Search

The ecological integrity of rivers ultimately depends on flow regime. Flow degradation is especially prominent in Mediterranean systems and assessing environmental flows in modified rivers is difficult, especially in environments with poor hydrologic monitoring and data availability. In many Mediterranean countries, which are characterized by pronounced natural variability and low summer flows, water management actions usually focus on prescribing minimum acceptable flows estimated by hydrologic methods. In this study, a comparative assessment of environmental flow estimation methods is developed in a river with poorly monitored flows and limited understanding of past reference conditions. This assessment incorporates both a hydrologic and a fish habitat simulation effort that takes into consideration hydrologic seasonality in a Greek mountainous river. The results of this study indicate that especially in data scarce regions the utilization of biotic indicators through habitat models, may provide valuable information, beyond that achievable with hydrologic methods, for developing regional environmental flow criteria. Despite the widespread use of the method, challenges in transferability of fish habitat simulation provide undefined levels of uncertainty and may require the concurrent use of different assessment tools and site-specific study.

Climate-change adaptation planning for managed wetlands is challenging under uncertain futures when the impact of historic climate variability on wetland response is unquantified. We assessed vulnerability of Modoc National Wildlife Refuge (MNWR) through use of the Basin Characterization Model (BCM) landscape hydrology model, and six global climate models, representing projected wetter and drier conditions. We further developed a conceptual model that provides greater value for water managers by incorporating the BCM outputs into a conceptual framework that links modeled parameters to refuge management outcomes. This framework was used to identify landscape hydrology parameters that reflect refuge sensitivity to changes in (1) climatic water deficit (CWD) and recharge, and (2) the magnitude, timing, and frequency of water inputs. BCM outputs were developed for 1981-2100 to assess changes and forecast the probability of experiencing wet and dry water year types that have historically resulted in challenging conditions for refuge habitat management. We used a Yule's Q skill score to estimate the probability of modeled discharge that best represents historic water year types. CWD increased in all models across 72.3-100 % of the water supply basin by 2100. Earlier timing in discharge, greater cool season discharge, and lesser irrigation season water supply were predicted by most models. Under the worst-case scenario, moderately dry years increased from 10-20 to 40-60 % by 2100. MNWR could adapt by storing additional water during the cool season for later use and prioritizing irrigation of habitats during dry years.

BACKGROUND AND OBJECTIVES: Land use change can directly affect rainfall-runoff relationships. The change in land use is an essential factor in runoff production. This research evaluated the effect of urban development scenarios of land use change on runoff in Gonabad city of Iran. The innovation and importance of this work are to determine which land use changes have the greatest impact on the flood discharge in this urban area. Also, determine how much the minimum development of urban green space is to control and reduce peak flood discharge in this city that is located in a dry area. METHODS: The effect of urban development scenarios on runoff was evaluated by the WinTR-55 model in 5 sub-basins of Gonabad city. The main data required for inputting to the WinTR-55 model are sub-area and reach characteristics, curve number, and storm data. The storm data in TR-55 are 24-hour rainfall amounts in a return period of 2, 5, 10, 25, 50, and 100 years. The changes in the maximum flood discharge and flow hydrograph in each sub-area and return period were calculated by the WinTR-55 model under existing land use conditions and 9 scenarios of urban development. FINDINGS: The greatest increase in runoff production was related to the conversion of abandoned fallow and agricultural lands to residential. Also, the most effective increase or decrease of land cover change in peak flow discharge and total flow volume was at the 2-year return period. The decreased effect of the development of green spaces and urban gardens on peak flow discharge and total flow volume was seen only if their development was more than 50%. The average maximum decrease in peak discharge and total flow volume was 22.7% and 16.1%, respectively. While the average maximum increase in peak discharge and total flow volume was 84.4% and 53.9%, respectively. CONCLUSION: The effect of increasing green spaces and urban gardens on the reduction of peak discharge and volume of runoff was also evident in the study area. Land management and preventing the conversion of permeable land uses such as agricultural, gardening, fallow lands, and rangeland will be much simpler and less costly. Urban land use management to prevent urban floods requires the expansion of permeable surfaces, especially green spaces, and urban gardens. These are the important novelty of this research that can be beneficial for future urban developments of Gonabad city and its flood management activities. [ABSTRACT FROM AUTHOR]

A coupled hydrologic and snowpack stable water isotope model assesses controls on isotopic inputs across a mountainous basin. Annually, the most depleted isotope conditions occur in the upper subalpine where snow accumulation is high, and rainfall is low. Snowmelt isotopic evolution over time indicates fractionation processes account for

Deeper flows through bedrock in mountain watersheds could be important, but lack of data to characterize bedrock properties limits understanding. To address data scarcity, we combine a previously published integrated hydrologic model of a snow-dominated, headwater basin of the Colorado River with a new method for dating baseflow age using dissolved gas tracers SF6, CFC-113, N2, and Ar. The original flow model predicts the majority of groundwater flow through shallow alluvium (

Parameters in hydrologic models used in mixed rain-snow regions are often uncertain to calibrate and overfitted on streamflow. To contribute addressing these challenges, we used an algorithm that assesses modeling performances through time (Dynamic Identifiability Analysis) to quantify the information content of spatially distributed ground-based measurements for identifying optimal parameter values in the Precipitation Runoff Modeling System (PRMS) model. Including spatially distributed ground-based measurements in Identifiability Analysis allowed us to unambiguously estimate more parameter values than only using streamflow (seven parameters instead of two out of a pool of thirty-three). Peaks in information gain were obtained when using dew-point temperature to identify precipitation phase-partitioning parameters. Multi-attribute identifiability analysis also yielded optimal parameter values that were temporally less variable than those estimated using streamflow alone. Overall, identifying parameter values using ground-based measurements improved the simulation of key drivers of the surface-water budget, such as air temperature and precipitation-phase partitioning. However, parameters simulating surface-to-subsurface mass fluxes like snow accumulation and melt or evapotranspiration were poorly identified by any attribute and so emerged as key sources of predictive uncertainty for this distributed-parameter hydrologic model. This work demonstrates the value of expanded ground-based measurements for identifying parameters in distributed-parameter hydrologic models and so diagnosing their conceptual uncertainty across the water budget.

Considerable efforts are underway to restore watersheds and estuaries downstream impacted by urban development; however, climate change (CC) may be undermining them. Current methods are limited in their ability to predict hydrology and water quality with CC and assess its effect on the efficiency of stormwater control measures (SCMs). We developed a method using downscaled global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to project precipitation and temperatures; these were used to force a Storm Water Management Model (SWMM). Three scenarios, a historical and two Representative Concentration Pathways (RCP 4.5 and 8.5) with five GCMs, were used to produce ensemble results. All GCMs in both RCP scenarios projected increases in precipitation and temperature compared to historical conditions. Both RCPs exhibited their largest increases in precipitation, streamflow, total suspended solids (TSS), total nitrogen (TN), and total phosphorous (TP) loads in the winter, summer exhibited the largest increase in temperature. Median loads of TSS, TN, and TP increased 3.1%, 2.5%, and 9.9%, respectively, for RCP 4.5, and increased 3.8%, 3.1%, and 10.4%, respectively, for RCP 8.5. Median reductions in TSS, TN, and TP SCM efficiency for RCP 4.5 were projected to be 6%, 7%, and 11%, respectively; and 11%, 12%, and 17% for RCP 8.5, respectively. Thus, it is likely that additional efforts will be needed to meet water quality goals in the future. Methods such as these can help create climate resilient watershed improvement strategies and guide urban stormwater planning against likely future changes as a result of CC. [ABSTRACT FROM AUTHOR]

Predicting the impact of land cover and climate change on hydrologic responses using modeling tools are essential in understanding the movement and pattern of hydrologic processes within the watershed. The paper provided potential implications of land conversions and climate change scenarios on the hydrologic processes of Muleta watershed using soil and water assessment tool model. Model inputs used include interferometric synthetic aperture radar-digital elevation model, 2016 land cover map, soil map, meteorological and hydrologic data. The model was calibrated using appropriate statistical parameters (R2 =0.80, NS=0.80 and RSR=0.45). Model validation using observed streamflow with the same statistical parameters (R2 = 0.79, NS = 0.67 and RSR = 0.57) showed that the result was statistically acceptable. The model provided potential implications of land conversions and climate change adversely affecting hydrologic processes of critical watersheds. Climate change projections with a 13% decrease in rainfall directly influenced the decrease in hydrologic processes. Meanwhile, urbanization had influenced the increase in surface runoff, evapotranspiration, and baseflow. The increase of forest vegetation resulted in a minimal decrease in baseflow and surface runoff. The watershed hydrologic processes were influenced by changes in land cover and climate. Results of this study are useful by the localities and policy makers in coming up with a more informed decision relative to the issues and concern on hydrological responses in the uplands. [ABSTRACT FROM AUTHOR]

The main goal of this study is to estimate the hydrologic parameters of Kocanaz watershed located in Western Black Sea Region, using a semi-distributed hydrologic model, Hydrologic Engineering Center - Hydrologic Modelling System (HEC-HMS). In this study, the hydrologic model was set up for two flood events occurred in 2002 and 2013, in which one was used for calibration while the other one was used for validation of the calibrated hydrologic parameters. The watershed was introduced into the model as a single basin. Hydrologic parameters used for transformation from rainfall to runoff and base flow estimations were searched using Nelder and Mead method and calibrated using the peakweighted root mean square error. The model results were deliberated by statistical indicators such as Nash-Sutcliffe efficiency coefficient (ENS), coefficient of determination (R2), mass balance error (MBE) and peak flow rate error (PE). The model results were found to be very good for calibration and satisfactory for validation while the peak flow rate was under estimated for both calibration and validation. It can be concluded that small watersheds such as Kocanaz might be modelled as a single basin without sacrificing the estimation capability of the model and increasing the model simulation time. Though, slightly improved peak discharge estimations were obtained in case of using sub basins. [ABSTRACT FROM AUTHOR]

Summary The multisensor Quantitative Precipitation Estimates (MQPEs) created by the US National Weather Service (NWS) are subject to a non-stationary bias. This paper quantifies the impacts of climatological adjustment of MQPEs alone, as well as the compound impacts of adjustment and model calibration, on the accuracy of simulated flood peak magnitude and that in detecting flood events. Our investigation is based on 19 watersheds in the mid-Atlantic region of US, which are grouped into small (<500 km 2 ) and large (>500 km 2 ) watersheds. NWS archival MQPEs over 1997–2013 for this region are adjusted to match concurrent gauge-based monthly precipitation accumulations. Then raw and adjusted MQPEs serve as inputs to the NWS distributed hydrologic model-threshold frequency framework (DHM-TF). Two experiments via DHM-TF are performed. The first one examines the impacts of adjustment alone through uncalibrated model simulations, whereas the second one focuses on the compound effects of adjustment and calibration on the detection of flood events. Uncalibrated model simulations show broad underestimation of flood peaks for small watersheds and overestimation those for large watersheds. Prior to calibration, adjustment alone tends to reduce the magnitude of simulated flood peaks for small and large basins alike, with 95% of all watersheds experienced decline over 2004–2013. A consequence is that a majority of small watersheds experience no improvement, or deterioration in bias (0% of basins experiencing improvement). By contrast, most (73%) of larger ones exhibit improved bias. Outcomes of the detection experiment show that the role of adjustment is not diminished by calibration for small watersheds, with only 25% of which exhibiting reduced bias after adjustment with calibrated parameters. Furthermore, it is shown that calibration is relatively effective in reducing false alarms (e.g., false alarm rate is down from 0.28 to 0.19 after calibration for small watersheds with calibrated parameters); but its impacts on detection rate are mixed. As an example, the detection rate of 2-Y events in fact declines for small watersheds after calibration is performed (from 0.4 to 0.28, and from 0.28 to 0.19 with raw and adjusted MQPE, respectively). These mixed outcomes underscore the complex interplays between errors in MQPEs, conditional bias in the reference gauge-based analysis, and structural deficiencies of the hydrologic model. [ABSTRACT FROM AUTHOR]

This study evaluates the impacts of possible future climate change scenarios on the hydrology of the catchment area of the Manjalar sub basin of River Vaigai, Tamil Nadu, India carried out at the department of Soil and Water Conservation Engineering, Tamil Nadu Agricultural University during the period of 2011-2014 using Soil and Water Assessment Tool (SWAT). For the climate impact assessment the hydrological model was driven with output of bias corrected Earth System Models of the Coupled Model Intercomparison Project Phase 5 (CMIP5): HadGEM2. Climate scenarios were downscaled to a grid resolution of 0.22° x 0.22°. In this study RCP 4.5 and RCP 8.5 were included for future assessment with three future periods: 2012-2039, 2040-2069, and 2070-2098. The projected increase in maximum and minimum temperature for RCP 4.5 scenario is 0.8 to 2.3 °C and 0.7 to 1.6 °C and for RCP 8.5 scenario is 1.1 to 4.0 °C and 1.0 to 3.1 °C, respectively. Rainfall is projected to an increase between 9.2 to 15.2 per cent for RCP 4.5 scenario and an increase of 13.6 to 18.8 per cent for RCP 8.5 scenario during 21st century. The soil water storage and stream flow contribution to ground water are likely to increase in RCP 4.5 scenario and it would again decline for RCP 8.5 scenario during 21st century. The increase in annual rainfall evapotranspiration and surface runoff would be more in RCP 8.5 scenario compared to RCP 4.5 scenario. The possible changes projected by the study provide a useful input to effective planning of water resources of the study area. [ABSTRACT FROM AUTHOR]

The Palmer indices (PIs) that have been most widely used for drought monitoring and assessment are criticized for two main drawbacks: coarse hydrological accounting processes with a simplified two-stage bucket soil water balance model and arbitrary rules for defining drought properties and standardizing index values through limited calibration and comparison. In this study, we introduce a new proposal of the VIC hydrologic model-based Palmer drought scheme, where traditional PIs (e.g. PDSI) can readily be calculated on the basis of distributed finescale hydrologic simulations. Moreover, recent variants of PI (i.e., SPDI and SPDI-JDI) also provide a preferable standardization strategy that allows probabilistic invariability and better spatio-temporal comparability of computed drought indices. Using gridded meteorological forcing, soil and vegetation data to drive the three-layer VIC model, both non-VIC and VIC-based PIs are investigated to examine their performances for drought characterization and detection. Results indicate that VIC hydrologic model would allow for adjustments in statistical properties of computed PDSI and VIC-based SPDI is also preferable to PDSI for better statistical robustness and spatio-temporal consistency/comparability. Moreover, the joint SPDI-JDI has the strength of integrating multi-scale probabilistic properties and drought information released by individual SPDI, providing overall drought conditions that take into account the onset, persistence and termination of droughts. At proposed 0.25° grid scale, the VIC-based SPDI-JDI indicates high frequency and long total time of drought condition in the Yellow River basin (YRB), China. Although no significant temporal trends are found in identified drought duration and severity, both the seasonal and annual drought index values demonstrate a downward trend (higher drought intensity) for considerable proportions of the YRB. These findings imply high drought risk and potential drying stress for this region. The new framework of hydrologic model-based PIs can help to strengthen our knowledge and/or practices in regional drought monitoring and assessment. [ABSTRACT FROM AUTHOR]

Summary A priori parameterization approaches that improve our ability to provide reliable hydrologic predictions in ungauged and poorly gauged basins, as well as in basins undergoing change are currently receiving considerable attention. However, such methods are typically based on local-scale process understanding and simplifying assumptions and an increasing body of evidence suggests that hydrologic models that utilize parameters estimated via such approaches may not always perform well. This paper proposes a Maximum Likelihood multi-criteria penalty function strategy for evaluating a priori parameter estimation approaches. We demonstrate the method by examining the extent to which a priori parameter estimates specified for the Hydrology Laboratory’s Research Distributed Hydrologic Model (via a set of pedotransfer functions) are consistent with the optimal model parameters required to simulate the dynamic input–output response of the Blue River basin. Our results indicated that whereas simulations using the a priori parameter estimates give consistently positive flow bias, unconstrained optimization to the response data results in parameter values that are very different from the a priori parameter set. Moreover, although unconstrained optimization performed best (as measured by the calibration criteria), poor hydrograph simulation performance was evident when evaluated in terms of multiple performance statistics not used in the calibration. On the other hand, the multi-criteria compromise solutions provided improved input–output performance in terms of measures not used in calibration, with generally more consistent behavior across calibration and evaluation years, while maintaining physically realistic a priori values for most of the model parameter estimates; adjustments were found to be necessary for only a few key model parameters. [ABSTRACT FROM AUTHOR]

Headwater streams are the primary sources of water in a drainage network and serve as a critical hydrologic link between the surrounding landscape and larger, downstream surface waters. Many states, including North Carolina, regulate activity in and near headwater streams for the protection of water quality and aquatic resources. A fundamental tool for regulatory management is an accurate representation of streams on a map. Limited resources preclude field mapping every headwater stream and its origin across a large region. It is more practical to develop a model for headwater streams based on a sample of field data that can then be extrapolated to a larger area of interest. The North Carolina Division of Water Quality has developed a cost-effective method for modeling and mapping the location, length, and flow classification (intermittent and perennial) of headwater streams. We used a multiple logistic regression approach that combined field data and terrain derivatives for watersheds located in the Triassic Basins ecoregion. Field data were collected using a standard methodology for identifying headwater streams and origins. Terrain derivatives were generated from digital elevation models interpolated from bare-earth Light Detection and Range data. Model accuracies greater than 80% were achieved in classifying stream presence and absence, stream length and perennial stream length, but were not as consistent in predicting intermittent stream length. [ABSTRACT FROM AUTHOR]

The research involves connecting hydrology modelling to climate change downscaled output by GIS system to enhance the understanding of the impact of climate change scenarios on the river flow. The study provides the useful hydrology data for the future development in Klang watershed. The Hadley Centre Third Generation-GCM model has been employed for emission scenarios A2 and B2 for the period 2001-2100. The output from statistical downscaling model is used as input into HEC-HMS hydrological modelling to project the discharge of Klang River. Then, the hydrological model output is used to determine the future streamflow in the watershed. To evaluate the future climate change, the long time period of projection to 2100 is divided into three parts (2020s, 2050s and 2080s). The mean annual discharge is predicted to be decreasing by 9.4, 4.9 %, and an increase of 3.4 % for the A2 and a decrease of about 17.3, 14.3 and 6.2 % for the B2 scenario, respectively, in the 2020s, 2050s, and 2080s. [ABSTRACT FROM AUTHOR]

The applications of computer technology to analysis of the rainfall-runoff process and the hydrological dynamics of natural rivers have greatly expanded in the past few years. A large number of general purpose programs and a few programs designed for specific application have been developed and applied to hydrologic engineering problems. This paper briefly describes the study of climate change effects on the hydrological dynamics of the Satluj and Beas river system using computer models like HEC- RTS (Hydrologic Engineering Center- Real Time Simulation). It also presents the use of real time data collection and processing on a GIS platform so as to derive a real time decision support system.

Recent U.S. Supreme Court rulings have limited federal protections for geographically isolated wetlands (GIWs) except where a 'significant nexus' to a navigable water body is demonstrated. Geographic isolation does not imply GIWs are hydrologically disconnected; indeed, wetland-groundwater interactions may yield important controls on regional hydrology. Differences in specific yield (Sy) between uplands and inundated GIWs drive differences in water level responses to precipitation and evapotranspiration, leading to frequent reversals in hydraulic gradients that cause GIWs to act as both groundwater sinks and sources. These reversals are predicted to buffer surficial aquifer dynamics and thus base flow delivery, a process we refer to as landscape hydrologic capacitance. To test this hypothesis, we connected models of soil moisture, upland water table, and wetland stage to simulate hydrology of a low-relief landscape with GIWs, and explored the influences of total wetland area, individual wetland size, climate, and soil texture on water table and base flow variation. Increasing total wetland area and decreasing individual wetland size substantially decreased water table and base flow variation (e.g., reducing base flow standard deviation by as much as 50%). GIWs also decreased the frequency of extremely high and low water tables and base flow deliveries. For the same total wetland area, landscapes with fewer (i.e., larger) wetlands exhibited markedly lower hydrologic capacitance than those with more (i.e., smaller) wetlands, highlighting the importance of small GIWs to regional hydrology. Our results suggest that GIWs buffer dynamics of the surficial aquifer and stream base flow, providing an indirect but significant nexus to the regional hydrologic system. [ABSTRACT FROM AUTHOR]

In the interest of assessing an alternative source of precipitation input for the Chesapeake Bay Watershed model, the goal of this study is to compare the next generation weather radar (NEXRAD)-based multisensor precipitation estimator (MPE) with currently available gauge-based precipitation inputs for the model at both point-pixel and spatially aggregated scales. The comparison of gauge-based data with MPE at a point-pixel scale offers insight into how commonly known characteristics of gauge-point data are reflected in the mean areal gauge-based precipitation product. The time and effort for recalibration using MPE can be significantly reduced by strategizing the procedure according to the results of this study. Techniques and findings described here should be of general value for model users to anticipate changes in model parameters and output when moving from gauge-based to MPE precipitation in continuous simulation models. [ABSTRACT FROM AUTHOR]

Retrieving precipitation data from a rain gauge network is a classical and common practice in hydrology and climatology. These data represent the key input in hydrological modeling to reproduce, for example, the characteristics of a flood phenomenon. The accuracy of the model results is strongly dependent on the consistency of the monitoring network in terms of spatial scale, i.e., network density and location of the rain gauges and time resolution. In this context, several studies have been carried out to analyze how the rainfall sampling influences the estimation of total runoff volume. The aim of this paper is to use a physically based and distributed-parameter hydrologic model to investigate how the number and the spatial distribution of a rain gauge network influence the estimation of the hydrograph and its characteristics in conjunction with different spatial and temporal characteristics of rainfall forcing and different soil-type characteristics. The TIN-based real-time integrated basin simulator (tRIBS) hydrologic model was used to simulate hydrologic response at Baron Fork Basin, Oklahoma. Downscaled next-generation radar (NEXRAD) measurements were assumed to represent the true precipitation distribution over the basin. Additional precipitation fields have been derived from the interpolation of eight fictitious rain gauges randomly placed in the area. The hydrological response from tRIBS that is driven by these precipitation fields has been compared with the response of the model forced with NEXRAD precipitation. The analysis has been carried out assuming first simplified spatial distributions of soil characteristics and then the real soil-type distribution. Results have shown the dependence of the best rain gauges configuration for the estimation of runoff on the spatiotemporal characteristics of storm events and the soil-type distribution. [ABSTRACT FROM AUTHOR]

This paper explores the predicted hydrologic responses associated with the compounded error of cascading global circulation model (GCM) uncertainty through hydrologic model uncertainty due to climate change. A coupled groundwater and surface water flow model (GSFLOW) was used within the differential evolution adaptive metropolis (DREAM) uncertainty approach and combined with eight GCMs to investigate uncertainties in hydrologic predictions for three subbasins of varying hydrogeology within the Santiam River basin in Oregon, USA. Predictions of future hydrology in the Santiam River include increases in runoff in the fall and winter months and decreases in runoff for the spring and summer months. One-year peak flows were predicted to increase whereas 100-year peak flows were predicted to slightly decrease. The predicted 10-year 7-day low flow decreased in two subbasins with little groundwater influences but increased in another subbasin with substantial groundwater influences. Uncertainty in GCMs represented the majority of uncertainty in the analysis, accounting for an average deviation from the median of 66%. The uncertainty associated with use of GSFLOW produced only an 8% increase in the overall uncertainty of predicted responses compared to GCM uncertainty. This analysis demonstrates the value and limitations of cascading uncertainty from GCM use through uncertainty in the hydrologic model, offers insight into the interpretation and use of uncertainty estimates in water resources analysis, and illustrates the need for a fully nonstationary approach with respect to calibrating hydrologic models and transferring parameters across basins and time for climate change analyses. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The Lavras Simulation of Hydrology (LASH) hydrological model is classified as a deterministic, semiconceptual, and spatially distributed model. This model was developed to make available a tool for hydrological analysis in watersheds with a limited database, and it has presented good streamflow predictions. The aim of this study was to calibrate and validate the LASH model for hydrological simulation of the following watersheds which make up the headwaters of the Grande River basin (southern Minas Gerais state, Brazil): the Aiuruoca, Grande, Sapucaí, and Verde river basins. The LASH model simulated adequately the hydrological regimes of the previously mentioned watersheds, presenting satisfactory performances for all the watersheds, which can be emphasized by the Nash-Sutclifffe coefficient () values greater than 0.70. The analysis of the main hydrological processes simulated by the LASH model confirmed that the results were consistent with the hydrological characteristics observed on the respective watersheds. The simulated daily flow-duration curves demonstrated good agreement in relation to the observed curves, indicating only a few errors in estimation of extreme streamflow events. It was found that the LASH model can be applied for hydrological simulation of headwater watersheds situated in the Grande River basin under land-use scenarios and meteorological and environmental conditions other than the ones used in this study. Therefore, it can be considered an important tool for planning and management of water resources in this region. [ABSTRACT FROM AUTHOR]

We present an assessment of a framework to reduce computational expense required for hydrologic prediction over new domains. A common problem in computational hydrology arises when a hydrologist seeks to model a new domain and is subsequently required to estimate representative model parameters for that domain. Our focus is to extend previous development of the Multiscale Parameter Regionalization (MPR) technique, to a broader set of climatic regimes and spatial scales to demonstrate the utility of this approach. We hypothesize that this technique will be applicable for (1) improving predictions in ungauged basins, and (2) as a tool for upscaling high-fidelity hydrologic simulations closer to a general circulation model (GCM) scales, while appreciably reducing computational expense in parameter estimation. We transfer hydrologic model parameters from a single central European basin, to 80 candidate basins within the United States. The regionalization is further tested across a range of climatic and land-cover conditions to identify potential biases in transferability. The results indicate a high degree of success in transferring parameters from central Europe to North America. Parameter scaling from 1/8° up to 1° confirms that MPR can produce a set of quasi-scale independent parameters, with only modest differences in model performance across scales (<3%). Model skill generally decreases approximately 10-20% when transferring parameters toward alternate climatic and land-cover conditions. Finally, we show that the success of model parameter transfer is contingent upon soil, land-cover, and climatic regimes relative to those used during calibration, particularly going from high-to-low clay content and from dense-to-sparse forest. [ABSTRACT FROM AUTHOR]

Abstract: Two commonly used strategies in modeling snowmelt are the energy balance and temperature-index methods. Here we evaluate the distributed hydrologic impacts of these two different snowmelt modeling strategies, each in conjunction with a physics-based hydrologic model (PIHM). Results illustrate that both the Isnobal energy-balance and calibrated temperature-index methods adequately reproduce snow depletion at the observation site. However, the models exhibit marked differences in the distribution of snowmelt. When combined with PIHM, both models capture streamflow reasonably during calibration year (WY06), but Isnobal model gives better streamflow results in the validation year (WY07). The uncalibrated temperature-index model predicts streamflow poorly in both years. Differences between distributed snowmelt, as predicted by Isnobal and calibrated temperature-index method, and its consequent effect on predicted hydrologic states suggest the need to carefully calibrate temperature-index models in both time and space. Combined physics-based snow and hydrologic models provide the best accuracy, while a temperature-index model using coefficients from the literature the poorest. [Copyright &y& Elsevier]

Summary: A wide variety of approaches to hydrologic (rainfall–runoff) modeling of river basins confounds our ability to select, develop, and interpret models, particularly in the evaluation of prediction uncertainty associated with climate change assessment. To inform the model selection process, we characterized and compared three structurally-distinct approaches and spatial scales of parameterization to modeling catchment hydrology: a large-scale approach (using the VIC model; 671,000km2 area), a basin-scale approach (using the PRMS model; 29,700km2 area), and a site-specific approach (the GSFLOW model; 4700km2 area) forced by the same future climate estimates. For each approach, we present measures of fit to historic observations and predictions of future response, as well as estimates of model parameter uncertainty, when available. While the site-specific approach generally had the best fit to historic measurements, the performance of the model approaches varied. The site-specific approach generated the best fit at unregulated sites, the large scale approach performed best just downstream of flood control projects, and model performance varied at the farthest downstream sites where streamflow regulation is mitigated to some extent by unregulated tributaries and water diversions. These results illustrate how selection of a modeling approach and interpretation of climate change projections require (a) appropriate parameterization of the models for climate and hydrologic processes governing runoff generation in the area under study, (b) understanding and justifying the assumptions and limitations of the model, and (c) estimates of uncertainty associated with the modeling approach. [ABSTRACT FROM AUTHOR]

Hydrologic models often are applied to adjust projections of hydroclimatic change that come from climate models. Such adjustment includes climate-bias correction, spatial refinement (''downscaling''), and consideration of the roles of hydrologic processes that were neglected in the climate model. Described herein is a quantitative analysis of the effects of hydrologic adjustment on the projections of runoff change associated with projected twenty-first-century climate change. In a case study including three climate models and 10 river basins in the contiguous United States, the authors find that relative (i.e., fractional or percentage) runoff change computed with hydrologic adjustment more often than not was less positive (or, equivalently, more negative) than what was projected by the climate models. The dominant contributor to this decrease in runoff was a ubiquitous change in runoff (median −−11%%) caused by the hydrologic model''s apparent amplification of the climate-model-implied growth in potential evapotranspiration. Analysis suggests that the hydrologic model, on the basis of the empirical, temperature-based modified Jensen--Haise formula, calculates a change in potential evapotranspiration that is typically 3 times the change implied by the climate models, which explicitly track surface energy budgets. In comparison with the amplification of potential evapotranspiration, central tendencies of other contributions from hydrologic adjustment (spatial refinement, climate-bias adjustment, and process refinement) were relatively small. The authors'' findings highlight the need for caution when projecting changes in potential evapotranspiration for use in hydrologic models or drought indices to evaluate climate-change impacts on water. [ABSTRACT FROM AUTHOR]

Abstract: Discharge and suspended sediment flux are predicted for the 21st century for the 8km2 West River, Cape Bounty, Melville Island in the Canadian High Arctic. Discharge predictions are made using a distributed hydrologic model, and sediment yields are predicted using a rating curve based on monitored relationships between discharge and suspended sediment concentration. Models were forced using statistically downscaled air temperature and precipitation from the A1b and A2 scenarios from the global climate model CGCM3. Under the A2 scenario, total seasonal runoff is expected to double by 2100, daily maximum discharge rates will double, and the melt season will increase in length by 30days, mostly in autumn. Sediment yield increases will be much more extreme, and are expected to increase by 100 to 600%, but these are almost certainly minimum estimates. Variability between and within global climate models is assessed for the grid cell closest to Cape Bounty, and variability within CGCM3 is assessed by examining data from five of its runs. Intra-model variability is relatively small, but inter-model variability is large. The impact of this variability is minimized, and the applicability of results is broadened by assessing relationships between weather variables, hydrologic variables, and sediment yield for multiple model runs. [Copyright &y& Elsevier]

In this study, an experimental 12-h lead-time flood forecasting methodology that combines the fifth generation mesoscale model (MM5) of the U.S. National Center of Atmospheric Research with the physically based, spatially distributed watershed environmental hydrology (WEHY) model is described and applied to the Shiobara Dam watershed in Japan in order to explore its utility. The Shiobara-Dam watershed is a mountainous steep-sloped watershed that has an area of 123 km2. Meanwhile, the routine atmospheric assimilation data that are provided by the Japan Meteorological Agency (JMA) over Japan, have spatial resolution of 20 km and are at 12-h time intervals. In order to utilize the JMA’s atmospheric data at 12-h intervals as initial and boundary conditions for 12-h lead-time hourly precipitation forecast inputs to the WEHY model of Shiobara-Dam watershed for runoff forecasts, the MM5 nonhydrostatic atmospheric forecast model was chosen and nested inside the JMA’s data domain. The JMA’s atmospheric data were used as initial and boundary conditions for MM5 which then produced detailed forecasted precipitation fields for the WEHY model of Shiobara-Dam watershed for its hourly runoff forecasts for a 12-h lead time. The results of an application of this forecasting scheme to a 48-h rainfall-runoff event over Shiobara-Dam watershed are presented and discussed. [ABSTRACT FROM AUTHOR]

Summary: The physically-based surface–subsurface HydroGeoSphere model is used to examine the hydrologic budget of the 286.6km2 Duffins Creek watershed, located 10km northeast of metropolitan Toronto. The primary objective of this study is to demonstrate the utility of the model to simulate the three-dimensional hydrologic response of the surface and subsurface flow systems in a large-scale watershed driven by multi-season precipitation events. The hydrologic model was calibrated to a consecutive sequence of hydrographs resulting from all precipitation events between the months of April and December 1986, while hydrographs from 1987 were used to test the model’s ability for prediction. Results demonstrate that a physically-based modeling approach which treats the surface and subsurface flow systems as an integrated continuum can capture the dynamic response of a large heterogeneous watershed as driven by transient precipitation events over a multi-season period. It was also revealed that full coupling of plant transpiration and surface–subsurface evaporation processes into the governing flow equations was critical for the successful calibration of the hydrographs. However, the ability of the model to predict the shape of individual hydrographs in the following year, during which the annual average precipitation rate decreased significantly, was diminished even though the annual average stream flows were closely replicated. We identify a number of data gaps that contribute to the decline in the predictive capacity of the model, including difficulty in establishing an appropriate initial condition, vertical mesh refinement issues within the root zone, and the reliance on a largely empirical relationship that distributes the net capacity for plant transpiration among various factors that may change from one year to the next. [Copyright &y& Elsevier]

Hydrologic modelling techniques may help to improve the representation and functioning of interactions between different factors that exist in watersheds. Geographic information systems (GIS) provide such models with data that need to be structured in adequate form (layers and databases). This paper presents an investigation of the hydrologic balance relating to the large Macta watershed located in the north-west region of Algeria using the SWAT hydrologic model and ArcView GIS software. The Macta watershed was selected to have the capacity for significant adaptation of the SWAT model and to test the possibilities offered by this model, which takes into account the main factors that determine the hydrologic balance. Its implementation requires a database to be built for its calibration and validation. The SWAT model is calibrated for the case study and some results are presented in this paper. It seems herein that the model reproduces the parameters of climate, water balance and stream flow. The obtained results show a good correlation between simulated and observed variables for the adopted model. The model offers interesting scenarios for comprehension and simulation of phenomena at a watershed scale, which are a decision-making aid for water resources management. [ABSTRACT FROM AUTHOR]

Summary: The Hydrologic Simulation Program – Fortran (HSPF) was applied to the Illinois River Basin using the U.S. Environmental Protection Agency’s (USEPA) Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) system. Values of the HSPF model parameters were based on the calibrations of three representative watersheds within the basin. Over the 1985–1995 simulation period, monthly and annual mass balances correlated well with observed discharges at three gaging stations along the Illinois River. However, poor correlation of daily flows was due largely to the weakness of the HSPF model in routing dynamic flows through the complicated Illinois River system. To address this problem, a one-dimensional unsteady state flow model (UNET) developed for the main stem of the Illinois River was coupled with the HSPF model to perform the flow routing. Comparison of hydrographs showed much closer correlation between coupled HSPF–UNET model simulations of daily flows and observed flow hydrographs. This study also showed that peak flows simulated by the HSPF model occurred several days before the actual observations. However, the coupled HSPF–UNET model simulated peak flow time more closely to the observations. The Nash-Sutcliffe efficiency (NSE) computed using observed and simulated daily flows from HSPF and HSPF–UNET models was 0.72 and 0.79 at Marseilles, 0.63 and 0.82 at Kingston Mines, and 0.40 and 0.85 at Valley City, respectively. As expected, the NSE computed using mean monthly flows was also slightly better from HSPF–UNET than from HSPF, but the annual NSE values were nearly same from both models. [Copyright &y& Elsevier]

Abstract: An object-oriented design (OOD) approach is used to describe watershed scale hydrologic processes. Individual objects (or processes) at multiple levels are described using the ‘inheritance’ concept, while the interactions of objects (or processes) are described using the ‘aggregation’ concept. This design methodology is applied to create the new watershed based hydrological model OBJTOP (OBJect oriented, TOPographic based model). In OBJTOP, the watershed (top level object) is composed of five sub-objects: precipitation, evapotranspiration, vegetation, soil and channel. These objects are further subdivided, such as soil into four sub-objects: surface, and root, unsaturated and saturated zones. Each sub-object, designed using the inheritance concept, has its own distinct attributes and behaviors and works independently to represent different individual processes such as soil processes, channel processes, etc. The sub-objects, designed using the aggregation principle, are interconnected and interact with each other within the higher level objects and thus constitute the hydrological process simulation. OBJTOP presents a description of hydrologic processes in a direct and concise manner. OBJTOP''s model structure should benefit model coding, maintenance, and future modification efforts, and therefore the program design strategies should be of interest to other program designers. [Copyright &y& Elsevier]

We constructed a hydrologic model to estimate the groundwater recharge rate for alluvial aquifers of the Eastern Desert from sporadic precipitation over the Red Sea hills. To estimate initial losses over sub-basins, transmission losses through channel routing, and downstream runoff, we developed an integrated model combining spatial rainfall distribution, an appropriate basin unit hydrograph, and appropriate infiltration parameters. Watersheds and stream networks identified from digital terrain elevation data were verified by comparison with co-registered Landsat thematic mapper scenes and geologic maps. Records of a November 1994 storm event acquired from rain gauges along the Nile River and the Red Sea shore were used to generate a spatial precipitation distribution for the study area. A 2 hour design hyetograph was adopted from rain gauge data for the 1994 flood event. The model was tested against records from the November 1994 flood event at the outlets of the Tarfa and Hammamat watersheds.Groundwater recharge rates were estimated for the alluvial aquifers within the major watersheds of the north Eastern Desert. We estimated that during the 1994 flood event, the ground water recharge through transmission losses ranged from 21 to 31% (Tarfa: 15.8×106 m3; Asyuti: 20×106 m3, Qena: 49×106 m3, Hammamat: 59×106 m3) of the precipitated volume. The initial losses ranged from 65 to 77%. Only 3–7% of the precipitation reached the watershed outlets. Archival data show that rainfall events of the size of the November 1994 storm or larger occur every 40 months; thus, the annual recharge rates for the Tarfa, Asyuti, Qena, and Hammamat alluvial aquifers are estimated at 4.7×106 m3, 6×106 m3, 14.7×106 m3, and 17.7×106 m3, respectively. Implications for the use of these renewable ground waters and similar water resources in other arid areas of Egypt and in neighboring countries are clear. [Copyright &y& Elsevier]