolution. Models that fail to account for patterns and the associated feedbacks miss a critical element of how systems at the interface of atmosphere, biosphere and pedosphere function. In contrast to what is widely believed, relatively simple, semi-distributed conceptual models have the potential to accommodate organizational features and their temporal evolution in an efficient way, a reason for that being that because their parameters (and their evolution over time) are effective at the modelling scale, and thus integrate natural heterogeneity within the system, they may be directly inferred from observations at the same scale, reducing the need for calibration and related problems. In particular, the emergence of new and more detailed observation systems from space will lead towards a more robust understanding of spatial organization and its evolution. This
Botto, Anna; Camporese, Matteo
Hydrological models allow scientists to predict the response of water systems under varying forcing conditions. In particular, many physically-based integrated models were recently developed in order to understand the fundamental hydrological processes occurring at the catchment scale. However, the use of this class of hydrological models is still relatively limited, as their prediction skills heavily depend on reliable parameter estimation, an operation that is never trivial, being normally affected by large uncertainty and requiring huge computational effort. The objective of this work is to test the potential of data assimilation to be used as an inverse modeling procedure for the broad class of integrated hydrological models. To pursue this goal, a Bayesian data assimilation (DA) algorithm based on a Monte Carlo approach, namely the ensemble Kalman filter (EnKF), is combined with the CATchment HYdrology (CATHY) model. In this approach, input variables (atmospheric forcing, soil parameters, initial conditions) are statistically perturbed providing an ensemble of realizations aimed at taking into account the uncertainty involved in the process. Each realization is propagated forward by the CATHY hydrological model within a parallel R framework, developed to reduce the computational effort. When measurements are available, the EnKF is used to update both the system state and soil parameters. In particular, four different assimilation scenarios are applied to test the capability of the modeling framework: first only pressure head or water content are assimilated, then, the combination of both, and finally both pressure head and water content together with the subsurface outflow. To demonstrate the effectiveness of the approach in a real-world scenario, an artificial hillslope was designed and built to provide real measurements for the DA analyses. The experimental facility, located in the Department of Civil, Environmental and Architectural Engineering of the
Moorhouse, H. L.; McGowan, S.; Jones, M.; Brayshaw, S.; Barker, P.; Leavitt, P.
A catchment-scale palaeolimnological investigation of sedimentary algal pigments spanning the past ~200 years was undertaken on lakes which drain into Windermere, England's largest and longest lake. We aimed to determine the relative influence of past regional (climatic, atmospheric deposition) and local (land-use, hydrological modification, point-source pollution) drivers of algal community change by comparing three fertile lowland lakes (Blelham Tarn, Esthwaite Water and Rydal Water) and two upland tarns (Stickle and Easedale Tarns) to better inform a catchment-wide management strategy for Windermere. Drivers of change at the upland sites included atmospheric acid deposition, climatic change and structural modifications caused by dam installation, whereas the influence of agriculture and point-source pollution is greater in the lakes in the lowland parts of the catchment. As a result, contrasting algal responses were noted in the lakes. For example, the cyanobacterial pigment zeaxanthin and the cryptophte pigment alloxanthin increased at Stickle Tarn (359% and 321% respectively) corresponding with the establishment of a dam at the outflow of the tarn in 1838. However, post-1900's the concentration of these pigments declined both at Stickle and at Easedale Tarn coincident with increased storm events and in the later decades of the century (~1980s onwards) decreases in acid deposition. In the lowland sites the cyanobacterial pigment aphanizophyll increased by 400-7000% and the indicator of total algal production β-carotene increased as much as six-fold indicating a substantial degradation in water quality and the onset of cyanobacterial blooms since the 1950's. In the lowland sites, degradation of water quality was closely linked to sewage installations and treatment work upgrades during the 1950's-70's and intensification of agricultural practices most notably increases in sheep stocking densities, which expanded in the 1950's. In lowland lakes with a higher
Franceschini, Samuela; Marani, Marco
Model predictions derived based on rainfall measurements and hydrological model results are often limited by the systematic error of measuring instruments, by the intrinsic variability of the natural processes and by the uncertainty of the mathematical representation. We propose a means to identify such sources of uncertainty and to quantify their effects based on point-estimate approaches, as a valid alternative to cumbersome Montecarlo methods. We present uncertainty analyses on the hydrologic response to selected meteorological events, in the mountain streamflow-generating portion of the Brenta basin at Bassano del Grappa, Italy. The Brenta river catchment has a relatively uniform morphology and quite a heterogeneous rainfall-pattern. In the present work, we evaluate two sources of uncertainty: data uncertainty (the uncertainty due to data handling and analysis) and model uncertainty (the uncertainty related to the formulation of the model). We thus evaluate the effects of the measurement error of tipping-bucket rain gauges, the uncertainty in estimating spatially-distributed rainfall through block kriging, and the uncertainty associated with estimated model parameters. To this end, we coupled a deterministic model based on the geomorphological theory of the hydrologic response to probabilistic methods. In particular we compare the results of Monte Carlo Simulations (MCS) to the results obtained, in the same conditions, using Li's Point Estimate Method (LiM). The LiM is a probabilistic technique that approximates the continuous probability distribution function of the considered stochastic variables by means of discrete points and associated weights. This allows to satisfactorily reproduce results with only few evaluations of the model function. The comparison between the LiM and MCS results highlights the pros and cons of using an approximating method. LiM is less computationally demanding than MCS, but has limited applicability especially when the model
R.T. McNider; C. Handyside; K. Doty; W.L. Ellenburg; J.F. Cruise; J.R. Christy; D. Moss; V. Sharda; G. Hoogenboom; Peter Caldwell
The present paper discusses a coupled gridded crop modeling and hydrologic modeling system that can examine the benefits of irrigation and costs of irrigation and the coincident impact of the irrigation water withdrawals on surface water hydrology. The system is applied to the Southeastern U.S. The system tools to be discussed include a gridded version (GriDSSAT) of...
Sharp, John M., Jr.
The past year saw a re-emphasis on the practical aspects of hydrology due to regional drought patterns, urban flooding, and agricultural and energy demands on water resources. Highlights of hydrologic symposia, publications, and events are included. (MA)
Tasker, Gary D.; Stedinger, J.R.
Recent Monte Carlo studies have documented the value of generalized least squares (GLS) procedures to estimate empirical relationships between streamflow statistics and physiographic basin characteristics. This paper presents a number of extensions of the GLS method that deal with realities and complexities of regional hydrologic data sets that were not addressed in the simulation studies. These extensions include: (1) a more realistic model of the underlying model errors; (2) smoothed estimates of cross correlation of flows; (3) procedures for including historical flow data; (4) diagnostic statistics describing leverage and influence for GLS regression; and (5) the formulation of a mathematical program for evaluating future gaging activities. ?? 1989.
Pande, S.; Savenije, H.; Rathore, P.
Small holders are farmers who own less than 2 ha of farmland. They often have low productivity and thus remain at subsistence level. A fact that nearly 80% of Indian farmers are smallholders, who merely own a third of total farmlands and belong to the poorest quartile, but produce nearly 40% of countries foodgrains underlines the importance of understanding the socio-hydrology of a small holder. We present a framework to understand the socio-hydrological system dynamics of a small holder. It couples the dynamics of 6 main variables that are most relevant at the scale of a small holder: local storage (soil moisture and other water storage), capital, knowledge, livestock production, soil fertility and grass biomass production. The model incorporates rule-based adaptation mechanisms (for example: adjusting expenditures on food and fertilizers, selling livestocks etc.) of small holders when they face adverse socio-hydrological conditions, such as low annual rainfall, higher intra-annual variability in rainfall or variability in agricultural prices. It allows us to study sustainability of small holder farming systems under various settings. We apply the framework to understand the socio-hydrology of small holders in Aurangabad, Maharashtra, India. This district has witnessed suicides of many sugarcane farmers who could not extricate themselves out of the debt trap. These farmers lack irrigation and are susceptible to fluctuating sugar prices and intra-annual hydroclimatic variability. This presentation discusses two aspects in particular: whether government interventions to absolve the debt of farmers is enough and what is the value of investing in local storages that can buffer intra-annual variability in rainfall and strengthening the safety-nets either by creating opportunities for alternative sources of income or by crop diversification.
Freer, Jim; Coxon, Gemma; Quinn, Niall; Dunne, Toby; Lane, Rosie; Bates, Paul; Wagener, Thorsten; Woods, Ross; Neal, Jeff; Howden, Nicholas; Musuuza, Jude
There is a huge challenge in developing hydrological model structures that can be used for hypothesis testing, prediction, impact assessment and risk analyses over a wide range of spatial scales. There are many reasons why this is the case, from computational demands, to how we define and characterize different features and pathway connectivities in the landscape, that differ depending on the objectives of the study. However there is certainly a need more than ever to explore the trade-offs between the complexity of modelling applied (i.e. spatial discretization, levels of process representation, complexity of landscape representation) compared to the benefits realized in terms of predictive capability and robustness of these predictions during hydrological extremes and during change. Furthermore, there is a further balance, particularly associated with prediction uncertainties, in that it is not desirable to have modelling systems that are too complex compared to the observed data that would ever be available to apply them. This is particularly the case when models are applied to quantify national impact assessments, especially if these are based on validation assessments from smaller more detailed case studies. Therefore the hydrological community needs modelling tools and approaches that enable these trade-offs to be explored and to understand the level of representation needed in models to be 'fit-for-purpose' for a given application. This paper presents a catchment scale national modelling framework based on Dynamic-TOPMODEL specifically setup to fulfil these aims. A key component of the modelling framework is it's structural flexibility, as is the ability to assess model outputs using Monte Carlo simulation techniques. The model build has been automated to work at any spatial scale to the national scale, and within that to control the level of spatial discretisation and connectivity of locally accounted landscape elements in the form of hydrological response
Santos, Léonard; Thirel, Guillaume; Perrin, Charles
Errors made by hydrological models may come from a problem in parameter estimation, uncertainty on observed measurements, numerical problems and from the model conceptualization that simplifies the reality. Here we focus on this last issue of hydrological modeling. One of the solutions to reduce structural uncertainty is to use a multimodel method, taking advantage of the great number and the variability of existing hydrological models. In particular, because different models are not similarly good in all situations, using multimodel approaches can improve the robustness of modeled outputs. Traditionally, in hydrology, multimodel methods are based on the output of the model (the simulated flow series). The aim of this poster is to introduce a different approach based on the internal variables of the models. The method is inspired by the SUper MOdel (SUMO, van den Berge et al., 2011) developed for climatology. The idea of the SUMO method is to correct the internal variables of a model taking into account the values of the internal variables of (an)other model(s). This correction is made bilaterally between the different models. The ensemble of the different models constitutes a super model in which all the models exchange information on their internal variables with each other at each time step. Due to this continuity in the exchanges, this multimodel algorithm is more dynamic than traditional multimodel methods. The method will be first tested using two GR4J models (in a state-space representation) with different parameterizations. The results will be presented and compared to traditional multimodel methods that will serve as benchmarks. In the future, other rainfall-runoff models will be used in the super model. References van den Berge, L. A., Selten, F. M., Wiegerinck, W., and Duane, G. S. (2011). A multi-model ensemble method that combines imperfect models through learning. Earth System Dynamics, 2(1) :161-177.
Singh, N.; Bomblies, A.; Wemple, B. C.; Ricketts, T.
Natural infrastructure (e.g., floodplains, forests) can offer multiple ecosystem services (ES), including flood resilience and water quality improvement. In order to maintain these ES, state, federal and non-profit organizations may consider various interventions, such as increased floodplain connectivity, reforestation, and wetland restoration to minimize flood peaks and erosion during events. However, the effect of these interventions on hydro-geomorphic responses of streams from reach to catchment scales (>100 km2) are rarely quantified. We used stream geomorphic assessment datasets with a hydraulic model to investigate the influence of above mentioned interventions on stream power (SP), water depth (WD) and channel velocity (VEL) during floods of 2yr and 100yr return periods for three catchments in the Lake Champlain basin, Vermont. To simulate the effect of forests and wetlands, we changed the Manning's coefficient in the model, and to simulate the increased connectivity of the floodplain, we edited the LIDAR data to lower bank elevations. We find that the wetland scenario resulted in the greatest decline in WD and SP, whereas forested scenario exhibited maximum reduction in VEL. The connectivity scenario showed a decline in almost all stream responses, but the magnitude of change was relatively smaller. On average, 35% (2yr) and 50% (100yr) of altered reaches demonstrated improvement over baseline, and 39% (2yr) and 31% (100yr) of altered reaches showed degradation over baseline, across all interventions. We also noted changes in stream response along unaltered reaches (>30%), where we did not make interventions. Overall, these results point to the complexity related to stream interventions and suggest careful evaluation of spatially explicit tradeoffs of these interventions on river-floodplain ecosystem. The proposed approach of simulating and understanding stream's response to interventions, prior to the implementation of restoration activities, may lead to
Konadu, D. D.; Fenner, R. A.
Long-term low-carbon energy transition policy of the UK presents national scale propositions of different low-carbon energy system options that lead to meeting GHG emissions reduction target of 80% on 1990 levels by 2050. Whilst national-scale assessments suggests that water availability may not be a significant constrain on future thermal power generation systems in this pursuit, these analysis fail to capture the appropriate spatial scale where water resource decisions are made, i.e. at the catchment scale. Water is a local resource, which also has significant spatio-temporal regional and national variability, thus any policy-relevant water-energy nexus analysis must be reflective of these characteristics. This presents a critical challenge for policy relevant water-energy nexus analysis. This study seeks to overcome the above challenge by using a linear spatial-downscaling model to allocate nationally projected water-intensive energy system infrastructure/technologies to the catchment level, and estimating the water requirements for the deployment of these technologies. The model is applied to the UK Committee on Climate Change Carbon Budgets to 2030 as a case study. The paper concludes that whilst national-scale analyses show minimal long-term water related impacts, catchment level appraisal of water resource requirements reveal significant constraints in some locations. The approach and results presented in this study thus, highlights the importance of bringing together scientific understanding, data and analysis tools to provide better insights for water-energy nexus decisions at the appropriate spatial scale. This is particularly important for water stressed regions where the water-energy nexus must be analysed at appropriate spatial resolution to capture the full water resource impact of national energy policy.
Ichiba, Abdellah; Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Bompard, Philippe; Ten Veldhuis, Marie-Claire
Hydrological models are extensively used in urban water management, development and evaluation of future scenarios and research activities. There is a growing interest in the development of fully distributed and grid-based models. However, some complex questions related to scale effects are not yet fully understood and still remain open issues in urban hydrology. In this paper we propose a two-step investigation framework to illustrate the extent of scale effects in urban hydrology. First, fractal tools are used to highlight the scale dependence observed within distributed data input into urban hydrological models. Then an intensive multi-scale modelling work is carried out to understand scale effects on hydrological model performance. Investigations are conducted using a fully distributed and physically based model, Multi-Hydro, developed at Ecole des Ponts ParisTech. The model is implemented at 17 spatial resolutions ranging from 100 to 5 m. Results clearly exhibit scale effect challenges in urban hydrology modelling. The applicability of fractal concepts highlights the scale dependence observed within distributed data. Patterns of geophysical data change when the size of the observation pixel changes. The multi-scale modelling investigation confirms scale effects on hydrological model performance. Results are analysed over three ranges of scales identified in the fractal analysis and confirmed through modelling. This work also discusses some remaining issues in urban hydrology modelling related to the availability of high-quality data at high resolutions, and model numerical instabilities as well as the computation time requirements. The main findings of this paper enable a replacement of traditional methods of
model calibration by innovative methods of
model resolution alteration based on the spatial data variability and scaling of flows in urban hydrology.
Hakala, Kirsti; Addor, Nans; Seibert, Jan
Streamflow stemming from Switzerland's mountainous landscape will be influenced by climate change, which will pose significant challenges to the water management and policy sector. In climate change impact research, the determination of future streamflow is impeded by different sources of uncertainty, which propagate through the model chain. In this research, we explicitly considered the following sources of uncertainty: (1) climate models, (2) downscaling of the climate projections to the catchment scale, (3) bias correction method and (4) parameterization of the hydrological model. We utilize climate projections at the 0.11 degree 12.5 km resolution from the EURO-CORDEX project, which are the most recent climate projections for the European domain. EURO-CORDEX is comprised of regional climate model (RCM) simulations, which have been downscaled from global climate models (GCMs) from the CMIP5 archive, using both dynamical and statistical techniques. Uncertainties are explored by applying a modeling chain involving 14 GCM-RCMs to ten Swiss catchments. We utilize the rainfall-runoff model HBV Light, which has been widely used in operational hydrological forecasting. The Lindström measure, a combination of model efficiency and volume error, was used as an objective function to calibrate HBV Light. Ten best sets of parameters are then achieved by calibrating using the genetic algorithm and Powell optimization (GAP) method. The GAP optimization method is based on the evolution of parameter sets, which works by selecting and recombining high performing parameter sets with each other. Once HBV is calibrated, we then perform a quantitative comparison of the influence of biases inherited from climate model simulations to the biases stemming from the hydrological model. The evaluation is conducted over two time periods: i) 1980-2009 to characterize the simulation realism under the current climate and ii) 2070-2099 to identify the magnitude of the projected change of
Zia, Huma; Harris, Nick; Merrett, Geoff
collaborative information sharing can have a direct influence on agricultural practice. We apply a nutrient management scheme to a model of an example catchment with several individual networks. The networks are able to correlate catchment events to events within their zone of influence, allowing them to adapt their monitoring and control strategy in light of wider changes across the catchment. Results indicate that this can lead to significant reductions in nutrient losses (up to 50%) and better reutilization of nutrients amongst farms, having a positive impact on catchment scale water quality and fertilizer costs. 1. EC, E.C., Directive 2000/60/EC establishing a framework for Community action in the field of water policy, 2000. 2. Rivers, M., K. Smettem, and P. Davies. Estimating future scenarios for farm-watershed nutrient fluxes using dynamic simulation modelling-Can on-farm BMPs really do the job at the watershed scale? in Proc.29th Int.Conf System Dynamics Society, 2011. 2010. Washington 3. Liu, C., et al., On-farm evaluation of winter wheat yield response to residual soil nitrate-N in North China Plain. Agronomy Journal, 2008. 100(6): p. 1527-1534. 4. Kotamäki, N., et al., Wireless in-situ sensor network for agriculture and water monitoring on a river basin scale in Southern Finland: Evaluation from a data user's perspective. Sensors, 2009. 9(4): p. 2862-2883.
Pielke, Roger; Steyaert, Lou; Arritt, Ray; Lahtakia, Mercedes; Smith, Chris; Ziegler, Conrad; Soong, Su Tzai; Avissar, Roni; Wetzel, Peter; Sellers, Piers
The topics covered include the following: prototype land cover characteristics data base for the conterminous United States; surface evapotranspiration effects on cumulus convection and implications for mesoscale models; the use of complex treatment of surface hydrology and thermodynamics within a mesoscale model and some related issues; initialization of soil-water content for regional-scale atmospheric prediction models; impact of surface properties on dryline and MCS evolution; a numerical simulation of heavy precipitation over the complex topography of California; representing mesoscale fluxes induced by landscape discontinuities in global climate models; emphasizing the role of subgrid-scale heterogeneity in surface-air interaction; and problems with modeling and measuring biosphere-atmosphere exchanges of energy, water, and carbon on large scales.
Werder, Mauro A.; de Fleurian, Basile; Creyts, Timothy T.; Damsgaard, Anders; Delaney, Ian; Dow, Christine F.; Gagliardini, Olivier; Hoffman, Matthew J.; Seguinot, Julien; Sommers, Aleah; Irarrazaval Bustos, Inigo; Downs, Jakob
The SHMIP project is the first intercomparison project of subglacial drainage models (http://shmip.bitbucket.org). Its synthetic test suites and evaluation were designed such that any subglacial hydrology model producing effective pressure can participate. In contrast to ice deformation, the physical processes of subglacial hydrology (which in turn impacts basal sliding of glaciers) are poorly known. A further complication is that different glacial and geological settings can lead to different drainage physics. The aim of the project is therefore to qualitatively compare the outputs of the participating models for a wide range of water forcings and glacier geometries. This will allow to put existing studies, which use different drainage models, into context and will allow new studies to select the most suitable model for the problem at hand. We present the results from the just completed intercomparison exercise. Twelve models participated: eight 2D and four 1D models; nine include both an efficient and inefficient system, the other three one of the systems; all but two models use R-channels as efficient system, and/or a linked-cavity like inefficient system, one exception uses porous layers with different characteristic for each of the systems, the other exception is based on canals. The main variable used for the comparison is effective pressure, as that is a direct proxy for basal sliding of glaciers. The models produce large differences in the effective pressure fields, in particular for higher water input scenarios. This shows that the selection of a subglacial drainage model will likely impact the conclusions of a study significantly.
Tonkin, Jonathan D.; Shah, Deep Narayan; Kuemmerlen, Mathias; Li, Fengqing; Cai, Qinghua; Haase, Peter; Jähnig, Sonja C.
Little work has been done on large-scale patterns of stream insect richness in China. We explored the influence of climatic and catchment-scale factors on stream insect (Ephemeroptera, Plecoptera, Trichoptera; EPT) richness across mid-latitude China. We assessed the predictive ability of climatic, catchment land cover and physical structure variables on genus richness of EPT, both individually and combined, in 80 mid-latitude Chinese streams, spanning a 3899-m altitudinal gradient. We performed analyses using boosted regression trees and explored the nature of their influence on richness patterns. The relative importance of climate, land cover, and physical factors on stream insect richness varied considerably between the three orders, and while important for Ephemeroptera and Plecoptera, latitude did not improve model fit for any of the groups. EPT richness was linked with areas comprising high forest cover, elevation and slope, large catchments and low temperatures. Ephemeroptera favoured areas with high forest cover, medium-to-large catchment sizes, high temperature seasonality, and low potential evapotranspiration. Plecoptera richness was linked with low temperature seasonality and annual mean, and high slope, elevation and warm-season rainfall. Finally, Trichoptera favoured high elevation areas, with high forest cover, and low mean annual temperature, seasonality and aridity. Our findings highlight the variable role that catchment land cover, physical properties and climatic influences have on stream insect richness. This is one of the first studies of its kind in Chinese streams, thus we set the scene for more in-depth assessments of stream insect richness across broader spatial scales in China, but stress the importance of improving data availability and consistency through time. PMID:25909190
Nearing, M. A.
The Rangeland Hydrology and Erosion Model (RHEM) is a process-based model that was designed to address rangelands conditions. RHEM is designed for government agencies, land managers and conservationists who need sound, science-based technology to model, assess, and predict runoff and erosion rates on rangelands and to assist in evaluating rangeland conservation practices effects. RHEM is an event-based model that estimates runoff, erosion, and sediment delivery rates and volumes at the spatial scale of the hillslope and the temporal scale of as single rainfall event. It represents erosion processes under normal and fire-impacted rangeland conditions. Moreover, it adopts a new splash erosion and thin sheet-flow transport equation developed from rangeland data, and it links the model hydrologic and erosion parameters with rangeland plant community by providing a new system of parameter estimation equations based on 204 plots at 49 rangeland sites distributed across 15 western U.S. states. A dynamic partial differential sediment continuity equation is used to model the total detachment rate of concentrated flow and rain splash and sheet flow. RHEM is also designed to be used as a calculator, or "engine", within other watershed scale models. From the research perspective RHEM acts as a vehicle for incorporating new scientific findings from rangeland infiltration, runoff, and erosion studies. Current applications of the model include: 1) a web site for general use (conservation planning, research, etc.), 2) National Resource Inventory reports to Congress, 3) as a computational engine within watershed scale models (e.g., KINEROS, HEC), 4) Ecological Site & State and Transition Descriptions, 5) proposed in 2015 to become part of the NRCS Desktop applications for field offices.
G. Thirel; V. Andreassian; C. Perrin; J.-N. Audouy; L. Berthet; Pamela Edwards; N. Folton; C. Furusho; A. Kuentz; J. Lerat; G. Lindstrom; E. Martin; T. Mathevet; R. Merz; J. Parajka; D. Ruelland; J. Vaze
Testing hydrological models under changing conditions is essential to evaluate their ability to cope with changing catchments and their suitability for impact studies. With this perspective in mind, a workshop dedicated to this issue was held at the 2013 General Assembly of the International Association of Hydrological Sciences (IAHS) in GÃ¶teborg, Sweden, in July 2013...
Baymani-Nezhad, M.; Han, D.
Hydrological conditions are changed continuously and these phenomenons generate errors on flood forecasting models and will lead to get unrealistic results. Therefore, to overcome these difficulties, a concept called model updating is proposed in hydrological studies. Real-time model updating is one of the challenging processes in hydrological sciences and has not been entirely solved due to lack of knowledge about the future state of the catchment under study. Basically, in terms of flood forecasting process, errors propagated from the rainfall-runoff model are enumerated as the main source of uncertainty in the forecasting model. Hence, to dominate the exciting errors, several methods have been proposed by researchers to update the rainfall-runoff models such as parameter updating, model state updating, and correction on input data. The current study focuses on investigations about the ability of rainfall-runoff model parameters to cope with three types of existing errors, timing, shape and volume as the common errors in hydrological modelling. The new lumped model, the ERM model, has been selected for this study to evaluate its parameters for its use in model updating to cope with the stated errors. Investigation about ten events proves that the ERM model parameters can be updated to cope with the errors without the need to recalibrate the model.
Haas, Edwin; Klatt, Steffen; Kiese, Ralf; Butterbach-Bahl, Klaus; Kraft, Philipp; Breuer, Lutz
The use of mineral nitrogen fertilizer sustains the global food production and therefore the livelihood of human kind. The rise in world population will put pressure on the global agricultural system to increase its productivity leading most likely to an intensification of mineral nitrogen fertilizer use. The fate of excess nitrogen and its distribution within landscapes is manifold. Process knowledge on the site scale has rapidly grown in recent years and models have been developed to simulate carbon and nitrogen cycling in managed ecosystems on the site scale. Despite first regional studies, the carbon and nitrogen cycling on the landscape or catchment scale is not fully understood. In this study we present a newly developed modelling approach by coupling the fully distributed hydrology model CMF (catchment modelling framework) to the process based regional ecosystem model LandscapeDNDC for the investigation of hydrological processes and carbon and nitrogen transport and cycling, with a focus on nutrient displacement and resulting greenhouse gas emissions in various virtual landscapes / catchment to demonstrate the capabilities of the modelling system. The modelling system was applied to simulate water and nutrient transport at the at the Yanting Agro-ecological Experimental Station of Purple Soil, Sichuan province, China. The catchment hosts cypress forests on the outer regions, arable fields on the sloping croplands cultivated with wheat-maize rotations and paddy rice fields in the lowland. The catchment consists of 300 polygons vertically stratified into 10 soil layers. Ecosystem states (soil water content and nutrients) and fluxes (evapotranspiration) are exchanged between the models at high temporal scales (hourly to daily) forming a 3-dimensional model application. The water flux and nutrients transport in the soil is modelled using a 3D Richards/Darcy approach for subsurface fluxes with a kinematic wave approach for surface water runoff and the
Li, Xinya; Vernon, Chris R.; Hejazi, Mohamad I.; ...
Xanthos is an open-source hydrologic model, written in Python, designed to quantify and analyse global water availability. Xanthos simulates historical and future global water availability on a monthly time step at a spatial resolution of 0.5 geographic degrees. Xanthos was designed to be extensible and used by scientists that study global water supply and work with the Global Change Assessment Model (GCAM). Xanthos uses a user-defined configuration file to specify model inputs, outputs and parameters. Xanthos has been tested using actual global data sets and the model is able to provide historical observations and future estimates of renewable freshwater resourcesmore » in the form of total runoff.« less
Li, Xinya; Vernon, Chris R.; Hejazi, Mohamad I.
Xanthos is an open-source hydrologic model, written in Python, designed to quantify and analyse global water availability. Xanthos simulates historical and future global water availability on a monthly time step at a spatial resolution of 0.5 geographic degrees. Xanthos was designed to be extensible and used by scientists that study global water supply and work with the Global Change Assessment Model (GCAM). Xanthos uses a user-defined configuration file to specify model inputs, outputs and parameters. Xanthos has been tested using actual global data sets and the model is able to provide historical observations and future estimates of renewable freshwater resourcesmore » in the form of total runoff.« less
Laiolo, Paola; Gabellani, Simone; Campo, Lorenzo; Cenci, Luca; Silvestro, Francesco; Delogu, Fabio; Boni, Giorgio; Rudari, Roberto
The reliable estimation of hydrological variables (e.g. soil moisture, evapotranspiration, surface temperature) in space and time is of fundamental importance in operational hydrology to improve the forecast of the rainfall-runoff response of catchments and, consequently, flood predictions. Nowadays remote sensing can offer a chance to provide good space-time estimates of several hydrological variables and then improve hydrological model performances especially in environments with scarce in-situ data. This work investigates the impact of the assimilation of different remote sensing products on the hydrological cycle by using a continuous physically based distributed hydrological model. Three soil moisture products derived by ASCAT (Advanced SCATterometer) are used to update the model state variables. The satellite-derived products are assimilated into the hydrological model using different assimilation techniques: a simple nudging and the Ensemble Kalman Filter. Moreover two assimilation strategies are evaluated to assess the impact of assimilating the satellite products at model spatial resolution or at the satellite scale. The experiments are carried out for three Italian catchments on multi year period. The benefits on the model predictions of discharge, LST, evapotranspiration and soil moisture dynamics are tested and discussed.
Brilly, Mitja; Vidmar, Andrej; Kryžanowski, Andrej; Bezak, Nejc; Šraj, Mojca
PEST is tool based on minimization of an objective function related to the root mean square error between the model output and the measurement. We use "singular value decomposition", section of the PEST control file, and Tikhonov regularization method for successfully estimation of model parameters. The PEST sometimes failed if inverse problems were ill-posed, but (SVD) ensures that PEST maintains numerical stability. The choice of the initial guess for the initial parameter values is an important issue in the PEST and need expert knowledge. The flexible nature of the PEST software and its ability to be applied to whole catchments at once give results of calibration performed extremely well across high number of sub catchments. Use of parallel computing version of PEST called BeoPEST was successfully useful to speed up calibration process. BeoPEST employs smart slaves and point-to-point communications to transfer data between the master and slaves computers. The HBV-light model is a simple multi-tank-type model for simulating precipitation-runoff. It is conceptual balance model of catchment hydrology which simulates discharge using rainfall, temperature and estimates of potential evaporation. Version of HBV-light-CLI allows the user to run HBV-light from the command line. Input and results files are in XML form. This allows to easily connecting it with other applications such as pre and post-processing utilities and PEST itself. The procedure was applied on hydrological model of Savinja catchment (1852 km2) and consists of twenty one sub-catchments. Data are temporary processed on hourly basis.
Hancock, G. R.; Martinez, C.; Wells, T.; Dever, C.; Willgoose, G. R.; Bissett, A.
Soils represent the largest terrestrial sink of carbon on Earth. Managing the soil organic carbon (SOC) pool is becoming increasingly important in light of growing concerns over global food security and the climatic effects of anthropogenic CO2 emissions. The development of accurate predictive SOC models are an important step for both land resource managers and policy makers alike. Presently, a number of SOC models are available which incorporate environmental data to produce SOC estimates. The accuracy of these models varies significantly over a range of landscapes due to the highly complex nature of SOC dynamics. Fundamental gaps exist in our understanding of SOC controls. To date, studies of SOC controls, and the subsequent models derived from their findings have focussed mainly on North American and European landscapes. Additionally, SOC studies often focus on the paddock to small catchment scale. Consequently, information about SOC in Australian landscapes and at the larger scale is limited. This study examines controls over SOC across a large catchment of approximately 600 km2 in the Upper Hunter Valley, New South Wales, Australia. The aim was to develop a predictive model for use across a range of catchment sizes and climate. Here it was found that elevation (derived from DEMs) and vegetation (above ground biomass quantified by remote sensing were the primary controls of SOC. SOC was seen to increase with elevation and NDVI. This relationship is believed to be a reflection of rainfall patterns across the study area and plant growth potential. Further, a relationship was observed between SOC and the environmental tracer 137Cs which suggests that SOC and 137Cs move through catchment via similar sediment transport mechanisms. Therefore loss of SOC by erosion and gain by deposition may be necessary to be accounted for in any SOC budget. Model validation indicated that the use of simple linear relationships could predict SOC based on rainfall and vegetation
Poppenga, Sandra K.; Worstell, Bruce B.
Elevation data derived from light detection and ranging present challenges for hydrologic modeling as the elevation surface includes bridge decks and elevated road features overlaying culvert drainage structures. In reality, water is carried through these structures; however, in the elevation surface these features impede modeled overland surface flow. Thus, a hydrologically-enforced elevation surface is needed for hydrodynamic modeling. In the Delaware River Basin, hydrologic-enforcement techniques were used to modify elevations to simulate how constructed drainage structures allow overland surface flow. By calculating residuals between unfilled and filled elevation surfaces, artificially pooled depressions that formed upstream of constructed drainage structure features were defined, and elevation values were adjusted by generating transects at the location of the drainage structures. An assessment of each hydrologically-enforced drainage structure was conducted using field-surveyed culvert and bridge coordinates obtained from numerous public agencies, but it was discovered the disparate drainage structure datasets were not comprehensive enough to assess all remotely located depressions in need of hydrologic-enforcement. Alternatively, orthoimagery was interpreted to define drainage structures near each depression, and these locations were used as reference points for a quantitative hydrologic-enforcement assessment. The orthoimagery-interpreted reference points resulted in a larger corresponding sample size than the assessment between hydrologic-enforced transects and field-surveyed data. This assessment demonstrates the viability of rules-based hydrologic-enforcement that is needed to achieve hydrologic connectivity, which is valuable for hydrodynamic models in sensitive coastal regions. Hydrologic-enforced elevation data are also essential for merging with topographic/bathymetric elevation data that extend over vulnerable urbanized areas and dynamic coastal
Mathias, A.; Niu, G.; Zeng, X.
Climate change has an effect on the resilience of ecosystems and the occurrence of ecological perturbations (e.g. spread of invasive species, wildfires). Changes in vegetation in turn can interrupt regional scale climate patterns and alter the spatial and temporal propagation of ecological disturbances. Understanding the controls of vegetation change are essential for predicting future changes, and for setting conservation and restoration targets. Vegetation change in transition zones between ecological regions is a significant indicator of future shifts in the composition of neighboring plant communities. The Walnut Gulch Experimental Watershed is in a grassland-shrubland transition zone between the Sonoran and Chihuahuan Desert in Southern Arizona. During the past decade, at some sites the cover of the invasive Lehmann lovegrass (Eragrostis lehmanniana) drastically increased and the abundance of native vegetation decreased, causing a major decline in biodiversity. Focusing on a catchment scale (Kendall Site), we used an individual based vegetation model (ECOTONE) and a coupled vegetation-3D surface/subsurface hydrology model (ECOTONE-CATHY) to simulate vegetation change. We set up the models with soil and climatological data (NLDAS and AmeriFlux), incorporated initial conditions of species and biomass distribution and species parameters for the site. Using ECOTONE we tested our hypothesis that a combination of dry years and subsequent wet period caused Lehmann lovegass to have advantage over the natives. In ECOTONE species composition and species distribution of plant communities arise from dynamic interactions of individual plants with species specific traits through intra- and interspecific competition for resources (H2O, nitrogen) and their interaction with the environment (precipitation and temperature). Our results indicate that the competitive advantage of Lehmann lovegrass stems from its ability to withstand dryer conditions during establishment and due to
van der Ploeg, M. J.; Teuling, R.
Models that will be able to cope with future precipitation and evaporation regimes need a solid base that describes the essence of the processes involved . Micro-behaviour in the soil-vegetation-atmosphere system may have a large impact on patterns emerging at larger scales. A complicating factor in the micro-behaviour is the constant interaction between vegetation and geology in which water plays a key role. The resilience of the coupled vegetation-soil system critically depends on its sensitivity to environmental changes. As a result of environmental changes vegetation may wither and die, but such environmental changes may also trigger gene adaptation. Constant exposure to environmental stresses, biotic or abiotic, influences plant physiology, gene adaptations, and flexibility in gene adaptation [2-6]. Gene expression as a result of different environmental conditions may profoundly impact drought responses across the same plant species. Differences in response to an environmental stress, has consequences for the way species are currently being treated in models (single plant to global scale). In particular, model parameters that control root water uptake and plant transpiration are generally assumed to be a property of the plant functional type. Assigning plant functional types does not allow for local plant adaptation to be reflected in the model parameters, nor does it allow for correlations that might exist between root parameters and soil type. Models potentially provide a means to link root water uptake and transport to large scale processes (e.g. Rosnay and Polcher 1998, Feddes et al. 2001, Jung 2010), especially when powered with an integrated hydrological, ecological and physiological base. We explore the experimental evidence from natural vegetation to formulate possible alternative modeling concepts.  Seibert, J. 2000. Multi-criteria calibration of a conceptual runoff model using a genetic algorithm. Hydrology and Earth System Sciences 4(2): 215
Ponížilová, Iva; Unucka, Jan
The contribution is focused on the modelling of surface and subsurface runoff in the Ploučnice basin. The used rainfall-runoff model is HEC-HMS comprising of the method of SCS CN curves and a recession method. The geological subsurface consisting of sandstone is characterised by reduced surface runoff and, on the contrary, it contributes to subsurface runoff. The aim of this paper is comparison of the rate of influence of sandstone on reducing surface runoff. The recession method for subsurface runoff was used to determine the subsurface runoff. The HEC-HMS model allows semi- and fully distributed approaches to schematisation of the watershed and rainfall situations. To determine the volume of runoff the method of SCS CN curves is used, which results depend on hydrological conditions of the soils. The rainfall-runoff model assuming selection of so-called methods of event of the SCS-CN type is used to determine the hydrograph and peak flow rate based on simulation of surface runoff in precipitation exceeding the infiltration capacity of the soil. The recession method is used to solve the baseflow (subsurface) runoff. The method is based on the separation of hydrograph to direct runoff and subsurface or baseflow runoff. The study area for the simulation of runoff using the method of SCS CN curves to determine the hydrological transformation is the Ploučnice basin. The Ploučnice is a hydrologically significant river in the northern part of the Czech Republic, it is a right tributary of the Elbe river with a total basin area of 1.194 km2. The average value of CN curves for the Ploučnice basin is 72. The geological structure of the Ploučnice basin is predominantly formed by Mesozoic sandstone. Despite significant initial loss of rainfall the basin response to the causal rainfall was demonstrated by a rapid rise of the surface runoff from the watershed and reached culmination flow. Basically, only surface runoff occures in the catchment during the initial phase of
Ajami, H.; Sharma, A.
A computationally efficient, semi-distributed hydrologic modeling framework is developed to simulate water balance at a catchment scale. The Soil Moisture and Runoff simulation Toolkit (SMART) is based upon the delineation of contiguous and topologically connected Hydrologic Response Units (HRUs). In SMART, HRUs are delineated using thresholds obtained from topographic and geomorphic analysis of a catchment, and simulation elements are distributed cross sections or equivalent cross sections (ECS) delineated in first order sub-basins. ECSs are formulated by aggregating topographic and physiographic properties of the part or entire first order sub-basins to further reduce computational time in SMART. Previous investigations using SMART have shown that temporal dynamics of soil moisture are well captured at a HRU level using the ECS delineation approach. However, spatial variability of soil moisture within a given HRU is ignored. Here, we examined a number of disaggregation schemes for soil moisture distribution in each HRU. The disaggregation schemes are either based on topographic based indices or a covariance matrix obtained from distributed soil moisture simulations. To assess the performance of the disaggregation schemes, soil moisture simulations from an integrated land surface-groundwater model, ParFlow.CLM in Baldry sub-catchment, Australia are used. ParFlow is a variably saturated sub-surface flow model that is coupled to the Common Land Model (CLM). Our results illustrate that the statistical disaggregation scheme performs better than the methods based on topographic data in approximating soil moisture distribution at a 60m scale. Moreover, the statistical disaggregation scheme maintains temporal correlation of simulated daily soil moisture while preserves the mean sub-basin soil moisture. Future work is focused on assessing the performance of this scheme in catchments with various topographic and climate settings.
Ferreira, Carla S. S.; Walsh, Rory P. D.; Shakesby, Richard A.; Steenhuis, Tammo S.; Ferreira, António J. D.; Coelho, Celeste O. A.
.063mm fraction was considered equivalent to the suspended sediment load during storm events. The elemental composition (33 elements) of each fraction was assessed using a Niton X-ray fluorescence analyzer. The results were used to identify distinctive composite signatures of each tributary catchment and their influence on the geochemistry of the catchment outlet bed-sediment was explored. An unmixing model was applied to estimate the relative contribution of each tributary to channel-stored sediment at the catchment outlet. Many of the chemical elements analysed, including Zr, Sr, Zn and Ti, showed significant differences between sandstone and limestone areas. The closeness of values at the catchment outlet to those of sandstone stream bed-sediment indicates that most of the current catchment erosion is derived from the sandstone area. This is supported by the higher measured discharges and suspended sediment concentrations in storm events from the latter. Eroded sediments from urban areas still under construction also showed distinctive characteristics. It is concluded that this methodology represents a potentially useful tool for river managers and policy-makers to detect and assess sediment sources in urbanized catchments.
Clapcott, Joanne E.; Goodwin, Eric O.; Harding, Jon S.
Coal mining activities can have severe and long-term impacts on freshwater ecosystems. At the individual stream scale, these impacts have been well studied; however, few attempts have been made to determine the predictors of mine impacts at a regional scale. We investigated whether catchment-scale measures of mining impacts could be used to predict biological responses. We collated data from multiple studies and analyzed algae, benthic invertebrate, and fish community data from 186 stream sites, including un-mined streams, and those associated with 620 mines on the West Coast of the South Island, New Zealand. Algal, invertebrate, and fish richness responded to mine impacts and were significantly higher in un-mined compared to mine-impacted streams. Changes in community composition toward more acid- and metal-tolerant species were evident for algae and invertebrates, whereas changes in fish communities were significant and driven by a loss of nonmigratory native species. Consistent catchment-scale predictors of mining activities affecting biota included the time post mining (years), mining density (the number of mines upstream per catchment area), and mining intensity (tons of coal production per catchment area). Mining was associated with a decline in stream biodiversity irrespective of catchment size, and recovery was not evident until at least 30 years after mining activities have ceased. These catchment-scale predictors can provide managers and regulators with practical metrics to focus on management and remediation decisions.
Clapcott, Joanne E; Goodwin, Eric O; Harding, Jon S
Coal mining activities can have severe and long-term impacts on freshwater ecosystems. At the individual stream scale, these impacts have been well studied; however, few attempts have been made to determine the predictors of mine impacts at a regional scale. We investigated whether catchment-scale measures of mining impacts could be used to predict biological responses. We collated data from multiple studies and analyzed algae, benthic invertebrate, and fish community data from 186 stream sites, including un-mined streams, and those associated with 620 mines on the West Coast of the South Island, New Zealand. Algal, invertebrate, and fish richness responded to mine impacts and were significantly higher in un-mined compared to mine-impacted streams. Changes in community composition toward more acid- and metal-tolerant species were evident for algae and invertebrates, whereas changes in fish communities were significant and driven by a loss of nonmigratory native species. Consistent catchment-scale predictors of mining activities affecting biota included the time post mining (years), mining density (the number of mines upstream per catchment area), and mining intensity (tons of coal production per catchment area). Mining was associated with a decline in stream biodiversity irrespective of catchment size, and recovery was not evident until at least 30 years after mining activities have ceased. These catchment-scale predictors can provide managers and regulators with practical metrics to focus on management and remediation decisions.
Wood, Eric F.
Particular attention is given to the spatial variability that affects the representation of water balance at the catchment scale in the context of macroscale water-balance modeling. Remotely sensed data are employed for parameterization, and the resulting model is developed so that subgrid spatial variability is preserved and therefore influences the grid-scale fluxes of the model. The model permits the quantitative evaluation of the surface-atmospheric interactions related to the large-scale hydrologic water balance.
Yang Yang; Theodore A. Endreny; David J. Nowak
This article presents snow hydrology updates made to iTree-Hydro, previously called the Urban Forest EffectsâHydrology model. iTree-Hydro Version 1 was a warm climate model developed by the USDA Forest Service to provide a process-based planning tool with robust water quantity and quality predictions given data limitations common to most urban areas. Cold climate...
Doell, P.; Lehner, B.; Kaspar, F.; Vassolo, S.
Freshwater availability has been recognized as a global issue, and its consistent quan- tification not only in individual river basins but also at the global scale is required to support the sustainable use of water. The Global Hydrology Model WGHM, which is a submodel of the global water use and availability model WaterGAP 2, computes sur- face runoff, groundwater recharge and river discharge at a spatial resolution of 0.5. WGHM is based on the best global data sets currently available, including a newly developed drainage direction map and a data set of wetlands, lakes and reservoirs. It calculates both natural and actual discharge by simulating the reduction of river discharge by human water consumption (as computed by the water use submodel of WaterGAP 2). WGHM is calibrated against observed discharge at 724 gauging sta- tions (representing about 50% of the global land area) by adjusting a parameter of the soil water balance. It not only computes the long-term average water resources but also water availability indicators that take into account the interannual and seasonal variability of runoff and discharge. The reliability of the model results is assessed by comparing observed and simulated discharges at the calibration stations and at se- lected other stations. We conclude that reliable results can be obtained for basins of more than 20,000 km2. In particular, the 90% reliable monthly discharge is simu- lated well. However, there is the tendency that semi-arid and arid basins are modeled less satisfactorily than humid ones, which is partially due to neglecting river channel losses and evaporation of runoff from small ephemeral ponds in the model. Also, the hydrology of highly developed basins with large artificial storages, basin transfers and irrigation schemes cannot be simulated well. The seasonality of discharge in snow- dominated basins is overestimated by WGHM, and if the snow-dominated basin is uncalibrated, discharge is likely to be underestimated
Bruland, O.; Kolberg, S.; Engeland, K.; Gragne, A. S.; Liston, G.; Sand, K.; Tøfte, L.; Alfredsen, K.
Operationally the main purpose of hydrological models is to provide runoff forecasts. The quality of the model state and the accuracy of the weather forecast together with the model quality define the runoff forecast quality. Input and model errors accumulate over time and may leave the model in a poor state. Usually model states can be related to observable conditions in the catchment. Updating of these states, knowing their relation to observable catchment conditions, influence directly the forecast quality. Norway is internationally in the forefront in hydropower scheduling both on short and long terms. The inflow forecasts are fundamental to this scheduling. Their quality directly influence the producers profit as they optimize hydropower production to market demand and at the same time minimize spill of water and maximize available hydraulic head. The quality of the inflow forecasts strongly depends on the quality of the models applied and the quality of the information they use. In this project the focus has been to improve the quality of the model states which the forecast is based upon. Runoff and snow storage are two observable quantities that reflect the model state and are used in this project for updating. Generally the methods used can be divided in three groups: The first re-estimates the forcing data in the updating period; the second alters the weights in the forecast ensemble; and the third directly changes the model states. The uncertainty related to the forcing data through the updating period is due to both uncertainty in the actual observation and to how well the gauging stations represent the catchment both in respect to temperatures and precipitation. The project looks at methodologies that automatically re-estimates the forcing data and tests the result against observed response. Model uncertainty is reflected in a joint distribution of model parameters estimated using the Dream algorithm.
Westerhoff, R.; Mu, Q.
Long-term time series of satellite evapotranspiration (ET) were trialled for their additional value in aquifer characterisation on the catchment scale in New Zealand. In a simple chain-of-events approach yearly natural groundwater recharge was calculated with a 1x1km resolution. The chain consisted of (1) rainfall; (2) runoff due to slope; (3) actual ET; (4) soil permeability and water holding capacity; and (5) hydraulic conductivity of the deeper geology. As ET is a large part of the water balance (in New Zealand on average appr. 50% of rainfall), high resolution and high quality ET data is important for estimating groundwater recharge. Most global satellite data already embed a pseudo-model with coarse, global, input data. An example is ET data from the MODIS MOD16 product: although the spatial footprint of the satellite data is 1x1 km, input data to calculate ET contains global meteorology data. These data do not capture the extreme diversity in the New Zealand climate, where yearly rainfall and ET can change considerably over small distances. However, enough national ground-observed data are available to improve the MOD16 data. We improved monthly MOD16 ET by using the satellite data pattern as an interpolator between approximately 80 ground stations. Simple least squares fitting gave the best result. The added value of satellite data is obvious: the corrected MOD16 ET data have much higher spatial resolution and vegetation cover and growth is taken into account better.We then used national data to estimate 1x1km natural groundwater recharge: the corrected MOD16 PET and AET, in-situ based precipitation models; soil maps; geology maps; and (satellite-based) elevation. Validation with lysimeters and existing sub-catchment model output data looks promising, and further improvement with satellite soil moisture to estimate monthly recharge is underway. This work was done in the SMART Aquifer Characterisation (SAC) programme, a six-year research project funded by the
Bogena, Heye R.; Huisman, Johan A.; Rosenbaum, Ulrike; Weuthen, Ansgar; Vereecken, Harry
Soil water content plays a key role in partitioning water and energy fluxes and controlling the pattern of groundwater recharge. Despite the importance of soil water content, it is not yet measured in an operational way at larger scales. The aim of this paper is to present the potential of real-time monitoring for the analysis of soil moisture patterns at the catchment scale using the recently developed wireless sensor network SoilNet , . SoilNet is designed to measure soil moisture, salinity and temperature in several depths (e.g. 5, 20 and 50 cm). Recently, a small forest catchment Wüstebach (~27 ha) has been instrumented with 150 sensor nodes and more than 1200 soil sensors in the framework of the Transregio32 and the Helmholtz initiative TERENO (Terrestrial Environmental Observatories). From August to November 2009, more than 6 million soil moisture measurements have been performed. We will present first results from a statistical and geostatistical analysis of the data. The observed spatial variability of soil moisture corresponds well with the 800-m scale variability described in . The very low scattering of the standard deviation versus mean soil moisture plots indicates that sensor network data shows less artificial soil moisture variations than soil moisture data originated from measurement campaigns. The variograms showed more or less the same nugget effect, which indicates that the sum of the sub-scale variability and the measurement error is rather time-invariant. Wet situations showed smaller spatial variability, which is attributed to saturated soil water content, which poses an upper limit and is typically not strongly variable in headwater catchments with relatively homogeneous soil. The spatiotemporal variability in soil moisture at 50 cm depth was significantly lower than at 5 and 20 cm. This finding indicates that the considerable variability of the top soil is buffered deeper in the soil due to lateral and vertical water fluxes
Cammeraat, L. H.
Geomorphological processes including soil erosion are active in specific spatio-temporal domains and lead eventually to various emerging soil properties and landscape structures which are evidently also scale dependent. In this study the scale and threshold dependency of landscapes will be compared involving three different landscapes from the temperate, Mediterranean and semi-arid Sahelian geo-ecosystems, especially with regard to the connectivity of water and sediment redistribution. The dominant processes and feed-backs interwoven with soil erosion processes will be discussed from a hierarchical theory type of approach. However, current processes are almost always affected by the presence of inherited soil and landscape properties that might be formed under very different climatological conditions than those that are dominant today. Another important factor in these processes is the role of animals and plants. It will be shown that in all discussed geo-ecosystems plants and animals can be seen as geo-ecosystem engineers and are also important at broader scales with respect to runoff generation and sediment transport. For the temperate zone a case study from the cuesta landscape of the Paris Basin will be discussed, showing that fine scale, soil physico-chemical processes, soil animal and vegetation related processes lead to the emergence of partial areas and also play an important role in the formation of the cuestas itself. For the Mediterranean a case study is discussed where vegetation pattern heterogeneity determines water and sediment distribution from the patch to the sub-catchment scale leading to the emergence of either sheetwash generated slopes (pediments) or concentrated flow generated slopes (gullies), but where inherited landscape elements such as pediments with calcretes strongly affect runoff generation and the availability of sediments and hence have a strong impact on the sediment redistribution and measured erosion rates that strongly vary with
GIS-based hydrologic modeling offers a convenient means of assessing the impacts associated with land-cover/use change for environmental planning efforts. Alternative future scenarios can be used as input to hydrologic models and compared with existing conditions to evaluate pot...
Ge Sun; Hans Rierkerk; Nicholas B. Comerford
The great temporal and spatial variability of pine flatwoods hydrology suggests traditional short-term field methods may not be effective in evaluating the hydrologic effects of forest management. The flatwoods model was developed, calibrated and validated specifically for the cypress wetland-pine upland landscape. The model was applied to two typical flatwoods sites...
Vithanage, J.; Miller, S. N.; Paige, G. B.; Liu, T.
We present a novel way to simulate the effects of rangeland management decisions in a GIS-based hydrologic modeling toolkit. We have implemented updates to the Automated Geospatial Watershed Assessment tool (AGWA) in which a landscape can be broken into management units (e.g., high intensity grazing, low intensity grazing, fire management, and unmanaged), each of which is assigned a different hydraulic conductivity (Ks) parameter in KINEmatic Runoff and EROSion model (KINEROS2). These updates are designed to provide modeling support to land managers tasked with rangeland watershed management planning and/or monitoring, and evaluation of water resources management. Changes to hydrologic processes and resulting hydrographs and sedigraphs are simulated within the AGWA framework. Case studies are presented in which a user selects various management scenarios and design storms, and the model identifies areas that become susceptible to change as a consequence of management decisions. The baseline (unmanaged) scenario is built using commonly available GIS data, after which the watershed is subdivided into management units. We used an array of design storms with various return periods and frequencies to evaluate the impact of management practices while changing the scale of watershed. Watershed parameters governing interception, infiltration, and surface runoff were determined with the aid of literature published on research studies carried out in the Walnut Gulch Experimental Watershed in southeast Arizona. We observed varied, but significant changes in hydrological responses (runoff) with different management practices as well with varied scales of watersheds. Results show that the toolkit can be used to quantify potential hydrologic change as a result of unitized land use decision-making.
Sharp, John M.
Lists many recent research projects in hydrology, including flow in fractured media, improvements in remote-sensing techniques, effects of urbanization on water resources, and developments in drainage basins. (MLH)
Cristiano, Elena; ten Veldhuis, Marie-Claire; Gaitan, Santiago; Ochoa Rodriguez, Susana; van de Giesen, Nick
Rainfall variability in space and time, in relation to catchment characteristics and model complexity, plays an important role in explaining the sensitivity of hydrological response in urban areas. In this work we present a new approach to classify rainfall variability in space and time and we use this classification to investigate rainfall aggregation effects on urban hydrological response. Nine rainfall events, measured with a dual polarimetric X-Band radar instrument at the CAESAR site (Cabauw Experimental Site for Atmospheric Research, NL), were aggregated in time and space in order to obtain different resolution combinations. The aim of this work was to investigate the influence that rainfall and catchment scales have on hydrological response in urban areas. Three dimensionless scaling factors were introduced to investigate the interactions between rainfall and catchment scale and rainfall input resolution in relation to the performance of the model. Results showed that (1) rainfall classification based on cluster identification well represents the storm core, (2) aggregation effects are stronger for rainfall than flow, (3) model complexity does not have a strong influence compared to catchment and rainfall scales for this case study, and (4) scaling factors allow the adequate rainfall resolution to be selected to obtain a given level of accuracy in the calculation of hydrological response.
Mclaughlin, D. L.; Jones, C. N.; Evenson, G. R.; Golden, H. E.; Lane, C.; Alexander, L. C.; Lang, M.
Combined geospatial and modeling approaches are required to fully enumerate wetland hydrologic connectivity and downstream effects. Here, we utilized both geospatial analysis and hydrologic modeling to explore drivers and consequences of modified surface water connectivity in the Delmarva Peninsula, with particular focus on increased connectivity via pervasive wetland ditching. Our geospatial analysis quantified both historical and contemporary wetland storage capacity across the region, and suggests that over 70% of historical storage capacity has been lost due to this ditching. Building upon this analysis, we applied a catchment-scale model to simulate implications of reduced storage capacity on catchment-scale hydrology. In short, increased connectivity (and concomitantly reduced wetland water storage capacity) decreases catchment inundation extent and spatial heterogeneity, shortens cumulative residence times, and increases downstream flow variation with evident effects on peak and baseflow dynamics. As such, alterations in connectivity have implications for hydrologically mediated functions in catchments (e.g., nutrient removal) and downstream systems (e.g., maintenance of flow for aquatic habitat). Our work elucidates such consequences in Delmarva Peninsula while also providing new tools for broad application to target wetland restoration and conservation. Views expressed are those of the authors and do not necessarily reflect policies of the US EPA or US FWS.
AghaKouchak, A.; Nakhjiri, N.; Habib, E. H.
This presentation provides an overview of a hands-on modeling tool developed for students in civil engineering and earth science disciplines to help them learn the fundamentals of hydrologic processes, model calibration, sensitivity analysis, uncertainty assessment, and practice conceptual thinking in solving engineering problems. The toolbox includes two simplified hydrologic models, namely HBV-EDU and HBV-Ensemble, designed as a complement to theoretical hydrology lectures. The models provide an interdisciplinary application-oriented learning environment that introduces the hydrologic phenomena through the use of a simplified conceptual hydrologic model. The toolbox can be used for in-class lab practices and homework assignments, and assessment of students' understanding of hydrological processes. Using this modeling toolbox, students can gain more insights into how hydrological processes (e.g., precipitation, snowmelt and snow accumulation, soil moisture, evapotranspiration and runoff generation) are interconnected. The educational toolbox includes a MATLAB Graphical User Interface (GUI) and an ensemble simulation scheme that can be used for teaching more advanced topics including uncertainty analysis, and ensemble simulation. Both models have been administered in a class for both in-class instruction and a final project, and students submitted their feedback about the toolbox. The results indicate that this educational software had a positive impact on students understanding and knowledge of hydrology.
Petersen, M. F.; Eriksson, E.; Binning, P. J.; Bjerg, P. L.
The water quality of surface waters is threatened by multiple anthropogenic pollutants and the large variety of pollutants challenges the monitoring and assessment of the water quality. The aim of this study was to characterize and quantify both point and diffuse sources of micropollutants impacting the water quality of a stream at catchment scale. Grindsted stream in western Jutland, Denmark was used as a study site. The stream passes both urban and agricultural areas and is impacted by severe groundwater contamination in Grindsted city. Along a 12 km reach of Grindsted stream, the potential pollution sources were identified including a pharmaceutical factory site with a contaminated old drainage ditch, two waste deposits, a wastewater treatment plant, overflow structures, fish farms, industrial discharges and diffuse agricultural and urban sources. Six water samples were collected along the stream and analyzed for general water quality parameters, inorganic constituents, pesticides, sulfonamides, chlorinated solvents, BTEXs, and paracetamol and ibuprofen. The latter two groups were not detected. The general water quality showed typical conditions for a stream in western Jutland. Minor impacts by releases of organic matter and nutrients were found after the fish farms and the waste water treatment plant. Nickel was found at concentrations 5.8 - 8.8 μg/l. Nine pesticides and metabolites of both agricultural and urban use were detected along the stream; among these were the two most frequently detected and some rarely detected pesticides in Danish water courses. The concentrations were generally consistent with other findings in Danish streams and in the range 0.01 - 0.09 μg/l; except for metribuzin-diketo that showed high concentrations up to 0.74 μg/l. The groundwater contamination at the pharmaceutical factory site, the drainage ditch and the waste deposits is similar in composition containing among others sulfonamides and chlorinated solvents (including vinyl
Khatiwada, K. R.; Nepal, S.; Panthi, J., Sr.; Shrestha, M.
Hydrological modelling plays an important role in understanding hydrological processes of a catchment. In the context of climate change, the understanding of hydrological characteristic of the catchment is very vital to understand how the climate change will affect the hydrological regime. This research facilitates in better understanding of the hydrological system dynamics of a himalayan mountainous catchment in western Nepal. The Karnali River, longest river flowing inside Nepal, is one of the three major basins of Nepal, having the area of 45269 sq. km. is unique. The basin has steep topography and high mountains to the northern side. The 40% of the basin is dominated by forest land while other land cover are: grass land, bare rocky land etc. About 2% of the areas in basin is covered by permanent glacier apart from that about 12% of basin has the snow and ice cover. There are 34 meteorological stations distributed across the basin. A process oriented distributed J2000 hydrologial model has been applied to understand the hydrological system dynamics. The model application provides distributed output of various hydrological components. The J2000 model applies Hydrological Response Unit (HRU) as a modelling entity. With 6861 HRU and 1010 reaches, the model was calibrated (1981-1999) and validated (2000-2004) at a daily scale using split-sample test. The model is able to capture the overall hydrological dynamics well. The rising limbs and recession limbs are simulated equally and with satisfactory ground water conditions. Based on the graphical and statistical evaluation of the model performance the model is able to simulate hydrological processes fairly well. Calibration shows that Nash Sutcliffe efficiency is 0.91, coefficient of determination is 0.92 Initial observation shows that during the pre-monsoon season(March to May) the glacial runoff is 25% of the total discharge while in the monsoon(June to September) season it is only 13%. The surface runoff
Mendez-Barroso, L. A.; Vivoni, E.; Robles-Morua, A.; Yepez, E. A.; Rodriguez, J. C.; Watts, C.; Saiz-Hernandez, J.
Seasonal vegetation changes highly affect the energy and hydrologic fluxes in semiarid regions around the world. Accounting for different water use strategies among drought-deciduous ecosystems is important for understanding how these exploit the temporally brief and localized rainfall pulses of the North American Monsoon (NAM). Furthermore, quantifying these plant-water relations can help elucidate the spatial patterns of ecohydrological processes at catchment scale in the NAM region. In this effort, we focus on the San Miguel river basin (~ 3500 km2) in Sonora, Mexico, which exhibits seasonal vegetation greening that varies across ecosystems organized along mountain fronts. To assess the spatial variability of ecohydrological conditions, we relied on diverse tools that included multi-temporal remote sensing observations, model-based meteorological forcing, ground-based water and energy flux measurements and hydrologic simulations carried out at multiple scales. We evaluated the impact of seasonal vegetation dynamics on evapotranspiration (ET), its partitioning into soil evaporation (E) and plant transpiration (T), as well as their spatiotemporal patterns over the course of the NAM season. We utilized ground observations of soil moisture and evapotranspiration estimated by the eddy covariance method at two sites, as well as inferences of ET partitioning from stable isotope measurements, to test the numerical simulations. We found that ecosystem phenological differences lead to variations in the time to peak in transpiration during a season and in the overall seasonal ratio of transpiration to evapotranspiration (T/ET). A sensitivity analysis of the numerical simulations revealed that vegetation cover and the soil moisure threshold at which stomata close exert strong controls on the seasonal dominance of transpiration or evaporation. The dynamics of ET and its partitioning are then mapped spatially revealing that mountain front ecosystems utilize water differently
Engman, Edwin T.
Many hydrologic processes display a unique signature that is detectable with microwave remote sensing. These signatures are in the form of the spatial and temporal distributions of surface soil moisture and portray the spatial heterogeneity of hydrologic processes and properties that one encounters in drainage basins. The hydrologic processes that may be detected include ground water recharge and discharge zones, storm runoff contributing areas, regions of potential and less than potential ET, and information about the hydrologic properties of soils and heterogeneity of hydrologic parameters. Microwave remote sensing has the potential to detect these signatures within a basin in the form of volumetric soil moisture measurements in the top few cm. These signatures should provide information on how and where to apply soil physical parameters in distributed and lumped parameter models and how to subdivide drainage basins into hydrologically similar sub-basins.
Water in its different forms has always been a source of wonder, curiosity and practical concern for humans everywhere. Hydrology - An Introduction presents a coherent introduction to the fundamental principles of hydrology, based on the course that Wilfried Brutsaert has taught at Cornell University for the last thirty years. Hydrologic phenomena are dealt with at spatial and temporal scales at which they occur in nature. The physics and mathematics necessary to describe these phenomena are introduced and developed, and readers will require a working knowledge of calculus and basic fluid mechanics. The book will be invaluable as a textbook for entry-level courses in hydrology directed at advanced seniors and graduate students in physical science and engineering. In addition, the book will be more broadly of interest to professional scientists and engineers in hydrology, environmental science, meteorology, agronomy, geology, climatology, oceanology, glaciology and other earth sciences. Emphasis on fundamentals Clarification of the underlying physical processes Applications of fluid mechanics in the natural environment
Li, Zhen; Yue, Jianping; Li, Wang; Lu, Dekai; Li, Xiaogen
The 0.5° × 0.5° gridded hydrological loading from Global Land Surface Discharge Model (LSDM) mass distributions is adopted for 32 GPS sites on the Eurasian plate from January 2010 to January 2014. When the heights of these sites that have been corrected for the effects of non-tidal atmospheric and ocean loading are adjusted by the hydrological loading deformation, more than one third of the root-mean-square (RMS) values of the GPS height variability become larger. After analyzing the results by continuous wavelet transform (CWT) and wavelet transform coherence (WTC), we confirm that hydrological loading primarily contributes to the annual variations in GPS heights. Further, the cross wavelet transform (XWT) is used to investigate the relative phase between the time series of GPS heights and hydrological deformation, and it is indicated that the annual oscillations in the two time series are physically related for some sites; other geophysical effect, GPS systematic errors and hydrological modeling errors could result in the phase asynchrony between GPS and hydrological loading signals for the other sites. Consequently, the phase asynchrony confirms that the annual fluctuations in GPS observations result from a combination of geophysical signals and systematic errors.
Hydrologic responses vary spatially and temporally according to watershed characteristics. In this study, the hydrologic models that we developed earlier for the Little Miami River (LMR) and Las Vegas Wash (LVW) watersheds were used for detail sensitivity analyses. To compare the...
Seth J. Wenger; Charles H. Luce; Alan F. Hamlet; Daniel J. Isaak; Helen M. Neville
Stream hydrology strongly affects the structure of aquatic communities. Changes to air temperature and precipitation driven by increased greenhouse gas concentrations are shifting timing and volume of streamflows potentially affecting these communities. The variable infiltration capacity (VIC) macroscale hydrologic model has been employed at regional scales to describe...
Eisenbies, Mark H.; Hughes, W. Brian
Hydrologic process are the main determinants of the type of wetland located on a site. Precipitation, groundwater, or flooding interact with soil properties and geomorphic setting to yield a complex matrix of conditions that control groundwater flux, water storage and discharge, water chemistry, biotic productivity, biodiversity, and biogeochemical cycling. Hydroperiod affects many abiotic factors that in turn determine plant and animal species composition, biodiversity, primary and secondary productivity, accumulation, of organic matter, and nutrient cycling. Because the hydrologic regime has a major influence on wetland functioning, understanding how hydrologic changes influence ecosystem processes is essential, especially in light of the pressures placed on remaining wetlands by society's demands for water resources and by potential global changes in climate.
Bormann, H.; Faß, T.; Giertz, S.; Junge, B.; Diekkrüger, B.; Reichert, B.; Skowronek, A.
This paper presents the concept, first results and perspectives of the hydrological sub-project of the IMPETUS-Benin project which is part of the GLOWA program funded by the German ministry of education and research. In addition to the research concept, first results on field hydrology, pedology, hydrogeology and hydrological modelling are presented, focusing on the understanding of the actual hydrological processes. For analysing the processes a 30 km 2 catchment acting as a super test site was chosen which is assumed to be representative for the entire catchment of about 15,000 km 2. First results of the field investigations show that infiltration, runoff generation and soil erosion strongly depend on land cover and land use which again influence the soil properties significantly. A conceptual hydrogeological model has been developed summarising the process knowledge on runoff generation and subsurface hydrological processes. This concept model shows a dominance of fast runoff components (surface runoff and interflow), a groundwater recharge along preferential flow paths, temporary interaction between surface and groundwater and separate groundwater systems on different scales (shallow, temporary groundwater on local scale and permanent, deep groundwater on regional scale). The findings of intensive measurement campaigns on soil hydrology, groundwater dynamics and soil erosion have been integrated into different, scale-dependent hydrological modelling concepts applied at different scales in the target region (upper Ouémé catchment in Benin, about 15,000 km 2). The models have been applied and successfully validated. They will be used for integrated scenario analyses in the forthcoming project phase to assess the impacts of global change on the regional water cycle and on typical problem complexes such as food security in West African countries.
Rouf, T.; Maggioni, V.; Houser, P.; Mei, Y.
Developing a predictive capability for terrestrial hydrology across landscapes, with water, energy and nutrients as the drivers of these dynamic systems, faces the challenge of scaling meter-scale process understanding to practical modeling scales. Hyper-resolution land surface modeling can provide a framework for addressing science questions that we are not able to answer with coarse modeling scales. In this study, we develop a hyper-resolution forcing dataset from coarser resolution products using a physically based downscaling approach. These downscaling techniques rely on correlations with landscape variables, such as topography, roughness, and land cover. A proof-of-concept has been implemented over the Oklahoma domain, where high-resolution observations are available for validation purposes. Hourly NLDAS (North America Land Data Assimilation System) forcing data (i.e., near-surface air temperature, pressure, and humidity) have been downscaled to 500m resolution over the study area for 2015-present. Results show that correlation coefficients between the downscaled temperature dataset and ground observations are consistently higher than the ones between the NLDAS temperature data at their native resolution and ground observations. Not only correlation coefficients are higher, but also the deviation around the 1:1 line in the density scatterplots is smaller for the downscaled dataset than the original one with respect to the ground observations. Results are therefore encouraging as they demonstrate that the 500m temperature dataset has a good agreement with the ground information and can be adopted to force the land surface model for soil moisture estimation. The study has been expanded to wind speed and direction, incident longwave and shortwave radiation, pressure, and precipitation. Precipitation is well known to vary dramatically with elevation and orography. Therefore, we are pursuing a downscaling technique based on both topographical and vegetation
The Pacific Northwest Hydrologic Landscapes (PNW HL) at the assessment unit scale has provided a solid conceptual classification framework to relate and transfer hydrologically meaningful information between watersheds without access to streamflow time series. A collection of techniques were applied to the HL assessment unit composition in watersheds across the Pacific Northwest to aggregate the hydrologic behavior of the Hydrologic Landscapes from the assessment unit scale to the watershed scale. This non-trivial solution both emphasizes HL classifications within the watershed that provide that majority of moisture surplus/deficit and considers the relative position (upstream vs. downstream) of these HL classifications. A clustering algorithm was applied to the HL-based characterization of assessment units within 185 watersheds to help organize watersheds into nine classes hypothesized to have similar hydrologic behavior. The HL-based classes were used to organize and describe hydrologic behavior information about watershed classes and both predictions and validations were independently performed with regard to the general magnitude of six hydroclimatic signature values. A second cluster analysis was then performed using the independently calculated signature values as similarity metrics, and it was found that the six signature clusters showed substantial overlap in watershed class membership to those in the HL-based classes. One hypothesis set forward from thi
Selle, B.; Muttil, N.
Genetic Programming is able to systematically explore many alternative model structures of different complexity from available input and response data. We hypothesised that genetic programming can be used to test the structure hydrological models and to identify dominant processes in hydrological systems. To test this, genetic programming was used to analyse a data set from a lysimeter experiment in southeastern Australia. The lysimeter experiment was conducted to quantify the deep percolation response under surface irrigated pasture to different soil types, water table depths and water ponding times during surface irrigation. Using genetic programming, a simple model of deep percolation was consistently evolved in multiple model runs. This simple and interpretable model confirmed the dominant process contributing to deep percolation represented in a conceptual model that was published earlier. Thus, this study shows that genetic programming can be used to evaluate the structure of hydrological models and to gain insight about the dominant processes in hydrological systems.
Rivera Villarreyes, C. A.; Baroni, G.; Oswald, S. E.
Soil water content at the plot or hill-slope scale is an important link between local vadose zone hydrology and catchment hydrology. However, so far only few methods are on the way to close this gap between point measurements and remote sensing. One new measurement methodology for integral quantifications of mean areal soil water content at the intermediate catchment scale is the aboveground sensing of cosmic-ray neutrons, more precisely ground albedo neutron sensing (GANS). Ground albedo natural neutrons, are generated by collisions of secondary cosmic rays with land surface materials (soil, water, biomass, snow, etc). Neutrons measured at the air/ground interface correlate with soil moisture contained in a footprint of ca. 600 m diameter and a depth ranging down to a few decimeters. This correlation is based on the crucial role of hydrogen as neutron moderator compared to others landscape materials. The present study performed ground albedo neutron sensing in different locations in Germany under different vegetative situations (cropped and bare field) and different seasonal conditions (summer, autumn and winter). Ground albedo neutrons were measured at (i) a farmland close to Potsdam (Brandenburg, Germany) cropped with corn in 2010 and sunflowers in 2011, and (ii) a mountainous farmland catchment (Schaefertal, Harz Mountains, Germany) in 2011. In order to test this method, classical soil moisture devices and meteorological data were used for comparison. Moreover, calibration approach, and transferability of calibration parameters to different times and locations are also evaluated. Our observations suggest that GANS can overcome the lack of data for hydrological processes at the intermediate scale. Soil water content from GANS compared quantitatively with mean water content values derived from a network of classical devices (RMSE = 0.02 m3/m3 and r2 = 0.98) in three calibration periods with cropped-field conditions. Then, same calibration parameters corresponded
Mark H. Eisenbies; W. Brian Hughes
Hydrologic processes are the main determinants of the type of wetland located on a site. Precipitation, groundwater, or flooding interact with soil properties and geomorphic setting to yield a complex matrix of conditions that control groundwater flux, water storage and discharge, water chemistry, biotic produvtivity, biodiversity, and biogeochemical cycling....
Selle, Benny; Muttil, Nitin
SummaryGenetic Programming is able to systematically explore many alternative model structures of different complexity from available input and response data. We hypothesised that Genetic Programming can be used to test the structure of hydrological models and to identify dominant processes in hydrological systems. To test this, Genetic Programming was used to analyse a data set from a lysimeter experiment in southeastern Australia. The lysimeter experiment was conducted to quantify the deep percolation response under surface irrigated pasture to different soil types, watertable depths and water ponding times during surface irrigation. Using Genetic Programming, a simple model of deep percolation was recurrently evolved in multiple Genetic Programming runs. This simple and interpretable model supported the dominant process contributing to deep percolation represented in a conceptual model that was published earlier. Thus, this study shows that Genetic Programming can be used to evaluate the structure of hydrological models and to gain insight about the dominant processes in hydrological systems.
Seidl, Roman; Barthel, Roland
Interdisciplinary scientific and societal knowledge plays an increasingly important role in global change research. Also, in the field of water resources interdisciplinarity as well as cooperation with stakeholders from outside academia have been recognized as important. In this contribution, we revisit an integrated regional modelling system (DANUBIA), which was developed by an interdisciplinary team of researchers and relied on stakeholder participation in the framework of the GLOWA-Danube project from 2001 to 2011 (Mauser and Prasch 2016). As the model was developed before the current increase in literature on participatory modelling and interdisciplinarity, we ask how a socio-hydrology approach would have helped and in what way it would have made the work different. The present contribution firstly presents the interdisciplinary concept of DANUBIA, mainly with focus on the integration of human behaviour in a spatially explicit, process-based numerical modelling system (Roland Barthel, Janisch, Schwarz, Trifkovic, Nickel, Schulz, and Mauser 2008; R. Barthel, Nickel, Meleg, Trifkovic, and Braun 2005). Secondly, we compare the approaches to interdisciplinarity in GLOWA-Danube with concepts and ideas presented by socio-hydrology. Thirdly, we frame DANUBIA and a review of key literature on socio-hydrology in the context of a survey among hydrologists (N = 184). This discussion is used to highlight gaps and opportunities of the socio-hydrology approach. We show that the interdisciplinary aspect of the project and the participatory process of stakeholder integration in DANUBIA were not entirely successful. However, important insights were gained and important lessons were learnt. Against the background of these experiences we feel that in its current state, socio-hydrology is still lacking a plan for knowledge integration. Moreover, we consider necessary that socio-hydrology takes into account the lessons learnt from these earlier examples of knowledge integration
Yan, Chang-An; Zhang, Wanchang; Zhang, Zhijie
A watershed hydrological model, hydrological simulation program-Fortran (HSPF), was applied to simulate the spatial and temporal variation of hydrological processes in the Jiaoyi watershed of Huaihe River Basin, the heaviest shortage of water resources and polluted area in China. The model was calibrated using the years 2001–2004 and validated with data from 2005 to 2006. Calibration and validation results showed that the model generally simulated mean monthly and daily runoff precisely due to the close matching hydrographs between simulated and observed runoff, as well as the excellent evaluation indicators such as Nash-Sutcliffe efficiency (NSE), coefficient of correlation (R 2), and the relative error (RE). The similar simulation results between calibration and validation period showed that all the calibrated parameters had a certain representation in Jiaoyi watershed. Additionally, the simulation in rainy months was more accurate than the drought months. Another result in this paper was that HSPF was also capable of estimating the water balance components reasonably and realistically in space through the whole watershed. The calibrated model can be used to explore the effects of climate change scenarios and various watershed management practices on the water resources and water environment in the basin. PMID:25013863
Wenger, Seth J.; Luce, Charles H.; Hamlet, Alan F.; Isaak, Daniel J.; Neville, Helen M.
Stream hydrology strongly affects the structure of aquatic communities. Changes to air temperature and precipitation driven by increased greenhouse gas concentrations are shifting timing and volume of streamflows potentially affecting these communities. The variable infiltration capacity (VIC) macroscale hydrologic model has been employed at regional scales to describe and forecast hydrologic changes but has been calibrated and applied mainly to large rivers. An important question is how well VIC runoff simulations serve to answer questions about hydrologic changes in smaller streams, which are important habitat for many fish species. To answer this question, we aggregated gridded VIC outputs within the drainage basins of 55 streamflow gages in the Pacific Northwest United States and compared modeled hydrographs and summary metrics to observations. For most streams, several ecologically relevant aspects of the hydrologic regime were accurately modeled, including center of flow timing, mean annual and summer flows and frequency of winter floods. Frequencies of high and low flows in the summer were not well predicted, however. Predictions were worse for sites with strong groundwater influence, and some sites showed errors that may result from limitations in the forcing climate data. Higher resolution (1/16th degree) modeling provided small improvements over lower resolution (1/8th degree). Despite some limitations, the VIC model appears capable of representing several ecologically relevant hydrologic characteristics in streams, making it a useful tool for understanding the effects of hydrology in delimiting species distributions and predicting the potential effects of climate shifts on aquatic organisms.
Blankenship, Doug; Sonnenthal, Eric
Archive contains thermal-mechanical simulation input/output files. Included are files which fall into the following categories: ( 1 ) Spreadsheets with various input parameter calculations ( 2 ) Final Simulation Inputs ( 3 ) Native-State Thermal-Hydrological Model Input File Folders ( 4 ) Native-State Thermal-Hydrological-Mechanical Model Input Files ( 5 ) THM Model Stimulation Cases See 'File Descriptions.xlsx' resource below for additional information on individual files.
Coron, Laurent; Perrin, Charles; Delaigue, Olivier; Andréassian, Vazken; Thirel, Guillaume
Lumped hydrological models are useful and convenient tools for research, engineering and educational purposes. They propose catchment-scale representations of the precipitation-discharge relationship. Thanks to their limited data requirements, they can be easily implemented and run. With such models, it is possible to simulate a number of hydrological key processes over the catchment with limited structural and parametric complexity, typically evapotranspiration, runoff, underground losses, etc. The Hydrology Group at Irstea (Antony) has been developing a suite of rainfall-runoff models over the past 30 years with the main objectives of designing models as efficient as possible in terms of streamflow simulation, applicable to a wide range of catchments and having low data requirements. This resulted in a suite of models running at different time steps (from hourly to annual) applicable for various issues including water balance estimation, forecasting, simulation of impacts and scenario testing. Recently, Irstea has developed an easy-to-use R-package (R Core Team, 2015), called airGR, to make these models widely available. It includes: - the water balance annual GR1A (Mouehli et al., 2006), - the monthly GR2M (Mouehli, 2003) models, - three versions of the daily model, namely GR4J (Perrin et al., 2003), GR5J (Le Moine, 2008) and GR6J (Pushpalatha et al., 2011), - the hourly GR4H model (Mathevet, 2005), - a degree-day snow module CemaNeige (Valéry et al., 2014). The airGR package has been designed to facilitate the use by non-expert users and allow the addition of evaluation criteria, models or calibration algorithms selected by the end-user. Each model core is coded in FORTRAN to ensure low computational time. The other package functions (i.e. mainly the calibration algorithm and the efficiency criteria) are coded in R. The package is already used for educational purposes. The presentation will detail the main functionalities of the package and present a case
Driscoll, J. M.; Meixner, T.; Ferré, T. P. A.; Williams, M. W.; Sickman, J. O.; Molotch, N. P.; Jepsen, S. M.
The role of dynamic storage in catchment discharge response to earlier snowmelt timing has not been fully quantified. Green Lake 4 (GL4) and Emerald Lake Watershed (ELW) have similar high-elevation settings but GL4 has greater estimated storage capacity relative to ELW due to differences in physical structure. Daily catchment area-normalized input (modelled snowmelt estimates) and output (measured discharge) in conjunction with mineral weathering products (hydrochemical data) for eleven snowmelt seasons from GL4 (more storage) and ELW (less storage) were used to determine the role of dynamic storage at the catchment scale. Daily fluxes generally show snowmelt is greater than discharge initially, changing mid-season to discharge being greater than snowmelt, creating a counter-clockwise hysteresis loop for each snowmelt season. This hysteresis loop can be approximated with a least-squares fitted ellipse. The properties of fitted ellipses were used to quantify catchment response, which were then compared between catchments with different storage capacities (GL4 and ELW). The eccentricity of the fitted ellipses can be used to quantify delay between snowmelt and discharge due to connection to subsurface storage; narrower loops show minimal storage delay whereas wider loops show greater storage delay. Variability of mineral weathering products shows changes in contribution from stored water over the snowmelt season. Both catchments show a moderate linear correlation between fitted ellipse area and total snowmelt volume (GL4 R2=0.516, ELW R2=0.614). Ellipse eccentricity is more consistent among years in ELW (range=0.81-0.94) than in GL4 (range=0.54-0.95), indicating a more consistent hydrologic structure and connectivity to shallow storage at ELW. The linear correlation between seasonal eccentricity versus snowmelt timing is stronger in ELW than GL4 (R2=0.741 and 0.223, respectively). ELW shows hydrochemical response independent of snowmelt timing, whereas GL4 shows more
Pandolfo, Tamara J.; Kwak, Thomas J.; Cope, W. Gregory; Heise, Ryan J.; Nichols, Robert B.; Pacifici, Krishna
Conservation of freshwater unionid mussels presents unique challenges due to their distinctive life cycle, cryptic occurrence and imperilled status. Relevant ecological information is urgently needed to guide their management and conservation.We adopted a modelling approach, which is a novel application to freshwater mussels to enhance inference on rare species, by borrowing data among species in a hierarchical framework to conduct the most comprehensive occurrence analysis for freshwater mussels to date. We incorporated imperfect detection to more accurately examine effects of biotic and abiotic factors at multiple scales on the occurrence of 14 mussel species and the entire assemblage of the Tar River Basin of North Carolina, U.S.A.The single assemblage estimate of detection probability for all species was 0.42 (95% CI, 0.36–0.47) with no species- or site-specific detection effects identified. We empirically observed 15 mussel species in the basin but estimated total species richness at 21 (95% CI, 16–24) when accounting for imperfect detection.Mean occurrence probability among species ranged from 0.04 (95% CI, 0.01–0.16) for Alasmidonta undulata, an undescribed Lampsilis sp., and Strophitus undulatus to 0.67 (95% CI, 0.42–0.86) for Elliptio icterina. Median occurrence probability among sites was <0.30 for all species with the exception of E. icterina. Site occurrence probability generally related to mussel conservation status, with reduced occurrence for endangered and threatened species.Catchment-scale abiotic variables (stream power, agricultural land use) and species traits (brood time, host specificity, tribe) influenced the occurrence of mussel assemblages more than reach- or microhabitat-scale features.Our findings reflect the complexity of mussel ecology and indicate that habitat restoration alone may not be adequate for mussel conservation. Catchment-scale management can benefit an entire assemblage, but species-specific strategies may be
Reusser, Dominik; Buytaert, Wouter
In hydrology, basic equations and procedures keep being implemented from scratch by scientist, with the potential for errors and inefficiency. The use of libraries can overcome these problems. Other scientific disciplines such as mathematics and physics have benefited significantly from such an approach with freely available implementations for many routines. As an example, hydrological libraries could contain: Major representations of hydrological processes such as infiltration, sub-surface runoff and routing algorithms. Scaling functions, for instance to combine remote sensing precipitation fields with rain gauge data Data consistency checks Performance measures. Here we present a beginning for such a library implemented in the high level data programming language R. Currently, Top-model, data import routines for WaSiM-ETH as well basic visualization and evaluation tools are implemented. The design is such, that a definition of import scripts for additional models is sufficient to have access to the full set of evaluation and visualization tools.
Weerts, Albrecht; Schellekens, Jaap; Kockx, Arno; Hummel, Stef
Data assimilation (DA) holds considerable potential for improving hydrologic predictions (Liu et al., 2012) and increase the potential for early warning and/or smart water management. However, advances in hydrologic DA research have not yet been adequately or timely implemented in operational forecast systems to improve the skill of forecasts for better informed real-world decision making. The objective of this work is to highlight the development of a generic linkage of the open source OpenDA package and the open source community hydrologic modeling framework Openstreams/WFLOW and its application in operational hydrological forecasting on various spatial scales. The coupling between OpenDA and Openstreams/wflow framework is based on the emerging standard Basic Model Interface (BMI) as advocated by CSDMS using cross-platform webservices (i.e. Apache Thrift) developed by Hut et al. (2016). The potential application of the OpenDA-WFLOW for operational hydrologic forecasting including its integration with Delft-FEWS (used by more than 40 operational forecast centers around the world (Werner et al., 2013)) is demonstrated by the presented case studies. We will also highlight the possibility to give real-time insight into the working of the DA methods applied for supporting the forecaster as mentioned as one of the burning issues by Liu et al., (2012).
Wilby, R.L.; Hay, L.E.; Gutowski, W.J.; Arritt, R.W.; Takle, E.S.; Pan, Z.; Leavesley, G.H.; Clark, M.P.
Daily rainfall and surface temperature series were simulated for the Animas River basin, Colorado using dynamically and statistically downscaled output from the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) re-analysis. A distributed hydrological model was then applied to the downscaled data. Relative to raw NCEP output, downscaled climate variables provided more realistic stimulations of basin scale hydrology. However, the results highlight the sensitivity of modeled processes to the choice of downscaling technique, and point to the need for caution when interpreting future hydrological scenarios.
The Hydrological Simulation Program– FORTRAN (HSPF) is a comprehensive watershed model that employs depth-area - volume - flow relationships known as the hydraulic function table (FTABLE) to represent the hydraulic characteristics of stream channel cross-sections and reservoirs. ...
Biederman, J. A.; Harpold, A. A.; Gutmann, E. D.; Reed, D. E.; Gochis, D. J.; Brooks, P. D.
stands to small catchments, maximal snow water equivalent (SWE) as a fraction of winter precipitation (P) ranged from 62 to 74%. Despite an expectation of decreased interception and increased snow accumulation with advanced mortality, surveys at stand and catchment scales found no significant increases in net snow water input between healthy and impacted forests. These observations suggest that the spatial scale of processes affecting net snow accumulation and ablation increase following die-off. Using data from our sites and other studies, this presentation will develop a predictive model of how interception, shading, and wind redistribution interact to control net snow water input following large-scale forest mortality.
Merwade, V.; Ruddell, B. L.; Song, C.; Zhao, L.; Kim, J.; Assi, A.
Most hydrologists use hydrologic models to simulate the hydrologic processes to understand hydrologic pathways and fluxes for research, decision making and engineering design. Once these tasks are complete including publication of results, the models generally are not published or made available to the public for further use and improvement. Although publication or sharing of models is not required for journal publications, sharing of models may open doors for new collaborations, and avoids duplication of efforts if other researchers are interested in simulating a particular watershed for which a model already exists. For researchers, who are interested in sharing models, there are limited avenues to publishing their models to the wider community. Towards filling this gap, a prototype cyberinfrastructure (CI), called WaterHUB, is developed for sharing hydrologic data and modeling tools in an interactive environment. To test the utility of WaterHUB for sharing hydrologic models, a system to publish and share SWAT (Soil Water Assessment Tool) is developed. Users can utilize WaterHUB to search and download existing SWAT models, and also upload new SWAT models. Metadata such as the name of the watershed, name of the person or agency who developed the model, simulation period, time step, and list of calibrated parameters also published with individual model.
Goodall, J. L.; Castronova, A. M.; Bandaragoda, C.; Morsy, M. M.; Sadler, J. M.; Essawy, B.; Tarboton, D. G.; Malik, T.; Nijssen, B.; Clark, M. P.; Liu, Y.; Wang, S. W.
Creating cyberinfrastructure to support reproducibility of computational hydrologic models is an important research challenge. Addressing this challenge requires open and reusable code and data with machine and human readable metadata, organized in ways that allow others to replicate results and verify published findings. Specific digital objects that must be tracked for reproducible computational hydrologic modeling include (1) raw initial datasets, (2) data processing scripts used to clean and organize the data, (3) processed model inputs, (4) model results, and (5) the model code with an itemization of all software dependencies and computational requirements. HydroShare is a cyberinfrastructure under active development designed to help users store, share, and publish digital research products in order to improve reproducibility in computational hydrology, with an architecture supporting hydrologic-specific resource metadata. Researchers can upload data required for modeling, add hydrology-specific metadata to these resources, and use the data directly within HydroShare.org for collaborative modeling using tools like CyberGIS, Sciunit-CLI, and JupyterHub that have been integrated with HydroShare to run models using notebooks, Docker containers, and cloud resources. Current research aims to implement the Structure For Unifying Multiple Modeling Alternatives (SUMMA) hydrologic model within HydroShare to support hypothesis-driven hydrologic modeling while also taking advantage of the HydroShare cyberinfrastructure. The goal of this integration is to create the cyberinfrastructure that supports hypothesis-driven model experimentation, education, and training efforts by lowering barriers to entry, reducing the time spent on informatics technology and software development, and supporting collaborative research within and across research groups.
Walko, R.L.; Band, L.E.; Baron, Jill S.; Kittel, T.G.F.; Lammers, R.; Lee, T.J.; Ojima, D.; Pielke, R.A.; Taylor, C.; Tague, C.; Tremback, C.J.; Vidale, P.L.
The formulation and implementation of LEAF-2, the Land Ecosystem–Atmosphere Feedback model, which comprises the representation of land–surface processes in the Regional Atmospheric Modeling System (RAMS), is described. LEAF-2 is a prognostic model for the temperature and water content of soil, snow cover, vegetation, and canopy air, and includes turbulent and radiative exchanges between these components and with the atmosphere. Subdivision of a RAMS surface grid cell into multiple areas of distinct land-use types is allowed, with each subgrid area, or patch, containing its own LEAF-2 model, and each patch interacts with the overlying atmospheric column with a weight proportional to its fractional area in the grid cell. A description is also given of TOPMODEL, a land hydrology model that represents surface and subsurface downslope lateral transport of groundwater. Details of the incorporation of a modified form of TOPMODEL into LEAF-2 are presented. Sensitivity tests of the coupled system are presented that demonstrate the potential importance of the patch representation and of lateral water transport in idealized model simulations. Independent studies that have applied LEAF-2 and verified its performance against observational data are cited. Linkage of RAMS and TOPMODEL through LEAF-2 creates a modeling system that can be used to explore the coupled atmosphere–biophysical–hydrologic response to altered climate forcing at local watershed and regional basin scales.
Garcia, M.; Portney, K.; Islam, S.
Human and hydrological systems are coupled: human activity impacts the hydrological cycle and hydrological conditions can, but do not always, trigger changes in human systems. Traditional modeling approaches with no feedback between hydrological and human systems typically cannot offer insight into how different patterns of natural variability or human-induced changes may propagate through this coupled system. Modeling of coupled human-hydrological systems, also called socio-hydrological systems, recognizes the potential for humans to transform hydrological systems and for hydrological conditions to influence human behavior. However, this coupling introduces new challenges and existing literature does not offer clear guidance regarding model conceptualization. There are no universally accepted laws of human behavior as there are for the physical systems; furthermore, a shared understanding of important processes within the field is often used to develop hydrological models, but there is no such consensus on the relevant processes in socio-hydrological systems. Here we present a question driven process to address these challenges. Such an approach allows modeling structure, scope and detail to remain contingent on and adaptive to the question context. We demonstrate the utility of this process by revisiting a classic question in water resources engineering on reservoir operation rules: what is the impact of reservoir operation policy on the reliability of water supply for a growing city? Our example model couples hydrological and human systems by linking the rate of demand decreases to the past reliability to compare standard operating policy (SOP) with hedging policy (HP). The model shows that reservoir storage acts both as a buffer for variability and as a delay triggering oscillations around a sustainable level of demand. HP reduces the threshold for action thereby decreasing the delay and the oscillation effect. As a result, per capita demand decreases during
Barth, Johannes; van Geldern, Robert; Veizer, Jan; Karim, Ajaz; Freitag, Heiko; Fowlwer, Hayley
Comparison of water stable isotopes of rivers to those of precipitation enables separation of evaporation from transpiration on the catchment scale. The method exploits isotope ratio changes that are caused exclusively by evaporation over longer time periods of at least one hydrological year. When interception is quantified by mapping plant types in catchments, the amount of water lost by transpiration can be determined. When in turn pairing transpiration with the water use efficiency (WUE i.e. water loss by transpiration per uptake of CO2) and subtracting heterotrophic soil respiration fluxes (Rh), catchment-wide carbon balances can be established. This method was applied to several regions including the Great Lakes and the Clyde River Catchments ...(Barth, et al., 2007, Karim, et al., 2008). In these studies evaporation loss was 24 % and 1.3 % and transpiration loss was 47 % and 22 % when compared to incoming precipitation for the Great Lakes and the Clyde Catchment, respectively. Applying WUE values for typical plant covers and using area-typical Rh values led to estimates of CO2 uptake of 251 g C m-2 a-1 for the Great Lakes Catchment and CO2 loss of 21 g C m2 a-1 for the Clyde Catchment. These discrepancies are most likely due to different vegetation covers. The method applies to scales of several thousand km2 and has good potential for improvement via calibration on smaller scales. This can for instance be achieved by separate treatment of sub-catchments with more detailed mapping of interception as a major unknown. These previous studies have shown that better uncertainty analyses are necessary in order to estimate errors in water and carbon balances. The stable isotope method is also a good basis for comparison to other landscape carbon balances for instance by eddy covariance techniques. This independent method and its up-scaling combined with the stable isotope and area-integrating methods can provide cross validation of large-scale carbon budgets
Kim, Kue Bum; Kwon, Hyun-Han; Han, Dawei
One of the important issues in hydrological modelling is to specify the initial conditions of the catchment since it has a major impact on the response of the model. Although this issue should be a high priority among modelers, it has remained unaddressed by the community. The typical suggested warm-up period for the hydrological models has ranged from one to several years, which may lead to an underuse of data. The model warm-up is an adjustment process for the model to reach an 'optimal' state, where internal stores (e.g., soil moisture) move from the estimated initial condition to an 'optimal' state. This study explores the warm-up period of two conceptual hydrological models, HYMOD and IHACRES, in a southwestern England catchment. A series of hydrologic simulations were performed for different initial soil moisture conditions and different rainfall amounts to evaluate the sensitivity of the warm-up period. Evaluation of the results indicates that both initial wetness and rainfall amount affect the time required for model warm up, although it depends on the structure of the hydrological model. Approximately one and a half months are required for the model to warm up in HYMOD for our study catchment and climatic conditions. In addition, it requires less time to warm up under wetter initial conditions (i.e., saturated initial conditions). On the other hand, approximately six months is required for warm-up in IHACRES, and the wet or dry initial conditions have little effect on the warm-up period. Instead, the initial values that are close to the optimal value result in less warm-up time. These findings have implications for hydrologic model development, specifically in determining soil moisture initial conditions and warm-up periods to make full use of the available data, which is very important for catchments with short hydrological records.
Samaniego, Luis; Kumar, Rohini; Thober, Stephan; Rakovec, Oldrich; Zink, Matthias; Wanders, Niko; Eisner, Stephanie; Müller Schmied, Hannes; Sutanudjaja, Edwin H.; Warrach-Sagi, Kirsten; Attinger, Sabine
Land surface and hydrologic models (LSMs/HMs) are used at diverse spatial resolutions ranging from catchment-scale (1-10 km) to global-scale (over 50 km) applications. Applying the same model structure at different spatial scales requires that the model estimates similar fluxes independent of the chosen resolution, i.e., fulfills a flux-matching condition across scales. An analysis of state-of-the-art LSMs and HMs reveals that most do not have consistent hydrologic parameter fields. Multiple experiments with the mHM, Noah-MP, PCR-GLOBWB, and WaterGAP models demonstrate the pitfalls of deficient parameterization practices currently used in most operational models, which are insufficient to satisfy the flux-matching condition. These examples demonstrate that J. Dooge's 1982 statement on the unsolved problem of parameterization in these models remains true. Based on a review of existing parameter regionalization techniques, we postulate that the multiscale parameter regionalization (MPR) technique offers a practical and robust method that provides consistent (seamless) parameter and flux fields across scales. Herein, we develop a general model protocol to describe how MPR can be applied to a particular model and present an example application using the PCR-GLOBWB model. Finally, we discuss potential advantages and limitations of MPR in obtaining the seamless prediction of hydrological fluxes and states across spatial scales.
Turner, Kate; Worrall, Fred
Only 3% of the earths land surface is covered by peatland yet boreal and subarctic peatlands store approximately 15-30% of the World's soil carbon as peat (Limpens et al. 2008). In comparison British bogs store carbon equivalent to 20 years worth of national emissions. The loss of carbon from these areas in the form of dissolved organic carbon (DOC) is increasing and it is expected to have grown by up to 40% by 2018. Extensive drainage of UK peatlands has been associated with dehydration of the peat, an increase in water colour and a loss of carbon storage. It has been considered that the blocking of these drainage channels represents a means of peat restoration and a way of reducing DOC loss. This study aims to assess the effectiveness of this drain blocking at both an individual drain scale and at a larger catchment scale. Gibson et al. (2009) considered the effects of blocking at a solely individual drain scale finding that a 20% drop in DOC export was recorded post blocking however this decrease was due to a reduction in water yield rather than a reduction in DOC concentration with the concentration record showing no significant reduction. The effect of external parameters become more pronounced as the DOC record is examined at larger scales. The catchment is an open system and water chemistry will be influence by mixing with water from other sources. Also it is likely that at some point the drains will cut across slope leading to the flow of any highly coloured water down slope, bypassing the blockages, and entering the surface waters downstream. Degradation of DOC will occur naturally downstream due to the effects of light and microbial activity. There is, consequently, a need to examine the wider effects of drain blocking at a catchment scale to ensure that what is observed for one drain transfers to the whole catchment. A series of blocked and unblocked catchments were studied in Upper Teesdale, Northern England. Drain water samples were taken at least
Lefrancq, Marie; Joaquín García Verdú, Antonio; Maillard, Elodie; Imfeld, Gwenaël; Payraudeau, Sylvain
Surface runoff and erosion during the course of rainfall events represent major processes of pesticides transport from agricultural land to aquatic ecosystem. In general, field and catchment studies on pesticide transfer are carried out separately. A study at both scales may enable to improve the understanding of scale effects on processes involved in pesticides transport and to give clues on the source areas within an agricultural catchment. In this study, the transport in runoff of two widely used fungicides, i.e. kresoxim methyl (KM) and cyazofamid (CY) was assessed in a 43 ha vineyard catchment and the relative contribution of the total fungicides export from one representative plot was evaluated. During an entire period of fungicide application, from May to August 2011, the discharge and loads of dissolved and particle-laden KM and CY were monitored at the plot and catchment scales. The results showed larger export coefficient of KM and CY from catchment (0.064 and 0.041‰ for KM and CY respectively) than from the studied plot (0.009 and 0.023 ‰ for KM and CY respectively). It suggests that the plot margins especially the road network contributed as well to the fungicide loads. This result underlines the impact of fungicide drift on non-target areas. Furthermore, a larger rainfall threshold is necessary at the plot scale to trigger runoff and mobilise pesticides than on the road network. At the plot scale, a rapid dissipation of the both fungicides in the top soil was observed. It highlights that the risky period encompasses the first rainfall events triggering runoff after the applications. At both scales, KM and CY were not detected in suspended solids (i.e. > 0.7 µm). However their partitioning in runoff water differed. 64.1 and 91.8% of the KM load was detected in the dissolved phase (i.e. < 0.22 µm) at the plot and catchment scales respectively, whereas 98.7 and 100% of the CY load was detected in the particulate phase (i.e. between 0.22 and 0.7 µm
Selle, B.; Schwientek, M.
Water quality of ground and surface waters in catchments is typically driven by many complex and interacting processes. While small scale processes are often studied in great detail, their relevance and interplay at catchment scales remain often poorly understood. For many catchments, extensive monitoring data on water quality have been collected for different purposes. These heterogeneous data sets contain valuable information on catchment scale processes but are rarely analysed using integrated methods. Principle component analysis (PCA) has previously been applied to this kind of data sets. However, a detailed analysis of scores, which are an important result of a PCA, is often missing. Mathematically, PCA expresses measured variables on water quality, e.g. nitrate concentrations, as linear combination of independent, not directly observable key processes. These computed key processes are represented by principle components. Their scores are interpretable as process intensities which vary in space and time. Subsequently, scores can be correlated with other key variables and catchment characteristics, such as water travel times and land use that were not considered in PCA. This detailed analysis of scores represents an extension of the commonly applied PCA which could considerably improve the understanding of processes governing water quality at catchment scales. In this study, we investigated the 170 km2 Ammer catchment in SW Germany which is characterised by an above average proportion of agricultural (71%) and urban (17%) areas. The Ammer River is mainly fed by karstic springs. For PCA, we separately analysed concentrations from (a) surface waters of the Ammer River and its tributaries, (b) spring waters from the main aquifers and (c) deep groundwater from production wells. This analysis was extended by a detailed analysis of scores. We analysed measured concentrations on major ions and selected organic micropollutants. Additionally, redox-sensitive variables
Sivapalan, Murugesu; Tian, Fuqiang; Liu, Dengfeng
Socio-hydrology studies the co-evolution and self-organization of humans in the hydrologic landscape, which requires a thorough understanding of the complex interactions between humans and water. On the one hand, the nature of water availability greatly impacts the development of society. On the other hand, humans can significantly alter the spatio-temporal distribution of water and in this way provide feedback to the society itself. The human-water system functions underlying such complex human-water interactions are not well understood. Exploratory models with the appropriate level of simplification in any given area can be valuable to understand these functions and the self-organization associated with socio-hydrology. In this study, a simple coupled modeling framework for socio-hydrology co-evolution is developed, and is used to illustrate the explanatory power of such models. In the Tarim River, humans depend heavily on agricultural production (other industries can be ignored for a start), and the social processes can be described principally by two variables, i.e., irrigated-area and human population. The eco-hydrological processes are expressed in terms of area under natural vegetation and stream discharge. The study area is the middle and the lower reaches of the Tarim River, which is divided into two modeling units, i.e. middle reach and lower reach. In each modeling unit, four ordinary differential equations are used to simulate the dynamics of the hydrological system represented by stream discharge, ecological system represented by area under natural vegetation, the economic system represented by irrigated area under agriculture and social system represented by human population. The four dominant variables are coupled together by several internal variables. For example, the stream discharge is coupled to irrigated area by the colonization rate and mortality rate of the irrigated area in the middle reach and the irrigated area is coupled to stream
Duan, Qingyun; Ajami, Newsha K.; Gao, Xiaogang; Sorooshian, Soroosh
Multi-model ensemble strategy is a means to exploit the diversity of skillful predictions from different models. This paper studies the use of Bayesian model averaging (BMA) scheme to develop more skillful and reliable probabilistic hydrologic predictions from multiple competing predictions made by several hydrologic models. BMA is a statistical procedure that infers consensus predictions by weighing individual predictions based on their probabilistic likelihood measures, with the better performing predictions receiving higher weights than the worse performing ones. Furthermore, BMA provides a more reliable description of the total predictive uncertainty than the original ensemble, leading to a sharper and better calibrated probability density function (PDF) for the probabilistic predictions. In this study, a nine-member ensemble of hydrologic predictions was used to test and evaluate the BMA scheme. This ensemble was generated by calibrating three different hydrologic models using three distinct objective functions. These objective functions were chosen in a way that forces the models to capture certain aspects of the hydrograph well (e.g., peaks, mid-flows and low flows). Two sets of numerical experiments were carried out on three test basins in the US to explore the best way of using the BMA scheme. In the first set, a single set of BMA weights was computed to obtain BMA predictions, while the second set employed multiple sets of weights, with distinct sets corresponding to different flow intervals. In both sets, the streamflow values were transformed using Box-Cox transformation to ensure that the probability distribution of the prediction errors is approximately Gaussian. A split sample approach was used to obtain and validate the BMA predictions. The test results showed that BMA scheme has the advantage of generating more skillful and equally reliable probabilistic predictions than original ensemble. The performance of the expected BMA predictions in terms of
Friedel, Michael J.
The government of Mauritania is interested in how to maintain hydrologic balance to ensure a long-term stable water supply for minerals-related, domestic, and other purposes. Because of the many complicating and competing natural and anthropogenic factors, hydrologists will perform quantitative analysis with specific objectives and relevant computer models in mind. Whereas various computer models are available for studying water-resource priorities, the success of these models to provide reliable predictions largely depends on adequacy of the model-calibration process. Predictive analysis helps us evaluate the accuracy and uncertainty associated with simulated dependent variables of our calibrated model. In this report, the hydrologic modeling process is reviewed and a strategy summarized for future Mauritanian hydrologic modeling studies.
Ridler, Marc; Hummel, Stef; van Velzen, Nils; Katrine Falk, Anne; Madsen, Henrik
An open-source data assimilation framework is proposed for hydrological modeling. Data assimilation (DA) in hydrodynamic and hydrological forecasting systems has great potential to improve predictions and improve model result. The basic principle is to incorporate measurement information into a model with the aim to improve model results by error minimization. Great strides have been made to assimilate traditional in-situ measurements such as discharge, soil moisture, hydraulic head and snowpack into hydrologic models. More recently, remotely sensed data retrievals of soil moisture, snow water equivalent or snow cover area, surface water elevation, terrestrial water storage and land surface temperature have been successfully assimilated in hydrological models. The assimilation algorithms have become increasingly sophisticated to manage measurement and model bias, non-linear systems, data sparsity (time & space) and undetermined system uncertainty. It is therefore useful to use a pre-existing DA toolbox such as OpenDA. OpenDA is an open interface standard for (and free implementation of) a set of tools to quickly implement DA and calibration for arbitrary numerical models. The basic design philosophy of OpenDA is to breakdown DA into a set of building blocks programmed in object oriented languages. To implement DA, a model must interact with OpenDA to create model instances, propagate the model, get/set variables (or parameters) and free the model once DA is completed. An open-source interface for hydrological models exists capable of all these tasks: OpenMI. OpenMI is an open source standard interface already adopted by key hydrological model providers. It defines a universal approach to interact with hydrological models during simulation to exchange data during runtime, thus facilitating the interactions between models and data sources. The interface is flexible enough so that models can interact even if the model is coded in a different language, represent
Wuellner, M R; Bramblett, R G; Guy, C S; Zale, A V; Roberts, D R; Johnson, J
The objectives of this study were (1) to determine whether the presence or absence of prairie fishes can be modelled using habitat and biotic characteristics measured at the reach and catchment scales and (2) to identify which scale (i.e. reach, catchment or a combination of variables measured at both scales) best explains the presence or absence of fishes. Reach and catchment information from 120 sites sampled from 1999 to 2004 were incorporated into tree classifiers for 20 prairie fish species, and multiple criteria were used to evaluate models. Fewer than six models were considered significant when modelling individual fish occurrences at the reach, catchment or combined scale, and only one species was successfully modelled at all three scales. The scarcity of significant models is probably related to the rigorous criteria by which these models were evaluated as well as the prevalence of tolerant, generalist fishes in these stochastic and intermittent streams. No significant differences in the amount of reduced deviance, mean misclassification error rates (MER), and mean improvement in MER metrics was detected among the three scales. Results from this study underscore the importance of continued habitat assessment at smaller scales to further understand prairie-fish occurrences as well as further evaluations of modelling methods to examine habitat relationships for tolerant, ubiquitous species. Incorporation of such suggestions in the future may help provide more accurate models that will allow for better management and conservation of prairie-fish species. © 2013 The Authors. Journal of Fish Biology © 2013 The Fisheries Society of the British Isles.
Peck, E. L.; Keefer, T. N.; Johnson, E. R. (Principal Investigator)
Present and planned remote sensing capabilities were evaluated. The usefulness of six remote sensing capabilities (soil moisture, land cover, impervious area, areal extent of snow cover, areal extent of frozen ground, and water equivalent of the snow cover) with seven hydrologic models (API, CREAMS, NWSRFS, STORM, STANFORD, SSARR, and NWSRFS Snowmelt) were reviewed. The results indicate remote sensing information has only limited value for use with the hydrologic models in their present form. With minor modifications to the models the usefulness would be enhanced. Specific recommendations are made for incorporating snow covered area measurements in the NWSRFS Snowmelt model. Recommendations are also made for incorporating soil moisture measurements in NWSRFS. Suggestions are made for incorporating snow covered area, soil moisture, and others in STORM and SSARR. General characteristics of a hydrologic model needed to make maximum use of remotely sensed data are discussed. Suggested goals for improvements in remote sensing for use in models are also established.
Ambaruch, R.; Salomonson, V. V.; Simmons, J. W.
Continuous simulation models of the hydrologic behavior of watersheds are important tools in several practical applications such as hydroelectric power planning, navigation, and flood control. Several recent studies have addressed the feasibility of using remote earth observations as sources of input data for hydrologic models. The objective of the study reported here was to determine how accurately remotely sensed measurements must be to provide inputs to hydrologic models of watersheds, within the tolerances needed for acceptably accurate synthesis of streamflow by the models. The study objective was achieved by performing a series of sensitivity analyses using continuous simulation models of three watersheds. The sensitivity analysis showed quantitatively how variations in each of 46 model inputs and parameters affect simulation accuracy with respect to five different performance indices.
Bellarby, Jessica; Surridge, Ben; Haygarth, Philip M.; Lai, Xin; Zhang, Guilong; Song, Xiaolong; Zhou, Jianbin; Meng, Fanqiao; Shen, Jianbo; Rahn, Clive; Smith, Laurence; Burke, Sean
Diffuse water pollution from agriculture (DWPA) represents a significant challenge in both the UK and China. The UK has developed policies and practices which seek to mitigate DWPA, yet the risks and adverse impacts of DWPA remain widespread. In contrast, China's past priorities have largely focussed on food security, with an emphasis on increasing food production through high fertiliser application rates with little attention being paid to enhanced nutrient export from land to water and to air. This has contributed to severe environmental problems which are only now beginning to be recognised and addressed. We have prepared nutrient balances (phosphorus and nitrogen) in contrasting agricultural production systems at sub-catchment scale within China and the UK. These draw from a variety of sources ranging from general yearly statistics collected by the respective government to farm surveys. Our aim is to use the resulting nutrient balances to underpin the sharing of knowledge and innovation to mitigate DWPA in both nations. In the UK, the case studies focus on the three Demonstration Test Catchment locations, covering a range of livestock and arable production systems across England. Here, the high frequency monitoring of phosphorus river loads enables the cross-validation of the simple nutrient budget approaches applied in this study. In China, our case studies span kiwi orchard, fruit and vegetable solar greenhouse systems, double cropped rice-wheat and wheat-maize production systems. Substantial differences in nutrient stocks and flows exist between individual production systems both across and within the two countries. These differences will be expressed along the source-mobilisation-delivery-impact continuum that underpins our budgets for both phosphorus and nitrogen. We will present the phosphorus cycles of some case studies and highlight their challenges and relevance at sub-catchment scale. Based on our nutrient budgets, general recommendations can be
Ferrant, S.; Le Page, M.; Kerr, Y. H.; Selles, A.; Mermoz, S.; Al-Bitar, A.; Muddu, S.; Gascoin, S.; Marechal, J. C.; Durand, P.; Salmon-Monviola, J.; Ceschia, E.; Bustillo, V.
Nitrogen transfers at agricultural catchment level are intricately linked to water transfers. Agro-hydrological modeling approaches aim at integrating spatial heterogeneity of catchment physical properties together with agricultural practices to spatially estimate the water and nitrogen cycles. As in hydrology, the calibration schemes are designed to optimize the performance of the temporal dynamics and biases in model simulations, while ignoring the simulated spatial pattern. Yet, crop uses, i.e. transpiration and nitrogen exported by harvest, are the main fluxes at the catchment scale, highly variable in space and time. Geo-information time-series of vegetation and water index with multi-spectral optical detection S2 together with surface roughness time series with C-band radar detection S1 are used to reset soil water holding capacity parameters (depth, porosity) and agricultural practices (sowing date, irrigated area extent) of a crop model coupled with a hydrological model. This study takes two agro-hydrological contexts as demonstrators: 1-spatial nitrogen excess estimation in south-west of France, and 2-groundwater extraction for rice irrigation in south-India. Spatio-temporal patterns are involved in respectively surface water contamination due to over-fertilization and local groundwater shortages due to over-pumping for above rice inundation. Optimized Leaf Area Index profiles are simulated at the satellite images pixel level using an agro-hydrological model to reproduce spatial and temporal crop growth dynamics in south-west of France, improving the in-stream nitrogen fluxes by 12%. Accurate detection of irrigated area extents are obtained with the thresholding method based on optical indices, with a kappa of 0.81 for the dry season 2016. The actual monsoon season is monitored and will be presented. These extents drive the groundwater pumping and are highly variable in time (from 2 to 8% of the total area).
Schimel, David S.
Interactions among the atmosphere, terrestrial ecosystems, and the hydrological cycle have been the subject of investigation for many years, although most of the research has had a regional focus. The topic is broad, including the effects of climate and hydrology on vegetation, the effects of vegetation on hydrology, the effects of the hydrological cycle on the atmosphere, and interactions of the cycles via material flux such as solutes and trace gases. The intent of this paper is to identify areas of critical uncertainty, discuss modeling approaches to resolving those problems, and then propose techniques for testing. I consider several interactions specifically to illustrate the range of problems. These areas are as follows: (1) cloud parameterizations and the land surface, (2) soil moisture, and (3) the terrestrial carbon cycle.
Lee, H.; Seo, D.; Koren, V.
A prototype 4DVAR (four-dimensional variational) data assimilator for gridded Sacramento soil-moisture accounting and kinematic-wave routing models in the Hydrology Laboratory's Research Distributed Hydrologic Model (HL-RDHM) has been developed. The prototype assimilates streamflow and in-situ soil moisture data and adjusts gridded precipitation and climatological potential evaporation data to reduce uncertainty in the model initial conditions for improved monitoring and prediction of streamflow and soil moisture at the outlet and interior locations within the catchment. Due to large degrees of freedom involved, data assimilation (DA) into distributed hydrologic models is complex. To understand and assess sensitivity of the performance of DA to uncertainties in the model initial conditions and in the data, two synthetic experiments have been carried out in an ensemble framework. Results from the synthetic experiments shed much light on the potential and limitations with DA into distributed models. For initial real-world assessment, the prototype DA has also been applied to the headwater basin at Eldon near the Oklahoma-Arkansas border. We present these results and describe the next steps.
Tarboton, D. G.; Idaszak, R.; Horsburgh, J. S.; Ames, D. P.; Goodall, J. L.; Band, L. E.; Merwade, V.; Couch, A.; Hooper, R. P.; Maidment, D. R.; Dash, P. K.; Stealey, M.; Yi, H.; Gan, T.; Castronova, A. M.; Miles, B.; Li, Z.; Morsy, M. M.
HydroShare is an online, collaborative system for open sharing of hydrologic data, analytical tools, and models. It supports the sharing of and collaboration around "resources" which are defined primarily by standardized metadata, content data models for each resource type, and an overarching resource data model based on the Open Archives Initiative's Object Reuse and Exchange (OAI-ORE) standard and a hierarchical file packaging system called "BagIt". HydroShare expands the data sharing capability of the CUAHSI Hydrologic Information System by broadening the classes of data accommodated to include geospatial and multidimensional space-time datasets commonly used in hydrology. HydroShare also includes new capability for sharing models, model components, and analytical tools and will take advantage of emerging social media functionality to enhance information about and collaboration around hydrologic data and models. It also supports web services and server/cloud based computation operating on resources for the execution of hydrologic models and analysis and visualization of hydrologic data. HydroShare uses iRODS as a network file system for underlying storage of datasets and models. Collaboration is enabled by casting datasets and models as "social objects". Social functions include both private and public sharing, formation of collaborative groups of users, and value-added annotation of shared datasets and models. The HydroShare web interface and social media functions were developed using the Django web application framework coupled to iRODS. Data visualization and analysis is supported through the Tethys Platform web GIS software stack. Links to external systems are supported by RESTful web service interfaces to HydroShare's content. This presentation will introduce the HydroShare functionality developed to date and describe ongoing development of functionality to support collaboration and integration of data and models.
Coupled models of terrestrial hydrology and climate have grown in complexity leading to better understanding of the coupling between the hydrosphere, biosphere, and the climate system. During the past two decades, these models have evolved through generational changes as they have grown in sophistication in their ability to resolve spatial heterogeneity as well as vegetation dynamics and biogeochemistry. These developments have, in part, been driven by data collection efforts ranging from focused field campaigns to long-term observational networks, advances in remote sensing and other measurement technologies, along with sophisticated estimation and assimilation methods. However, the hydrologic cycle is changing leading to unexpected and unanticipated behavior through emergent dynamics and patterns that are not part of the historical milieu. Is there a new thinking that is needed to address this challenge? The goal of this talk is to draw from the modeling developments in the past two decades to foster a debate for moving forward.
Gwinn, Daniel C; Middleton, Jen A; Beesley, Leah; Close, Paul; Quinton, Belinda; Storer, Tim; Davies, Peter M
The degradation of streams caused by urbanization tends to follow predictable patterns; however, there is a growing appreciation for heterogeneity in stream response to urbanization due to the local geoclimatic context. Furthermore, there is building evidence that streams in mildly sloped, permeable landscapes respond uncharacteristically to urban stress calling for a more nuanced approach to restoration. We evaluated the relative influence of local-scale riparian characteristics and catchment-scale imperviousness on the macroinvertebrate assemblages of streams in the flat, permeable urban landscape of Perth, Western Australia. Using a hierarchical multi-taxa model, we predicted the outcomes of stylized stream restoration strategies to increase the riparian integrity at the local scale or decrease the influences of imperviousness at the catchment scale. In the urban streams of Perth, we show that local-scale riparian restoration can influence the structure of macroinvertebrate assemblages to a greater degree than managing the influences of catchment-scale imperviousness. We also observed an interaction between the effect of riparian integrity and imperviousness such that the effect of increased riparian integrity was enhanced at lower levels of catchment imperviousness. This study represents one of few conducted in flat, permeable landscapes and the first aimed at informing urban stream restoration in Perth, adding to the growing appreciation for heterogeneity of the Urban Stream Syndrome and its importance for urban stream restoration. © 2017 by the Ecological Society of America.
Gardner, M.; Niswonger, R. G.; Morton, C.; Henson, W.; Huntington, J. L.
Integrated hydrologic modeling encompasses a vast number of processes and specifications, variable in time and space, and development of model datasets can be arduous. Model input construction techniques have not been formalized or made easily reproducible. Creating the input files for integrated hydrologic models (IHM) requires complex GIS processing of raster and vector datasets from various sources. Developing stream network topology that is consistent with the model resolution digital elevation model is important for robust simulation of surface water and groundwater exchanges. Distribution of meteorologic parameters over the model domain is difficult in complex terrain at the model resolution scale, but is necessary to drive realistic simulations. Historically, development of input data for IHM models has required extensive GIS and computer programming expertise which has restricted the use of IHMs to research groups with available financial, human, and technical resources. Here we present a series of Python scripts that provide a formalized technique for the parameterization and development of integrated hydrologic model inputs for GSFLOW. With some modifications, this process could be applied to any regular grid hydrologic model. This Python toolkit automates many of the necessary and laborious processes of parameterization, including stream network development and cascade routing, land coverages, and meteorological distribution over the model domain.
Yu, Xuan; Lamačová, Anna; Duffy, Christopher; Krám, Pavel; Hruška, Jakub
Evapotranspiration (ET) continues to be a difficult process to estimate in seasonal and long-term water balances in catchment models. Approaches to estimate ET typically use vegetation parameters (e.g., leaf area index [LAI], interception capacity) obtained from field observation, remote sensing data, national or global land cover products, and/or simulated by ecosystem models. In this study we attempt to quantify the uncertainty that spatial evapotranspiration estimation introduces into hydrological simulations when the age of the forest is not precisely known. The Penn State Integrated Hydrologic Model (PIHM) was implemented for the Lysina headwater catchment, located 50°03‧N, 12°40‧E in the western part of the Czech Republic. The spatial forest patterns were digitized from forest age maps made available by the Czech Forest Administration. Two ET methods were implemented in the catchment model: the Biome-BGC forest growth sub-model (1-way coupled to PIHM) and with the fixed-seasonal LAI method. From these two approaches simulation scenarios were developed. We combined the estimated spatial forest age maps and two ET estimation methods to drive PIHM. A set of spatial hydrologic regime and streamflow regime indices were calculated from the modeling results for each method. Intercomparison of the hydrological responses to the spatial vegetation patterns suggested considerable variation in soil moisture and recharge and a small uncertainty in the groundwater table elevation and streamflow. The hydrologic modeling with ET estimated by Biome-BGC generated less uncertainty due to the plant physiology-based method. The implication of this research is that overall hydrologic variability induced by uncertain management practices was reduced by implementing vegetation models in the catchment models.
Nijzink, Remko; Hutton, Christopher; Pechlivanidis, Ilias; Capell, René; Arheimer, Berit; Freer, Jim; Han, Dawei; Wagener, Thorsten; McGuire, Kevin; Savenije, Hubert; Hrachowitz, Markus
The core component of many hydrological systems, the moisture storage capacity available to vegetation, is impossible to observe directly at the catchment scale and is typically treated as a calibration parameter or obtained from a priori available soil characteristics combined with estimates of rooting depth. Often this parameter is considered to remain constant in time. Using long-term data (30-40 years) from three experimental catchments that underwent significant land cover change, we tested the hypotheses that: (1) the root-zone storage capacity significantly changes after deforestation, (2) changes in the root-zone storage capacity can to a large extent explain post-treatment changes to the hydrological regimes and that (3) a time-dynamic formulation of the root-zone storage can improve the performance of a hydrological model.A recently introduced method to estimate catchment-scale root-zone storage capacities based on climate data (i.e. observed rainfall and an estimate of transpiration) was used to reproduce the temporal evolution of root-zone storage capacity under change. Briefly, the maximum deficit that arises from the difference between cumulative daily precipitation and transpiration can be considered as a proxy for root-zone storage capacity. This value was compared to the value obtained from four different conceptual hydrological models that were calibrated for consecutive 2-year windows.It was found that water-balance-derived root-zone storage capacities were similar to the values obtained from calibration of the hydrological models. A sharp decline in root-zone storage capacity was observed after deforestation, followed by a gradual recovery, for two of the three catchments. Trend analysis suggested hydrological recovery periods between 5 and 13 years after deforestation. In a proof-of-concept analysis, one of the hydrological models was adapted to allow dynamically changing root-zone storage capacities, following the observed changes due to
Das, Narendra; Stampoulis, Dimitrios; Ines, Amor; Fisher, Joshua B.; Granger, Stephanie; Kawata, Jessie; Han, Eunjin; Behrangi, Ali
The Regional Hydrologic Extremes Assessment System (RHEAS) is a prototype software framework for hydrologic modeling and data assimilation that automates the deployment of water resources nowcasting and forecasting applications. A spatially-enabled database is a key component of the software that can ingest a suite of satellite and model datasets while facilitating the interfacing with Geographic Information System (GIS) applications. The datasets ingested are obtained from numerous space-borne sensors and represent multiple components of the water cycle. The object-oriented design of the software allows for modularity and extensibility, showcased here with the coupling of the core hydrologic model with a crop growth model. RHEAS can exploit multi-threading to scale with increasing number of processors, while the database allows delivery of data products and associated uncertainty through a variety of GIS platforms. A set of three example implementations of RHEAS in the United States and Kenya are described to demonstrate the different features of the system in real-world applications. PMID:28545077
Andreadis, Konstantinos M; Das, Narendra; Stampoulis, Dimitrios; Ines, Amor; Fisher, Joshua B; Granger, Stephanie; Kawata, Jessie; Han, Eunjin; Behrangi, Ali
The Regional Hydrologic Extremes Assessment System (RHEAS) is a prototype software framework for hydrologic modeling and data assimilation that automates the deployment of water resources nowcasting and forecasting applications. A spatially-enabled database is a key component of the software that can ingest a suite of satellite and model datasets while facilitating the interfacing with Geographic Information System (GIS) applications. The datasets ingested are obtained from numerous space-borne sensors and represent multiple components of the water cycle. The object-oriented design of the software allows for modularity and extensibility, showcased here with the coupling of the core hydrologic model with a crop growth model. RHEAS can exploit multi-threading to scale with increasing number of processors, while the database allows delivery of data products and associated uncertainty through a variety of GIS platforms. A set of three example implementations of RHEAS in the United States and Kenya are described to demonstrate the different features of the system in real-world applications.
We examined the effect of forest thinning on runoff generation at plot and catchment scales in headwater basins draining a Japanese cypress (Chamaecyparis obtusa) forest. We removed 58.3% of the stems (corresponding to 43.2% of the basal area) in the treated headwater basin (catc...
Spies, R. R.; Franz, K. J.; Bowman, A.; Hogue, T. S.; Kim, J.
Distributed models have the ability of incorporating spatially variable data, especially high resolution forcing inputs such as precipitation, temperature and evapotranspiration in hydrologic modeling. Use of distributed hydrologic models for operational streamflow prediction has been partially hindered by a lack of readily available, spatially explicit input observations. Potential evapotranspiration (PET), for example, is currently accounted for through PET input grids that are based on monthly climatological values. The goal of this study is to assess the use of satellite-based PET estimates that represent the temporal and spatial variability, as input to the National Weather Service (NWS) Hydrology Laboratory Research Distributed Hydrologic Model (HL-RDHM). Daily PET grids are generated for six watersheds in the upper Mississippi River basin using a method that applies only MODIS satellite-based observations and the Priestly Taylor formula (MODIS-PET). The use of MODIS-PET grids will be tested against the use of the current climatological PET grids for simulating basin discharge. Gridded surface temperature forcing data are derived by applying the inverse distance weighting spatial prediction method to point-based station observations from the Automated Surface Observing System (ASOS) and Automated Weather Observing System (AWOS). Precipitation data are obtained from the Climate Prediction Center's (CPC) Climatology-Calibrated Precipitation Analysis (CCPA). A-priori gridded parameters for the Sacramento Soil Moisture Accounting Model (SAC-SMA), Snow-17 model, and routing model are initially obtained from the Office of Hydrologic Development and further calibrated using an automated approach. The potential of the MODIS-PET to be used in an operational distributed modeling system will be assessed with the long-term goal of promoting research to operations transfers and advancing the science of hydrologic forecasting.
Merwade, V.; Rajib, A.; Ruddell, B. L.; Fox, S.
Hydrology instruction typically involves teaching of the hydrologic cycle and the processes associated with it such as precipitation, evapotranspiration, infiltration, runoff generation and hydrograph analysis. With the availability of observed and remotely sensed data related to many hydrologic fluxes, there is an opportunity to use these data for place based learning in hydrology classrooms. However, it is not always easy and possible for an instructor to complement an existing hydrology course with new material that requires both the time and technical expertise, which the instructor may not have. The work presented here describes an effort where students create the data and modeling driven instruction material as a part of their class assignment for a hydrology course at Purdue University. The data driven hydrology education project within Science Education Resources Center (SERC) is used as a platform to publish and share the instruction material so it can be used by future students in the same course or any other course anywhere in the world. Students in the class were divided into groups, and each group was assigned a topic such as precipitation, evapotranspiration, streamflow, flow duration curve and frequency analysis. Each student in the group was then asked to get data and do some analysis for an area with specific landuse characteristic such as urban, rural and agricultural. The student contribution were then organized into learning units such that someone can do a flow duration curve analysis or flood frequency analysis to see how it changes for rural area versus urban area. The hydrology education project within SERC cyberinfrastructure enables any other instructor to adopt this material as is or through modification to suit his/her place based instruction needs.
Elmer, N. J.; Zavodsky, B.; Molthan, A.
The operational National Water Model (NWM), implemented in August 2016, is an instantiation of the Weather Research and Forecasting hydrological extension package (WRF-Hydro). Currently, the NWM only covers the contiguous United States, but will be expanded to include an Alaska domain in the future. It is well known that Alaska presents several hydrological modeling challenges, including unique arctic/sub-arctic hydrological processes not observed elsewhere in the United States and a severe lack of in-situ observations for model initialization. This project sets up an experimental version of WRF-Hydro in Alaska mimicking the NWM to gauge the ability of WRF-Hydro to represent hydrological processes in Alaska and identify model calibration challenges. Recent and upcoming launches of hydrology-focused NASA satellite missions such as the Soil Moisture Active Passive (SMAP) and Surface Water Ocean Topography (SWOT) expand the spatial and temporal coverage of observations in Alaska, so this study also lays the groundwork for assimilating these NASA datasets into WRF-Hydro in the future.
Loritz, Ralf; Neuper, Malte; Gupta, Hoshin; Zehe, Erwin
The amount of data we observe in our environmental systems is larger than ever. This leads to a new kind of problem where hydrological modelers can have access to large datasets with various quantitative and qualitative observations but are uncertain about the information content with respect to the hydrological functioning of a landscape. For example digital elevation models obviously contain plenty of information about the topography of a landscape; however the question of relevance for Hydrology is how much of this information is important for the hydrological functioning of a landscape. This kind of question is not limited to topography and we can ask similar questions when handling distributed rainfall data or geophysical images. In this study we would like to show how one can separate dominant patterns in the landscape from idiosyncratic system details. We use a 2D numerical hillslope model in combination with an extensive research data set to test a variety of different model setups that are built upon different landscape characteristics and run by different rainfalls measurements. With the help of information theory based measures we can identify and learn how much heterogeneity is really necessary for successful hydrological simulations and how much of it we can neglect.
Markstrom, Steven; Hay, Lauren E.; Clark, Martyn P.
The Precipitation–Runoff Modeling System (PRMS), a distributed-parameter hydrologic model, has been applied to the conterminous US (CONUS). Parameter sensitivity analysis was used to identify: (1) the sensitive input parameters and (2) particular model output variables that could be associated with the dominant hydrologic process(es). Sensitivity values of 35 PRMS calibration parameters were computed using the Fourier amplitude sensitivity test procedure on 110 000 independent hydrologically based spatial modeling units covering the CONUS and then summarized to process (snowmelt, surface runoff, infiltration, soil moisture, evapotranspiration, interflow, baseflow, and runoff) and model performance statistic (mean, coefficient of variation, and autoregressive lag 1). Identified parameters and processes provide insight into model performance at the location of each unit and allow the modeler to identify the most dominant process on the basis of which processes are associated with the most sensitive parameters. The results of this study indicate that: (1) the choice of performance statistic and output variables has a strong influence on parameter sensitivity, (2) the apparent model complexity to the modeler can be reduced by focusing on those processes that are associated with sensitive parameters and disregarding those that are not, (3) different processes require different numbers of parameters for simulation, and (4) some sensitive parameters influence only one hydrologic process, while others may influence many
The coupling of land surface models and hydrological models potentially improves the land surface representation, benefiting both the streamflow prediction capabilities as well as providing improved estimates of water and energy fluxes into the atmosphere. In this study, the simple biosphere model 2...
Versini, Pierre-Antoine; Gires, Auguste; Tchinguirinskaia, Ioulia; Schertzer, Daniel
Currently widespread in new urban projects, green roofs have shown a positive impact on urban runoff at the building scale: decrease and slow-down of the peak discharge, and decrease of runoff volume. The present work aims to study their possible impact at the catchment scale, more compatible with stormwater management issues. For this purpose, a specific module dedicated to simulating the hydrological behaviour of a green roof has been developed in the distributed rainfall-runoff model (Multi-Hydro). It has been applied on a French urban catchment where most of the building roofs are flat and assumed to accept the implementation of a green roof. Catchment responses to several rainfall events covering a wide range of meteorological situations have been simulated. The simulation results show green roofs can significantly reduce runoff volume and the magnitude of peak discharge (up to 80%) depending on the rainfall event and initial saturation of the substrate. Additional tests have been made to assess the susceptibility of this response regarding both spatial distributions of green roofs and precipitation. It appears that the total area of greened roofs is more important than their locations. On the other hand, peak discharge reduction seems to be clearly dependent on spatial distribution of precipitation.
Urbanization is the world development trend for the past century, and the developing countries have been experiencing much rapider urbanization in the past decades. Urbanization brings many benefits to human beings, but also causes negative impacts, such as increasing flood risk. Impact of urbanization on flood response has long been observed, but quantitatively studying this effect still faces great challenges. For example, setting up an appropriate hydrological model representing the changed flood responses and determining accurate model parameters are very difficult in the urbanized or urbanizing watershed. In the Pearl River Delta area, rapidest urbanization has been observed in China for the past decades, and dozens of highly urbanized watersheds have been appeared. In this study, a physically based distributed watershed hydrological model, the Liuxihe model is employed and revised to simulate the hydrological processes of the highly urbanized watershed flood in the Pearl River Delta area. A virtual soil type is then defined in the terrain properties dataset, and its runoff production and routing algorithms are added to the Liuxihe model. Based on a parameter sensitive analysis, the key hydrological processes of a highly urbanized watershed is proposed, that provides insight into the hydrological processes and for parameter optimization. Based on the above analysis, the model is set up in the Songmushan watershed where there is hydrological data observation. A model parameter optimization and updating strategy is proposed based on the remotely sensed LUC types, which optimizes model parameters with PSO algorithm and updates them based on the changed LUC types. The model parameters in Songmushan watershed are regionalized at the Pearl River Delta area watersheds based on the LUC types of the other watersheds. A dozen watersheds in the highly urbanized area of Dongguan City in the Pearl River Delta area were studied for the flood response changes due to
Abebe, N. A.; Ogden, F. L.
Hydrological models are mathematical formulations intended to represent observed hydrological processes in a watershed. Simulated watersheds in turn vary in their nature based on their geographic location, altitude, climatic variables and geology and soil formation. Due to these variations, available hydrologic models vary in process formulation, spatial and temporal resolution and data demand. Many tropical watersheds are characterized by extensive and persistent biological activity and a large amount of rain. The Agua Salud catchments located within the Panama Canal Watershed, Panama, are such catchments identified by steep rolling topography, deep soils derived from weathered bedrock, and limited exposed bedrock. Tropical soils are highly affected by soil cracks, decayed tree roots and earthworm burrows forming a network of preferential flow paths that drain to a perched water table, which forms at a depth where the vertical hydraulic conductivity is significantly reduced near the bottom of the bioturbation layer. We have developed a physics-based, spatially distributed, multi-layered hydrologic model to simulate the dominant processes in these tropical watersheds. The model incorporates the major flow processes including overland flow, channel flow, matrix and non-Richards film flow infiltration, lateral downslope saturated matrix and non-Darcian pipe flow in the bioturbation layer, and deep saturated groundwater flow. Emphasis is given to the modeling of subsurface unsaturated zone soil moisture dynamics and the saturated preferential lateral flow from the network of macrospores. Preliminary results indicate that the model has the capability to simulate the complex hydrological processes in the catchment and will be a useful tool in the ongoing comprehensive ecohydrological studies in tropical catchments, and help improve our understanding of the hydrological effects of deforestation and aforestation.
The Soil and Water Assessment Tool (SWAT) and MODFLOW models are being used worldwide for managing surface and groundwater water resources. The SWAT models hydrological processes occurring at the surface including shallow aquifers, while MODFLOW simulate groundwater processes. However, neither SWAT ...
A survey of literature and examination in particular of terminology use in a previous special collection of modeling calibration and validation papers has been conducted to arrive at a list of consistent terminology recommended for writing about hydrologic and water quality model calibration and val...
Kirkby, Mike; Naden, Pam
Learning about the physical environment from computer simulation models is discussed in terms of three stages: exploration, experimentation, and calibration. Discusses the effective use of models and presents two computer simulations written in BBC BASIC, STORFLO (for catchment hydrology) and SLOPEK (for hillslope evolution). (Author/GEA)
Performance measures and criteria are essential for model calibration and validation. This presentation will include a summary of one of the papers that will be included in the 2014 Hydrologic and Water Quality Model Calibration & Validation Guidelines Special Collection of the ASABE Transactions. T...
Alexander, R. B.; Schwarz, G. E.; Boyer, E. W.
Mechanistic and empirical watershed models are increasingly used to inform water resource decisions. Growing access to historical stream measurements and data from in-situ sensor technologies has increased the need for improved techniques for coupling models with hydrological measurements. Techniques that account for the intrinsic uncertainties of both models and measurements are especially needed. Hierarchical Bayesian methods provide an efficient modeling tool for quantifying model and prediction uncertainties, including those associated with measurements. Hierarchical methods can also be used to explore spatial and temporal variations in model parameters and uncertainties that are informed by hydrological measurements. We used hierarchical Bayesian methods to develop a hybrid (statistical-mechanistic) SPARROW (SPAtially Referenced Regression On Watershed attributes) model of long-term mean annual streamflow across diverse environmental and climatic drainages in 18 U.S. hydrological regions. Our application illustrates the use of a new generation of Bayesian methods that offer more advanced computational efficiencies than the prior generation. Evaluations of the effects of hierarchical (regional) variations in model coefficients and uncertainties on model accuracy indicates improved prediction accuracies (median of 10-50%) but primarily in humid eastern regions, where model uncertainties are one-third of those in arid western regions. Generally moderate regional variability is observed for most hierarchical coefficients. Accounting for measurement and structural uncertainties, using hierarchical state-space techniques, revealed the effects of spatially-heterogeneous, latent hydrological processes in the "localized" drainages between calibration sites; this improved model precision, with only minor changes in regional coefficients. Our study can inform advances in the use of hierarchical methods with hydrological models to improve their integration with stream
Vansteenkiste, Thomas; Ntegeka, Victor; Willems, Patrick
It is vital to investigate how the hydrological model structure affects the climate change impact given that future changes not in the range for which the models were calibrated or validated are likely. Thus an ensemble modelling approach which involves a diversity of models with different structures such as spatial resolutions and process descriptions is crucial. The ensemble modelling approach was applied to a set of models: from the lumped conceptual models NAM, PDM and VHM, an intermediate detailed and distributed model WetSpa, to the highly detailed and fully distributed model MIKE-SHE. Explicit focus was given to the high and low flow extremes. All models were calibrated for sub flows and quick flows derived from rainfall and potential evapotranspiration (ETo) time series. In general, all models were able to produce reliable estimates of the flow regimes under the current climate for extreme peak and low flows. An intercomparison of the low and high flow changes under changed climatic conditions was made using climate scenarios tailored for extremes. Tailoring was important for two reasons. First, since the use of many scenarios was not feasible it was necessary to construct few scenarios that would reasonably represent the range of extreme impacts. Second, scenarios would be more informative as changes in high and low flows would be easily traced to changes of ETo and rainfall; the tailored scenarios are constructed using seasonal changes that are defined using different levels of magnitude (high, mean and low) for rainfall and ETo. After simulation of these climate scenarios in the five hydrological models, close agreement was found among the models. The different models predicted similar range of peak flow changes. For the low flows, however, the differences in the projected impact range by different hydrological models was larger, particularly for the drier scenarios. This suggests that the hydrological model structure is critical in low flow predictions
Obeysekera, J.; Kuebler, L.; Ahmed, S.; Chang, M.-L.; Engel, V.; Langevin, C.; Swain, E.; Wan, Y.
Planning and implementation of unprecedented projects for restoring the greater Everglades ecosystem are underway and the hydrologic and hydrodynamic modeling of restoration alternatives has become essential for success of restoration efforts. In view of the complex nature of the South Florida water resources system, regional-scale (system-wide) hydrologic models have been developed and used extensively for the development of the Comprehensive Everglades Restoration Plan. In addition, numerous subregional-scale hydrologic and hydrodynamic models have been developed and are being used for evaluating project-scale water management plans associated with urban, agricultural, and inland costal ecosystems. The authors provide a comprehensive summary of models of all scales, as well as the next generation models under development to meet the future needs of ecosystem restoration efforts in South Florida. The multiagency efforts to develop and apply models have allowed the agencies to understand the complex hydrologic interactions, quantify appropriate performance measures, and use new technologies in simulation algorithms, software development, and GIS/database techniques to meet the future modeling needs of the ecosystem restoration programs. Copyright ?? 2011 Taylor & Francis Group, LLC.
Fuka, Daniel; Collick, Amy; MacAlister, Charlotte; Braeckel, Aaron; Wright, Dawn; Jodha Khalsa, Siri; Boldrini, Enrico; Easton, Zachary
Data brokering aims to provide those in the the sciences with quick and repeatable access to data that represents physical, biological, and chemical characteristics; specifically to accelerate scientific discovery. Environmental models are useful tools to understand the behavior of hydrological systems. Unfortunately, parameterization of these hydrological models requires many different data, from different sources, and from different disciplines (e.g., atmospheric, geoscience, ecology). In basin scale hydrological modeling, the traditional procedure for model initialization starts with obtaining elevation models, land-use characterizations, soils maps, and weather data. It is often the researcher's past experience with these datasets that determines which datasets will be used in a study, and often newer, or more suitable data products will exist. An added complexity is that various science communities have differing data formats, storage protocols, and manipulation methods, which makes use by a non native user exceedingly difficult and time consuming. We demonstrate data brokering as a means to address several of these challenges. We present two test case scenarios in which researchers attempt to reproduce hydrological model results using 1) general internet based data gathering techniques, and 2) a scientific data brokering interface. We show that data brokering can increase the efficiency with which data are obtained, models are initialized, and results are analyzed. As an added benefit, it appears brokering can significantly increase the repeatability of a given study.
Wang, Jianhua; Lu, Chuiyu; Sun, Qingyan; Xiao, Weihua; Cao, Guoliang; Li, Hui; Yan, Lingjia; Zhang, Bo
Large-scale ground subsidence caused by coal mining and subsequent water-filling leads to serious environmental problems and economic losses, especially in plains with a high phreatic water level. Clarifying the hydrologic cycle in subsidence areas has important practical value for environmental remediation, and provides a scientific basis for water resource development and utilisation of the subsidence areas. Here we present a simulation approach to describe interactions between subsidence area water (SW) and several hydrologic factors from the River-Subsidence-Groundwater Model (RSGM), which is developed based on the distributed hydrologic model. Analysis of water balance shows that the recharge of SW from groundwater only accounts for a small fraction of the total water source, due to weak groundwater flow in the plain. The interaction between SW and groundwater has an obvious annual cycle. The SW basically performs as a net source of groundwater in the wet season, and a net sink for groundwater in the dry season. The results show there is an average 905.34 million m3 per year of water available through the Huainan coal mining subsidence areas (HCMSs). If these subsidence areas can be integrated into water resource planning, the increasingly precarious water supply infrastructure will be strengthened. PMID:28106048
Boje, Søren; Skaugen, Thomas; Møen, Knut; Myrabø, Steinar
The tiny Sæternbekken Minifelt (Muren) catchment (7500 m2) in Bærumsmarka, Norway, was during the 1990s, densely instrumented with more than a 100 observation points for measuring groundwater levels. The aim was to investigate the link between shallow groundwater dynamics and runoff. The DDD (Distance Distribution Dynamics) model is a newly developed rainfall-runoff model used operationally by the Norwegian Flood-Forecasting service at NVE. The model estimates the capacity of the subsurface reservoir at different levels of saturation and predicts overland flow. The subsurface in the DDD model has a 2-D representation that calculates the saturated and unsaturated soil moisture along a hillslope representing the entire catchment in question. The groundwater observations from more than two decades ago are used to verify assumptions of the subsurface reservoir in the DDD model and to validate its spatial representation of the subsurface reservoir. The Muren catchment will, during 2017, be re-instrumented in order to continue the work to bridge the gap between conceptual hydrological models, with typically single value or 0-dimension representation of the subsurface, and models with more realistic 2- or 3-dimension representation of the subsurface.
Hagemann, Stefan; Chen, Cui; Haerter, Jan O.; Gerten, Dieter; Heinke, Jens; Piani, Claudio
Future climate model scenarios depend crucially on their adequate representation of the hydrological cycle. Within the European project "Water and Global Change" (WATCH) special care is taken to couple state-of-the-art climate model output to a suite of hydrological models. This coupling is expected to lead to a better assessment of changes in the hydrological cycle. However, due to the systematic model errors of climate models, their output is often not directly applicable as input for hydrological models. Thus, the methodology of a statistical bias correction has been developed, which can be used for correcting climate model output to produce internally consistent fields that have the same statistical intensity distribution as the observations. As observations, global re-analysed daily data of precipitation and temperature are used that are obtained in the WATCH project. We will apply the bias correction to global climate model data of precipitation and temperature from the GCMs ECHAM5/MPIOM, CNRM-CM3 and LMDZ-4, and intercompare the bias corrected data to the original GCM data and the observations. Then, the orginal and the bias corrected GCM data will be used to force two global hydrology models: (1) the hydrological model of the Max Planck Institute for Meteorology (MPI-HM) consisting of the Simplified Land surface (SL) scheme and the Hydrological Discharge (HD) model, and (2) the dynamic vegetation model LPJmL operated by the Potsdam Institute for Climate Impact Research. The impact of the bias correction on the projected simulated hydrological changes will be analysed, and the resulting behaviour of the two hydrology models will be compared.
Huang, Pengnian; Li, Zhijia; Chen, Ji; Li, Qiaoling; Yao, Cheng
To simulate the hydrological processes in semi-arid areas properly is still challenging. This study assesses the impact of different modeling strategies on simulating flood processes in semi-arid catchments. Four classic hydrological models, TOPMODEL, XINANJIANG (XAJ), SAC-SMA and TANK, were selected and applied to three semi-arid catchments in North China. Based on analysis and comparison of the simulation results of these classic models, four new flexible models were constructed and used to further investigate the suitability of various modeling strategies for semi-arid environments. Numerical experiments were also designed to examine the performances of the models. The results show that in semi-arid catchments a suitable model needs to include at least one nonlinear component to simulate the main process of surface runoff generation. If there are more than two nonlinear components in the hydrological model, they should be arranged in parallel, rather than in series. In addition, the results show that the parallel nonlinear components should be combined by multiplication rather than addition. Moreover, this study reveals that the key hydrological process over semi-arid catchments is the infiltration excess surface runoff, a non-linear component.
José Polo, María; José Pérez-Palazón, María; Saénz de Rodrigáñez, Marta; Pimentel, Rafael; Arheimer, Berit
global values and an additional correction was performed based on the relative anomalies obtained instead of the absolute values. This approach was used to derive the future projections of selected local indicators for each end-user in the area under different climate change scenarios. Despite the spatial scale conflicts, the SWICCA river flow indicators (simulated by the E-HYPEv3.1.2 model) succeeded in approximating the observations during the reference period 1970-2000 when provided on a catchment scale, once local transfer functions and further anomaly correction were performed. Satisfactory results were obtained on a monthly scale for river flow in the main stream of the watershed, and on a daily scale for the headwater streams. The accessibility to the hydrological model WiMMed, which includes a snow module, locally validated in the study area has been crucial to downscale the SWICCA results and prove their usefulness.
Wilson, C. J.; Andresen, C. G.; Atchley, A. L.; Bolton, W. R.; Busey, R.; Coon, E.; Charsley-Groffman, L.
The CMIP5 Earth System Models were unable to adequately predict the fate of the 16GT of permafrost carbon in a warming climate due to poor representation of Arctic ecosystem processes. The DOE Office of Science Next Generation Ecosystem Experiment, NGEE-Arctic project aims to reduce uncertainty in the Arctic carbon cycle and its impact on the Earth's climate system by improved representation of the coupled physical, chemical and biological processes that drive how much buried carbon will be converted to CO2 and CH4, how fast this will happen, which form will dominate, and the degree to which increased plant productivity will offset increased soil carbon emissions. These processes fundamentally depend on permafrost thaw rate and its influence on surface and subsurface hydrology through thermal erosion, land subsidence and changes to groundwater flow pathways as soil, bedrock and alluvial pore ice and massive ground ice melts. LANL and its NGEE colleagues are co-developing data and models to better understand controls on permafrost degradation and improve prediction of the evolution of permafrost and its impact on Arctic hydrology. The LANL Advanced Terrestrial Simulator was built using a state of the art HPC software framework to enable the first fully coupled 3-dimensional surface-subsurface thermal-hydrology and land surface deformation simulations to simulate the evolution of the physical Arctic environment. Here we show how field data including hydrology, snow, vegetation, geochemistry and soil properties, are informing the development and application of the ATS to improve understanding of controls on permafrost stability and permafrost hydrology. The ATS is being used to inform parameterizations of complex coupled physical, ecological and biogeochemical processes for implementation in the DOE ACME land model, to better predict the role of changing Arctic hydrology on the global climate system. LA-UR-17-26566.
Böttcher, T.; Schroll, R.
Spray-drift, drainage, erosion and runoff events are the major causes responsible for deportation of agrochemicals as micropollutants to aquatic non-target sites. These processes can lead to the contamination of nearby freshwater ecosystems with considerably high concentrations of xenobiotics. Thus, it is important to unravel the fate of these pollutants and to evaluate their ecological effects. A novel approach to address this goal was established by the development of a microcosm with multiple sampling abilities enabling quantitative assessment of organic volatilisation, mineralization, metabolization and distribution within the aquatic ecosystem. This microcosm system was designed to support modelling approaches of the catchment scale and gain insights into the fate of pesticides simulating a large scale water body. The potential of this microcosm was exemplified for Isoproturon (IPU), a phenylurea derived systemic herbicide, which is frequently found as contaminant in water samples and with the free-floating macrophyte Lemna minor as non-target species, that is common to occur in rural water bodies. During 21 days exposure time, only a small amount of 14C labeled IPU was removed from the aquatic medium. The major portion (about 5%) was accumulated by Lemna minor resulting in a BCF of 15.8. IPU-volatilisation was very low with 0.13% of the initially applied herbicide. Only a minor amount of IPU was completely metabolized, presumably by rhizosphere microorganisms and released as 14CO2. The novel experimental system allowed to quantitatively investigate the fate of IPU and showed a high reproducibility with a mean average 14C-recovery rate of 97.1
Tompkins, Adrian; Asare, Ernest; Bomblies, Arne; Amekudzi, Leonard
Small, sun-lit temporary pools that form during the rainy season are important breeding sites for many key mosquito vectors responsible for the transmission of malaria and other diseases. The representation of this surface hydrology in mathematical disease models is challenging, due to their small-scale, dependence on the terrain and the difficulty of setting soil parameters. Here we introduce a model that represents the temporal evolution of the aggregate statistics of breeding sites in a single pond fractional coverage parameter. The model is based on a simple, geometrical assumption concerning the terrain, and accounts for the processes of surface runoff, pond overflow, infiltration and evaporation. Soil moisture, soil properties and large-scale terrain slope are accounted for using a calibration parameter that sets the equivalent catchment fraction. The model is calibrated and then evaluated using in situ pond measurements in Ghana and ultra-high (10m) resolution explicit simulations for a village in Niger. Despite the model's simplicity, it is shown to reproduce the variability and mean of the pond aggregate water coverage well for both locations and validation techniques. Example malaria simulations for Uganda will be shown using this new scheme with a generic calibration setting, evaluated using district malaria case data. Possible methods for implementing regional calibration will be briefly discussed.
Dozier, A.; Arabi, M.; David, O.
Many challenges are introduced to interdisciplinary research in and around the hydrologic science community due to advances in computing technology and modeling capabilities in different programming languages, across different platforms and frameworks by researchers in a variety of fields with a variety of experience in computer programming. Many new hydrologic models as well as optimization, parameter estimation, and uncertainty characterization techniques are developed in scripting languages such as Matlab, R, Python, or in newer languages such as Java and the .Net languages, whereas many legacy models have been written in FORTRAN and C, which complicates inter-model communication for two-way feedbacks. However, most hydrologic researchers and industry personnel have little knowledge of the computing technologies that are available to address the model integration process. Therefore, the goal of this study is to address these new challenges by utilizing a novel approach based on a publish-subscribe-type system to enhance modeling capabilities of legacy socio-economic, hydrologic, and ecologic software. Enhancements include massive parallelization of executions and access to legacy model variables at any point during the simulation process by another program without having to compile all the models together into an inseparable 'super-model'. Thus, this study provides two-way feedback mechanisms between multiple different process models that can be written in various programming languages and can run on different machines and operating systems. Additionally, a level of abstraction is given to the model integration process that allows researchers and other technical personnel to perform more detailed and interactive modeling, visualization, optimization, calibration, and uncertainty analysis without requiring deep understanding of inter-process communication. To be compatible, a program must be written in a programming language with bindings to a common
Lüdtke, Stefan; Apel, Heiko; Nied, Manuela; Carl, Peter; Merz, Bruno
A universal problem of the calibration of hydrological models is the equifinality of different parameter sets derived from the calibration of models against total runoff values. This is an intrinsic problem stemming from the quality of the calibration data and the simplified process representation by the model. However, discharge data contains additional information which can be extracted by signal processing methods. An analysis specifically developed for the disaggregation of runoff time series into flow components is the Functional Streamflow Disaggregation (FSD; Carl & Behrendt, 2008). This method is used in the calibration of an implementation of the hydrological model SWIM in a medium sized watershed in Thailand. FSD is applied to disaggregate the discharge time series into three flow components which are interpreted as base flow, inter-flow and surface runoff. In addition to total runoff, the model is calibrated against these three components in a modified GLUE analysis, with the aim to identify structural model deficiencies, assess the internal process representation and to tackle equifinality. We developed a model dependent (MDA) approach calibrating the model runoff components against the FSD components, and a model independent (MIA) approach comparing the FSD of the model results and the FSD of calibration data. The results indicate, that the decomposition provides valuable information for the calibration. Particularly MDA highlights and discards a number of standard GLUE behavioural models underestimating the contribution of soil water to river discharge. Both, MDA and MIA yield to a reduction of the parameter ranges by a factor up to 3 in comparison to standard GLUE. Based on these results, we conclude that the developed calibration approach is able to reduce the equifinality of hydrological model parameterizations. The effect on the uncertainty of the model predictions is strongest by applying MDA and shows only minor reductions for MIA. Besides
Regan, R. Steven; Markstrom, Steven L.; Hay, Lauren E.; Viger, Roland J.; Norton, Parker A.; Driscoll, Jessica M.; LaFontaine, Jacob H.
This report documents several components of the U.S. Geological Survey National Hydrologic Model of the conterminous United States for use with the Precipitation-Runoff Modeling System (PRMS). It provides descriptions of the (1) National Hydrologic Model, (2) Geospatial Fabric for National Hydrologic Modeling, (3) PRMS hydrologic simulation code, (4) parameters and estimation methods used to compute spatially and temporally distributed default values as required by PRMS, (5) National Hydrologic Model Parameter Database, and (6) model extraction tool named Bandit. The National Hydrologic Model Parameter Database contains values for all PRMS parameters used in the National Hydrologic Model. The methods and national datasets used to estimate all the PRMS parameters are described. Some parameter values are derived from characteristics of topography, land cover, soils, geology, and hydrography using traditional Geographic Information System methods. Other parameters are set to long-established default values and computation of initial values. Additionally, methods (statistical, sensitivity, calibration, and algebraic) were developed to compute parameter values on the basis of a variety of nationally-consistent datasets. Values in the National Hydrologic Model Parameter Database can periodically be updated on the basis of new parameter estimation methods and as additional national datasets become available. A companion ScienceBase resource provides a set of static parameter values as well as images of spatially-distributed parameters associated with PRMS states and fluxes for each Hydrologic Response Unit across the conterminuous United States.
Kroll, Charles N.; Song, Peter
Often hydrologic regression models are developed with ordinary least squares (OLS) procedures. The use of OLS with highly correlated explanatory variables produces multicollinearity, which creates highly sensitive parameter estimators with inflated variances and improper model selection. It is not clear how to best address multicollinearity in hydrologic regression models. Here a Monte Carlo simulation is developed to compare four techniques to address multicollinearity: OLS, OLS with variance inflation factor screening (VIF), principal component regression (PCR), and partial least squares regression (PLS). The performance of these four techniques was observed for varying sample sizes, correlation coefficients between the explanatory variables, and model error variances consistent with hydrologic regional regression models. The negative effects of multicollinearity are magnified at smaller sample sizes, higher correlations between the variables, and larger model error variances (smaller R2). The Monte Carlo simulation indicates that if the true model is known, multicollinearity is present, and the estimation and statistical testing of regression parameters are of interest, then PCR or PLS should be employed. If the model is unknown, or if the interest is solely on model predictions, is it recommended that OLS be employed since using more complicated techniques did not produce any improvement in model performance. A leave-one-out cross-validation case study was also performed using low-streamflow data sets from the eastern United States. Results indicate that OLS with stepwise selection generally produces models across study regions with varying levels of multicollinearity that are as good as biased regression techniques such as PCR and PLS.
Bouaziz, Laurène; Sperna Weiland, Frederiek; Drogue, Gilles; Brauer, Claudia; Weerts, Albrecht
International collaboration between institutes and universities working and studying the same transboundary basin is needed for consensus building around possible effects of climate change and climate adaptation measures. Education, experience and expert knowledge of the hydrological community have resulted in the development of a great variety of model concepts, calibration and analysis techniques. Intercomparison could be a first step into consensus modeling or an ensemble based modeling strategy. Besides these practical objectives, such an intercomparison offers the opportunity to explore different ranges of models and learn from each other, hopefully increasing the insight into the hydrological processes that play a role in the transboundary basin. In this experiment, different international research groups applied their rainfall-runoff model in the Ourthe, a Belgium sub-catchment of the Meuse. Data preparation involved the interpolation of hourly precipitation station data collected and owned by the Service Public de Wallonie1 and the freely available E-OBS dataset for daily temperature (Haylock et al., 2008). Daily temperature was disaggregated to hourly values and potential evaporation was derived with the Hargreaves formula. The data was made available to the researchers through an FTP server. The protocol for the modeling involved a split-sample calibration and validation for pre-defined periods. Objective functions for calibration were fixed but the calibration algorithm was a free choice of the research groups. The selection of calibration algorithm was considered model dependent because lumped as well as computationally less efficient distributed models were used. For each model, an ensemble of best performing parameter sets was selected and several performance metrics enabled to assess the models' abilities to simulate discharge. The aim of this experiment is to identify those model components and structures that increase model performance and may best
Yamanaka, T.; Sato, R.
Transpiration (T) through plants (i.e., green water) does not induce isotopic fractionation, although evaporation (E) from soils and water surfaces do. Therefore, water stable isotopes offer a powerful tool to partition evapotranspiration (ET) components. We attempted to evaluate catchment-scale T/ET for five mountainous catchments in the central Japan, using river water isotopes and isotope maps of precipitation and soil water as well as climatic and radar precipitation maps. The estimated T/ET ranged from 56% to 79% (ET not including interception loss), and negatively correlated with mean elevation of the catchments (r = -0.88). This is due to decreasing transpiration (-82 mm/yr per 100 m) and slightly increasing evaporation (8 mm/yr per 100 m) with increasing elevation. Another estimation scheme using isotope data only showed a positive correlation between elevation and E/P*, where P* is effective precipitation defined by gross precipitation minus interception. Because the forest coverage within the catchments has positive correlation with catchment-mean-elevation, both decrease in transpiration and increase in soil evaporation seem to reflect structural change in forests (e.g., dense to sparse) along elevation and thus temperature gradients. Applying the space-for-time substitution, our results indicates that global warming will increase transpiration (and thus carbon intake) at mid-latitude mountainous landscapes.
Mariano Hernandez; Scott N. Miller
An integrated hydrologic modeling/watershed assessment tool is being developed to aid in determining the susceptibility of semiarid landscapes to natural and human-induced changes across a range of scales. Watershed processes are by definition spatially distributed and are highly variable through time, and this approach is designed to account for their spatial and...
R.S. Mansell; S.A. Bloom; Ge Sun
WETLANDS, a multidimensional model describing water flow in variably saturated soil and evapotranspiration, was used to simulate successfully 3-years of local hydrology for a cypress pond located within a relatively flat Coastal Plain pine forest landscape. Assumptions included negligible net regional groundwater flow and radially symmetric local flow impinging on a...
A permeable pavement system can capture stormwater to reduce runoff volume and flow rate, improve onsite groundwater recharge, and enhance pollutant controls within the site. A new unit process model for evaluating the hydrologic performance of a permeable pavement system has be...
Salt marsh hydrology presents many difficulties from a modeling standpoint: the bi-directional flows of tidal waters, variable water densities due to mixing of fresh and salt water, significant influences from vegetation, and complex stream morphologies. Because of these difficu...
Li, Yanling; Babcock, Roger W
Green roofs reduce runoff from impervious surfaces in urban development. This paper reviews the technical literature on green roof hydrology. Laboratory experiments and field measurements have shown that green roofs can reduce stormwater runoff volume by 30 to 86%, reduce peak flow rate by 22 to 93% and delay the peak flow by 0 to 30 min and thereby decrease pollution, flooding and erosion during precipitation events. However, the effectiveness can vary substantially due to design characteristics making performance predictions difficult. Evaluation of the most recently published study findings indicates that the major factors affecting green roof hydrology are precipitation volume, precipitation dynamics, antecedent conditions, growth medium, plant species, and roof slope. This paper also evaluates the computer models commonly used to simulate hydrologic processes for green roofs, including stormwater management model, soil water atmosphere and plant, SWMS-2D, HYDRUS, and other models that are shown to be effective for predicting precipitation response and economic benefits. The review findings indicate that green roofs are effective for reduction of runoff volume and peak flow, and delay of peak flow, however, no tool or model is available to predict expected performance for any given anticipated system based on design parameters that directly affect green roof hydrology.
The accuracy-based model performance metrics not necessarily reflect the qualitative correspondence between simulated and measured streamflow time series. The objective of this work was to use the information theory-based metrics to see whether they can be used as complementary tool for hydrologic m...
Hydrological models are commonly evaluated through the residual-based performance measures such as the root-mean square error or efficiency criteria. Such measures, however, do not evaluate the degree of similarity of patterns in simulated and measured time series. The objective of this study was to...
Van Loon, Anne
Drought is a global challenge. To be able to manage drought effectively on global or national scales without losing smaller scale variability and local context, we need to understand what the important hydrological drought processes are at different scales. Global scale models and satellite data are providing a global overview and catchment scale studies provide detailed site-specific information. I am interested in bridging these two scale levels by learning from catchments from around the world. Much information from local case studies is currently underused on larger scales because there is too much complexity. However, some of this complexity might be crucial on the level where people are facing the consequences of drought. In this talk, I will take you on a journey around the world to unlock catchment scale information and see if the comparison of many catchments gives us additional understanding of hydrological drought processes on the global scale. I will focus on the role of storage in different compartments of the terrestrial hydrological cycle, and how we as humans interact with that storage. I will discuss aspects of spatial and temporal variability in storage that are crucial for hydrological drought development and persistence, drawing from examples of catchments with storage in groundwater, lakes and wetlands, and snow and ice. The added complexity of human activities shifts the focus from natural to catchments with anthropogenic increases in storage (reservoirs), decreases in storage (groundwater abstraction), and changes in hydrological processes (urbanisation). We learn how local information is providing valuable insights, in some cases challenging theoretical understanding or model outcomes. Despite the challenges of working across countries, with a high number of collaborators, in a multitude of languages, under data-scarce conditions, the scientific advantages of bridging scales are substantial. The comparison of catchments around the world can
Kralisch, Sven; Fischer, Christian
Current challenges of understanding and assessing the impacts of climate and land use changes on environmental systems demand for an ever-increasing integration of data and process knowledge in corresponding simulation models. Software frameworks that allow for a seamless creation of integrated models based on less complex components (domain models, process simulation routines) have therefore gained increasing attention during the last decade. JAMS is an Open-Source software framework that has been especially designed to cope with the challenges of eco-hydrological modelling. This is reflected by (i) its flexible approach for representing time and space, (ii) a strong separation of process simulation components from the declarative description of more complex models using domain specific XML, (iii) powerful analysis and visualization functions for spatial and temporal input and output data, and (iv) parameter optimization and uncertainty analysis functions commonly used in environmental modelling. Based on JAMS, different hydrological and nutrient-transport simulation models were implemented and successfully applied during the last years. We will present the JAMS core concepts and give an overview of models, simulation components and support tools available for that framework. Sample applications will be used to underline the advantages of component-based model designs and to show how JAMS can be used to address the challenges of integrated hydrological modelling.
Yang, Y.; Donohue, R. J.; McVicar, T.
Plant rooting depth (Zr) is a key parameter in hydrological and biogeochemical models, yet the global spatial distribution of Zr is largely unknown due to the difficulties in its direct measurement. Moreover, Zr observations are usually only representative of a single plant or several plants, which can differ greatly from the effective Zr over a modelling unit (e.g., catchment or grid-box). Here, we provide a global parameterization of an analytical Zr model that balances the marginal carbon cost and benefit of deeper roots, and produce a climatological (i.e., 1982-2010 average) global Zr map. To test the Zr estimates, we apply the estimated Zr in a highly transparent hydrological model (i.e., the Budyko-Choudhury-Porporato (BCP) model) to estimate mean annual actual evapotranspiration (E) across the globe. We then compare the estimated E with both water balance-based E observations at 32 major catchments and satellite grid-box retrievals across the globe. Our results show that the BCP model, when implemented with Zr estimated herein, optimally reproduced the spatial pattern of E at both scales and provides improved model outputs when compared to BCP model results from two already existing global Zr datasets. These results suggest that our Zr estimates can be effectively used in state-of-the-art hydrological models, and potentially biogeochemical models, where the determination of Zr currently largely relies on biome type-based look-up tables.
Schmengler, A. C.; Vlek, P. L. G.
Modelling soil erosion requires a holistic understanding of the sediment dynamics in a complex environment. As most erosion models are scale-dependent and their parameterization is spatially limited, their application often requires special care, particularly in data-scarce environments. This study presents a hierarchical approach to overcome the limitations of a single model by using various quantitative methods and soil erosion models to cope with the issues of scale. At hillslope scale, the physically-based Water Erosion Prediction Project (WEPP)-model is used to simulate soil loss and deposition processes. Model simulations of soil loss vary between 5 to 50 t ha-1 yr-1 dependent on the spatial location on the hillslope and have only limited correspondence with the results of the 137Cs technique. These differences in absolute soil loss values could be either due to internal shortcomings of each approach or to external scale-related uncertainties. Pedo-geomorphological soil investigations along a catena confirm that estimations by the 137Cs technique are more appropriate in reflecting both the spatial extent and magnitude of soil erosion at hillslope scale. In order to account for sediment dynamics at a larger scale, the spatially-distributed WaTEM/SEDEM model is used to simulate soil erosion at catchment scale and to predict sediment delivery rates into a small water reservoir. Predicted sediment yield rates are compared with results gained from a bathymetric survey and sediment core analysis. Results show that specific sediment rates of 0.6 t ha-1 yr-1 by the model are in close agreement with observed sediment yield calculated from stratigraphical changes and downcore variations in 137Cs concentrations. Sediment erosion rates averaged over the entire catchment of 1 to 2 t ha-1 yr-1 are significantly lower than results obtained at hillslope scale confirming an inverse correlation between the magnitude of erosion rates and the spatial scale of the model. The
Marshall, L.; Sharma, A.; Nott, D.
Estimation of parameter uncertainty (and in turn model uncertainty) allows assessment of the risk in likely applications of hydrological models. Bayesian statistical inference provides an ideal means of assessing parameter uncertainty whereby prior knowledge about the parameter is combined with information from the available data to produce a probability distribution (the posterior distribution) that describes uncertainty about the parameter and serves as a basis for selecting appropriate values for use in modelling applications. Widespread use of Bayesian techniques in hydrology has been hindered by difficulties in summarizing and exploring the posterior distribution. These difficulties have been largely overcome by recent advances in Markov chain Monte Carlo (MCMC) methods that involve random sampling of the posterior distribution. This study presents an adaptive MCMC sampling algorithm which has characteristics that are well suited to model parameters with a high degree of correlation and interdependence, as is often evident in hydrological models. The MCMC sampling technique is used to compare six alternative configurations of a commonly used conceptual rainfall-runoff model, the Australian Water Balance Model (AWBM), using 11 years of daily rainfall runoff data from the Bass river catchment in Australia. The alternative configurations considered fall into two classes - those that consider model errors to be independent of prior values, and those that model the errors as an autoregressive process. Each such class consists of three formulations that represent increasing levels of complexity (and parameterisation) of the original model structure. The results from this study point both to the importance of using Bayesian approaches in evaluating model performance, as well as the simplicity of the MCMC sampling framework that has the ability to bring such approaches within the reach of the applied hydrological community.
Boyce, S. E.; Hanson, R. T.
The One-Water Hydrologic Flow Model (MF-OWHM) is a MODFLOW-based integrated hydrologic flow model that is the most complete version, to date, of the MODFLOW family of hydrologic simulators needed for the analysis of a broad range of conjunctive-use issues. MF-OWHM fully links the movement and use of groundwater, surface water, and imported water for consumption by agriculture and natural vegetation on the landscape, and for potable and other uses within a supply-and-demand framework. MF-OWHM is based on the Farm Process for MODFLOW-2005 combined with Local Grid Refinement, Streamflow Routing, Surface-water Routing Process, Seawater Intrusion, Riparian Evapotranspiration, and the Newton-Raphson solver. MF-OWHM also includes linkages for deformation-, flow-, and head-dependent flows; additional observation and parameter options for higher-order calibrations; and redesigned code for facilitation of self-updating models and faster simulation run times. The next version of MF-OWHM, currently under development, will include a new surface-water operations module that simulates dynamic reservoir operations, the conduit flow process for karst aquifers and leaky pipe networks, a new subsidence and aquifer compaction package, and additional features and enhancements to enable more integration and cross communication between traditional MODFLOW packages. By retaining and tracking the water within the hydrosphere, MF-OWHM accounts for "all of the water everywhere and all of the time." This philosophy provides more confidence in the water accounting by the scientific community and provides the public a foundation needed to address wider classes of problems such as evaluation of conjunctive-use alternatives and sustainability analysis, including potential adaptation and mitigation strategies, and best management practices. By Scott E. Boyce and Randall T. Hanson
Marsh, C.; Pomeroy, J. W.; Wheater, H. S.
There is a need for hydrological land surface schemes that can link to atmospheric models, provide hydrological prediction at multiple scales and guide the development of multiple objective water predictive systems. Distributed raster-based models suffer from an overrepresentation of topography, leading to wasted computational effort that increases uncertainty due to greater numbers of parameters and initial conditions. The Canadian Hydrological Model (CHM) is a modular, multiphysics, spatially distributed modelling framework designed for representing hydrological processes, including those that operate in cold-regions. Unstructured meshes permit variable spatial resolution, allowing coarse resolutions at low spatial variability and fine resolutions as required. Model uncertainty is reduced by lessening the necessary computational elements relative to high-resolution rasters. CHM uses a novel multi-objective approach for unstructured triangular mesh generation that fulfills hydrologically important constraints (e.g., basin boundaries, water bodies, soil classification, land cover, elevation, and slope/aspect). This provides an efficient spatial representation of parameters and initial conditions, as well as well-formed and well-graded triangles that are suitable for numerical discretization. CHM uses high-quality open source libraries and high performance computing paradigms to provide a framework that allows for integrating current state-of-the-art process algorithms. The impact of changes to model structure, including individual algorithms, parameters, initial conditions, driving meteorology, and spatial/temporal discretization can be easily tested. Initial testing of CHM compared spatial scales and model complexity for a spring melt period at a sub-arctic mountain basin. The meshing algorithm reduced the total number of computational elements and preserved the spatial heterogeneity of predictions.
Water erosion is a serious and continuous environmental problem worldwide. In cold regions, soil freeze and thaw has great impacts on infiltration and erosion. Rain or snowmelt on a thawing soil can cause severe water erosion. Of equal importance is snow accumulation and snowmelt, which can be the predominant hydrological process in areas of mid- to high latitudes and forested watersheds. Modelers must properly simulate winter processes to adequately represent the overall hydrological outcome and sediment and chemical transport in these areas. Modeling winter hydrology is presently lacking in water erosion models. Most of these models are based on the functional Universal Soil Loss Equation (USLE) or its revised forms, e.g., Revised USLE (RUSLE). In RUSLE a seasonally variable soil erodibility factor (K) was used to account for the effects of frozen and thawing soil. Yet the use of this factor requires observation data for calibration, and such a simplified approach cannot represent the complicated transient freeze-thaw processes and their impacts on surface runoff and erosion. The Water Erosion Prediction Project (WEPP) watershed model, a physically-based erosion prediction software developed by the USDA-ARS, has seen numerous applications within and outside the US. WEPP simulates winter processes, including snow accumulation, snowmelt, and soil freeze-thaw, using an approach based on mass and energy conservation. However, previous studies showed the inadequacy of the winter routines in the WEPP model. Therefore, the objectives of this study were: (1) To adapt a modeling approach for winter hydrology based on mass and energy conservation, and to implement this approach into a physically-oriented hydrological model, such as WEPP; and (2) To assess this modeling approach through case applications to different geographic conditions. A new winter routine was developed and its performance was evaluated by incorporating it into WEPP (v2008.9) and then applying WEPP to
Shu, L.; Duffy, C.
There has been extensive research on LUC modeling with broad applications to simulating urban growth and changing demographic patterns across multiple scales. The importance of land conversion is a critical issue in watershed scale studies and is generally not treated in most watershed modeling approaches. In this study we apply spatially explicit hydrologic and landuse change models and the Conestoga Watershed in Lancaster County, Pennsylvania. The Penn State Integrated Hydrologic Model (PIHM) partitions the water balance in space and time over the urban catchment, the coupled Cellular Automata Land Use Change model (CALUC) dynamically simulates the evolution of land use classes based on physical measures associated with population change and land use demand factors. The CALUC model is based on iteratively applying discrete rules to each individual spatial cell. The essence the CA modeling involves calculation of the Transition Potential (TP) for conversion of a grid cell from one land use class to another. This potential includes five factors: random perturbation, suitability, accessibility, neighborhood effect, inertia effects and zonal factors. In spite of simplicity, this CALUC model has been shown to be very effective for simulating LUC leading to the emergence of complex spatial patterns. The components of TP are derived from present land use data for landuse reanalysis and for realistic future land use scenarios. For the CALUC we use early-settlement (circa 1790) initial land class values and final or present-day (2010) land classes to calibrate the model. CALUC- PIHM dynamically simulates the hydrologic response of conversion from pre-settlement to present landuse. The simulations highlight the capability and value of dynamic coupling of catchment hydrology with land use change over long time periods. Analysis of the simulation uses various metrics such as the distributed water balance, flow duration curves, etc. to show how deforestation, urbanization and
Holkje Barendrecht, Marlies; Viglione, Alberto; Kreibich, Heidi; Vorogushyn, Sergiy; Merz, Bruno; Blöschl, Günter
Socio-hydrological modelling studies that have been published so far show that dynamic coupled human-flood models are a promising tool to represent the phenomena and the feedbacks in human-flood systems. So far these models are mostly generic and have not been developed and calibrated to represent specific case studies. We believe that applying and calibrating these type of models to real world case studies can help us to further develop our understanding about the phenomena that occur in these systems. In this paper we propose a method to estimate the parameter values of a socio-hydrological model and we test it by applying it to an artificial case study. We postulate a model that describes the feedbacks between floods, awareness and preparedness. After simulating hypothetical time series with a given combination of parameters, we sample few data points for our variables and try to estimate the parameters given these data points using Bayesian Inference. The results show that, if we are able to collect data for our case study, we would, in theory, be able to estimate the parameter values for our socio-hydrological flood model.
Zheng, Shuang; Lourenço, Sérgio D. N.; Cleall, Peter J.; Chui, Ting Fong May; Ng, Angel K. Y.; Millis, Stuart W.
In the natural environment, soil water repellency decreases infiltration, increases runoff, and increases erosion in slopes. In the built environment, soil water repellency offers the opportunity to develop granular materials with controllable wettability for slope stabilization. In this paper, the influence of soil water repellency on the hydrological response of slopes is investigated. Twenty-four flume tests were carried out in model slopes under artificial rainfall; soils with various wettability levels were tested, including wettable (Contact Angle, CA < 90°), subcritical water repellent (CA ∼ 90°) and water repellent (CA > 90°). Various rainfall intensities (30 mm/h and 70 mm/h), slope angles (20° and 40°) and relative compactions (70% and 90%) were applied to model the response of natural and man-made slopes to rainfall. To quantitatively assess the hydrological response, a number of measurements were made: runoff rate, effective rainfall rate, time to ponding, time to steady state, runoff acceleration, total water storage and wetting front rate. Overall, an increase in soil water repellency reduces infiltration and shortens the time for runoff generation, with the effects amplified for high rainfall intensity. Comparatively, the slope angle and relative compaction had only a minor contribution to the slope hydrology. The subcritical water repellent soils sustained infiltration for longer than both the wettable and water repellent soils, which presents an added advantage if they are to be used in the built environment as barriers. This study revealed substantial impacts of man-made or synthetically induced soil water repellency on the hydrological behavior of model slopes in controlled conditions. The results shed light on our understanding of hydrological processes in environments where the occurrence of natural soil water repellency is likely, such as slopes subjected to wildfires and in agricultural and forested slopes.
Wildemeersch, Jasmien; Garba, Maman; Sabiou, Mahaman; Al-Barri, Bashar; Cornelis, Wim
transpiration increased with WSC and highest millet yields were found with zaï pits (4 to 5 times higher than under the fertilized control). Although rainwater was better partitioned in case of demi-lune microcatchments resulting in highest amounts of water stored in the soil, yield was only 40-60% of that with zaï pits. This was due to a higher plant density within each demi-lune microcatchment in an attempt to attain similar plant densities at field scale across the treatments. An optimized design for demi-lune microcatchments, in which the number of catchments per surface area is increased while reducing plant density per catchment, is therefore suggested. This was demonstrated using the fully coupled surface-subsurface process-based model that enabled to simulate at field scale overland and soil-water flow in 3D under various WSC designs. The model would also allow to evaluate the effect of WSC practices at catchment scale.
Rakovec, Oldrich; Kumar, Rohini; Attinger, Sabine; Samaniego, Luis
Increased availability and quality of near real-time observations should improve understanding of predictive skills of hydrological models. Recent studies have shown the limited capability of river discharge data alone to adequately constrain different components of distributed model parameterizations. In this study, the GRACE satellite-based total water storage (TWS) anomaly is used to complement the discharge data with an aim to improve the fidelity of mesoscale hydrologic model (mHM) through multivariate parameter estimation. The study is conducted in 83 European basins covering a wide range of hydro-climatic regimes. The model parameterization complemented with the TWS anomalies leads to statistically significant improvements in (1) discharge simulations during low-flow period, and (2) evapotranspiration estimates which are evaluated against independent (FLUXNET) data. Overall, there is no significant deterioration in model performance for the discharge simulations when complemented by information from the TWS anomalies. However, considerable changes in the partitioning of precipitation into runoff components are noticed by in-/exclusion of TWS during the parameter estimation. A cross-validation test carried out to assess the transferability and robustness of the calibrated parameters to other locations further confirms the benefit of complementary TWS data. In particular, the evapotranspiration estimates show more robust performance when TWS data are incorporated during the parameter estimation, in comparison with the benchmark model constrained against discharge only. This study highlights the value for incorporating multiple data sources during parameter estimation to improve the overall realism of hydrologic model and its applications over large domains. Rakovec, O., Kumar, R., Attinger, S. and Samaniego, L. (2016): Improving the realism of hydrologic model functioning through multivariate parameter estimation. Water Resour. Res., 52, http://dx.doi.org/10
Botta, Fabrizio; Chevreuil, Marc; Blanchoud, Hélène
The general use of pesticides in the Orge Basin, located in the southern part of the Paris suburb (France), is damaging surface water quality. Consequently, an increase in the water supply costs is registered by the water supply agencies that are situated downstream the Orge confluence with the Seine River. In this catchment, high uses of glyphosate are registered for fallow fields (upstream part) and for roadway weed control (downstream part). The proportion of glyphosate coming from these two zones was not well known, along with the double source of its metabolite AMPA originated from the degradation of some detergent phosphonates. The aim of this work was firstly to identify the potential sources of glyphosate and AMPA in urban sectors (such as sewerage system inputs) and in agricultural areas and to quantify the origins of urban pesticides pathways towards surface waters at the basin scale. The new approach of this project was to collect information at three different scales to establish a first step of modeling. At the basin scale, 1 year of surface water monitoring at the outlet of the Orge River was useful to establish the inputs towards the Seine River. At the urban catchment scale, the investigations have permitted to record glyphosate and AMPA loads transferred by storm waters and by wastewaters. Loads were estimated during and out of application calendar, in different hydrological conditions such as rainfall with high intensity or dry conditions. Impact of WWTP on surface water was also demonstrated. The third phase of this work was the interpretation of agricultural inputs from two different agricultural catchments of the Orge River. The results showed the impact of urban uses of glyphosate upon the Orge River contamination with annual loads from 100 times higher from the urban zone than from the agricultural one. Storm sewers were recognized to be the main way for glyphosate transfer towards surface waters. A budget of glyphosate and AMPA inputs and
Hydrologic Landscapes (HLs) are units that can be used in aggregate to describe the watershed-scale hydrologic response of an area through use of physical and climatic properties. The HL assessment unit is a useful classification tool to relate and transfer hydrologically meaning...
Hydrologic Landscapes (HLs) are units that can be used in aggregate to describe the watershed-scale hydrologic response of an area through use of physical and climatic properties. The HL assessment unit is a useful classification tool to relate and transfer hydrologically meaning...
Goktas, R. K.; Tezel, U.; Kargi, P. G.; Ayvaz, T.; Tezyapar, I.; Mesta, B.; Kentel, E.
Hydrological models are useful in predicting and developing management strategies for controlling the system behaviour. Specifically they can be used for evaluating streamflow at ungaged catchments, effect of climate change, best management practices on water resources, or identification of pollution sources in a watershed. This study is a part of a TUBITAK project named "Development of a geographical information system based decision-making tool for water quality management of Ergene Watershed using pollutant fingerprints". Within the scope of this project, first water resources in Ergene Watershed is studied. Streamgages found in the basin are identified and daily streamflow measurements are obtained from State Hydraulic Works of Turkey. Streamflow data is analysed using box-whisker plots, hydrographs and flow-duration curves focusing on identification of extreme periods, dry or wet. Then a hydrological model is developed for Ergene Watershed using HEC-HMS in the Watershed Modeling System (WMS) environment. The model is calibrated for various time periods including dry and wet ones and the performance of calibration is evaluated using Nash-Sutcliffe Efficiency (NSE), correlation coefficient, percent bias (PBIAS) and root mean square error. It is observed that calibration period affects the model performance, and the main purpose of the development of the hydrological model should guide calibration period selection. Acknowledgement: This study is funded by The Scientific and Technological Research Council of Turkey (TUBITAK) under Project Number 115Y064.
Sproles, E. A.; Orrego Nelson, C.; Kerr, T.; Lopez Aspe, D.
We present two runoff models that use remotely-sensed snow cover products from the Moderate Resolution Imaging Spectrometer (MODIS) as the first order hydrologic input. These simplistic models are the first step in developing an operational model for the Elqui River watershed located in northern Central Chile (30°S). In this semi-arid region, snow and glacier melt are the dominant hydrologic inputs where annual precipitation is limited to three or four winter events. Unfortunately winter access to the Andean Cordillera where snow accumulates is limited. While a monitoring network to measure snow where it accumulates in the upper elevations is under development, management decisions regarding water resources cannot wait. The two models we present differ in structure. The first applies a Monte Carlo approach to determine relationships between lagged changes in monthly snow cover frequency and monthly discharge. The second is a modified degree-day melt model, utilizing the MODIS snow cover product to determine where and when snow melt occurs. These models are not watershed specific and are applicable in other regions where snow dominates hydrologic inputs, but measurements are minimal.
Davidsen, Claus; Pereira-Cardenal, Silvio Javier; Liu, Suxia; Mo, Xingguo; Rosbjerg, Dan; Bauer-Gottwein, Peter
A hydro-economic modelling approach is used to optimize reservoir management at river basin level. We demonstrate the potential of this integrated approach on the Ziya River basin, a complex basin on the North China Plain south-east of Beijing. The area is subject to severe water scarcity due to low and extremely seasonal precipitation, and the intense agricultural production is highly dependent on irrigation. Large reservoirs provide water storage for dry months while groundwater and the external South-to-North Water Transfer Project are alternative sources of water. An optimization model based on stochastic dynamic programming has been developed. The objective function is to minimize the total cost of supplying water to the users, while satisfying minimum ecosystem flow constraints. Each user group (agriculture, domestic and industry) is characterized by fixed demands, fixed water allocation costs for the different water sources (surface water, groundwater and external water) and fixed costs of water supply curtailment. The multiple reservoirs in the basin are aggregated into a single reservoir to reduce the dimensions of decisions. Water availability is estimated using a hydrological model. The hydrological model is based on the Budyko framework and is forced with 51 years of observed daily rainfall and temperature data. 23 years of observed discharge from an in-situ station located downstream a remote mountainous catchment is used for model calibration. Runoff serial correlation is described by a Markov chain that is used to generate monthly runoff scenarios to the reservoir. The optimal costs at a given reservoir state and stage were calculated as the minimum sum of immediate and future costs. Based on the total costs for all states and stages, water value tables were generated which contain the marginal value of stored water as a function of the month, the inflow state and the reservoir state. The water value tables are used to guide allocation decisions in
Gan, T.; Tarboton, D. G.; Dash, P. K.; Gichamo, T.; Horsburgh, J. S.
Web based apps, web services and online data and model sharing technology are becoming increasingly available to support research. This promises benefits in terms of collaboration, platform independence, transparency and reproducibility of modeling workflows and results. However, challenges still exist in real application of these capabilities and the programming skills researchers need to use them. In this research we combined hydrologic modeling web services with an online data and model sharing system to develop functionality to support reproducible hydrologic modeling work. We used HydroDS, a system that provides web services for input data preparation and execution of a snowmelt model, and HydroShare, a hydrologic information system that supports the sharing of hydrologic data, model and analysis tools. To make the web services easy to use, we developed a HydroShare app (based on the Tethys platform) to serve as a browser based user interface for HydroDS. In this integration, HydroDS receives web requests from the HydroShare app to process the data and execute the model. HydroShare supports storage and sharing of the results generated by HydroDS web services. The snowmelt modeling example served as a use case to test and evaluate this approach. We show that, after the integration, users can prepare model inputs or execute the model through the web user interface of the HydroShare app without writing program code. The model input/output files and metadata describing the model instance are stored and shared in HydroShare. These files include a Python script that is automatically generated by the HydroShare app to document and reproduce the model input preparation workflow. Once stored in HydroShare, inputs and results can be shared with other users, or published so that other users can directly discover, repeat or modify the modeling work. This approach provides a collaborative environment that integrates hydrologic web services with a data and model sharing
The program models rainfall, runoff, infiltration, and other water pathways to estimate how much water builds up above each landfill liner. It can incorporate data on vegetation, soil types, geosynthetic materials, initial moisture conditions, slopes, etc.
Pejanovic, Goran; Petkovic, Slavko; Cvetkovic, Bojan; Nickovic, Slobodan
Numerical hydrologic modeling has achieved limited success in the past due to, inter alia, lack of adequate input data. Over the last decade, data availability has improved substantially. For modelling purposes, high-resolution data on topography, river routing, and land cover and soil features have meanwhile become available, as well as the observations such as radar precipitation information. In our study, we have implemented the HYPROM model (Hydrology Prognostic Model) to predict a flash flood event at a smaller-scale basin in Southern Serbia. HYPROM is based on the full set of governing equations for surface hydrological dynamics, in which momentum components, along with the equation of mass continuity, are used as full prognostic equations. HYPROM also includes a river routing module serving as a collector for the extra surface water. Such approach permits appropriate representation of different hydrology scales ranging from flash floods to flows of large and slow river basins. The use of full governing equations, if not appropriately parameterized, may lead to numerical instability systems when the surface water in a model is vanishing. To resolve these modelling problems, an unconditionally stable numerical scheme and a method for height redistribution avoiding shortwave height noise have been developed in HYPROM, which achieve numerical convergence of u, v and h when surface water disappears. We have applied HYPROM, driven by radar-estimated precipitation, to predict flash flooding occurred over smaller and medium-size river basins. Two torrential rainfall cases have been simulated to check the accuracy of the model: the exceptional flooding of May 2014 in Western Serbia, and the convective flash flood of January 2015 in Southern Serbia. The second episode has been successfully predicted by HYPROM in terms of timing and intensity six hours before the event occurred. Such flash flood warning system is in preparation to be operationally implemented in the
Mendizabal, Maddalen; Moncho, Roberto; Chust, Guillem; Torp, Peter
Future climate change will affect aquatic systems on various pathways. Regarding the hydrological cycle, which is a very important pathway, changes in hydrometeorological variables (air temperature, precipitation, evapotranspiration) in first order impact discharges. The fourth report assessment of the Intergovernmental Panel for Climate Change indicates there is evidence that the recent warming of the climate system would result in more frequent extreme precipitation events, increased winter flood likelihoods, increased and widespread melting of snow and ice, longer and more widespread droughts, and rising sea level. Available research and climate model outputs indicate a range of hydrological impacts with likely to very likely probabilities (67 to 99%). For example, it is likely that up to 20% of the world population will live in areas where river flood potential could increase by the 2080s. In Spain, within the Atlantic basin, the hydrological variability will increase in the future due to the intensification of the positive phase of the North Atlantic Oscillation (NAO) index. This might cause flood frequency decreases, but its magnitude does not decrease. The generation of flood, its duration and magnitude are closely linked to changes in winter precipitation. The climatic conditions and relief of the Iberian Peninsula favour the generation of floods. In Spain, floods had historically strong socio-economic impacts, with more than 1525 victims in the past five decades. This upward trend of hydrological variability is expected to remain in the coming decades (medium uncertainty) when the intensification of the positive phase of the NAO index (MMA, 2006) is considered. In order to adapt or minimize climate change impacts in water resources, it is necessary to use climate projections as well as hydrological modelling tools. The main objective of this paper is to evaluate and assess the hydrological response to climate changes in flow conditions in Nerbioi river
Rasmussen, Jes J; McKnight, Ursula S; Loinaz, Maria C; Thomsen, Nanna I; Olsson, Mikael E; Bjerg, Poul L; Binning, Philip J; Kronvang, Brian
Mitigation activities to improve water quality and quantity in streams as well as stream management and restoration efforts are conducted in the European Union aiming to improve the chemical, physical and ecological status of streams. Headwater streams are often characterised by impairment of hydromorphological, chemical, and ecological conditions due to multiple anthropogenic impacts. However, they are generally disregarded as water bodies for mitigation activities in the European Water Framework Directive despite their importance for supporting a higher ecological quality in higher order streams. We studied 11 headwater streams in the Hove catchment in the Copenhagen region. All sites had substantial physical habitat and water quality impairments due to anthropogenic influence (intensive agriculture, urban settlements, contaminated sites and low base-flow due to water abstraction activities in the catchment). We aimed to identify the dominating anthropogenic stressors at the catchment scale causing ecological impairment of benthic macroinvertebrate communities and provide a rank-order of importance that could help in prioritising mitigation activities. We identified numerous chemical and hydromorphological impacts of which several were probably causing major ecological impairments, but we were unable to provide a robust rank-ordering of importance suggesting that targeted mitigation efforts on single anthropogenic stressors in the catchment are unlikely to have substantial effects on the ecological quality in these streams. The SPEcies At Risk (SPEAR) index explained most of the variability in the macroinvertebrate community structure, and notably, SPEAR index scores were often very low (<10% SPEAR abundance). An extensive re-sampling of a subset of the streams provided evidence that especially insecticides were probably essential contributors to the overall ecological impairment of these streams. Our results suggest that headwater streams should be considered in
Le Maitre, D C; Gush, M B; Dzikiti, S
There have been many studies of the diverse impacts of invasions by alien plants but few have assessed impacts on water resources. We reviewed the information on the impacts of invasions on surface runoff and groundwater resources at stand to catchment scales and covering a full annual cycle. Most of the research is South African so the emphasis is on South Africa's major invaders with data from commercial forest plantations where relevant. Catchment studies worldwide have shown that changes in vegetation structure and the physiology of the dominant plant species result in changes in surface runoff and groundwater discharge, whether they involve native or alien plant species. Where there is little change in vegetation structure [e.g. leaf area (index), height, rooting depth and seasonality] the effects of invasions generally are small or undetectable. In South Africa, the most important woody invaders typically are taller and deeper rooted than the native species. The impacts of changes in evaporation (and thus runoff) in dryland settings are constrained by water availability to the plants and, thus, by rainfall. Where the dryland invaders are evergreen and the native vegetation (grass) is seasonal, the increases can reach 300-400 mm/year. Where the native vegetation is evergreen (shrublands) the increases are ∼200-300 mm/year. Where water availability is greater (riparian settings or shallow water tables), invading tree water-use can reach 1.5-2.0 times that of the same species in a dryland setting. So, riparian invasions have a much greater impact per unit area invaded than dryland invasions. The available data are scattered and incomplete, and there are many gaps and issues that must be addressed before a thorough understanding of the impacts at the site scale can be gained and used in extrapolating to watershed scales, and in converting changes in flows to water supply system yields. Published by Oxford University Press on behalf of the Annals of Botany
Le Maitre, D. C.; Gush, M. B.; Dzikiti, S.
There have been many studies of the diverse impacts of invasions by alien plants but few have assessed impacts on water resources. We reviewed the information on the impacts of invasions on surface runoff and groundwater resources at stand to catchment scales and covering a full annual cycle. Most of the research is South African so the emphasis is on South Africa's major invaders with data from commercial forest plantations where relevant. Catchment studies worldwide have shown that changes in vegetation structure and the physiology of the dominant plant species result in changes in surface runoff and groundwater discharge, whether they involve native or alien plant species. Where there is little change in vegetation structure [e.g. leaf area (index), height, rooting depth and seasonality] the effects of invasions generally are small or undetectable. In South Africa, the most important woody invaders typically are taller and deeper rooted than the native species. The impacts of changes in evaporation (and thus runoff) in dryland settings are constrained by water availability to the plants and, thus, by rainfall. Where the dryland invaders are evergreen and the native vegetation (grass) is seasonal, the increases can reach 300–400 mm/year. Where the native vegetation is evergreen (shrublands) the increases are ∼200–300 mm/year. Where water availability is greater (riparian settings or shallow water tables), invading tree water-use can reach 1.5–2.0 times that of the same species in a dryland setting. So, riparian invasions have a much greater impact per unit area invaded than dryland invasions. The available data are scattered and incomplete, and there are many gaps and issues that must be addressed before a thorough understanding of the impacts at the site scale can be gained and used in extrapolating to watershed scales, and in converting changes in flows to water supply system yields. PMID:25935861
Fowler, T. R.; Castruccio, P. A.; Loats, H. L., Jr.
The development of a remote sensing model and its efficiency in determining parameters of hydrologic models are reviewed. Procedures for extracting hydrologic data from LANDSAT imagery, and the visual analysis of composite imagery are presented. A hydrologic planning model is developed and applied to determine seasonal variations in watershed conditions. The transfer of this technology to a user community and contract arrangements are discussed.
Driscoll, J. M.; Molotch, N. P.; Jepsen, S. M.; Meixner, T.; Williams, M. W.; Sickman, J. O.
Snowmelt from high elevation catchments is the primary source of water resources in the Southwestern United States. Timing and duration of snowmelt and resulting catchment response can show the physical and chemical importance of storage at the catchment scale. Storage of waters in subsurface materials provides a physical and chemical buffer to hydrologic input variability. We expect the hydrochemistry of catchments with less storage capacity will more closely reflect input waters than a catchment with more storage and therefore more geochemical evolution of waters. Two headwater catchments were compared for this study; Emerald Lake Watershed (ELW) in the southern Sierra Nevada and Green Lake 4 (GL4) in the Colorado Front Range. These sites have geochemically similar granitic terrane, and negligible evaporation and transpiration due to their high-elevation setting. Eleven years of data (1996-2006) from spatially-distributed snowmelt models were spatially and temporally aggregated to generate daily values of snowmelt volume for each catchment area. Daily storage flux was calculated as the difference between snowmelt input and catchment outflow at a daily timestep, normalized to the catchment area. Daily snowmelt values in GL4 are more consistent (the annual standard deviation ranged from 0.19 to 0.76 cm) than the daily snowmelt in ELW (0.60 to 1.04 cm). Outflow follows the same trend, with an even narrower range of standard deviations from GL4 (0.27 to 0.54 cm) compared to the standard deviation of outflow in ELW (0.38 to 0.98 cm). The dampening of the input variability could be due to storage in the catchment; the larger effect would mean a larger storage capacity in the catchment. Calculations of storage flux (the input snowmelt minus the output catchment discharge) show the annual sum of water into storage in ELW ranges from -0.9200 to 1.1124 meters, in GL4 the ranger is narrower, from -0.655 to 0.0992 meters. Cumulative storage for each year can be negative
Patrick, Christopher J; Yuan, Lester L
Flow alteration is widespread in streams, but current understanding of the effects of differences in flow characteristics on stream biological communities is incomplete. We tested hypotheses about the effect of variation in hydrology on stream communities by using generalized additive models to relate watershed information to the values of different flow metrics at gauged sites. Flow models accounted for 54-80% of the spatial variation in flow metric values among gauged sites. We then used these models to predict flow metrics in 842 ungauged stream sites in the mid-Atlantic United States that were sampled for fish, macroinvertebrates, and environmental covariates. Fish and macroinvertebrate assemblages were characterized in terms of a suite of metrics that quantified aspects of community composition, diversity, and functional traits that were expected to be associated with differences in flow characteristics. We related modeled flow metrics to biological metrics in a series of stressor-response models. Our analyses identified both drying and base flow instability as explaining 30-50% of the observed variability in fish and invertebrate community composition. Variations in community composition were related to variations in the prevalence of dispersal traits in invertebrates and trophic guilds in fish. The results demonstrate that we can use statistical models to predict hydrologic conditions at bioassessment sites, which, in turn, we can use to estimate relationships between flow conditions and biological characteristics. This analysis provides an approach to quantify the effects of spatial variation in flow metrics using readily available biomonitoring data. © 2017 by the Ecological Society of America.
Dow, C F; Kulessa, B; Rutt, I C; Tsai, V C; Pimentel, S; Doyle, S H; van As, D; Lindbäck, K; Pettersson, R; Jones, G A; Hubbard, A
The rapid drainage of supraglacial lakes injects substantial volumes of water to the bed of the Greenland ice sheet over short timescales. The effect of these water pulses on the development of basal hydrological systems is largely unknown. To address this, we develop a lake drainage model incorporating both (1) a subglacial radial flux element driven by elastic hydraulic jacking and (2) downstream drainage through a linked channelized and distributed system. Here we present the model and examine whether substantial, efficient subglacial channels can form during or following lake drainage events and their effect on the water pressure in the surrounding distributed system. We force the model with field data from a lake drainage site, 70 km from the terminus of Russell Glacier in West Greenland. The model outputs suggest that efficient subglacial channels do not readily form in the vicinity of the lake during rapid drainage and instead water is evacuated primarily by a transient turbulent sheet and the distributed system. Following lake drainage, channels grow but are not large enough to reduce the water pressure in the surrounding distributed system, unless preexisting channels are present throughout the domain. Our results have implications for the analysis of subglacial hydrological systems in regions where rapid lake drainage provides the primary mechanism for surface-to-bed connections. Key Points Model for subglacial hydrological analysis of rapid lake drainage events Limited subglacial channel growth during and following rapid lake drainage Persistence of distributed drainage in inland areas where channel growth is limited PMID:26640746
Dow, C F; Kulessa, B; Rutt, I C; Tsai, V C; Pimentel, S; Doyle, S H; van As, D; Lindbäck, K; Pettersson, R; Jones, G A; Hubbard, A
The rapid drainage of supraglacial lakes injects substantial volumes of water to the bed of the Greenland ice sheet over short timescales. The effect of these water pulses on the development of basal hydrological systems is largely unknown. To address this, we develop a lake drainage model incorporating both (1) a subglacial radial flux element driven by elastic hydraulic jacking and (2) downstream drainage through a linked channelized and distributed system. Here we present the model and examine whether substantial, efficient subglacial channels can form during or following lake drainage events and their effect on the water pressure in the surrounding distributed system. We force the model with field data from a lake drainage site, 70 km from the terminus of Russell Glacier in West Greenland. The model outputs suggest that efficient subglacial channels do not readily form in the vicinity of the lake during rapid drainage and instead water is evacuated primarily by a transient turbulent sheet and the distributed system. Following lake drainage, channels grow but are not large enough to reduce the water pressure in the surrounding distributed system, unless preexisting channels are present throughout the domain. Our results have implications for the analysis of subglacial hydrological systems in regions where rapid lake drainage provides the primary mechanism for surface-to-bed connections. Model for subglacial hydrological analysis of rapid lake drainage eventsLimited subglacial channel growth during and following rapid lake drainagePersistence of distributed drainage in inland areas where channel growth is limited.
van de Giesen, Nick; Bierkens, Marc; Drost, Niels; Hut, Rolf; Sutanudjaja, Edwin
In 2013, the eWaterCycle project was started, which has the ambitious goal to run a high resolution global hydrological model. Starting point was the PCR-GLOBWB built by Utrecht University. The software behind this model will partially be re-engineered in order to enable to run it in a High Performance Computing (HPC) environment. The aim is to have a spatial resolution of 1km x 1km. The idea is also to run the model in real-time and forecasting mode, using data assimilation. An on-demand hydraulic model will be available for detailed flow and flood forecasting in support of navigation and disaster management. The project faces a set of scientific challenges. First, to enable the model to run in a HPC environment, model runs were analyzed to examine on which parts of the program most CPU time was spent. These parts were re-coded in Open MPI to allow for parallel processing. Different parallelization strategies are thinkable. In our case, it was decided to use watershed logic as a first step to distribute the analysis. There is rather limited recent experience with HPC in hydrology and there is much to be learned and adjusted, both on the hydrological modeling side and the computer science side. For example, an interesting early observation was that hydrological models are, due to their localized parameterization, much more memory intensive than models of sister-disciplines such as meteorology and oceanography. Because it would be deadly to have to swap information between CPU and hard drive, memory management becomes crucial. A standard Ensemble Kalman Filter (enKF) would, for example, have excessive memory demands. To circumvent these problems, an alternative to the enKF was developed that produces equivalent results. This presentation shows the most recent results from the model, including a 5km x 5km simulation and a proof of concept for the new data assimilation approach. Finally, some early ideas about financial sustainability of an operational global
Liu, Hongli; Tolson, Bryan A.; Craig, James R.; Shafii, Mahyar
Watershed spatial discretization is an important step in developing a distributed hydrologic model. A key difficulty in the spatial discretization process is maintaining a balance between the aggregation-induced information loss and the increase in computational burden caused by the inclusion of additional computational units. Objective identification of an appropriate discretization scheme still remains a challenge, in part because of the lack of quantitative measures for assessing discretization quality, particularly prior to simulation. This study proposes a priori discretization error metrics to quantify the information loss of any candidate discretization scheme without having to run and calibrate a hydrologic model. These error metrics are applicable to multi-variable and multi-site discretization evaluation and provide directly interpretable information to the hydrologic modeler about discretization quality. The first metric, a subbasin error metric, quantifies the routing information loss from discretization, and the second, a hydrological response unit (HRU) error metric, improves upon existing a priori metrics by quantifying the information loss due to changes in land cover or soil type property aggregation. The metrics are straightforward to understand and easy to recode. Informed by the error metrics, a two-step discretization decision-making approach is proposed with the advantage of reducing extreme errors and meeting the user-specified discretization error targets. The metrics and decision-making approach are applied to the discretization of the Grand River watershed in Ontario, Canada. Results show that information loss increases as discretization gets coarser. Moreover, results help to explain the modeling difficulties associated with smaller upstream subbasins since the worst discretization errors and highest error variability appear in smaller upstream areas instead of larger downstream drainage areas. Hydrologic modeling experiments under
Maher, K.; Chamberlain, C. P.
Catchment-scale chemical fluxes have been linked to a number of different parameters that describe the conditions at the Earth’s surface, including runoff, temperature, rock type, vegetation, and the rate of tectonic uplift. However, many of the relationships relating chemical denudation to surface processes and conditions, while based on established theoretical principles, are largely empirical and derived solely from modern observations. Thus, an enhanced mechanistic basis for linking global solute fluxes to both surface processes and climate may improve our confidence in extrapolating modern solute fluxes to past and future conditions. One approach is to link observations from detailed soil-based studies with catchment-scale properties. For example, a number of recent studies of chemical weathering at the soil-profile scale have reinforced the importance of hydrologic processes in controlling chemical weathering rates. An analysis of data from granitic soils shows that weathering rates decrease with increasing fluid residence times and decreasing flow rates—over moderate fluid residence times, from 5 days to 10 years, transport-controlled weathering explains the orders of magnitude variation in weathering rates to a better extent than soil age. However, the importance of transport-controlled weathering is difficult to discern at the catchment scale because of the range of flow rates and fluid residence times captured by a single discharge or solute flux measurement. To assess the importance of transport-controlled weathering on catchment scale chemical fluxes, we present a model that links the chemical flux to the extent of reaction between the soil waters and the solids, or the fluid residence time. Different approaches for describing the distribution of fluid residence times within a catchment are then compared with the observed Si fluxes for a limited number of catchments. This model predicts high solute fluxes in regions with high run-off, relief, and
Kumari, Babita; Paul, Pranesh Kumar; Singh, Rajendra; Mishra, Ashok; Gupta, Praveen Kumar; Singh, Raghvendra P.
A new semi-distributed conceptual hydrological model, namely Satellite based Hydrological Model (SHM), has been developed under 'PRACRITI-2' program of Space Application Centre (SAC), Ahmedabad for sustainable water resources management of India by using data from Indian Remote Sensing satellites. Entire India is divided into 5km x 5km grid cells and properties at the center of the cells are assumed to represent the property of the cells. SHM contains five modules namely surface water, forest, snow, groundwater and routing. Two empirical equations (SCS-CN and Hargreaves) and water balance method have been used in the surface water module; the forest module is based on the calculations of water balancing & dynamics of subsurface. 2-D Boussinesq equation is used for groundwater modelling which is solved using implicit finite-difference. The routing module follows a distributed routing approach which requires flow path and network with the key point of travel time estimation. The aim of this study is to evaluate the performance of SHM using regionalization technique which also checks the usefulness of a model in data scarce condition or for ungauged basins. However, homogeneity analysis is pre-requisite to regionalization. Similarity index (Φ) and hierarchical agglomerative cluster analysis are adopted to test the homogeneity in terms of physical attributes of three basins namely Brahmani (39,033 km km^2)), Baitarani (10,982 km km^2)) and Kangsabati (9,660 km km^2)) with respect to Subarnarekha (29,196 km km^2)) basin. The results of both homogeneity analysis show that Brahmani basin is the most homogeneous with respect to Subarnarekha river basin in terms of physical characteristics (land use land cover classes, soiltype and elevation). The calibration and validation of model parameters of Brahmani basin is in progress which are to be transferred into the SHM set up of Subarnarekha basin and results are to be compared with the results of calibrated and validated
Kreye, Phillip; Meon, Günter
State-of-the-art hydrological applications require a process-based, spatially distributed hydrological model. Runoff characteristics are demanded to be well reproduced by the model. Despite that, the model should be able to describe the processes at a subcatchment scale in a physically credible way. The objective of this study is to present a robust procedure to generate various sets of parameterisations of soil hydraulic functions for the description of soil heterogeneity on a subgrid scale. Relations between Rosetta-generated values of saturated hydraulic conductivity (Ks) and van Genuchten's parameters of soil hydraulic functions were statistically analysed. An universal function that is valid for the complete bandwidth of Ks values could not be found. After concentrating on natural texture classes, strong correlations were identified for all parameters. The obtained regression results were used to parameterise sets of hydraulic functions for each soil class. The methodology presented in this study is applicable on a wide range of spatial scales and does not need input data from field studies. The developments were implemented into a hydrological modelling system.
Swain, N. R.; Latu, K.; Christiensen, S.; Jones, N.; Nelson, J.
Advances in computation resources and greater availability of water resources data represent an untapped resource for addressing hydrologic uncertainties in water resources decision-making. The current practice of water authorities relies on empirical, lumped hydrologic models to estimate watershed response. These models are not capable of taking advantage of many of the spatial datasets that are now available. Physically-based, distributed hydrologic models are capable of using these data resources and providing better predictions through stochastic analysis. However, there exists a digital divide that discourages many science-minded decision makers from using distributed models. This divide can be spanned using a combination of existing web technologies. The purpose of this presentation is to present a cloud-based environment that will offer hydrologic modeling tools or 'apps' for decision support and the web technologies that have been selected to aid in its implementation. Compared to the more commonly used lumped-parameter models, distributed models, while being more intuitive, are still data intensive, computationally expensive, and difficult to modify for scenario exploration. However, web technologies such as web GIS, web services, and cloud computing have made the data more accessible, provided an inexpensive means of high-performance computing, and created an environment for developing user-friendly apps for distributed modeling. Since many water authorities are primarily interested in the scenario exploration exercises with hydrologic models, we are creating a toolkit that facilitates the development of a series of apps for manipulating existing distributed models. There are a number of hurdles that cloud-based hydrologic modeling developers face. One of these is how to work with the geospatial data inherent with this class of models in a web environment. Supporting geospatial data in a website is beyond the capabilities of standard web frameworks and it
Escobar, I. S.; Lopez, S. R.; Kinoshita, A. M.
Wildfires alter the natural processes within a watershed, such as surface runoff, evapotranspiration rates, and subsurface water storage. Post-fire hydrologic models are typically one-dimensional, empirically-based models or two-dimensional, conceptually-based models with lumped parameter distributions. These models are useful for modeling and predictions at the watershed outlet; however, do not provide detailed, distributed hydrologic processes at the point scale within the watershed. This research uses ParFlow, a three-dimensional, distributed hydrologic model to simulate post-fire hydrologic processes by representing the spatial and temporal variability of soil burn severity (via hydrophobicity) and vegetation recovery. Using this approach, we are able to evaluate the change in post-fire water components (surface flow, lateral flow, baseflow, and evapotranspiration). This work builds upon previous field and remote sensing analysis conducted for the 2003 Old Fire Burn in Devil Canyon, located in southern California (USA). This model is initially developed for a hillslope defined by a 500 m by 1000 m lateral extent. The subsurface reaches 12.4 m and is assigned a variable cell thickness to explicitly consider soil burn severity throughout the stages of recovery and vegetation regrowth. We consider four slope and eight hydrophobic layer configurations. Evapotranspiration is used as a proxy for vegetation regrowth and is represented by the satellite-based Simplified Surface Energy Balance (SSEBOP) product. The pre- and post-fire surface runoff, subsurface storage, and surface storage interactions are evaluated at the point scale. Results will be used as a basis for developing and fine-tuning a watershed-scale model. Long-term simulations will advance our understanding of post-fire hydrological partitioning between water balance components and the spatial variability of watershed processes, providing improved guidance for post-fire watershed management. In reference
Krogh, S.; Pomeroy, J. W.; McPhee, J. P.
Remote regions in South America are often characterized by insufficient observations of meteorology for robust hydrological model operation. Yet water resources must be quantified, understood and predicted in order to develop effective water management policies. Here, we developed a physically based hydrological model for a major river in Patagonia using the modular Cold Regions Hydrological Modelling Platform (CRHM) in order to better understand hydrological processes leading to streamflow generation in this remote region. The Baker River -with the largest mean annual streamflow in Chile-, drains snowy mountains, glaciers, wet forests, peat and semi-arid pampas into a large lake. Meteorology over the basin is poorly monitored in that there are no high elevation weather stations and stations at low elevations are sparsely distributed, only measure temperature and rainfall and are poorly maintained. Streamflow in the basin is gauged at several points where there are high quality hydrometric stations. In order to quantify the impact of meteorological data scarcity on prediction, two additional data sources were used: the ERA-Interim (ECMWF Re-analyses) and CFSR (Climate Forecast System Reanalysis) atmospheric reanalyses. Precipitation temporal distribution and magnitude from the models and observations were compared and the reanalysis data was found to have about three times the number of days with precipitation than the observations did. Better synchronization between measured peak streamflows and modeled precipitation was found compared to observed precipitation. These differences are attributed to: (i) lack of any snowfall observations (so precipitation records does not consider snowfall events) and (ii) available rainfall observations are all located at low altitude (<500 m a.s.l), and miss the occurrence of high altitude precipitation events. CRHM parameterization was undertaken by using local physiographic and vegetation characteristics where available and
Wang, X.; Liu, T.; Li, R.; Yang, X.; Duan, L.; Luo, Y.
Wetlands are one of the most important watershed microtopographic features that affect, in combination rather than individually, hydrologic processes (e.g., routing) and the fate and transport of constituents (e.g., sediment and nutrients). Efforts to conserve existing wetlands and/or to restore lost wetlands require that watershed-level effects of wetlands on water quantity and water quality be quantified. Because monitoring approaches are usually cost or logistics prohibitive at watershed scale, distributed watershed models, such as the Soil and Water Assessment Tool (SWAT), can be a best resort if wetlands can be appropriately represented in the models. However, the exact method that should be used to incorporate wetlands into hydrologic models is the subject of much disagreement in the literature. In addition, there is a serious lack of information about how to model wetland conservation-restoration effects using such kind of integrated modeling approach. The objectives of this study were to: 1) develop a "hydrologic equivalent wetland" (HEW) concept; and 2) demonstrate how to use the HEW concept in SWAT to assess effects of wetland restoration within the Broughton's Creek watershed located in southwestern Manitoba of Canada, and of wetland conservation within the upper portion of the Otter Tail River watershed located in northwestern Minnesota of the United States. The HEWs were defined in terms of six calibrated parameters: the fraction of the subbasin area that drains into wetlands (WET_FR), the volume of water stored in the wetlands when filled to their normal water level (WET_NVOL), the volume of water stored in the wetlands when filled to their maximum water level (WET_MXVOL), the longest tributary channel length in the subbasin (CH_L1), Manning's n value for the tributary channels (CH_N1), and Manning's n value for the main channel (CH_N2). The results indicated that the HEW concept allows the nonlinear functional relations between watershed processes
Caporali, E.; Fatichi, S.; Ivanov, V. Y.
There is a growing interest to extend climate change predictions to smaller, catchment-size scales and identify their implications on hydrological and ecological processes. Small scale processes are, in fact, expected to mediate climate changes, producing local effects and feedbacks that can interact with the principal consequences of the change. This is particularly applicable, when a complex interaction, such as the inter-relationship between the hydrological cycle and vegetation dynamics, is considered. This study presents a blueprint methodology for studying climate change impacts, as inferred from climate models, on eco-hydrological dynamics at the catchment scale. Climate conditions, present or future, are imposed through input hydrometeorological variables for hydrological and eco-hydrological models. These variables are simulated with an hourly weather generator as an outcome of a stochastic downscaling technique. The generator is parameterized to reproduce the climate of southwestern Arizona for present (1961-2000) and future (2081-2100) conditions. The methodology provides the capability to generate ensemble realizations for the future that take into account the heterogeneous nature of climate predictions from different models. The generated time series of meteorological variables for the two scenarios corresponding to the current and mean expected future serve as input to a coupled hydrological and vegetation dynamics model, “Tethys-Chloris”. The hydrological model reproduces essential components of the land-surface hydrological cycle, solving the mass and energy budget equations. The vegetation model parsimoniously parameterizes essential plant life-cycle processes, including photosynthesis, phenology, carbon allocation, and tissue turnover. The results for the two mean scenarios are compared and discussed in terms of changes in the hydrological balance components, energy fluxes, and indices of vegetation productivity The need to account for
Segurado, Pedro; Branco, Paulo; Jauch, Eduardo; Neves, Ramiro; Ferreira, M Teresa
Climate change will predictably change hydrological patterns and processes at the catchment scale, with impacts on habitat conditions for fish. The main goal of this study is to assess how shifts in fish habitat favourability under climate change scenarios are affected by hydrological stressors. The interplay between climate and hydrological stressors has important implications in river management under climate change because management actions to control hydrological parameters are more feasible than controlling climate. This study was carried out in the Tamega catchment of the Douro basin. A set of hydrological stressor variables were generated through a process-based modelling based on current climate data (2008-2014) and also considering a high-end future climate change scenario. The resulting parameters, along with climatic and site-descriptor variables were used as explanatory variables in empirical habitat models for nine fish species using boosted regression trees. Models were calibrated for the whole Douro basin using 254 fish sampling sites and predictions under future climate change scenarios were made for the Tamega catchment. Results show that models using climatic variables but not hydrological stressors produce more stringent predictions of future favourability, predicting more distribution contractions or stronger range shifts. The use of hydrological stressors strongly influences projections of habitat favourability shifts; the integration of these stressors in the models thinned shifts in range due to climate change. Hydrological stressors were retained in the models for most species and had a high importance, demonstrating that it is important to integrate hydrology in studies of impacts of climate change on freshwater fishes. This is a relevant result because it means that management actions to control hydrological parameters in rivers will have an impact on the effects of climate change and may potentially be helpful to mitigate its negative
Zhaohua Dai; Devendra M. Amatya; Ge Sun; Changsheng Li; Carl C. Trettin; Harbin Li
Since hydrology is one of main factors controlling wetland functions, hydrologic models are useful for evaluating the effects of land use change on we land ecosystems. We evaluated two process-based hydrologic models with...
Barendrecht, M.; Viglione, A.; Kreibich, H.; Vorogushyn, S.; Merz, B.; Bloeschl, G.
Long-term feedbacks between humans and floods may lead to complex phenomena such as coping strategies, levee effects, call effects, adaptation effects, and poverty traps. Dynamic coupled human-flood models are a promising tool to represent such phenomena and the feedbacks leading to them. These socio-hydrological models may play an important role in integrated flood risk management when they are applied to real world case studies. They can help develop hypotheses about the phenomena that have been observed in the case study of interest, by describing the interactions between the social and hydrological variables as well as other relevant variables, such as economic, environmental, political or technical, that play a role in the system. We discuss the case of Dresden where the 2002 flood, which was preceded by a period without floods but was less severe, resulted in a higher damage than the 2013 flood, which was preceded by the 2002 flood and a couple of less severe floods. The lower damage in 2013 may be explained by the fact that society has become aware of the flood risk and has adapted to it. Developing and applying a socio-hydrological flood model to the case of Dresden can help discover whether it is possible that the lower damage is caused by an adaptation effect, or if there are other feedbacks that can explain the observed phenomenon.
Anghileri, Daniela; Giudici, Federico; Castelletti, Andrea; Burlando, Paolo
Last decades have seen significant advances in our capacity of characterizing and reproducing hydrological processes within physically based models. Yet, when the human component is considered (e.g. reservoirs, water distribution systems), the associated decisions are generally modeled with very simplistic rules, which might underperform in reproducing the actual operators' behaviour on a daily or sub-daily basis. For example, reservoir operations are usually described by a target-level rule curve, which represents the level that the reservoir should track during normal operating conditions. The associated release decision is determined by the current state of the reservoir relative to the rule curve. This modeling approach can reasonably reproduce the seasonal water volume shift due to reservoir operation. Still, it cannot capture more complex decision making processes in response, e.g., to the fluctuations of energy prices and demands, the temporal unavailability of power plants or varying amount of snow accumulated in the basin. In this work, we link a physically explicit hydrological model with detailed hydropower behavioural models describing the decision making process by the dam operator. In particular, we consider two categories of behavioural models: explicit or rule-based behavioural models, where reservoir operating rules are empirically inferred from observational data, and implicit or optimization based behavioural models, where, following a normative economic approach, the decision maker is represented as a rational agent maximising a utility function. We compare these two alternate modelling approaches on the real-world water system of Lake Como catchment in the Italian Alps. The water system is characterized by the presence of 18 artificial hydropower reservoirs generating almost 13% of the Italian hydropower production. Results show to which extent the hydrological regime in the catchment is affected by different behavioural models and reservoir
Liu, Hongli; Tolson, Bryan; Craig, James; Shafii, Mahyar; Basu, Nandita
In distributed hydrologic modelling, a watershed is treated as a set of small homogeneous units that address the spatial heterogeneity of the watershed being simulated. The ability of models to reproduce observed spatial patterns firstly depends on the spatial discretization, which is the process of defining homogeneous units in the form of grid cells, subwatersheds, or hydrologic response units etc. It is common for hydrologic modelling studies to simply adopt a nominal or default discretization strategy without formally assessing alternative discretization levels. This approach lacks formal justifications and is thus problematic. More formalized discretization strategies are either a priori or a posteriori with respect to building and running a hydrologic simulation model. A posteriori approaches tend to be ad-hoc and compare model calibration and/or validation performance under various watershed discretizations. The construction and calibration of multiple versions of a distributed model can become a seriously limiting computational burden. Current a priori approaches are more formalized and compare overall heterogeneity statistics of dominant variables between candidate discretization schemes and input data or reference zones. While a priori approaches are efficient and do not require running a hydrologic model, they do not fully investigate the internal spatial pattern changes of variables of interest. Furthermore, the existing a priori approaches focus on landscape and soil data and do not assess impacts of discretization on stream channel definition even though its significance has been noted by numerous studies. The primary goals of this study are to (1) introduce new a priori discretization quality metrics considering the spatial pattern changes of model input data; (2) introduce a two-step discretization decision-making approach to compress extreme errors and meet user-specified discretization expectations through non-uniform discretization threshold
Vidmar, Andrej; Brilly, Mitja
Hydrological phenomena take place in the hydrological system, which is governed by nature, and are essentially stochastic. These phenomena are unique, non-recurring, and changeable across space and time. Since any river basin with its own natural characteristics and any hydrological event therein, are unique, this is a complex process that is not researched enough. Calibration is a procedure of determining the parameters of a model that are not known well enough. Input and output variables and mathematical model expressions are known, while only some parameters are unknown, which are determined by calibrating the model. The software used for hydrological modelling nowadays is equipped with sophisticated algorithms for calibration purposes without possibility to manage process by modeler. The results are not the best. We develop procedure for expert driven process of calibration. We use HBV-light-CLI hydrological model which has command line interface and coupling it with PEST. PEST is parameter estimation tool which is used widely in ground water modeling and can be used also on surface waters. Process of calibration managed by expert directly, and proportionally to the expert knowledge, affects the outcome of the inversion procedure and achieves better results than if the procedure had been left to the selected optimization algorithm. First step is to properly define spatial characteristic and structural design of semi-distributed model including all morphological and hydrological phenomena, like karstic area, alluvial area and forest area. This step includes and requires geological, meteorological, hydraulic and hydrological knowledge of modeler. Second step is to set initial parameter values at their preferred values based on expert knowledge. In this step we also define all parameter and observation groups. Peak data are essential in process of calibration if we are mainly interested in flood events. Each Sub Catchment in the model has own observations group
Urbanizing environments alter the hydrological cycle by redirecting stream networks for stormwater and wastewater transmission and increasing impermeable surfaces. These changes thereby accelerate the runoff of water and its constituents following precipitation events, alter evap...
A spatially distributed representation of basin hydrology and transport processes in eco-hydrological models facilitates the identification of critical source areas and the placement of management and conservation measures. Floodplains are critical landscape features that differ from neighboring up...
Modelling approaches to transfer hydrologically-relevant information from locations with streamflow measurements to locations without such measurements continues to be an active field of research for hydrologists. The Pacific Northwest Hydrologic Landscapes (PNW HL) provide a sol...
Channell, K.; Gronewold, A.; Rood, R. B.; Xiao, C.; Lofgren, B. M.; Hunter, T.
Climate change is already having a profound impact on the global hydrologic cycle. In the Laurentian Great Lakes, changes in long-term evaporation and precipitation can lead to rapid water level fluctuations in the lakes, as evidenced by unprecedented change in water levels seen in the last two decades. These fluctuations often have an adverse impact on the region's human, environmental, and economic well-being, making accurate long-term water level projections invaluable to regional water resources management planning. Here we use hydrological components from a downscaled climate model (GFDL-CM3/WRF), to obtain future water supplies for the Great Lakes. We then apply a suite of bias correction procedures before propagating these water supplies through a routing model to produce lake water levels. Results using conventional bias correction methods suggest that water levels will decline by several feet in the coming century. However, methods that reflect the seasonal water cycle and explicitly debias individual hydrological components (overlake precipitation, overlake evaporation, runoff) imply that future water levels may be closer to their historical average. This discrepancy between debiased results indicates that water level forecasts are highly influenced by the bias correction method, a source of sensitivity that is commonly overlooked. Debiasing, however, does not remedy misrepresentation of the underlying physical processes in the climate model that produce these biases and contribute uncertainty to the hydrological projections. This uncertainty coupled with the differences in water level forecasts from varying bias correction methods are important for water management and long term planning in the Great Lakes region.
Fleischmann, Ayan; Siqueira, Vinícius; Paris, Adrien; Collischonn, Walter; Paiva, Rodrigo; Gossett, Marielle; Pontes, Paulo; Calmant, Stephane; Biancamaria, Sylvain; Crétaux, Jean-François; Tanimoune, Bachir
The Upper Niger Basin is located in Western Africa, flowing from Guinea Highlands towards the Sahel region. In this area lies the seasonally inundated Niger Inland Delta, which supports important environmental services such as habitats for wildlife, climate and flood regulation, as well as large fishery and agricultural areas. In this study, we present the application of MGB-IPH large scale hydrologic and hydrodynamic model for the Upper Niger Basin, totaling c.a. 650,000 km2 and set up until the city of Niamey in Niger. The model couples hydrological vertical balance and runoff generation with hydrodynamic flood wave propagation, by allowing infiltration from floodplains into soil column as well as representing backwater effects and floodplain storage throughout flat areas such as the Inland Delta. The model is forced with TRMM 3B42 daily precipitation and Climate Research Unit (CRU) climatology for the period 2000-2010, and was calibrated against in-situ discharge gauges and validated with in-situ water level, remotely sensed estimations of flooded areas (classification of MODIS imagery) and satellite altimetry (JASON-2 mission). Model results show good predictions for calibrated daily discharge and validated water level and altimetry at stations both upstream and downstream of the delta (Nash-Sutcliffe Efficiency>0.7 for all stations), as well as for flooded areas within the delta region (ENS=0.5; r2=0.8), allowing a good representation of flooding dynamics basinwide and simulation of flooding behavior of both perennial (e.g., Niger main stem) and ephemeral rivers (e.g., Niger Red Flood tributaries in Sahel). Coupling between hydrology and hydrodynamic processes indicates an important feedback between floodplain and soil water storage that allows high evapotranspiration rates even after the flood passage around the inner delta area. Also, representation of water retention in floodplain channels and distributaries in the inner delta (e.g., Diaka river
Kowalsky, M. B.; Majer, E.; Peterson, J. E.; Finsterle, S.; Mazzella, A.
Past studies have shown reasonable sensitivity of geophysical data for detecting or monitoring the movement of non-aqueous phase liquids (NAPLs) in the subsurface. However, heterogeneity in subsurface properties and in NAPL distribution commonly results in non-unique data interpretation. Combining multiple geophysical data types and incorporating constraints from hydrological models will potentially decrease the non-uniqueness in data interpretation and aid in site characterization. Large-scale laboratory experiments have been conducted over several years to evaluate the use of various geophysical methods, including ground-penetrating radar (GPR), seismic, and electrical methods, for monitoring controlled spills of tetrachloroethylene (PCE), a hazardous industrial solvent that is pervasive in the subsurface. In the current study, we consider an experiment in which PCE was introduced into a large tank containing a heterogeneous distribution of sand and clay mixtures, and allowed to migrate while time-lapse geophysical data were collected. We consider two approaches for interpreting the surface GPR and crosswell seismic data. The first approach involves (a) waveform inversion of the surface GPR data using a non-gradient based optimization algorithm to estimate the dielectric constant distributions and (b) conversion of crosswell seismic travel times to acoustic velocity distributions; the dielectric constant and acoustic velocity distributions are then related to NAPL saturation using appropriate petrophysical models. The second approach takes advantage of a recently developed framework for coupled hydrological-geophysical modeling, providing a hydrological constraint on interpretation of the geophysical data and additionally resulting in quantitative estimates of the most relevant hydrological parameters that determine NAPL behavior in the system. Specifically, we simulate NAPL migration using the multiphase multicomponent flow simulator TOUGH2 with a 2-D radial
Lajer Hojberg, Anker; Jørgen Henriksen, Hans; Olsen, Martin; der Keur Peter, van; Seaby, Lauren Paige; Troldborg, Lars; Sonnenborg, Torben; Refsgaard, Jens Christian
Future climate may have a profound effect on the freshwater cycle, which must be taken into consideration by water management for future planning. Developments in the future climate are nevertheless uncertain, thus adding to the challenge of managing an uncertain system. To support the water managers at various levels in Denmark, the national water resources model (DK-model) (Højberg et al., 2012; Stisen et al., 2012) was used to propagate future climate to hydrological response under considerations of the main sources of uncertainty. The DK-model is a physically based and fully distributed model constructed on the basis of the MIKE SHE/MIKE11 model system describing groundwater and surface water systems and the interaction between the domains. The model has been constructed for the entire 43.000 km2 land area of Denmark only excluding minor islands. Future climate from General Circulation Models (GCM) was downscaled by Regional Climate Models (RCM) by a distribution-based scaling method (Seaby et al., 2012). The same dataset was used to train all combinations of GCM-RCMs and they were found to represent the mean and variance at the seasonal basis equally well. Changes in hydrological response were computed by comparing the short term development from the period 1990 - 2010 to 2021 - 2050, which is the time span relevant for water management. To account for uncertainty in future climate predictions, hydrological response from the DK-model using nine combinations of GCMs and RCMs was analysed for two catchments representing the various hydrogeological conditions in Denmark. Three GCM-RCM combinations displaying high, mean and low future impacts were selected as representative climate models for which climate impact studies were carried out for the entire country. Parameter uncertainty was addressed by sensitivity analysis and was generally found to be of less importance compared to the uncertainty spanned by the GCM-RCM combinations. Analysis of the simulations
Lau, W. K.-M.; Sud, Y. C.; Kim, J.-H.
In this report, we address the intercomparison of precipitation (P), evaporation (E), and surface hydrologic forcing (P-E) for 23 Atmospheric Model Intercomparison Project (AMIP) general circulation models (GCM's) including relevant observations, over a variety of spatial and temporal scales. The intercomparison includes global and hemispheric means, latitudinal profiles, selected area means for the tropics and extratropics, ocean and land, respectively. In addition, we have computed anomaly pattern correlations among models and observations for different seasons, harmonic analysis for annual and semiannual cycles, and rain-rate frequency distribution. We also compare the joint influence of temperature and precipitation on local climate using the Koeppen climate classification scheme.
Doppler, T.; Honti, M.; Zihlmann, U.; Weisskopf, P.; Stamm, C.
Spatially distributed hydrological models are popular tools in hydrology and they are claimed to be useful to support management decisions. Despite the high spatial resolution of the computed variables, calibration and validation is often carried out only on discharge time-series at specific locations due to the lack of spatially distributed reference data. Because of this restriction, the predictive power of these models, with regard to predicted spatial patterns, can usually not be judged. An example of spatial predictions in hydrology is the prediction of saturated areas in agricultural catchments. These areas can be important source areas for the transport of agrochemicals to the stream. We set up a spatially distributed model to predict saturated areas in a 1.2 km2 catchment in Switzerland with moderate topography. Around 40% of the catchment area are artificially drained. We measured weather data, discharge and groundwater levels in 11 piezometers for 1.5 yr. For broadening the spatially distributed data sets that can be used for model calibration and validation, we translated soil morphological data available from soil maps into an estimate of the duration of soil saturation in the soil horizons. We used redox-morphology signs for these estimates. This resulted in a data set with high spatial coverage on which the model predictions were validated. In general, these saturation estimates corresponded well to the measured groundwater levels. We worked with a model that would be applicable for management decisions because of its fast calculation speed and rather low data requirements. We simultaneously calibrated the model to the groundwater levels in the piezometers and discharge. The model was able to reproduce the general hydrological behavior of the catchment in terms of discharge and absolute groundwater levels. However, the accuracy of the groundwater level predictions was not high enough to be used for the prediction of saturated areas. The groundwater
Wu, Yiping; Li, Tiejian; Sun, Liqun; Chen, Ji
With the increasing knowledge about the natural processes, hydrological models such as the Soil and Water Assessment Tool (SWAT) are becoming larger and more complex with increasing computation time. Additionally, other procedures such as model calibration, which may require thousands of model iterations, can increase running time and thus further reduce rapid modeling and analysis. Using the widely-applied SWAT as an example, this study demonstrates how to parallelize a serial hydrological model in a Windows® environment using a parallel programing technology—Message Passing Interface (MPI). With a case study, we derived the optimal values for the two parameters (the number of processes and the corresponding percentage of work to be distributed to the master process) of the parallel SWAT (P-SWAT) on an ordinary personal computer and a work station. Our study indicates that model execution time can be reduced by 42%–70% (or a speedup of 1.74–3.36) using multiple processes (two to five) with a proper task-distribution scheme (between the master and slave processes). Although the computation time cost becomes lower with an increasing number of processes (from two to five), this enhancement becomes less due to the accompanied increase in demand for message passing procedures between the master and all slave processes. Our case study demonstrates that the P-SWAT with a five-process run may reach the maximum speedup, and the performance can be quite stable (fairly independent of a project size). Overall, the P-SWAT can help reduce the computation time substantially for an individual model run, manual and automatic calibration procedures, and optimization of best management practices. In particular, the parallelization method we used and the scheme for deriving the optimal parameters in this study can be valuable and easily applied to other hydrological or environmental models.
Maxwell, R. M.; Condon, L. E.
Recent studies demonstrate feedbacks between groundwater dynamics, overland flow, land surface and vegetation processes, and atmospheric boundary layer development that significantly affect local and regional climate across a range of climatic conditions. Furthermore, the type and distribution of vegetation cover alters land-atmosphere water and energy fluxes, as well as runoff generation and overland flow processes. These interactions can result in significant feedbacks on local and regional climate. In mountainous regions, recent research has shown that spatial and temporal variability in annual evapotranspiration, and thus water budgets, is strongly dependent on lateral groundwater flow; however, the full effects of these feedbacks across varied terrain (e.g. from plains to mountains) are not well understood. Here, we present a high-resolution, integrated hydrology model that covers much of continental North America and encompasses the Mississippi and Colorado watersheds. The model is run in a fully-transient manner at hourly temporal resolution incorporating fully-coupled land energy states and fluxes with integrated surface and subsurface hydrology. Connections are seen between hydrologic variables (such as water table depth) and land energy fluxes (such as latent heat) and spatial and temporal scaling is shown to span many orders of magnitude. Using these transient simulations as a proof of concept, we present a vision for future integrated simulation capabilities.
Burtin, A.; Hovius, N.; Milodowski, D.; Chen, Y.-G.; Wu, Y.-M.; Lin, C.-W.; Chen, H.
The monitoring of geomorphic processes during extreme climatic events is of a primary interest to estimate their impact on the landscape dynamics. However, available techniques to survey the surface activity do not provide a relevant time and/or space resolution. Furthermore, these methods hardly investigate the dynamics of the events since their detection are made a posteriori. To increase our knowledge of the landscape evolution and the influence of extreme climatic events on a catchment dynamics, we need to develop new tools and procedures. In many past works, it has been shown that seismic signals are relevant to detect and locate surface processes (landslides, debris flows). During the 2010 typhoon season, we deployed a network of 12 seismometers dedicated to monitor the surface processes of the Chenyoulan catchment in Taiwan. We test the ability of a two dimensional array and small inter-stations distances (~ 11 km) to map in continuous and at a catchment-scale the geomorphic activity. The spectral analysis of continuous records shows a high-frequency (> 1 Hz) seismic energy that is coherent with the occurrence of hillslope and river processes. Using a basic detection algorithm and a location approach running on the analysis of seismic amplitudes, we manage to locate the catchment activity. We mainly observe short-time events (> 300 occurrences) associated with debris falls and bank collapses during daily convective storms, where 69% of occurrences are coherent with the time distribution of precipitations. We also identify a couple of debris flows during a large tropical storm. In contrast, the FORMOSAT imagery does not detect any activity, which somehow reflects the lack of extreme climatic conditions during the experiment. However, high resolution pictures confirm the existence of links between most of geomorphic events and existing structures (landslide scars, gullies...). We thus conclude to an activity that is dominated by reactivation processes. It
Zhuo, Lu; Han, Dawei
Although many conceptual models are very effective in simulating river runoff, their soil moisture schemes are generally not realistic in comparison with the reality (i.e., getting the right answers for the wrong reasons). This study reveals two significant misrepresentations in those models through a case study using the Xinanjiang model which is representative of many well-known conceptual hydrological models. The first is the setting of the upper limit of its soil moisture at the field capacity, due to the 'holding excess runoff' concept (i.e., runoff begins on repletion of its storage to the field capacity). The second is neglect of capillary rise of water movement. A new scheme is therefore proposed to overcome those two issues. The amended model is as effective as its original form in flow modelling, but represents more logically realistic soil water processes. The purpose of the study is to enable the hydrological model to get the right answers for the right reasons. Therefore, the new model structure has a better capability in potentially assimilating soil moisture observations to enhance its real-time flood forecasting accuracy. The new scheme is evaluated in the Pontiac catchment of the USA through a comparison with satellite observed soil moisture. The correlation between the XAJ and the observed soil moisture is enhanced significantly from 0.64 to 0.70. In addition, a new soil moisture term called SMDS (Soil Moisture Deficit to Saturation) is proposed to complement the conventional SMD (Soil Moisture Deficit).
A permeable pavement system can capture stormwater to reduce runoff volume and flow rate, improve onsite groundwater recharge, and enhance pollutant controls within the site. A new unit process model for evaluating the hydrologic performance of a permeable pavement system has been developed in this study. The developed model can continuously simulate infiltration through the permeable pavement surface, exfiltration from the storage to the surrounding in situ soils, and clogging impacts on infiltration/exfiltration capacity at the pavement surface and the bottom of the subsurface storage unit. The exfiltration modeling component simulates vertical and horizontal exfiltration independently based on Darcy’s formula with the Green-Ampt approximation. The developed model can be arranged with physically-based modeling parameters, such as hydraulic conductivity, Manning’s friction flow parameters, saturated and field capacity volumetric water contents, porosity, density, etc. The developed model was calibrated using high-frequency observed data. The modeled water depths are well matched with the observed values (R2 = 0.90). The modeling results show that horizontal exfiltration through the side walls of the subsurface storage unit is a prevailing factor in determining the hydrologic performance of the system, especially where the storage unit is developed in a long, narrow shape; or with a high risk of bottom compaction and clogging. This paper presents unit
De Dreuzy, J. R.; Marçais, J.; Moatar, F.; Minaudo, C.; Courtois, Q.; Thomas, Z.; Longuevergne, L.; Pinay, G.
Integration of hydrological and biogeochemical processes led to emerging patterns at the catchment scale. Monitoring in rivers reflects the aggregation of these effects. While discharge time series have been measured for decades, high frequency water quality monitoring in rivers now provides prominent measurements to characterize the interplay between hydrological and biogeochemical processes, especially to infer the processes that happen in the heterogeneous subsurface. However, we still lack frameworks to relate observed patterns to specific processes, because of the "organized complexity" of hydrological systems. Indeed, it is unclear what controls, for example, patterns in concentration-discharge (C/Q) relationships due to non-linear processes and hysteresis effects. Here we develop a non-intensive process-based model to test how the integration of different landforms (i.e. geological heterogeneities and structures, topographical features) with different biogeochemical reactivity assumptions (e.g. reactive zone locations) can shape the overall water quality time series. With numerical experiments, we investigate typical patterns in high frequency C/Q relationships. In headwater basins, we found that typical hysteretic patterns in C/Q relationships observed in data time series can be attributed to differences in water and solute locations stored across the hillslope. At the catchment scale though, these effects tend to average out by integrating contrasted hillslopes' landforms. Together these results suggest that information contained in headwater water quality monitoring can be used to understand how hydrochemical processes determine downstream conditions.
Van Eerdenbrugh, Katrien; Van Hoey, Stijn; Verhoest, Niko E. C.
Evaluation and discrimination of model structures is crucial to ensure an appropriate use of hydrological models. When evaluating model results by aggregating their quality in (a subset of) individual observations, overall results of this analysis sometimes conceal important detailed information about model structural deficiencies. Analyzing model results within their local (time) context can uncover this detailed information. In this research, a methodology called Bidirectional Reach (BReach) is proposed to evaluate and analyze results of a hydrological model by assessing the maximum left and right reach in each observation point that is used for model evaluation. These maximum reaches express the capability of the model to describe a subset of the evaluation data both in the direction of the previous (left) and of the following data (right). This capability is evaluated on two levels. First, on the level of individual observations, the combination of a parameter set and an observation is classified as non-acceptable if the deviation between the accompanying model result and the measurement exceeds observational uncertainty. Second, the behavior in a sequence of observations is evaluated by means of a tolerance degree. This tolerance degree expresses the condition for satisfactory model behavior in a data series and is defined by the percentage of observations within this series that can have non-acceptable model results. Based on both criteria, the maximum left and right reaches of a model in an observation represent the data points in the direction of the previous respectively the following observations beyond which none of the sampled parameter sets both are satisfactory and result in an acceptable deviation. After assessing these reaches for a variety of tolerance degrees, results can be plotted in a combined BReach plot that show temporal changes in the behavior of model results. The methodology is applied on a Probability Distributed Model (PDM) of the river
McManamay, Ryan A
Despite the ubiquitous existence of dams within riverscapes, much of our knowledge about dams and their environmental effects remains context-specific. Hydrology, more than any other environmental variable, has been studied in great detail with regard to dam regulation. While much progress has been made in generalizing the hydrologic effects of regulation by large dams, many aspects of hydrology show site-specific fidelity to dam operations, small dams (including diversions), and regional hydrologic regimes. A statistical modeling framework is presented to quantify and generalize hydrologic responses to varying degrees of dam regulation. Specifically, the objectives were to 1) compare the effects ofmore » local versus cumulative dam regulation, 2) determine the importance of different regional hydrologic regimes in influencing hydrologic responses to dams, and 3) evaluate how different regulation contexts lead to error in predicting hydrologic responses to dams. Overall, model performance was poor in quantifying the magnitude of hydrologic responses, but performance was sufficient in classifying hydrologic responses as negative or positive. Responses of some hydrologic indices to dam regulation were highly dependent upon hydrologic class membership and the purpose of the dam. The opposing coefficients between local and cumulative-dam predictors suggested that hydrologic responses to cumulative dam regulation are complex, and predicting the hydrology downstream of individual dams, as opposed to multiple dams, may be more easy accomplished using statistical approaches. Results also suggested that particular contexts, including multipurpose dams, high cumulative regulation by multiple dams, diversions, close proximity to dams, and certain hydrologic classes are all sources of increased error when predicting hydrologic responses to dams. Statistical models, such as the ones presented herein, show promise in their ability to model the effects of dam regulation effects
Buytaert, W.; Ochoa Tocachi, B. F.
Andean ecosystems are major water sources for cities and communities located in the Tropical Andes; however, there is a considerable lack of knowledge about their hydrology. Two problems are especially important: (i) the lack of monitoring to assess the impacts of historical land-use and cover change and degradation (LUCCD) at catchment scale, and (ii) the high variability in climatic and hydrological conditions that complicate the evaluation of land management practices. This study analyses how a reliable LUCCD impacts assessment can be performed in an environment of high variability combined with data-scarcity and low-quality records. We use data from participatory hydrological monitoring activities in 20 catchments distributed along the tropical Andes. A set of 46 hydrological indices is calculated and regionalized by relating them to 42 physical catchment properties. Principal Component Analysis (PCA) is performed to maximise available data while minimising redundancy in the sets of variables. Hydrological model parameters are constrained by estimated indices, and different behavioural predictions are assembled to provide a generalised response on which we assess LUCCD impacts. Results from this methodology show that the attributed effects of LUCCD in pair-wise catchment comparisons may be overstated or hidden by different sources of uncertainty, including measurement inaccuracies and model structural errors. We propose extrapolation and evaluation in ungauged catchments as a way to regionalize LUCCD predictions and to provide statistically significant conclusions in the Andean region. These estimations may deliver reliable knowledge to evaluate the hydrological impact of different watershed management practices.
Pimentel, Rafael; Crochemore, Louise; Hasan, Abdulghani; Pineda, Luis; Isberg, Kristina; Arheimer, Berit
The advances in remote sensing in the last decades combined with the creation of different open hydrological databases have generated a very large amount of useful information for global hydrological modelling. Working with this huge number of datasets to set up a global hydrological model can constitute challenges such as multiple data formats and big heterogeneity on spatial and temporal resolutions. Different initiatives have made effort to homogenize some of these data sources, i.e. GRDC (Global Runoff Data Center), HYDROSHEDS (SHuttle Elevation Derivatives at multiple Scales), GLWD (Global Lake and Wetland Database) for runoff, watershed delineation and water bodies respectively. However, not all the related issues are covered or homogenously solved at the global scale and new information is continuously available to complete the current ones. This work presents synchronising efforts to make use of different global data sources needed to set up the semi-distributed hydrological model HYPE (Hydrological Predictions for the Environment) at the global scale. These data sources included: topography for watershed delineation, gauging stations of river flow, and extention of lakes, flood plains and land cover classes. A new database with approximately 100 000 subbasins, with an average area of 1000 km2, was created. Subbasin delineation was done combining Global Width Database for Large River (GWD-LR), SRTM high-resolution elevation data and a number of forced points of interest (gauging station of river flow, lakes, reservoirs, urban areas, nuclear plants and areas with high risk of flooding). Regarding flow data, the locations of GRDC stations were checked or placed along the river network when necessary, and completed with available information from national water services in data-sparse regions. A screening of doublet stations and associated time series was necessary to efficiently combine the two types of data sources. A total number about 21 000 stations were
Vivoni, Enrique R.; Mascaro, Giuseppe; Mniszewski, Susan; Fasel, Patricia; Springer, Everett P.; Ivanov, Valeriy Y.; Bras, Rafael L.
SummaryA major challenge in the use of fully-distributed hydrologic models has been the lack of computational capabilities for high-resolution, long-term simulations in large river basins. In this study, we present the parallel model implementation and real-world hydrologic assessment of the Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator (tRIBS). Our parallelization approach is based on the decomposition of a complex watershed using the channel network as a directed graph. The resulting sub-basin partitioning divides effort among processors and handles hydrologic exchanges across boundaries. Through numerical experiments in a set of nested basins, we quantify parallel performance relative to serial runs for a range of processors, simulation complexities and lengths, and sub-basin partitioning methods, while accounting for inter-run variability on a parallel computing system. In contrast to serial simulations, the parallel model speed-up depends on the variability of hydrologic processes. Load balancing significantly improves parallel speed-up with proportionally faster runs as simulation complexity (domain resolution and channel network extent) increases. The best strategy for large river basins is to combine a balanced partitioning with an extended channel network, with potential savings through a lower TIN resolution. Based on these advances, a wider range of applications for fully-distributed hydrologic models are now possible. This is illustrated through a set of ensemble forecasts that account for precipitation uncertainty derived from a statistical downscaling model.
Kelsey G. Jencso; Brian L. McGlynn; Michael N. Gooseff; Kenneth E. Bencala; Steven M. Wondzell
Hydrologic connectivity between catchment upland and near stream areas is essential for the transmission of water, solutes, and nutrients to streams. However, our current understanding of the role of riparian zones in mediating landscape hydrologic connectivity and the catchment scale export of water and solutes is limited. We tested the relationship between the...
Ashouri, H.; Chinnayakanahalli, K.; Chowdhary, H.; Sen Gupta, A.
Flooding has been the most frequent natural disaster that claims lives and imposes significant economic losses to human societies worldwide. Japan, with an annual rainfall of up to approximately 4000 mm is extremely vulnerable to flooding. The focus of this research is to develop a macroscale hydrologic model for simulating flooding toward an improved understanding and assessment of flood risk across Japan. The framework employs a conceptual hydrological model, known as the Probability Distributed Model (PDM), as well as the Muskingum-Cunge flood routing procedure for simulating streamflow. In addition, a Temperature-Index model is incorporated to account for snowmelt and its contribution to streamflow. For an efficient calibration of the model, in terms of computational timing and convergence of the parameters, a set of A Priori parameters is obtained based on the relationships between the model parameters and the physical properties of watersheds. In this regard, we have implemented a particle tracking algorithm and a statistical model which use high resolution Digital Terrain Models to estimate different time related parameters of the model such as time to peak of the unit hydrograph. In addition, global soil moisture and depth data are used to generate A Priori estimation of maximum soil moisture capacity, an important parameter of the PDM model. Once the model is calibrated, its performance is examined during the Typhoon Nabi which struck Japan in September 2005 and caused severe flooding throughout the country. The model is also validated for the extreme precipitation event in 2012 which affected Kyushu. In both cases, quantitative measures show that simulated streamflow depicts good agreement with gauge-based observations. The model is employed to simulate thousands of possible flood events for the entire Japan which makes a basis for a comprehensive flood risk assessment and loss estimation for the flood insurance industry.
Kay, Paul; Grayson, Richard; Phillips, Martin; Stanley, Karen; Dodsworth, Alan; Hanson, Ann; Walker, Andrew; Foulger, Miles; McDonnell, Iain; Taylor, Simon
SummaryAgriculture is estimated to be responsible for 70% of nitrate and 30-50% of phosphorus pollution, contributing to ecological and water treatment problems. Despite the fact that significant gaps remain in our understanding, it is known that agricultural stewardship can be highly effective in controlling water pollution at the plot and field scales. Knowledge at the catchment scale is, to a large extent, entirely lacking though and this is of paramount concern given that the catchment is the management unit used by regulatory authorities. The few studies that have examined the impact of agricultural stewardship at the catchment scale have found that Nitrate Vulnerable Zones (NVZs) in the UK have resulted in little improvement in water quality which concurs with the current catchment study. In addition to NVZs, there was little evidence to suggest that the England Catchment Sensitive Farming Delivery Initiative had impacted water quality and suggestions have been made for improvements, such as ensuring that stewardship measures are used in key pollution source areas and their implementation and impacts are monitored more closely. This will be essential if agricultural catchment management schemes are going to provide the benefits expected of them. Nevertheless, more intensive monitoring than that carried out by regulators showed a significant trend in decreasing winter nitrate peaks in some streams which is hypothesised to be due to recent reduced inorganic fertiliser application as a result of increasing prices. It was concluded that, collectively, these findings indicate that agricultural stewardship measures have the potential to improve water quality at the catchment scale but that voluntary schemes with insufficient financial reward or regulatory pressure are unlikely to be successful.
Ajami, Hoori; Troch, Peter A.; Maddock, Thomas, III; Meixner, Thomas; Eastoe, Chris
Despite the importance of mountainous catchments for providing freshwater resources, especially in semi-arid regions, little is known about key hydrological processes such as mountain block recharge (MBR). Here we implement a data-based method informed by isotopic data to quantify MBR rates using recession flow analysis. We applied our hybrid method in a semi-arid sky island catchment in southern Arizona, United States. Sabino Creek is a 91 km2 catchment with its sources near the summit of the Santa Catalina Mountains northeast of Tucson. Southern Arizona's climate has two distinct wet seasons separated by prolonged dry periods. Winter frontal storms (November-March) provide about 50% of annual precipitation, and summers are dominated by monsoon convective storms from July to September. Isotope analyses of springs and surface water in the Sabino Creek catchment indicate that streamflow during dry periods is derived from groundwater storage in fractured bedrock. Storage-discharge relationships are derived from recession flow analysis to estimate changes in storage during wet periods. To provide reliable estimates, several corrections and improvements to classic base flow recession analysis are considered. These corrections and improvements include adaptive time stepping, data binning, and the choice of storage-discharge functions. Our analysis shows that (1) incorporating adaptive time steps to correct for streamflow measurement errors improves the coefficient of determination, (2) the quantile method is best for streamflow data binning, (3) the choice of the regression model is critical when the stage-discharge function is used to predict changes in bedrock storage beyond the maximum observed flow in the catchment, and (4) the use of daily or night-time hourly streamflow does not affect the form of the storage-discharge relationship but will impact MBR estimates because of differences in the observed range of streamflow in each series.
Engel, Michael; Bertoldi, Giacomo; Notarnicola, Claudia; Comiti, Francesco
threshold of 100 mm, leading to increased OA (> 0.8) in 13‰ of the catchment area. SCA agreement in January 2012 and 2013 was slightly limited by MODIS sensor detection due to shading effects and low illumination in areas exposed north-west to north. On the contrary, during the melting season in April 2013 and after the September 2013 snowfall event seemed to depend more on parameterisation than on snow depth thresholds. In contrast, inaccuracies during the melting season March to June 2013 could hardly be attributed to topographic characteristics and different snow depth thresholds but rather on model parameterisation. We identified specific conditions (p.e. specific snowfall events in autumn 2012 and spring 2013) when either MODIS data or the hydrological model was less accurate, thus justifying the need for improvements of precision in the snow cover detection algorithms or in the model's process description. In consequence, our study observations could support future snow cover evaluations in mountain areas, where spatially and temporally dynamic snow depth thresholds are transferred from the catchment scale to the regional scale. Keywords: snow cover, snow modelling, MODIS, snow depth sensitivity, alpine catchment
Mazzoleni, Maurizio; Alfonso, Leonardo; Chacon-Hurtado, Juan; Solomatine, Dimitri
Catastrophic floods cause significant socio-economical losses. Non-structural measures, such as real-time flood forecasting, can potentially reduce flood risk. To this end, data assimilation methods have been used to improve flood forecasts by integrating static ground observations, and in some cases also remote sensing observations, within water models. Current hydrologic and hydraulic research works consider assimilation of observations coming from traditional, static sensors. At the same time, low-cost, mobile sensors and mobile communication devices are becoming also increasingly available. The main goal and innovation of this study is to demonstrate the usefulness of assimilating uncertain streamflow observations that are dynamic in space and intermittent in time in the context of two different semi-distributed hydrological model structures. The developed method is applied to the Brue basin, where the dynamic observations are imitated by the synthetic observations of discharge. The results of this study show how model structures and sensors locations affect in different ways the assimilation of streamflow observations. In addition, it proves how assimilation of such uncertain observations from dynamic sensors can provide model improvements similar to those of streamflow observations coming from a non-optimal network of static physical sensors. This can be a potential application of recent efforts to build citizen observatories of water, which can make the citizens an active part in information capturing, evaluation and communication, helping simultaneously to improvement of model-based flood forecasting.
Filby, S.K.; Locke, Sharon M.; Person, M.A.; Winter, T.C.; Rosenberry, D.O.; Nieber, J.L.; Gutowski, W.J.; Ito, E.
A hydrologifc model of the Shingobee Watershed in north-central Minnesota was developed to reconstruct mid-Holocene paleo-lake levels for Williams Lake, a surface-water body located in the southern portion of the watershed. Hydrologic parameters for the model were first estimated in a calibration exercise using a 9-yr historical record (1990-1998) of climatic and hydrologic stresses. The model reproduced observed temporal and spatial trends in surface/groundwater levels across the watershed. Mid-Holocene aquifer and lake levels were then reconstructed using two paleoclimatic data sets: CCM1 atmospheric general circulation model output and pollen-transfer functions using sediment core data from Williams Lake. Calculated paleo-lake levels based on pollen-derived paleoclimatic reconstructions indicated a 3.5-m drop in simulated lake levels and were in good agreement with the position of mid-Holocene beach sands observed in a Williams Lake sediment core transect. However, calculated paleolake levels based on CCM1 climate forcing produced only a 0.05-m drop in lake levels. We found that decreases in winter precipitation rather than temperature increases had the largest effect on simulated mid-Holocene lake levels. The study illustrates how watershed models can be used to critically evaluate paleoclimatic reconstructions by integrating geologic, climatic, limnologic, and hydrogeologic data sets. ?? 2002 University of Washington.
Miller, L. D.; Tom, C.; Nualchawee, K.
A tropical forest area of Northern Thailand provided a test case of the application of the approach in more natural surroundings. Remote sensing imagery subjected to proper computer analysis has been shown to be a very useful means of collecting spatial data for the science of hydrology. Remote sensing products provide direct input to hydrologic models and practical data bases for planning large and small-scale hydrologic developments. Combining the available remote sensing imagery together with available map information in the landscape model provides a basis for substantial improvements in these applications.
Richard D. Woodsmith; Kellie B. Vache; Jeffrey J. McDonnell; J. David Helvey
Effects of wildfire on water quantity and quality are issues of major concern. Much has been learned from previous research, although site specific data from both before and after wildfire are rare. The Entiat Experimental Forest (EEF) in central Washington State provides such a hydrologic record. In August 1970 a severe wildfire occurred following 10 years of stream...
Hwang, Y.; Clark, M.R.; Rajagopalan, B.; Leavesley, G.
Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs. ?? 2011 Springer-Verlag.
Flamig, Z.; Gourley, J. J.; Vergara, H. J.; Kirstetter, P. E.; Hong, Y.
This study will describe a CONUS flash flood climatology created over the period from 2002 through 2011. The MRMS reanalysis precipitation dataset was used as forcing into the Ensemble Framework For Flash Flood Forecasting (EF5). This high resolution 1-sq km 5-minute dataset is ideal for simulating flash floods with a distributed hydrologic model. EF5 features multiple water balance components including SAC-SMA, CREST, and a hydrophobic model all coupled with kinematic wave routing. The EF5/SAC-SMA and EF5/CREST water balance schemes were used for the creation of dual flash flood climatologies based on the differing water balance principles. For the period from 2002 through 2011 the daily maximum streamflow, unit streamflow, and time of peak streamflow was stored along with the minimum soil moisture. These variables are used to describe the states of the soils right before a flash flood event and the peak streamflow that was simulated during the flash flood event. The results will be shown, compared and contrasted. The resulting model simulations will be verified on basins less than 1,000-sq km with USGS gauges to ensure the distributed hydrologic models are reliable. The results will also be compared spatially to Storm Data flash flood event observations to judge the degree of agreement between the simulated climatologies and observations.
Gateuille, D.; Evrard, O.; Lefevre, I.; Moreau-Guigon, E.; Alliot, F.; Chevreuil, M.; Mouchel, J.-M.
Reducing environmental contamination constitutes a major challenge for industrialized countries. Furthermore, in the European Union, Water Framework Directive (WFD; Directive 2000/60/EC) requires that the member state water bodies reach good ecological and chemical status by 2015. Polycyclic Aromatic Hydrocarbons (PAHs) are a group of persistent organic pollutants considered as priority pollutants because of their mutagenic and carcinogenic properties. They are mostly emitted by human activities such as household heating or road traffic. Although emissions have decreased during the last decades, a large amount of PAHs have been released into the atmosphere for the last two centuries. In recent years, studies dealing with PAHs have grown in number but most of them were restricted to the measurement of PAHs concentrations in the different compartments of the environment (air, soil, sediment, water, etc.). In this context, there remains a lack of knowledge about the transfers and, consequently, about the persistence of these compounds in the environment. This question is particularly acute in the Seine River basin where very high concentrations in PAHs are reported in sediment, thereby compromising the achievement of the good chemical status required by WFD. Our study aims to quantify PAHs transfers at the catchment scale by combining chemical analysis with gamma spectrometry. Atmospheric fallout, soil, river water and sediment samples were collected in two upstream sub-catchments of the Seine River basin during one year. Chemical analyses, restricted to 15 of the 16 PAHs selected by the US Environmental Protection Agency (USEPA), were carried out to determine PAHs concentrations in all samples. Contamination spectra were used to outline the potential origin of pollution. Measurement of fallout radionuclides (Beryllium-7, Lead-210, Caesium-137) in both rainfall and river sediment provided a way to discriminate between freshly eroded sediment vs. material that
Kim, Kue Bum; Kwon, Hyun-Han; Han, Dawei
Traditional hydrological modelling assumes that the catchment does not change with time (i.e., stationary conditions) which means the model calibrated for the historical period is valid for the future period. However, in reality, due to change of climate and catchment conditions this stationarity assumption may not be valid in the future. It is a challenge to make the hydrological model adaptive to the future climate and catchment conditions that are not observable at the present time. In this study a lumped conceptual rainfall-runoff model called IHACRES was applied to a catchment in southwest England. Long observation data from 1961 to 2008 were used and seasonal calibration (in this study only summer period is further explored because it is more sensitive to climate and land cover change than the other three seasons) has been done since there are significant seasonal rainfall patterns. We expect that the model performance can be improved by calibrating the model based on individual seasons. The data is split into calibration and validation periods with the intention of using the validation period to represent the future unobserved situations. The success of the non-stationary model will depend not only on good performance during the calibration period but also the validation period. Initially, the calibration is based on changing the model parameters with time. Methodology is proposed to adapt the parameters using the step forward and backward selection schemes. However, in the validation both the forward and backward multiple parameter changing models failed. One problem is that the regression with time is not reliable since the trend may not be in a monotonic linear relationship with time. The second issue is that changing multiple parameters makes the selection process very complex which is time consuming and not effective in the validation period. As a result, two new concepts are explored. First, only one parameter is selected for adjustment while the other
Engman, E. T.; Jackson, T. J.; Schmugge, T. J.
A series of six microwave data collection flights for measuring soil moisture were made over a small 7.8 square kilometer watershed in southwestern Minnesota. These flights were made to provide 100 percent coverage of the basin at a 400 m resolution. In addition, three flight lines were flown at preselected areas to provide a sample of data at a higher resolution of 60 m. The low level flights provide considerably more information on soil moisture variability. The results are discussed in terms of reproducibility, spatial variability and temporal variability, and their implications for hydrologic modeling.
Doppler, T.; Honti, M.; Zihlmann, U.; Weisskopf, P.; Stamm, C.
Spatially distributed models are popular tools in hydrology claimed to be useful to support management decisions. Despite the high spatial resolution of the computed variables, calibration and validation is often carried out only on discharge time series at specific locations due to the lack of spatially distributed reference data. Because of this restriction, the predictive power of these models, with regard to predicted spatial patterns, can usually not be judged. An example of spatial predictions in hydrology is the prediction of saturated areas in agricultural catchments. These areas can be important source areas for inputs of agrochemicals to the stream. We set up a spatially distributed model to predict saturated areas in a 1.2 km2 catchment in Switzerland with moderate topography and artificial drainage. We translated soil morphological data available from soil maps into an estimate of the duration of soil saturation in the soil horizons. This resulted in a data set with high spatial coverage on which the model predictions were validated. In general, these saturation estimates corresponded well to the measured groundwater levels. We worked with a model that would be applicable for management decisions because of its fast calculation speed and rather low data requirements. We simultaneously calibrated the model to observed groundwater levels and discharge. The model was able to reproduce the general hydrological behavior of the catchment in terms of discharge and absolute groundwater levels. However, the the groundwater level predictions were not accurate enough to be used for the prediction of saturated areas. Groundwater level dynamics were not adequately reproduced and the predicted spatial saturation patterns did not correspond to those estimated from the soil map. Our results indicate that an accurate prediction of the groundwater level dynamics of the shallow groundwater in our catchment that is subject to artificial drainage would require a model that
Sinha, Sumit; Rode, Michael; Kumar, Rohini; Yang, Xiaoqiang; Samaniego, Luis; Borchardt, Dietrich
Precise measurements of where, when and how much denitrification occurs on the basis of measurements alone persist to be vexing and intractable research problem at all spatial and temporal scales. As a result, models have become essential and vital tools for furthering our current understanding of the processes that control denitrification on catchment scale. Emplacement of Water Framework Directive (WFD) and continued efforts in improving water treatment facilities has resulted in alleviating the problems associated with point sources of pollution. However, the problem of eutrophication still persists and is primarily associated with the diffused sources of pollution originating from agricultural area. In this study, the nitrate transport and reaction (NTR) routines are developed inside the distributed mesoscale Hydrological Model (mHM www.ufz.de/mhm) which is a fully distributed hydrological model with a novel parameter regionalization scheme (Samaniego et al. 2010; Kumar et al. 2013) and has been applied to whole Europe (Rakovec et al. 2016) and numerous catchments worldwide. The aforementioned NTR model is applied to a mesoscale river basin, Selke (463 km2) located in central Germany. The NTR model takes in account the critical and pertinent processes like transformation in vadose zone, atmospheric deposition, plant uptake, instream denitrification and also simulates the process of manure and fertilizer application. Both streamflow routines and the NTR model are run on daily time steps. The split-sample approach was used for model calibration (1994-1999) and validation (2000-2004). Flow dynamics at three gauging stations located inside this catchment are successfully captured by the model with consistently high Nash-Sutcliffe Efficiency (NSE) of at least 0.8. Regarding nitrate estimates, the NSE values are greater than 0.7 for both validation and calibration periods. Finally, the NTR model is used for identifying the critical source areas (CSAs) that contribute
Deng, Chao; Liu, Pan; Guo, Shenglian; Li, Zejun; Wang, Dingbao
Hydrological model parameters play an important role in the ability of model prediction. In a stationary context, parameters of hydrological models are treated as constants; however, model parameters may vary with time under climate change and anthropogenic activities. The technique of ensemble Kalman filter (EnKF) is proposed to identify the temporal variation of parameters for a two-parameter monthly water balance model (TWBM) by assimilating the runoff observations. Through a synthetic experiment, the proposed method is evaluated with time-invariant (i.e., constant) parameters and different types of parameter variations, including trend, abrupt change and periodicity. Various levels of observation uncertainty are designed to examine the performance of the EnKF. The results show that the EnKF can successfully capture the temporal variations of the model parameters. The application to the Wudinghe basin shows that the water storage capacity (SC) of the TWBM model has an apparent increasing trend during the period from 1958 to 2000. The identified temporal variation of SC is explained by land use and land cover changes due to soil and water conservation measures. In contrast, the application to the Tongtianhe basin shows that the estimated SC has no significant variation during the simulation period of 1982-2013, corresponding to the relatively stationary catchment properties. The evapotranspiration parameter (C) has temporal variations while no obvious change patterns exist. The proposed method provides an effective tool for quantifying the temporal variations of the model parameters, thereby improving the accuracy and reliability of model simulations and forecasts.
Lee-Cullin, J. A.; Zarnetske, J. P.; Wiewiora, E.; Ruhala, S.; Hampton, T. B.
Dissolved organic carbon (DOC) is a critical component to biogeochemical cycling and water quality in surface waters. As DOC moves through stream networks, from headwaters to higher order streams, the sediment-water interface (SWI), where streams and groundwater readily interact, exerts a strong influence on DOC concentrations and compositional characteristics (i.e., molecular properties). Few studies examine SWI patterns at larger spatial scales, instead focusing primarily on site-level studies because sampling in the SWI is methodologically time and labor intensive. It is presently unknown how land use and landcover influence the fate of DOC in the SWI and therefore the function of the SWI on catchment-scale DOC conditions. Here, we performed a catchment-scale, high spatial-resolution SWI sampling campaign to test how landscape pattern DOC signatures are propagated into the stream and groundwater, and to assess the fate of these signatures when DOC travels through the SWI. We sampled across 39 sites composed of first-, second-, and third-order locations in a lowland, third-order catchment composed of diverse landscape units and properties, including wetland, upland forest, and agriculture. At each of these locations, surface water, groundwater, and SWI water were collected, including six discrete depths across the SWI. The major land use and landcover properties were also determined for each of these locations. We developed two simple generalized linear models to identify the landscape properties with greatest explanatory power for DOC conditions - one for stream water and one for groundwater. The correlation between landscape properties and surface water DOC characteristics was stronger than between landscape properties and groundwater DOC characteristics. To test if the DOC properties from surface and groundwater were preserved or removed by the SWI, the resulting best-fit models for each water source were used to predict the DOC conditions across the SWI. The
Lee-Cullin, J. A.; Zarnetske, J. P.; Wiewiora, E.; Ruhala, S.; Hampton, T. B.
Dissolved organic carbon (DOC) is a critical component to biogeochemical cycling and water quality in surface waters. As DOC moves through stream networks, from headwaters to higher order streams, the sediment-water interface (SWI), where streams and groundwater readily interact, exerts a strong influence on DOC concentrations and compositional characteristics (i.e., molecular properties). Few studies examine SWI patterns at larger spatial scales, instead focusing primarily on site-level studies because sampling in the SWI is methodologically time and labor intensive. It is presently unknown how land use and landcover influence the fate of DOC in the SWI and therefore the function of the SWI on catchment-scale DOC conditions. Here, we performed a catchment-scale, high spatial-resolution SWI sampling campaign to test how landscape pattern DOC signatures are propagated into the stream and groundwater, and to assess the fate of these signatures when DOC travels through the SWI. We sampled across 39 sites composed of first-, second-, and third-order locations in a lowland, third-order catchment composed of diverse landscape units and properties, including wetland, upland forest, and agriculture. At each of these locations, surface water, groundwater, and SWI water were collected, including six discrete depths across the SWI. The major land use and landcover properties were also determined for each of these locations. We developed two simple generalized linear models to identify the landscape properties with greatest explanatory power for DOC conditions - one for stream water and one for groundwater. The correlation between landscape properties and surface water DOC characteristics was stronger than between landscape properties and groundwater DOC characteristics. To test if the DOC properties from surface and groundwater were preserved or removed by the SWI, the resulting best-fit models for each water source were used to predict the DOC conditions across the SWI. The
Lee H. MacDonald; Drew Coe; Sandra Litschert
Cumulative effects result from the combined impact of multiple activities over space and time. Land and aquatic resource managers are particularly concerned with cumulative watershed effects (CWEs). CWEs can encompass a broad range of concerns, but primary issues are changes in runoff, water quality, channel morphology, and aquatic ecosystems at the watershed scale (...
Hanson, Randall T.; Boyce, Scott E.; Schmid, Wolfgang; Hughes, Joseph D.; Mehl, Steffen W.; Leake, Stanley A.; Maddock, Thomas; Niswonger, Richard G.
The One-Water Hydrologic Flow Model (MF-OWHM) is a MODFLOW-based integrated hydrologic flow model (IHM) that is the most complete version, to date, of the MODFLOW family of hydrologic simulators needed for the analysis of a broad range of conjunctive-use issues. Conjunctive use is the combined use of groundwater and surface water. MF-OWHM allows the simulation, analysis, and management of nearly all components of human and natural water movement and use in a physically-based supply-and-demand framework. MF-OWHM is based on the Farm Process for MODFLOW-2005 (MF-FMP2) combined with Local Grid Refinement (LGR) for embedded models to allow use of the Farm Process (FMP) and Streamflow Routing (SFR) within embedded grids. MF-OWHM also includes new features such as the Surface-water Routing Process (SWR), Seawater Intrusion (SWI), and Riparian Evapotrasnpiration (RIP-ET), and new solvers such as Newton-Raphson (NWT) and nonlinear preconditioned conjugate gradient (PCGN). This IHM also includes new connectivities to expand the linkages for deformation-, flow-, and head-dependent flows. Deformation-dependent flows are simulated through the optional linkage to simulated land subsidence with a vertically deforming mesh. Flow-dependent flows now include linkages between the new SWR with SFR and FMP, as well as connectivity with embedded models for SFR and FMP through LGR. Head-dependent flows now include a modified Hydrologic Flow Barrier Package (HFB) that allows optional transient HFB capabilities, and the flow between any two layers that are adjacent along a depositional or erosional boundary or displaced along a fault. MF-OWHM represents a complete operational hydrologic model that fully links the movement and use of groundwater, surface water, and imported water for consumption by irrigated agriculture, but also of water used in urban areas and by natural vegetation. Supply and demand components of water use are analyzed under demand-driven and supply
Habib, E. H.; Tarboton, D. G.; Lall, U.; Bodin, M.; Rahill-Marier, B.; Chimmula, S.; Meselhe, E. A.; Ali, A.; Williams, D.; Ma, Y.
The hydrologic community has long recognized the need for broad reform in hydrologic education. A paradigm shift is critically sought in undergraduate hydrology and water resource education by adopting context-rich, student-centered, and active learning strategies. Hydrologists currently deal with intricate issues rooted in complex natural ecosystems containing a multitude of interconnected processes. Advances in the multi-disciplinary field include observational settings such as Critical Zone and Water, Sustainability and Climate Observatories, Hydrologic Information Systems, instrumentation and modeling methods. These research advances theory and practices call for similar efforts and improvements in hydrologic education. The typical, text-book based approach in hydrologic education has focused on specific applications and/or unit processes associated with the hydrologic cycle with idealizations, rather than the contextual relations in the physical processes and the spatial and temporal dynamics connecting climate and ecosystems. An appreciation of the natural variability of these processes will lead to graduates with the ability to develop independent learning skills and understanding. This appreciation cannot be gained in curricula where field components such as observational and experimental data are deficient. These types of data are also critical when using simulation models to create environments that support this type of learning. Additional sources of observations in conjunction with models and field data are key to students understanding of the challenges associated with using models to represent such complex systems. Recent advances in scientific visualization and web-based technologies provide new opportunities for the development of active learning techniques utilizing ongoing research. The overall goal of the current study is to develop visual, case-based, data and simulation driven learning experiences to instructors and students through a web
WANG, L.; Wang, Z.; Changming, L.; Li, J.; Bai, P.
Simulating water cycling process temporally and spatially fitting for the characteristics of the study area was important for floods prediction and streamflow simulation with high accuracy, as soil properties, land scape, climate, and land managements were the critical factors influencing the non-linear relationship of rainfall-runoff at watershed scales. Most existing hydrological models cannot simulate water cycle process at different places with customized mechanisms with fixed single structure and mode. This study develops Hydro-Informatic Modeling System (HIMS) model with modular of each critical hydrological process with multiple choices for various scenarios to solve this problem. HIMS has the structure accounting for two runoff generation mechanisms of infiltration excess and saturation excess and estimated runoff with different methods including Time Variance Gain Model (TVGM), LCM which has good performance at ungauged areas, besides the widely used Soil Conservation Service-Curve Number (SCS-CN) method. Channel routing model contains the most widely used Muskingum, and kinematic wave equation with new solving method. HIMS model performance with its symbolic runoff generation model LCM was evaluated through comparison with the observed streamflow datasets of Lasha river watershed at hourly, daily, and monthly time steps. Comparisons between simulational and obervational streamflows were found with NSE higher than 0.87 and WE within ±20%. Water balance analysis about precipitation, streamflow, actual evapotranspiration (ET), and soil moisture change was conducted temporally at annual time step and it has been proved that HIMS model performance was reliable through comparison with literature results at the Lhasa River watershed.
Istanbulluoglu, E.; Vivoni, E. R.; Ivanov, V. Y.; Bras, R. L.
Landscape morphology has an important control on the spatial and temporal organization of basin hydrologic response to climate forcing, affecting soil moisture redistribution as well as vegetation function. On the other hand, erosion, driven by hydrology and modulated by vegetation, produces landforms over geologic time scales that reflect characteristic signatures of the dominant land forming process. Responding to extreme climate events or anthropogenic disturbances of the land surface, infrequent but rapid forms of erosion (e.g., arroyo development, landsliding) can modify topography such that basin hydrology is significantly influenced. Despite significant advances in both hydrologic and geomorphic modeling over the past two decades, the dynamic interactions between basin hydrology, geomorphology and terrestrial ecology are not adequately captured in current model frameworks. In order to investigate hydrologic-geomorphic-ecologic interactions at the basin scale we present initial efforts in integrating the CHILD landscape evolution model (Tucker et al. 2001) with the tRIBS hydrology model (Ivanov et al. 2004), both developed in a common software environment. In this talk, we present preliminary results of the numerical modeling of the coupled evolution of basin hydro-geomorphic response and resulting landscape morphology in two sets of examples. First, we discuss the long-term evolution of both the hydrologic response and the resulting basin morphology from an initially uplifted plateau. In the second set of modeling experiments, we implement changes in climate and land-use to an existing topography and compare basin hydrologic response to the model results when landscape form is fixed (e.g. no coupling between hydrology and geomorphology). Model results stress the importance of internal basin dynamics, including runoff generation mechanisms and hydrologic states, in shaping hydrologic response as well as the importance of employing comprehensive
Gelfan, Alexander; Kalugin, Andrei; Motovilov, Yury
A regional hydrological model was setup to assess possible impact of climate change on the hydrological regime of the Amur drainage basin (the catchment area is 1 855 000 km2). The model is based on the ECOMAG hydrological modeling platform and describes spatially distributed processes of water cycle in this great basin with account for flow regulation by the Russian and Chinese reservoirs. Earlier, the regional hydrological model was intensively evaluated against 20-year streamflow data over the whole Amur basin and, being driven by 252-station meteorological observations as input data, demonstrated good performance. In this study, we firstly assessed the reliability of the model to reproduce the historical streamflow series when Global Climate Model (GCM) simulation data are used as input into the hydrological model. Data of nine GCMs involved in CMIP5 project was utilized and we found that ensemble mean of annual flow is close to the observed flow (error is about 14%) while data of separate GCMs may result in much larger errors. Reproduction of seasonal flow for the historical period turned out weaker; first of all because of large errors in simulated seasonal precipitation, so hydrological consequences of climate change were estimated just in terms of annual flow. We analyzed the hydrological projections from the climate change scenarios. The impacts were assessed in four 20-year periods: early- (2020-2039), mid- (2040-2059) and two end-century (2060-2079; 2080-2099) periods using an ensemble of nine GCMs and four Representative Concentration Pathways (RCP) scenarios. Mean annual runoff anomalies calculated as percentages of the future runoff (simulated under 36 GCM-RCP combinations of climate scenarios) to the historical runoff (simulated under the corresponding GCM outputs for the reference 1986-2005 period) were estimated. Hydrological model gave small negative runoff anomalies for almost all GCM-RCP combinations of climate scenarios and for all 20-year