Development Of Hydrological Models Research Articles

Rainfall/runoff simulation with 2D full shallow water equations: Sensitivity analysis and calibration of infiltration parameters

Summary One of the most difficult issues in the development of hydrologic models is to find a rigorous source of data and specific parameters to a given problem, on a given location that enable reliable calibration. In this paper, a distributed and physically based model (2D Shallow Water Equations) is used for surface flow and runoff calculations in combination with two infiltration laws (Horton and Green–Ampt) for estimating infiltration in a watershed. This technique offers the capability of assigning a local and time-dependent infiltration rate to each computational cell depending on the available surface water, soil type or vegetation. We investigate how the calibration of parameters is affected by transient distributed Shallow Water model and the complexity of the problem. In the first part of this work, we calibrate the infiltration parameters for both Horton and Green–Ampt models under flat ponded soil conditions. Then, by means of synthetic test cases, we perform a space-distributed sensitivity analysis in order to show that this calibration can be significantly affected by the introduction of topography or rainfall. In the second part, parameter calibration for a real catchment is addressed by comparing the numerical simulations with two different sets of experimental data, corresponding to very different events in terms of the rainfall volume. We show that the initial conditions of the catchment and the rainfall pattern have a special relevance in the quality of the adjustment. Hence, it is shown that the topography of the catchment and the storm characteristics affect the calibration of infiltration parameters.

Marmot Creek Experimental Watershed Study

The origins and results of the scientific experiments in Marmot Creek Experimental Watershed, now the Marmot Creek Research Basin, over more than 50 years are reviewed. Marmot Creek was established to better understand how forest manipulations could be used to manage streamflow hydrographs and was actively manipulated in the 1970s and 1980s. While small forest clearings were shown to increase snow accumulation consistently, the impacts on melt rates depended on clearing size, slope and aspect. As a result, clearing treatments whether through large cutblocks or small clearings had modest impacts on the hydrograph timing and variability and only local impacts on streamflow volume. Changes in climate are primarily manifested as warming which has substantially reduced snowpacks at low elevations. These climate changes have not been evident in hydrograph change and there is no trend to volumes or timing of streamflow over the last 50 years. Overall the basin shows remarkable resiliency to climate and land use change due to its wide range of elevations, slopes, snow environments and sub-surface storage. The basin has become a hydrological process observatory where multi-scale models are developed and evaluated for operation over larger areas. It has served an invaluable role for this and the scientific results from Marmot Creek have supported the development of global climate models and hydrological models that are now applied throughout the world.

Genetic Programming Based Approach Towards Understanding the Dynamics of Urban Rainfall-runoff Process

Genetic Programming (GP) is an evolutionary-algorithm based methodology that is the best suited to model non-linear dynamic systems. The potential of GP has not been exploited to the fullest extent in the field of hydrology to understand the complex dynamics involved. The state of the art applications of GP in hydrological modelling involve the use of GP as a short-term prediction and forecast tool rather than as a framework for the development of a better model that can handle current challenges. In today's scenario, with increasing monitoring programmes and computational power, the techniques like GP can be employed for the development and evaluation of hydrological models, balancing, prior information, model complexity, and parameter and output uncertainty. In this study, GP based data driven model in a single and multi-objective framework is trained to capture the dynamics of the urban rainfall-runoff process using a series of tanks, where each tank is a storage unit in a watershed that corresponds to varying depths below the surface. The hydro-meteorological data employed in this study belongs to the Kent Ridge catchment of National University Singapore, a small urban catchment (8.5 hectares) that receives a mean annual rainfall of 2500 mm and consists of all the major land uses of Singapore.

Soil Water Repellency and its Impact on Hydraulic Characteristics in a Beech Forest under Simulated Climate Change

Core Ideas Rainfall redistribution increased soil water repellency in a beech forest soil Soil water repellency correlated with organic matter composition and C/N ratio Contact angles correlated with air‐entry value of hydraulic soil characteristics Climate change is expected to result in prolonged dry periods and an increased occurrence of extreme rainfall events that can increase soil water repellency (SWR). However, this relationship has not been studied under field conditions yet. Also, for the development of hydrological models accounting for SWR, dependencies between SWR and soil hydraulic characteristics would be required. Our hypotheses were that (i) prolonged dry periods increase SWR by changing the composition of the soil organic matter (SOM) and that (ii) SWR alters hydraulic soil properties by the air‐entry value. The objective of the study was to assess the impact of different rainfall redistributions on the degree of SWR, physicochemical soil characteristics, and soil hydraulic properties. A field experiment was conducted on a Podsolic Cambisol in a beech forest with plots covered by roofs and irrigated artificially. Two rainfall redistribution treatments (moderate and extreme) and control plots were compared after two vegetation periods. Potential SWR was characterized by the soil–water contact angle, while the actual degree of SWR was derived indirectly from infiltration experiments with water and ethanol. We found an increase in SWR due to rainfall redistribution. Contact angles correlated positively with the contents of organic carbon (OC) and nitrogen and the relative amount of hydrophobic groups in the organic matter and negatively with the C/N ratio. Differences between intrinsic and actual hydraulic properties increased with prolonged dry periods. Contact angles correlated with the air‐entry value (inverse of van Genuchten parameter α). This finding offers a way to account for SWR in hydraulic models.

Present and future of hydrology

The complexities of hydrological phenomena, the causes that lead to these complexities, and the essences and defects of reductionism are analyzed. The driving forces for the development of hydrology and the formation of branch subjects of hydrology are discussed. The theoretical basis and limitations of existing hydrology are summarized. Existing misunderstandings in the development of the watershed hydrological model are put forward. Finally, the necessity of the expansion of hydrology from linear to nonlinear is discussed.

The River Systems in Small Catchments in the Context of the Horton’s and Schumm’s Laws – Implication for Hydrological Modelling. The Case Study of the Polish Carpathians

Abstract In ungauged catchments, flood hydrographs are usually simulated/reconstructed by simple rainfall-runoff and routing models. Horton’s and Schumm’s ratios serve as the input data for many of these models. In this paper, more than 800 Carpathian catchments (up to 35.2 km2 in area) were investigated in context of the “Horton’s and Schumm’s laws”. Results reveal that the “law of stream number” and “law of stream areas” are fulfilled in almost all catchments. The mean that values of the bifurcation ratio (RB) and the area ratio (RA) reach 3.8 and 4.8, respectively, and are thus comparable to values reported in other regions of the world. However, the “law of stream lengths” is not fulfilled in more than half of the catchments, which is not consistent with many theoretical studies reported in the literature. Only 383 (48%) catchments fulfill the “law of stream length”, with the mean value of the length ratio (RL)=2.3. There was no relationship found between the geological/geomorphological settings that influence river system development and the spatial distribution of catchments where the “law of stream length” was or was not was fulfilled. A similar conclusion was reached for the spatial distribution of the RB, RL, and RA ratios. These results confirmed that the use of Horton’s and Schumm’s ratios for the evaluation of the influence of geological/geomorphological settings on the river system development is limited. Among the lumped hydrological models, those requiring the RB, RL, and RA ratios have been extensively studied over last decades. This study suggests that the application of these models may be limited in small catchment areas; therefore, more attention should be placed on the development of hydrological models where the RB, RL, and RA ratios are not necessary.

Evaluating the Performance of Hydrological Models via Cross-Spectral Analysis: Case Study of the Thames Basin, United Kingdom

AbstractNine distributed hydrological models, forced with common meteorological inputs, simulated naturalized daily discharge from the Thames basin for 1963–2001. While model-dependent evaporative losses are critical for modeling mean discharge, multiple physical processes at many time scales influence the variability and timing of discharge. Here the use of cross-spectral analysis is advocated to measure how the average amplitude—and independently, the average phase—of modeled discharge differ from observed discharge at daily to decadal time scales. Simulation of the spectral properties of the model discharge via numerical manipulation of precipitation confirms that modeled transformation involves runoff generation and routing that amplify the annual cycle, while subsurface storage and routing of runoff between grid boxes introduces most of the autocorrelation and delays. Too much or too little modeled evaporation affects discharge variability, as do the capacity and time constants of modeled stores. Additionally, the performance of specific models would improve if four issues were tackled: 1) nonsinusoidal annual variations in model discharge (prolonged low base flow and shortened high base flow; three models), 2) excessive attenuation of high-frequency variability (three models), 3) excessive short-term variability in winter half years but too little variability in summer half years (two models), and 4) introduction of phase delays at the annual scale only during runoff generation (three models) or only during routing (one model). Cross-spectral analysis reveals how reruns of one model using alternative methods of runoff generation—designed to improve performance at the weekly to monthly time scales—degraded performance at the annual scale. The cross-spectral approach facilitates hydrological model diagnoses and development.

Stochastic structure of annual discharges of large European rivers

Abstract Water resource has become a guarantee for sustainable development on both local and global scales. Exploiting water resources involves development of hydrological models for water management planning. In this paper we present a new stochastic model for generation of mean annul flows. The model is based on historical characteristics of time series of annual flows and consists of the trend component, long-term periodic component and stochastic component. The rest of specified components are model errors which are represented as a random time series. The random time series is generated by the single bootstrap model (SBM). Stochastic ensemble of error terms at the single hydrological station is formed using the SBM method. The ultimate stochastic model gives solutions of annual flows and presents a useful tool for integrated river basin planning and water management studies. The model is applied for ten large European rivers with long observed period. Validation of model results suggests that the stochastic flows simulated by the model can be used for hydrological simulations in river basins.

Hydrologic and Water Quality Model Development Using Simulink

A stormwater runoff model based on the Soil Conservation Service (SCS) method and a finite-volume based water quality model have been developed to investigate the use of Simulink for use in teaching and research. Simulink, a MATLAB extension, is a graphically based model development environment for system modeling and simulation. Widely used for mechanical and electrical systems, Simulink has had less use for modeling of hydrologic systems. The watershed model is being considered for use in teaching graduate-level courses in hydrology and/or stormwater modeling. Simulink’s block (data process) and arrow (data transfer) object model, the copy and paste user interface, the large number of existing blocks, and the absence of computer code allows students to become model developers almost immediately. The visual depiction of systems, their component subsystems, and the flow of data through the systems are ideal attributes for hands-on teaching of hydrologic and mass balance processes to today’s computer-savvy visual learners. Model development with Simulink for research purposes is also investigated. A finite volume, multi-layer pond model using the water quality kinetics present in CE-QUAL-W2 has been developed using Simulink. The model is one of the first uses of Simulink for modeling eutrophication dynamics in stratified natural systems. The model structure and a test case are presented. One use of the model for teaching a graduate-level water quality modeling class is also described.

Prioritization of sub-watersheds based on morphometric analysis using geospatial technique in Piperiya watershed, India

Hydrological investigation and behavior of watershed depend upon geo-morphometric characteristics of catchment. Morphometric analysis is commonly used for development of regional hydrological model of ungauged watershed. A critical valuation and assessment of geo-morphometric constraints has been carried out. Prioritization of watersheds based on water plot capacity of Piperiya watershed has been evaluated by linear, aerial and relief aspects. Morphometric analysis has been attempted for prioritization for nine sub-watersheds of Piperiya watershed in Hasdeo river basin, which is a tributary of the Mahanadi. Sub-watersheds are delineated by ArcMap 9.3 software as per digital elevation model (DEM). Assessment of drainages and their relative parameters such as stream order, stream length, stream frequency, drainage density, texture ratio, form factor, circulatory ratio, elongation ratio, bifurcation ratio and compactness ratio has been calculated separately for each sub-watershed using the Remote Sensing (RS) and Geospatial techniques. Finally, the prioritized score on the basis of morphometric behavior of each sub-watershed is assigned and thereafter consolidated scores have been estimated to identify the most sensitive parameters. The analysis reveals that stream order varies from 1 to 5; however, the first-order stream covers maximum area of about 87.7 %. Total number of stream segment of all order is 1,264 in the watershed. The study emphasizes the prioritization of the sub-watersheds on the basis of morphometric analysis. The final score of entire nine sub-watersheds is assigned as per erosion threat. The sub-watershed with the least compound parameter value was assigned as highest priority. However, the sub-watersheds has been categorized into three classes as high (4.1–4.7), medium (4.8–5.3) and low (>5.4) priority on the basis of their maximum (6.0) and minimum (4.1) prioritized score.

Upper washita river experimental watersheds: reservoir, groundwater, and stream flow data.

Surface and groundwater quantity and quality data are essential in many hydrologic applications and to the development of hydrologic and water quality simulation models. We describe the hydrologic data available in the Little Washita River Experimental Watershed (LWREW) of the Southern Great Plains Research Watershed (SGPRW) and Fort Cobb Reservoir Experimental Watershed (FCREW), both located in southwest Oklahoma. Specifically, we describe the flood retarding structures and corresponding stage, discharge, seepage, and consumptive use data (), stream gauges, and groundwater wells and their corresponding stream flow (; LWREW ARS 522-526 stream gauges) and groundwater level data (SGPRW groundwater levels data; LWREW groundwater data; ; ), respectively. Data collection is a collaborative effort between federal and state agencies. Stage, discharge, seepage, and consumptive use data for the Fort Cobb Reservoir are available from the Bureau of Reclamation and cover a period of 1959 to present. There are 15 stream gauges in the LWREW and six in the FCREW with varying data records. There were 479 observation wells with data in the SGPRW and 80 in the LWREW, with the latest records collected in 1992. In addition, groundwater level data are available from five real-time monitoring wells and 34 historical wells within the FCREW. These data sets have been used for several research applications. Plans for detailed groundwater data collection are underway to calibrate and validate the linked Soil and Water Assessment Tool (SWAT)-MODFLOW model. Also, plans are underway to conduct reservoir bathymetric surveys to determine the current reservoir capacity as affected by land use/land cover and overland and stream channel soil erosion.

Effects of climate change on daily minimum and maximum temperatures and cloudiness in the Shikoku region: a statistical downscaling model approach

In this study, we present a detailed analysis of the effect of changes in cloudiness (CLD) between a future period (2071–2099) and the base period (1961–1990) on daily minimum temperature (TMIN) and maximum temperature (TMAX) in the same period for the Shikoku region, Japan. This analysis was performed using climate data obtained with the use of the Statistical DownScaling Model (SDSM). We calibrated the SDSM using the National Center for Environmental Prediction (NCEP) reanalysis dataset for the SDSM input and daily time series of temperature and CLD from 10 surface data points (SDP) in Shikoku. Subsequently, we validated the SDSM outputs, specifically, TMIN, TMAX, and CLD, obtained with the use of the NCEP reanalysis dataset and general circulation model (GCM) data against the SDP. The GCM data used in the validation procedure were those from the Hadley Centre Coupled Model, version 3 (HadCM3) for the Special Report on Emission Scenarios (SRES) A2 and B2 scenarios and from the third generation Coupled Global Climate Model (CGCM3) for the SRES A2 and A1B scenarios. Finally, the validated SDSM was run to study the effect of future changes in CLD on TMIN and TMAX. Our analysis showed that (1) the negative linear fit between changes in TMAX and those in CLD was statistically significant in winter while the relationship between the two changes was not evident in summer, (2) the dependency of future changes in TMAX and TMIN on future changes in CLD were more evident in winter than in other seasons with the present SDSM, (3) the diurnal temperature range (DTR) decreased in the southern part of Shikoku in summer in all the SDSM projections while DTR increased in the northern part of Shikoku in the same season in these projections, (4) the dependencies of changes in DTR on changes in CLD were unclear in summer and winter. Results of the SDSM simulations performed for climate change scenarios such as those from this study contribute to local-scale agricultural and hydrological simulations and development of agricultural and hydrological models.

Physical parameterization and sensitivity of urban hydrological models: Application to green roof systems

Rapid urbanization has emerged as the source of many adverse environmental effects and brings cities to a vulnerable situation under future climate challenges. Green roofs are proven to be an effective solution to alleviate these effects by field observations under a wide range of climate conditions. Recent advances in modeling urban land-atmosphere interactions provide a useful tool in capturing the dynamics of coupled transport of water and energy in urban conies, thus bridge the gap of modeling at city to regional scales. The performance of urban hydrological models depends heavily on the accurate determination of the input parameter space, where uncertainty is ubiquitous. In this paper, we use an advanced Monte Carlo approach, viz. the Subset Simulation, to quantify the sensitivity of urban hydrological modeling to parameter uncertainties. Results of the sensitivity analysis reveal that green roofs exhibit markedly different thermal and hydrological behavior as compared to conventional roofs, due to the modification of the surface energy portioning by well-irrigated vegetation. In addition, statistical predictions of critical responses of green roofs (extreme surface temperature, heat fluxes, etc.) have relatively weak dependence on climatic conditions. The statistical quantification of sensitivity provides guidance for future development of urban hydrological models with practical applications such as urban heat island mitigation.

Meta-heuristic algorithms as tools for hydrological science

In this paper, meta-heuristic optimization techniques are introduced and their applications to water resources engineering, particularly in hydrological science are introduced. In recent years, meta-heuristic optimization techniques have been introduced that can overcome the problems inherent in iterative simulations. These methods are able to find good solutions and require limited computation time and memory use without requiring complex derivatives. Simulation-based meta-heuristic methods such as Genetic algorithms (GAs) and Harmony Search (HS) have powerful searching abilities, which can occasionally overcome the several drawbacks of traditional mathematical methods. For example, HS algorithms can be conceptualized from a musical performance process and used to achieve better harmony; such optimization algorithms seek a near global optimum determined by the value of an objective function, providing a more robust determination of musical performance than can be achieved through typical aesthetic estimation. In this paper, meta-heuristic algorithms and their applications (focus on GAs and HS) in hydrological science are discussed by subject, including a review of existing literature in the field. Then, recent trends in optimization are presented and a relatively new technique such as Smallest Small World Cellular Harmony Search (SSWCHS) is briefly introduced, with a summary of promising results obtained in previous studies. As a result, previous studies have demonstrated that meta-heuristic algorithms are effective tools for the development of hydrological models and the management of water resources.

Multimodel assessment of water scarcity under climate change

Water scarcity severely impairs food security and economic prosperity in many countries today. Expected future population changes will, in many countries as well as globally, increase the pressure on available water resources. On the supply side, renewable water resources will be affected by projected changes in precipitation patterns, temperature, and other climate variables. Here we use a large ensemble of global hydrological models (GHMs) forced by five global climate models and the latest greenhouse-gas concentration scenarios (Representative Concentration Pathways) to synthesize the current knowledge about climate change impacts on water resources. We show that climate change is likely to exacerbate regional and global water scarcity considerably. In particular, the ensemble average projects that a global warming of 2 °C above present (approximately 2.7 °C above preindustrial) will confront an additional approximate 15% of the global population with a severe decrease in water resources and will increase the number of people living under absolute water scarcity (<500 m(3) per capita per year) by another 40% (according to some models, more than 100%) compared with the effect of population growth alone. For some indicators of moderate impacts, the steepest increase is seen between the present day and 2 °C, whereas indicators of very severe impacts increase unabated beyond 2 °C. At the same time, the study highlights large uncertainties associated with these estimates, with both global climate models and GHMs contributing to the spread. GHM uncertainty is particularly dominant in many regions affected by declining water resources, suggesting a high potential for improved water resource projections through hydrological model development.

Development of Hydrological Model for Sustainable Irrigated Agriculture in Al-Ahsa Oasis

Development of Hydrological Model for Sustainable Irrigated Agriculture in Al-Ahsa Oasis

Simulating wetland impacts on stream flow in southern Africa using a monthly hydrological model

AbstractThe processes that occur in wetlands and natural lakes are often overlooked and not fully incorporated in the conceptual development of many hydrological models of basin runoff. These processes can exert a considerable influence on downstream flow regimes and are critical in understanding the general patterns of runoff generation at the basin scale. This is certainly the case for many river basins of southern Africa which contain large wetlands and natural lakes and for which downstream flow regimes are altered through attenuation, storage and slow release processes that occur within the water bodies. Initial hydrological modelling studies conducted in some of these areas identified the need to explicitly account for wetland storage processes in the conceptual development of models. This study presents an attempt to incorporate wetland processes into an existing hydrological model, with the aim of reducing model structural uncertainties and improving model simulations where the impacts of wetlands or natural lakes on stream flow are evident. The approach is based on relatively flexible functions that account for the input–storage–output relationships between the river channel and the wetland. The simulation results suggest that incorporating lake and wetland storage processes into modelling can provide improved representation (the right results for the right reason) of the hydrological behaviour of some large river basins, as well as reducing some of the uncertainties in the quantification of the original model parameters used for generating the basin runoff. Copyright © 2013 John Wiley &amp; Sons, Ltd.

Application and Development of Stochastic Hydrological Models in China

By reviewing the application of stochastic hydrological models in flood control safety design, risk analysis, water conservancy project planning and scheduling in recent years in China, it is presented that stochastic hydrological models are good tools for optimizing decisions in planning, design and operation of water resources development and utilization. Also, it deals with the problems which are difficult to solve in traditional hydrological calculation method. Besides, it is focused on some work which should be improvedand popularized about stochastic hydrological models in the future.

Hydrologic Trends and Correlations in South Texas River Basins: 1950–2009

The identification of seasonal and annual trends in precipitation and streamflow volumes at the regional scale contributes to the understanding of global climate change and variation and is essential to the development of hydrologic models, hydrologic forecasting, and water resources planning and management for basins. This study examines such trends over the past 60 years (1950–2009) for the Nueces River basin, the San Antonio River basin, and the Guadalupe River basin, all in south Texas. The correlation of precipitation and streamflow with the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO) climatic indices is also evaluated, with a view toward incorporating these two relatively predictable cyclical patterns into modeling and forecasting of precipitation and streamflow. Trends and correlations were measured using the Kendall and Mann-Kendall test statistics, while the more commonly used Pearson r coefficient was shown not to be consistently appropriate for the data analyses. The influence of PDO on annual precipitation is substantially less in these basins than it was found to be in a basin approximately 1,000 km northwest of them. The majority of trends and correlations were found to be statistically significant at the level of 0.05, and all such relationships were positive (or increasing). The analyses suggest that forecasting and management practices require a deterministic hydrologic model capable of accommodating natural features, management practices, and meteorological input for estimating evapotranspiration potential. Calibration and uncertainty analysis must be of a sophistication to accommodate nonnormal residuals, so that confidence intervals may be reliably used in forecasting and in management decisions.

Physically-based modeling of topographic effects on spatial evapotranspiration and soil moisture patterns through radiation and wind

Abstract. In this paper, simulations with the Soil Water Atmosphere Plant (SWAP) model are performed to quantify the spatial variability of both potential and actual evapotranspiration (ET), and soil moisture content (SMC) caused by topography-induced spatial wind and radiation differences. To obtain the spatially distributed ET/SMC patterns, the field scale SWAP model is applied in a distributed way for both pointwise and catchment wide simulations. An adapted radiation model from r.sun and the physically-based meso-scale wind model METRAS PC are applied to obtain the spatial radiation and wind patterns respectively, which show significant spatial variation and correlation with aspect and elevation respectively. Such topographic dependences and spatial variations further propagate to ET/SMC. A strong spatial, seasonal-dependent, scale-relevant intra-catchment variability in daily/annual ET and less variability in SMC can be observed from the numerical experiments. The study concludes that topography has a significant effect on ET/SMC in the humid region where ET is a energy limited rather than water availability limited process. It affects the spatial runoff generation through spatial radiation and wind, therefore should be applied to inform hydrological model development. In addition, the methodology used in the study can serve as a general method for physically-based ET estimation for data sparse regions.