Dam construction impacts on multiscale characterization of sediment discharge in two typical karst watersheds of southwest China J. Hydrol. (IF 3.483) Pub Date : 2018-01-16 Zhenwei Li, Xianli Xu, Chaohao Xu, Meixian Liu, Kelin Wang
Optimal Spatio-temporal Design of Water Quality Monitoring Networks for Reservoirs: Application of the Concept of Value of Information J. Hydrol. (IF 3.483) Pub Date : 2018-01-16 Nahal Maymandi, Reza Kerachian, Mohammad Reza Nikoo
This paper presents a new methodology for optimizing WQM networks of reservoirs and lakes using the concept of the value of information (VOI) and utilizing results of a calibrated numerical water quality simulation model. With reference to the value of information theory, water quality of every checkpoint with a specific prior probability differs in time. After analyzing water quality samples taken from potential monitoring points, the posterior probabilities are updated using the Baye's theorem, and VOI of the samples is calculated. In the next step, the stations with maximum VOI is selected as optimal stations. This Process is repeated for each sampling interval to obtain optimal monitoring network locations for each interval. The results of the proposed VOI-based methodology is compared with those obtained using an entropy theoretic approach. As the results of the two methodologies would be partially different, in the next step, the results are combined using a weighting method. Finally, the optimal sampling interval and location of WQM stations are chosen using the Evidential Reasoning (ER) decision making method. The efficiency and applicability of the methodology are evaluated using available water quantity and quality data of the Karkheh Reservoir in the southwestern part of Iran.
Assessing Cumulative Impacts of the Proposed Lower Mekong Basin Hydropower Cascade on the Mekong River Floodplains and Delta – Overview of Integrated Modeling Methods and Results J. Hydrol. (IF 3.483) Pub Date : 2018-01-13 Le Duc Trung, Nguyen Anh Duc, Linh Thu Nguyen, Tran Hong Thai, Anwar Khan, Kurt Rautenstrauch, Cheryl Schmidt
Approach, methods, and results from a comprehensive integrated water resources modeling framework for the Lower Mekong Basin (LMB) are presented in this paper. The modeling suite was specifically tailored to the known conditions and data availability at key locations within the LMB and more particularly within the floodplains of Cambodia and the Mekong River Delta of Vietnam. Model simulation output was used to project cumulative changes to hydraulic, sediment, and water quality parameters likely to occur in this relatively unique system under multiple scenarios of hydropower development in the LMB. While substantial changes in river flow regimes are predicted as a result of hydropeaking operations especially when combined with dry-season drawdowns to maximize power production, the multiple-scenario analysis indicated that overall, the largest changes are expected to be in loss of sediment and nutrient transport and reduction of water quality due to increased salinity intrusion into areas of the Mekong Delta.
Influence of meteorological variables on rainfall partitioning for deciduous and coniferous tree species in urban area J. Hydrol. (IF 3.483) Pub Date : 2018-01-13 Katarina Zabret, Jože Rakovec, Mojca Šraj
Rainfall partitioning is an important part of the ecohydrological cycle, influenced by numerous variables. Rainfall partitioning for pine (Pinus nigra Arnold) and birch (Betula pendula Roth.) trees was measured from January 2014 to June 2017 in an urban area of Ljubljana, Slovenia. 180 events from more than three years of observations were analyzed, focusing on 13 meteorological variables, including the number of raindrops, their diameter, and velocity. Regression tree and boosted regression tree analyses were performed to evaluate the influence of the variables on rainfall interception loss, throughfall, and stemflow in different phenoseasons. The amount of rainfall was recognized as the most influential variable, followed by rainfall intensity and the number of raindrops. Higher rainfall amount, intensity, and the number of drops decreased percentage of rainfall interception loss. Rainfall amount and intensity were the most influential on interception loss by birch and pine trees during the leafed and leafless periods, respectively. Lower wind speed was found to increase throughfall, whereas wind direction had no significant influence. Consideration of drop size spectrum properties proved to be important, since the number of drops, drop diameter, and median volume diameter were often recognized as important influential variables.
Using solute and heat tracers for aquifer characterization in a strongly heterogeneous alluvial aquifer J. Hydrol. (IF 3.483) Pub Date : 2018-01-13 Theo S. Sarris, Murray Close, Phillip Abraham
A test using Rhodamine WT and heat as tracers, conducted over a 78 day period in a strongly heterogeneous alluvial aquifer, was used to evaluate the utility of the combined observation dataset for aquifer characterization. A highly parameterized model was inverted, with concentration and temperature time-series as calibration targets. Groundwater heads recorded during the experiment were boundary dependent and were ignored during the inversion process. The inverted model produced a high resolution depiction of the hydraulic conductivity and porosity fields. Statistical properties of these fields are in very good agreement with estimates from previous studies at the site. Spatially distributed sensitivity analysis suggests that both solute and heat transport were most sensitive to the hydraulic conductivity and porosity fields and less sensitive to dispersivity and thermal distribution factor, with sensitivity to porosity greatly reducing outside the monitored area. The issues of model over-parameterization and non-uniqueness are addressed through identifiability analysis. Longitudinal dispersivity and thermal distribution factor are highly identifiable, however spatially distributed parameters are only identifiable near the injection point. Temperature related density effects became observable for both heat and solute, as temperature increased above 12 centigrade, and affected down gradient propagation. Finally we demonstrate that high frequency and spatially dense temperature data cannot inform a dual porosity model in the absence of frequent solute concentration measurements.
Carbon dioxide degassing at the groundwater-stream-atmosphere interface: isotopic equilibration and hydrological mass balance in a sandy watershed J. Hydrol. (IF 3.483) Pub Date : 2018-01-12 Loris Deirmendjian, Gwenaël Abril
Streams and rivers emit significant amounts of CO2 and constitute a preferential pathway of carbon transport from terrestrial ecosystems to the atmosphere. However, the estimation of CO2 degassing based on the water-air CO2 gradient, gas transfer velocity and stream surface area is subject to large uncertainties. Furthermore, the stable isotope signature of dissolved inorganic carbon (δ13C-DIC) in streams is strongly impacted by gas exchange, which makes it a useful tracer of CO2 degassing under specific conditions. For this study, we characterized the annual transfers of dissolved inorganic carbon (DIC) along the groundwater-stream-river continuum based on dissolved inorganic carbon (DIC) concentrations, stable isotope composition and measurements of stream discharges. We selected a homogeneous, forested and sandy lowland watershed (Leyre River) as a study site, where the hydrology occurs almost exclusively through drainage of shallow groundwater (no surface runoff). We observed the first general spatial pattern of decreases in pCO2 and DIC and an increase in δ13C-DIC from groundwater to stream orders 1 and 2, which was due to the experimentally verified faster degassing of groundwater 12C-DIC compared to 13C-DIC. This downstream enrichment in 13C-DIC could be modelled by simply considering the isotopic equilibration of groundwater-derived DIC with the atmosphere during CO2 degassing. A second spatial pattern occurred between stream orders 2 and 4, consisting of an increase in the proportion of carbonate alkalinity to the DIC accompanied by the enrichment of 13C in the stream DIC, which was due to the occurrence of carbonate rock weathering downstream. We could separate the contribution of these two processes (gas exchange and carbonate weathering) in the stable isotope budget of the river network. Thereafter, we built a hydrological mass balance based on drainages and the relative contribution of groundwater in streams of increasing order. After combining with the dissolved CO2 concentrations, we quantified CO2 degassing for each stream order for the whole watershed. Approximately 75% of the total CO2 degassing from the watershed occurred in first- and second-order streams. Furthermore, from stream order 2 to 4, our CO2 degassing fluxes compared well with those based on stream hydraulic geometry, water pCO2, gas transfer velocity, and stream surface area. In first-order streams, however, our approach showed CO2 fluxes that were twice as large, suggesting that a fraction of degassing occurred as hotspots in the vicinity of groundwater resurgence and was missed by conventional stream sampling.
Assessment of flood susceptible areas using spatially explicit, probabilistic multi-criteria decision analysis J. Hydrol. (IF 3.483) Pub Date : 2018-01-12 Zhongqian Tang, Hua Zhang, Shanzhen Yi, Yangfan Xiao
GIS-based multi-criteria decision analysis (MCDA) is increasingly used to support flood risk assessment. However, conventional GIS-MCDA methods fail to adequately represent spatial variability and are accompanied with considerable uncertainty. It is, thus, important to incorporate spatial variability and uncertainty into GIS-based decision analysis procedures. This research develops a spatially explicit, probabilistic GIS-MCDA approach for the delineation of potentially flood susceptible areas. The approach integrates the probabilistic and the local ordered weighted averaging (OWA) methods via Monte Carlo simulation, to take into account the uncertainty related to criteria weights, spatial heterogeneity of preferences and the risk attitude of the analyst. The approach is applied to a pilot study for the Gucheng County, central China, heavily affected by the hazardous 2012 flood. A GIS database of six geomorphological and hydrometeorological factors for the evaluation of susceptibility was created. Moreover, uncertainty and sensitivity analysis were performed to investigate the robustness of the model. The results indicate that the ensemble method improves the robustness of the model outcomes with respect to variation in criteria weights and identifies which criteria weights are most responsible for the variability of model outcomes. Therefore, the proposed approach is an improvement over the conventional deterministic method and can provides a more rational, objective and unbiased tool for flood susceptibility evaluation.
Impacts of Mesopotamian wetland re-flooding on the lipid biomarker distributions in sediments J. Hydrol. (IF 3.483) Pub Date : 2018-01-12 Ahmed I. Rushdi, Ali A.Z. DouAbul, Sama S. Al-Maarofi, Bernd R.T. Simoneit
An ensemble-based dynamic Bayesian averaging approach for discharge simulations using multiple global precipitation products and hydrological models J. Hydrol. (IF 3.483) Pub Date : 2018-01-11 Wei Qi, Junguo Liu, Hong Yang, Chris Sweetapple
Global precipitation products are very important datasets in flow simulations, especially in poorly gauged regions. Uncertainties resulting from precipitation products, hydrological models and their combinations vary with time and data magnitude, and undermine their application to flow simulations. However, previous studies have not quantified these uncertainties individually and explicitly. This study developed an ensemble-based dynamic Bayesian averaging approach (e-Bay) for deterministic discharge simulations using multiple global precipitation products and hydrological models. In this approach, the joint probability of precipitation products and hydrological models being correct is quantified based on uncertainties in maximum and mean estimation, posterior probability is quantified as functions of the magnitude and timing of discharges, and the law of total probability is implemented to calculate expected discharges. Six global fine-resolution precipitation products and two hydrological models of different complexities are included in an illustrative application. e-Bay can effectively quantify uncertainties and therefore generate better deterministic discharges than traditional approaches (weighted average methods with equal and varying weights and maximum likelihood approach). The mean Nash-Sutcliffe Efficiency values of e-Bay are up to 0.97 and 0.85 in training and validation periods respectively, which are at least 0.06 and 0.13 higher than traditional approaches. In addition, with increased training data, assessment criteria values of e-Bay show smaller fluctuations than traditional approaches and its performance becomes outstanding. The proposed e-Bay approach bridges the gap between global precipitation products and their pragmatic applications to discharge simulations, and is beneficial to water resources management in ungauged or poorly gauged regions across the world.
Fill and spill drives runoff connectivity over frozen ground J. Hydrol. (IF 3.483) Pub Date : 2018-01-11 A.E. Coles, J.J. McDonnell
Snowmelt-runoff processes on frozen ground are poorly understood at the hillslope scale. This is especially true for hillslopes on the northern Great Plains of North America where long periods of snow-covered frozen ground with very shallow slopes mask any spatial patterns and process controls on connectivity and hillslope runoff generation. This study examines a 4.66 ha (46,600 m2) hillslope on the northern Great Plains during the 2014 spring snowmelt season to explore hillslope runoff processes. Specifically, we explore the spatial patterns of runoff production source areas and examine how surface topography and patterns of snow cover, snow water equivalent, soil water content, and thawed layer depth – which we measured on a 10 m grid across our 46,600 m2 hillslope – affect melt water partitioning and runoff connectivity. A key question was whether or not the controls on connectivity are consistent with the fill and spill mechanism found in rain-dominated and unfrozen soil domains. The contrast between the slow infiltration rates into frozen soil and the relatively fast rates of snowmelt delivery to the soil surface resulted in water accumulation in small depressions under the snowpack. Consequently, infiltration was minimal over the 12 day melt period. Instead, nested filling of micro- and meso-depressions was followed by macro-scale, whole-slope spilling. This spilling occurred when large patches of ponded water exceeded the storage capacity behind downslope micro barriers in the surface topography, and flows from them coalesced to drive a rapid increase in runoff at the hillslope outlet. These observations of ponded water and flowpaths followed mapable fill and spill locations based on 2 m resolution digital topographic analysis. Interestingly, while surface topography is relatively unimportant under unfrozen conditions at our site because of low relief and high infiltrability, surface topography shows episodically critical importance for connectivity and runoff generation when the ground is frozen.
Greenhouse gas scenario sensitivity and uncertainties in precipitation projections for central Belgium J. Hydrol. (IF 3.483) Pub Date : 2018-01-10 E. Van Uytven, P. Willems
Climate change impact assessment on meteorological variables involves large uncertainties as a result of incomplete knowledge on the future greenhouse gas concentrations and climate model physics, next to the inherent internal variability of the climate system. Given that the alteration in greenhouse gas concentrations is the driver for the change, one expects the impacts to be highly dependent on the considered greenhouse gas scenario (GHS). In this study, we denote this behavior as GHS sensitivity. Due to the climate model related uncertainties, this sensitivity is, at local scale, not always that strong as expected. This paper aims to study the GHS sensitivity and its contributing role to climate scenarios for a case study in Belgium. An ensemble of 160 CMIP5 climate model runs is considered and climate change signals are studied for precipitation accumulation, daily precipitation intensities and wet day frequencies. This was done for the different seasons of the year and the scenario periods 2011-2040, 2031-2060, 2051-2081 and 2071-2100. By means of variance decomposition, the total variance in the climate change signals was separated in the contribution of the differences in GHSs and the other model-related uncertainty sources. These contributions were found dependent on the variable and season. Following the time of emergence concept, the GHS uncertainty contribution is found dependent on the time horizon and increases over time. For the most distinct time horizon (2071-2100), the climate model uncertainty accounts for the largest uncertainty contribution. The GHS differences explain up to 18% of the total variance in the climate change signals. The results point further at the importance of the climate model ensemble design, specifically the ensemble size and the combination of climate models, whereupon climate scenarios are based. The numerical noise, introduced at scales smaller than the skillful scale, e.g. at local scale, was not considered in this study.
Effects of horizontal grid resolution on evapotranspiration partitioning using TerrSysMP J. Hydrol. (IF 3.483) Pub Date : 2018-01-10 P. Shrestha, M. Sulis, C. Simmer, S. Kollet
Biotic leaf transpiration (T) and abiotic evaporation (E) are the two major pathways by which water is transferred from land surfaces to the atmosphere. Earth system models simulating the terrestrial water, carbon and energy cycle are required to reliably embed the role of soil and vegetation processes in order to realistically reproduce both fluxes including their relative contributions to total evapotranspiration (ET). Earth system models are also being used with increasing spatial resolutions to better simulate the effects of surface heterogeneity on the regional water and energy cycle and to realistically include effects of subsurface lateral flow paths, which are expected to feed back on the exchange fluxes and their partitioning in the model. Using the hydrological component of the Terrestrial Systems Modeling Platform (TerrSysMP), we examine the uncertainty in the estimates of T/ET ratio due to horizontal model grid resolution for a dry and wet year in the Inde catchment (western Germany). The aggregation of topography results in smoothing of slope magnitudes and the filtering of small-scale convergence and divergence zones, which directly impacts the surface-subsurface flow. Coarsening of the grid resolution from 120 m to 960 m increased the available soil moisture for ground evaporation, and decreased T/ET ratio by about 5% and 8% for dry and wet year respectively. The change in T/ET ratio was more pronounced for agricultural crops compared to forested areas, indicating a strong local control of vegetation on the ground evaporation, affecting the domain average statistics.
Coupled prediction of flash flood response and debris flow occurrence: application on an alpine extreme flood event J. Hydrol. (IF 3.483) Pub Date : 2018-01-10 Elisa Destro, William Amponsah, Efthymios I. Nikolopoulos, Lorenzo Marchi, Francesco Marra, Davide Zoccatelli, Marco Borga
The concurrence of flash floods and debris flows is of particular concern, because it may amplify the hazard corresponding to the individual generative processes. This paper presents a coupled modelling framework for the predictions of flash flood response and of the occurrence of debris flows initiated by channel bed mobilization. The framework combines a spatially distributed flash flood response model and a debris flow initiation model to define a threshold value for the peak flow which permits identification of channelized debris flow initiation. The threshold is defined over the channel network as a function of the upslope area and of the local channel bed slope, and it is based on assumptions concerning the properties of the channel bed material and of the morphology of the channel network. The model is validated using data from an extreme rainstorm that impacted the 140 km2 Vizze basin in the Eastern Italian Alps on August 4-5, 2012. The results show that the proposed methodology has improved skill in identifying the catchments where debris-flows are triggered, compared to the use of simpler thresholds based on rainfall properties.
An adaptive middle and long-term runoff forecast model using EEMD-ANN hybrid approach J. Hydrol. (IF 3.483) Pub Date : 2018-01-10 Qiao-feng Tan, Xiao-hui Lei, Xu Wang, Hao Wang, Xin Wen, Yi Ji, Ai-qin Kang
It remains a challenge to obtain an accurate middle and long-term runoff forecast, especially in flood seasons. The forecast performance can be improved using ensemble empirical mode decomposition (EEMD) to produce cleaner signals as model inputs. In many EEMD based forecast models, the entire time series are decomposed into several sub-series, and each sub-series is divided into calibration and validation datasets and forecasted by some common models, such as artificial neural network (ANN), and finally an ensemble forecast is obtained by summing the forecasted results of each sub-series. In such a decomposition-ensemble framework, some future information is used, and thus it is a hindcast experiment. Attempts have also been made to propose a real forecast experiment, which, however, often can not be able to adapt to the non-stationary changes in runoff due to the lack of adaptive ability. Therefore, this study tries to improve the decomposition-ensemble framework and propose an adaptive middle and long-term runoff forecast model especially for flood seasons. Unlike a hindcast experiment, it does not use any future information; and unlike conventional forecast experiments, its decomposition and forecast models are adjusted adaptively as long as new runoff information is added. EEMD is used to decompose the original time series and ANN is used to forecast each sub-series, hence the name an adaptive EEMD-ANN (AEEMD-ANN) model. This model is applied to forecast the 1-month ahead streamflow of three stations in China, and the results show that the AEEMD-ANN model can improve forecast accuracy in flood seasons, but it is not as good as ANN, adaptive neuro-fuzzy inference system (ANFIS), support vector machine (SVM) and seasonal first-order autoregressive (SAR (1)) models in dry seasons. While the conventional forecast models, especially the SAR (1) models, are more suitable in dry season. Therefore, it is recommended to use SAR (1) model in dry season and AEEMD-ANN model in flood season to forecast the monthly runoff in Yangtze River Basin.
Role of slope on infiltration: a review J. Hydrol. (IF 3.483) Pub Date : 2018-01-10 Renato Morbidelli, Carla Saltalippi, Alessia Flammini, Rao S. Govindaraju
Partitioning of rainfall at the soil-atmosphere interface is important for both surface and subsurface hydrology, and influences many events of major hydrologic interest such as runoff generation, aquifer recharge, and transport of pollutants in surface waters as well as the vadose zone. This partitioning is achieved through the process of infiltration that has been widely investigated at the local scale, and more recently also at the field scale, by models that were designed for horizontal surfaces. However, infiltration, overland flows, and deep flows in most real situations are generated by rainfall over sloping surfaces that bring in additional effects. Therefore, existing models for local infiltration into homogeneous and layered soils and those as for field-scale infiltration, have to be adapted to account for the effects of surface slope. Various studies have investigated the role of surface slope on infiltration based on a theoretical formulations for the dynamics of infiltration, extensions of the Green-Ampt approach, and from laboratory and field experiments. However, conflicting results have been reported in the scientific literature on the role of surface slope on infiltration. We summarize the salient points from previous studies and provide plausible reasons for discrepancies in conclusions of previous authors, thus leading to a critical assessment of the current state of our understanding on this subject. We offer suggestions for future efforts to advance our knowledge of infiltration over sloping surfaces.
Evaluation of uncertainty in capturing the spatial variability and magnitudes of extreme hydrological events for the uMngeni catchment, South Africa J. Hydrol. (IF 3.483) Pub Date : 2018-01-10 Samuel Kusangaya, Michele L. Warburton, Emma Archer van Garderen
Downscaled General Circulation Models (GCMs) data are used to forecast climate change and provide information used as input for hydrological modelling. Given that our understanding of climate change points towards an increasing frequency, timing and intensity of extreme hydrological events, there is therefore the need to assess the ability of downscaled GCMs to capture these extreme hydrological events. Extreme hydrological events play a significant role in regulating the structure and function of rivers and associated ecosystems. In this study, the Indicators of Hydrologic Alteration (IHA) method was adapted to assess the ability of simulated streamflow (using downscaled GCMs (dGCMs)) in capturing extreme river dynamics (high and low flows), as compared to streamflow simulated using historical climate data from 1960-2000. The ACRU hydrological model was used for simulating streamflow for the 13 water management units of the uMngeni Catchment, South Africa. Statistically downscaled climate models obtained from the Climate System Analysis Group at the University of Cape Town were used as input for the ACRU Model. Results indicated that, high flows and extreme high flows (one in ten year high flows / large flood events) were poorly represented both in terms of timing, frequency and magnitude. Simulated streamflow using dGCMs data also captures more low flows and extreme low flows (one in ten year lowest flows) than that captured in streamflow simulated using historical climate data. The overall conclusion was that although dGCMs data can reasonably be used to simulate overall streamflow, it performs poorly when simulating extreme high and low flows. Streamflow simulation from dGCMs must thus be used with caution in hydrological applications, particularly for design hydrology, as extreme high and low flows are still poorly represented. This, arguably calls for the further improvement of downscaling techniques in order to generate climate data more relevant and useful for hydrological applications such as in design hydrology. Nevertheless, the availability of downscaled climatic data provide the potential of exploring climate model uncertainties in different hydro climatic regions at local scales where forcing data is often less accessible but more accurate at finer spatial scales and with adequate spatial detail.
A Two-Dimensional Transient Analytical Solution for a Ponded Ditch Drainage System under the Influence of Source/Sink J. Hydrol. (IF 3.483) Pub Date : 2018-01-09 Ratan Sarmah, Shubham Tiwari
An analytical solution is developed for predicting two-dimensional transient seepage into ditch drainage network receiving water from a non-uniform steady ponding field from the surface of the soil under the influence of source/sink in the flow domain. The flow domain is assumed to be saturated, homogeneous and anisotropic in nature and have finite extends in horizontal and vertical directions. The drains are assumed to be standing vertical and penetrating up to impervious layer. The water levels in the drains are unequal and invariant with time. The flow field is also assumed to be under the continuous influence of time-space dependent arbitrary source/sink term. The correctness of the proposed model is checked by developing a numerical code and also with the existing analytical solution for the simplified case. The study highlights the significance of source/sink influence in the subsurface flow. With the imposition of the source and sink term in the flow domain, the pathline and travel time of water particles started deviating from their original position and above that the side and top discharge to the drains are also observed to have a strong influence of the source/sink terms. The travel time and pathline of water particles are also observed to have a dependency on the height of water in the ditches and on the location of source/sink activation area.
Footprint radius of a cosmic-ray neutron probe for measuring soil-water content and its spatiotemporal variability in an alpine meadow ecosystem J. Hydrol. (IF 3.483) Pub Date : 2018-01-09 Xuchao Zhu, Ruixue Cao, Mingan Shao, Yin Liang
Cosmic-ray neutron probes (CRNPs) have footprint radii for measuring soil-water content (SWC). The theoretical radius is much larger at high altitude, such as the northern Tibetan Plateau, than the radius at sea level. The most probable practical radius of CRNPs for the northern Tibetan Plateau, however, is not known due to the lack of SWC data in this hostile environment. We calculated the theoretical footprint of the CRNP based on a recent simulation and analyzed the practical radius of a CRNP for the northern Tibetan Plateau by measuring SWC at 113 sampling locations on 21 measuring occasions to a depth of 30 cm in a 33.5 ha plot in an alpine meadow at 4600 m a.s.l. The temporal variability and spatial heterogeneity of SWC within the footprint were then analyzed. The theoretical footprint radius was between 360 and 420 m after accounting for the influences of air humidity, soil moisture, vegetation and air pressure. A comparison of SWCs measured by the CRNP and a neutron probe from access tubes in circles with different radii conservatively indicated that the most probable experimental footprint radius was >200 m. SWC within the CRNP footprint was moderately variable over both time and space, but the temporal variability was higher. Spatial heterogeneity was weak, but should be considered in future CRNP calibrations. This study provided theoretical and practical bases for the application and promotion of CRNPs in alpine meadows on the Tibetan Plateau.
Hydrologic model calibration using remotely sensed soil moisture and discharge measurements: the impact on predictions at gauged and ungauged locations J. Hydrol. (IF 3.483) Pub Date : 2018-01-09 Yuan Li, Stefania Grimaldi, Valentijn R.N. Pauwels, Jeffrey P. Walker
The skill of hydrologic models, such as those used in operational flood prediction, is currently restricted by the availability of flow gauges and by the quality of the streamflow data used for calibration. The increased availability of remote sensing products provides the opportunity to further improve the model forecasting skill. A joint calibration scheme using streamflow measurements and remote sensing derived soil moisture values was examined and compared with a streamflow only calibration scheme. The efficacy of the two calibration schemes was tested in three modelling setups: 1) a lumped model; 2) a semi-distributed model with only the outlet gauge available for calibration; and 3) a semi-distributed model with multiple gauges available for calibration. The joint calibration scheme was found to slightly degrade the streamflow prediction at gauged sites during the calibration period compared with streamflow only calibration, but improvement was found at the same gauged sites during the independent validation period. A more consistent and statistically significant improvement was achieved at gauged sites not used in the calibration, due to the spatial information introduced by the remotely sensed soil moisture data. It was also found that the impact of using soil moisture for calibration tended to be stronger at the upstream and tributary sub-catchments than at the downstream sub-catchments.
Experimental study on the artificial recharge of semiconfined aquifers involved in deep excavation engineering J. Hydrol. (IF 3.483) Pub Date : 2018-01-09 G. Zheng, J.R. Cao, X.S. Cheng, D. Ha, F.J. Wang
Artificial recharge measures have been adopted to control the drawdown of confined aquifers and the ground subsidence caused by dewatering during deep excavation in Tianjin, Shanghai and other regions in China. However, research on recharge theory is still limited. Additionally, confined aquifers consisting of silt and silty sand in Tianjin have lower hydraulic conductivities than those consisting of sand or gravel, and the feasibility and effectiveness of recharge methods in these semiconfined aquifers urgently require investigation. A series of single-well and multiwell pumping and recharge tests was conducted at a metro station excavation site in Tianjin. The test results showed that it was feasible to recharge silt and silty sand semiconfined aquifers, and, to a certain extent, the hydrogeological parameters obtained from the pumping tests could be used to predict the water level rise during single-well recharge. However, the predicted results underestimated the water level rise near the recharge well (within 7 m) by approximately 10-25%, likely because the permeability coefficient around the well was reduced during the recharge process. Pressured recharge significantly improved the efficiency of the recharge process. Maintaining the recharge and pumping rates at a nearly equal level effectively controlled the surrounding surface and building settlement. However, the surrounding surface subsidence tended to rapidly develop when recharge stopped. Therefore, the recharge process should continue and gradually stop after the pumping stops. The twin-well combined recharge technique can be used to control the head loss of an aquifer when one of the recharge wells requires pumping to solve the associated clogging problems.
Investigation clogging dynamic of permeable pavement systems using embedded sensors J. Hydrol. (IF 3.483) Pub Date : 2018-01-09 Mostafa Razzaghmanesh, Michael Borst
Permeable pavement is a stormwater control measure commonly selected in both new and retrofit applications. However, there is limited information about the clogging mechanism of these systems that effects the infiltration. A permeable pavement site located at the Seitz Elementary School, on Fort Riley, Kansas was selected for this study. An 80-space parking lot was built behind the school as part of an EPA collaboration with the U.S. Army. The parking lot design includes a permeable interlocking concrete pavement section along the downgradient edge. This study monitored the clogging progress of the pavement section using twelve water content reflectometers and three buried tipping bucket rain gauges. This clogging dynamic investigation was divided into three stages namely pre-clogged, transitional, and clogged. Recorded initial relative water content of all three stages were significantly and negatively correlated to antecedent dry weather periods with stronger correlations during clogged conditions. The peak relative water content correlation with peak rainfall 10-min intensity was significant for the water content reflectometers located on the western edge away from the eastern edge; this correlation was strongest during transition stage. Once clogged, rainfall measurements no longer correlated with the buried tipping bucket rain gauges. Both water content reflectometers and buried tipping bucket rain gauges showed the progress of surface clogging. For every 6mm of rain, clogging advanced 1 mm across the surface. The results generally support the hypothesis that the clogging progresses from the upgradient to the downgradient edge. The magnitude of the contributing drainage area and rainfall characteristics are effective factors on rate and progression of clogging.
Water flux characterization through hydraulic head and temperature data assimilation: Numerical modeling and sandbox experiments J. Hydrol. (IF 3.483) Pub Date : 2018-01-08 Lei Ju, Jiangjiang Zhang, Cheng Chen, Laosheng Wu, Lingzao Zeng
Spatial distribution of groundwater recharge/discharge fluxes has an important impact on mass and energy exchanges in shallow streambeds. During the last two decades, extensive studies have been devoted to the quantification of one-dimensional (1-D) vertical exchange fluxes. Nevertheless, few studies were conducted to characterize two-dimensional (2-D) heterogeneous flux fields that commonly exist in real-world cases. In this study, we used an iterative ensemble smoother (IES) to quantify the spatial distribution of 2-D exchange fluxes by assimilating hydraulic head and temperature measurements. Four assimilation scenarios corresponding to different potential field applications were tested. In the first three scenarios, the heterogeneous hydraulic conductivity fields were first inferred from hydraulic head and/or temperature measurements, and then the flux fields were derived through Darcy’s law using the estimated conductivity fields. In the fourth scenario, the flux fields were estimated directly from the temperature measurements, which is more efficient and especially suitable for the situation that a complete knowledge of flow boundary conditions is unavailable. We concluded that, the best estimation could be achieved through jointly assimilating hydraulic head and temperature measurements, and temperature data were superior to the head data when they were used independently. Overall, the IES method provided more robust and accurate vertical flux estimations than those given by the widely used analytical solution-based methods. Furthermore, IES gave reasonable uncertainty estimations, which were unavailable in traditional methods. Since temperature can be accurately monitored with high spatial and temporal resolutions, the coupling of heat tracing techniques and IES provides promising potential in quantifying complex exchange fluxes under field conditions.
Impact of the bottom drag coefficient on saltwater intrusion in the extremely shallow estuary J. Hydrol. (IF 3.483) Pub Date : 2018-01-06 Hanghang Lyu, Jianrong Zhu
The interactions between the extremely shallow, funnel-shaped topography and dynamic processes in the North Branch (NB) of the Changjiang Estuary produce a particular type of saltwater intrusion, saltwater spillover (SSO), from the NB into the South Branch (SB). This dominant type of saltwater intrusion threatens the winter water supplies of reservoirs located in the estuary. Simulated SSO was weaker than actual SSO in previous studies, and this problem has not been solved until now. The improved ECOM-si model with the advection scheme HSIMT-TVD was applied in this study. Logarithmic and Chézy-Manning formulas of the bottom drag coefficient (BDC) were established in the model to investigate the associated effect on saltwater intrusion in the NB. Modeled data and data collected at eight measurement stations located in the NB from February 19 to March 1, 2017, were compared, and three skill assessment indicators, the correlation coefficient (CC), root-mean-square error (RMSE), and skill score (SS), of water velocity and salinity were used to quantitatively validate the model. The results indicated that the water velocities modeled using the Chézy-Manning formula of BDC were slightly more accurate than those based on the logarithmic BDC formula, but the salinities produced by the latter formula were more accurate than those of the former. The results showed that the BDC increases when water depth decreases during ebb tide, and the results based on the Chézy-Manning formula were smaller than those based on the logarithmic formula. Additionally, the landward net water flux in the upper reaches of the NB during spring tide increases based on the Chézy-Manning formula, and saltwater intrusion in the NB was enhanced, especially in the upper reaches of the NB. At a transect in the upper reaches of the NB, the net transect water flux (NTWF) is upstream in spring tide and downstream in neap tide, and the values produced by the Chézy-Manning formula are much larger than those based on the logarithmic formula. Notably, SSO during spring tide was 1.8 times larger based on the Chézy-Manning formula than that based on the logarithmic formula. The model underestimated SSO and salinity at the hydrological stations in the SB based on the logarithmic BDC formula but successfully simulated SSO and the temporal variations in salinity in the SB using the Chézy-Manning formula of BDC.
The relative importance of different grass components in controlling runoff and erosion on a hillslope under simulated rainfall J. Hydrol. (IF 3.483) Pub Date : 2018-01-06 Changjia Li, Chengzhong Pan
The effects of vegetation cover on overland flow and erosion processes on hillslopes vary with vegetation type and spatial distribution and the different vegetation components, including the above- and below-ground biomass. However, few attempts have been made to quantify how these factors affect erosion processes. Field experimental plots (5 m × 2 m) with a slope of approximately 25° were constructed and simulated rainfall (60 mm hr-1) (Rainfall) and simulated rainfall combined with upslope overland flow (20 L min-1) (Rainfall +Flow) were applied. Three grass species were selected, specifically Astragalus adsurgens (A. adsurgens), Medicago sativa (M. sativa) and Cosmos bipinnatus (C. bipinnatus). To isolate and quantify the relative contributions of the above-ground grass parts (stems, litter cover and leaves) and the roots to reducing surface runoff and erosion, each of the three grass species was subjected to three treatments: intact grass control (IG), no litter or leaves (only the grass stems and roots were reserved) (NLL), and only roots remaining (OR). The results showed that planting grass significantly reduced overland flow rate and velocity and sediment yield, and the mean reductions were 21.8%, 29.1% and 67.1%, respectively. M. sativa performed the best in controlling water and soil losses due to its thick canopy and dense, fine roots. Grasses reduced soil erosion mainly during the early stage of overland flow generation. The above-ground grass parts mainly contributed to reducing overland flow rate and velocity, with mean relative contributions of 64% and 86%, respectively. The roots played a predominant role in reducing soil erosion, with mean contribution of 84%. Due to the impact of upslope inflow, overland flow rate and velocity and sediment yield increased under the Rainfall +Flow conditions. The results suggest that grass species on downslope parts of semi-arid hillslopes performed better in reducing water and soil losses. This study is beneficial for forage selection, allocation and management practices, such as forage harvesting, when implementing restoration strategies to control soil and water losses.
Monitoring and modelling of shallow groundwater dynamics in urban context: The case study of Jakarta J. Hydrol. (IF 3.483) Pub Date : 2018-01-03 Kashif Shaad, Paolo Burlando
An overview of the urban shallow groundwater dynamics in Jakarta is provided. The modifications to the water budget at the micro and mesoscale due to anthropogenic influences are described and the diffusive nature of the interaction analysed. The scale of urbanisation (> 10 million residents) in conjunction with the lack of infrastructure for water-related services is seen to have fostered a dependency on the shallow groundwater resources and, in turn, led to a tangible impact on the groundwater domain, which is difficult to quantify and study. Using short duration yet high temporal resolution groundwater level data collected at an urban site within Jakarta, two metrics are developed that can describe the daily variation in groundwater levels driven by the human interaction. Numerical models of varying complexity for the urban shallow groundwater dynamics are then used. Here, by employing a process of gradually improving the model’s physical description while performing parameter estimation based on the new metrics, the study provides evidence of the role of the unsaturated zone in influencing the urban shallow groundwater dynamics. We further identify Jakarta’s wastewater seepage as the crucial yet overlooked component of the urban cycle, having direct implications for the region’s water security. The innovation of this study lies at the combination of high temporal resolution data with flexible modelling frameworks that can be developed to give insights into rapidly growing, unstructured stressors on water resources in data poor Mega Cities from the developing world.
Quantifying rainfall-derived inflow and infiltration in sanitary sewer systems based on conductivity monitoring J. Hydrol. (IF 3.483) Pub Date : 2018-01-03 Mingkai Zhang, Yanchen Liu, Xun Cheng, David Z. Zhu, Hanchang Shi, Zhiguo Yuan
Megacities and Rivers: Scalar Mismatches between Urban Water Management and River Basin Management J. Hydrol. (IF 3.483) Pub Date : 2018-01-02 Francine van den Brandeler, Joyeeta Gupta, Michaela Hordijk
Due to rapid urbanization, population growth and economic drivers, megacities and metropolises around the world face increasing water challenges, such as water scarcity, degradation of water resources and water-related risks such as flooding. Climate change is expected to put additional stress on already strained metropolitan water management systems. Although there is considerable research on river basin management and on urban water management, there is hardly any on metropolitan water management. Similarly, as urban water generally emerges from and returns to river basins, it is surprising how little literature there is that explicitly connects these two spheres of governance. Hence this review paper addresses the question: What does a review of the literature tell us about the overlap and reconciliation between the concepts of Integrated Water Resources/River Basin Management and Metropolitan/Urban Water Management, particularly in relation to megacities? Based on an extensive literature review, this paper concludes that the key differences between the two are in relation to their overarching framework, scope, inputs and outputs of water and in relation to dealing with extreme weather events. The literature review reveals how sustainable and integrated urban water management increasingly adopt principles and rhetoric from integrated water resource management, this has yet to translate into significant changing practices on the ground. Urban water management still often occurs independently of river basin issues. Achieving coherence between river basin management and sustainable/integrated urban water management is even more difficult in metropolises and megacities, because the latter consists of multiple political-administrative units. The article concludes that the scalar mismatch between river basin management and metropolitan/megacity water governance deserves much greater attention than it currently receives in the academic and policy debates.
Hydrological performance of modular-tray green roof systems for increasing the resilience of mega-cities to climate change J. Hydrol. (IF 3.483) Pub Date : 2018-01-02 Claudia Maria Loiola do Nascimento, Wellington Mary, Luciene Pimentel da Silva
This paper investigates the performance of modular-tray green roof systems on rainwater retention and total runoff delay under heavy rain conditions, typical of countries with a tropical climate. It involved the building of a rain-spray system simulator and worktops to support the experimental units. Three green roof modular-tray systems were studied, M-4L, M-17L and F-17L, with a mix of succulent plant species. The volume and delay of total runoff were sampled for both dry and wet soil-moisture stages for a simulated rainstorm of 155 mm/h and duration of 7 minutes, which approaches the value of the design rainfall of 10-year return-period and an observed rainfall event that caused flooding in 2011 in the area where the experiments took place. These results were compared to three bare-soil similar experimental units and with a control unit consisting of a corrugated fibre-cement roof sheet. In addition, classic rainfall-runoff parameterization, also important for catchment analysis, such as the rational coefficient method (C) and Curve Number (CN) were also applied. The results showed to be consistent. Overall, module F-17L presented the best performance with regard to both water retention and delay of total runoff. The average percentage of retention, considering all module types, was 58% of the total induced water volume, and the average delay for total runoff was approximately 12 minutes. In some tests, for the wet soil stage, the bare soil units performed better than the vegetated units. Soil moisture analysis revealed that considering the same period of time, the bare soil units lost more water through evaporation than the vegetated units through evapotranspiration. The average values of C for vegetated units for the wet and dry soil stages were equal to 0.66 and 0.27, respectively. The CN values were high, ranging from 88 to 97. Although fairly new on the market in Rio de Janeiro, modular-tray green roof systems are easy to build and hydrologically effective, mainly in the dry soil stages, performing as well as other extensive green roof systems. The values obtained for C and CN may be useful for the modelling of catchment rainfall and runoff especially for scenarios involving green roofs, as well as for establishing regulatory benchmarks towards more resilient and sustainable cities.
A surrogate-based sensitivity quantification and Bayesian inversion of a regional groundwater flow model J. Hydrol. (IF 3.483) Pub Date : 2018-01-02 Mingjie Chen, Azizallah Izady, Osman A. Abdalla, Mansoor Amerjeed
Bayesian inference using Markov Chain Monte Carlo (MCMC) provides an explicit framework for stochastic calibration of hydrogeologic models accounting for uncertainties; however, the MCMC sampling entails a large number of model calls, and could easily become computationally unwieldy if the high-fidelity hydrogeologic model simulation is time consuming. This study proposes a surrogate-based Bayesian framework to address this notorious issue, and illustrates the methodology by inverse modeling a regional MODFLOW model. The high-fidelity groundwater model is approximated by a fast statistical model using Bagging Multivariate Adaptive Regression Spline (BMARS) algorithm, and hence the MCMC sampling can be efficiently performed. In this study, the MODFLOW model is developed to simulate the groundwater flow in an arid region of Oman consisting of mountain-coast aquifers, and used to run representative simulations to generate training dataset for BMARS model construction. A BMARS-based Sobol’ method is also employed to efficiently calculate input parameter sensitivities, which are used to evaluate and rank their importance for the groundwater flow model system. According to sensitivity analysis, insensitive parameters are screened out of Bayesian inversion of the MODFLOW model, further saving computing efforts. The posterior probability distribution of input parameters is efficiently inferred from the prescribed prior distribution using observed head data, demonstrating that the presented BMARS-based Bayesian framework is an efficient tool to reduce parameter uncertainties of a groundwater system.
How can streamflow and climate-landscape data be used to estimate baseflow mean response time? J. Hydrol. (IF 3.483) Pub Date : 2017-12-30 Runrun Zhang, Xi Chen, Zhicai Zhang, Chris Soulsby, Man Gao
Mean response time (MRT) is a metric describing the propagation of catchment hydraulic behavior that reflects both hydro-climatic conditions and catchment characteristics. To provide a comprehensive understanding of catchment response over a longer-time scale for hydraulic processes, the MRT function for baseflow generation was derived using an instantaneous unit hydrograph (IUH) model that describes the subsurface response to effective rainfall inputs. IUH parameters were estimated based on the “match test” between the autocorrelation function (ACFs) derived from the filtered base flow time series and from the IUH parameters, under the GLUE framework. Regionalization of MRT was conducted using estimates and hydroclimate-landscape indices in 22 sub-basins of the Jinghe River Basin (JRB) in the Loess Plateau of northwest China. Results indicate there is strong equifinality in determination of the best parameter sets but the median values of the MRT estimates are relatively stable in the acceptable range of the parameters. MRTs vary markedly over the studied sub-basins, ranging from tens of days to more than a year. Climate, topography and geomorphology were identified as three first-order controls on recharge-baseflow response processes. Human activities involving the cultivation of permanent crops may elongate the baseflow MRT and hence increase the dynamic storage. Cross validation suggests the model can be used to estimate MRTs in ungauged catchments in similar regions of throughout the Loess Plateau. The proposed method provides a systematic approach for MRT estimation and regionalization in terms of hydroclimate and catchment characteristics, which is helpful in the sustainable water resources utilization and ecological protection in the Loess Plateau.
Global assessment of predictability of water availability: a bivariate probabilistic Budyko analysis J. Hydrol. (IF 3.483) Pub Date : 2017-12-28 Weiguang Wang, Jianyu Fu
Estimating continental water availability is of great importance for water resources management, in terms of maintaining ecosystem integrity and sustaining society development. To more accurately quantify the predictability of water availability, on the basis of univariate probabilistic Budyko framework, a bivariate probabilistic Budyko approach was developed using copula-based joint distribution model for considering the dependence between parameter ω of Wang-Tang’s equation and the Normalized Difference Vegetation Index (NDVI), and was applied globally. The results indicate the predictive performance in global water availability is conditional on the climatic condition. In comparison with simple univariate distribution, the bivariate one produces the lower interquartile range under the same global dataset, especially in the regions with higher NDVI values, highlighting the importance of developing the joint distribution by taking into account the dependence structure of parameter ω and NDVI, which can provide more accurate probabilistic evaluation of water availability.
Preferential Flow in the Vadose Zone and Interface Dynamics: Impact of Microbial Exudates J. Hydrol. (IF 3.483) Pub Date : 2017-12-28 Biting Li, Ashley R. Pales, Heather M. Clifford, Shyla Kupis, Sarah Hennessy, Wei-Zhen Liang, Stephen Moysey, Brian Powell, Kevin T. Finneran, Christophe J.G. Darnault
In the hydrological cycle, the infiltration process is a critical component in the distribution of water into the soil and in the groundwater system. The nonlinear dynamics of the soil infiltration process yield preferential flow which affects the water distribution in soil. Preferential flow is influenced by the interactions between water, soil, plants, and microorganisms. Although the relationship among the plant roots, their rhizodeposits and water transport in soil has been the subject of extensive study, the effect of microbial exudates has been studied in only a few cases. Here the authors investigated the influence of two artificial microbial exudates–catechol and riboflavin–on the infiltration process, particularly unstable fingered flow, one form of preferential flow. Flow experiments investigating the effects of types and concentrations of microbial exudates on unstable fingered flow were conducted in a two-dimensional tank that was filled with ASTM C778 graded silica sand. The light transmission method (LTM) which is based on capturing the light intensity transmitted through a sand-water system and then converting it into degree of water saturation was used to visualize and characterize the flow of water in porous media as well as to image and measure the spatial and temporal distribution of water in porous media. Flow patterns, vertical and horizontal profiles of the degree of water saturation of the fingers, as well as measurements of the fingers dimension (width), number, and velocity were determined using the light transmission method. Interfacial experiments exploring the influence of microbial exudates on the wettability behavior of water were performed by measuring the contact angle and the interfacial tension of the (solid)-gas-microbial exudate solution systems. Unstable wetting front generating fingered flow was observed in all infiltration experiments. The experimental results showed that the microbial exudate addition affected the infiltration process, as the measurements of the degree of saturation profiles and widths of the fingers differed from those of the control NaCl solution. These differences may be due to an improved water holding capacity in the presence of the microbial exudates. The lowest catechol solution concentration (10 μM) produced the largest finger width (9.69 cm) among the tested catechol solution concentrations and all the other solutions including the control solution (7.24 cm). Moreover, the wettability of the medium for the catechol solution increased with an increase in concentration. The highest riboflavin solution concentration (1000 μM) generated the highest finger width (7.75 cm) among the tested riboflavin solution concentrations. However, the wettability of the medium for the riboflavin solution decreased with an increase in concentration. Our study demonstrated that the microbial exudates which are biochemical compounds produced and released by microbes in the environment are capable influencing the soil infiltration process. The results of this study also demonstrated that the influence of the contact angle expressed as (cosθ)1/2 ( cos θ ) 1 / 2 should be integrated in the scaling of the finger dimension, i.e., finger width, when the Miller and Miller (1956) scaling theory is applied for the hydrodynamic scaling in porous media.
An export coefficient based inexact fuzzy bi-level multi-objective programming model for the management of agricultural nonpoint source pollution under uncertainty J. Hydrol. (IF 3.483) Pub Date : 2017-12-28 Yanpeng Cai, Qiangqiang Rong, Zhifeng Yang, Wencong Yue, Qian Tan
In this research, an export coefficient based inexact fuzzy bi-level multi-objective programming (EC-IFBLMOP) model was developed through integrating export coefficient model (ECM), interval parameter programming (IPP) and fuzzy parameter programming (FPP) within a bi-level multi-objective programming framework. The proposed EC-IFBLMOP model can effectively deal with the multiple uncertainties expressed as discrete intervals and fuzzy membership functions. Also, the complexities in agricultural systems, such as the cooperation and gaming relationship between the decision makers at different levels, can be fully considered in the model. The developed model was then applied to identify the optimal land use patterns and BMP implementing levels for agricultural nonpoint source (NPS) pollution management in a subcatchment in the upper stream watershed of the Miyun Reservoir in north China. The results of the model showed that the desired optimal land use patterns and BMP implementing levels would be obtained. It is the gaming result between the upper- and lower-level decision makers, when the allowable discharge amounts of NPS pollutants were limited. Moreover, results corresponding to different decision scenarios could provide a set of decision alternatives for the upper- and lower-level decision makers to identify the most appropriate management strategy. The model has a good applicability and can be effectively utilized for agricultural NPS pollution management.
Entropy-based derivation of generalized distributions for hydrometeorological frequency analysis J. Hydrol. (IF 3.483) Pub Date : 2017-12-28 Lu Chen, Vijay P. Singh
Frequency analysis of hydrometeorological and hydrological extremes is needed for the design of hydraulic and civil infrastructure facilities as well as water resources management. A multitude of distributions have been employed for frequency analysis of these extremes. However, no single distribution has been accepted as a global standard. Employing the entropy theory, this study derived five generalized distributions for frequency analysis that used different kinds of information encoded as constraints. These distributions were the generalized gamma (GG), the generalized beta distribution of the second kind (GB2), and the Halphen type A distribution (Hal-A), Halphen type B distribution (Hal-B) and Halphen type inverse B distribution (Hal-IB), among which the GG and GB2 distribution were previously derived by Papalexiou and Koutsoyiannis (2012) and the Halphen family was first derived using entropy theory in this paper. The entropy theory allowed to estimate parameters of the distributions in terms of the constraints used for their derivation. The distributions were tested using extreme daily and hourly rainfall data. Results show that the root mean square error (RMSE) values were very small, which indicated that the five generalized distributions fitted the extreme rainfall data well. Among them, according to the Akaike information criterion (AIC) values, generally the GB2 and Halphen family gave a better fit. Therefore, those general distributions are one of the best choices for frequency analysis. The entropy-based derivation led to a new way for frequency analysis of hydrometeorological extremes.
Identification of relationships between climate indices and long-term precipitation in South Korea using ensemble empirical mode decomposition J. Hydrol. (IF 3.483) Pub Date : 2017-12-28 Taereem Kim, Ju-Young Shin, Sunghun Kim, Jun-Haeng Heo
Climate indices characterize climate systems and may identify important indicators for long-term precipitation, which are driven by climate interactions in atmosphere-ocean circulation. In this study, we investigated the climate indices that are effective indicators of long-term precipitation in South Korea, and examined their relationships based on statistical methods. Monthly total precipitation was collected from a total of 60 meteorological stations, and they were decomposed by ensemble empirical mode decomposition (EEMD) to identify the inherent oscillating patterns or cycles. Cross-correlation analysis and stepwise variable selection were employed to select the significant climate indices at each station. The climate indices that affect the monthly precipitation in South Korea were identified based on the selection frequencies of the selected indices at all stations. The NINO12 indices with four- and ten-month lags and AMO index with no lag were identified as indicators of monthly precipitation in South Korea. Moreover, they indicate meaningful physical information (e.g. periodic oscillations and long-term trend) inherent in the monthly precipitation. The NINO12 index with four- and ten- month lags was a strong indicator representing periodic oscillations in monthly precipitation. In addition, the long-term trend of the monthly precipitation could be explained by the AMO index. A multiple linear regression model was constructed to investigate the influences of the identified climate indices on the prediction of monthly precipitation. Three identified climate indices successfully explained the monthly precipitation in the winter dry season. Compared to the monthly precipitation in coastal areas, the monthly precipitation in inland areas showed stronger correlation to the identified climate indices.
Development of a methodology to assess future trends in low flows at the watershed scale using solely climate data J. Hydrol. (IF 3.483) Pub Date : 2017-12-27 Étienne Foulon, Alain N. Rousseau, Patrick Gagnon
Low flow conditions are governed by short-to-medium term weather conditions or long term climate conditions. This prompts the question: given climate scenarios, is it possible to assess future extreme low flow conditions from climate data indices (CDIs)? Or should we rely on the conventional approach of using outputs of climate models as inputs to a hydrological model? Several CDIs were computed using 42 climate scenarios over the years 1961 to 2100 for two watersheds located in Québec, Canada. The relationship between the CDIs and hydrological data indices (HDIs; 7- and 30-day low flows for two hydrological seasons) were examined through correlation analysis to identify the indices governing low flows. Results of the Mann-Kendall test, with a modification for autocorrelated data, clearly identified trends. A partial correlation analysis allowed attributing the observed trends in HDIs to trends in specific CDIs. Furthermore, results showed that, even during the spatial validation process, the methodological framework was able to assess trends in low flow series from: (i) trends in the effective drought index (EDI) computed from rainfall plus snowmelt minus PET amounts over ten to twelve months of the hydrological snow cover season or (ii) the cumulative difference between rainfall and potential evapotranspiration over five months of the snow free season. For 80% of the climate scenarios, trends in HDIs were successfully attributed to trends in CDIs. Overall, this paper introduces an efficient methodological framework to assess future trends in low flows given climate scenarios. The outcome may prove useful to municipalities concerned with source water management under changing climate conditions.
Monthly Paleostreamflow Reconstruction from Annual Tree-Ring Chronologies J. Hydrol. (IF 3.483) Pub Date : 2017-12-27 J.H. Stagge, D.E. Rosenberg, R.J. DeRose, T.M. Rittenour
Paleoclimate reconstructions are increasingly used to characterize annual climate variability prior to the instrumental record, to improve estimates of climate extremes, and to provide a baseline for climate-change projections. To date, paleoclimate records have seen limited engineering use to estimate hydrologic risks because water systems models and managers usually require streamflow input at the monthly scale. This study explores the hypothesis that monthly streamflows can be adequately modeled by statistically decomposing annual flow reconstructions. To test this hypothesis, a multiple linear regression model for monthly streamflow reconstruction is presented that expands the set of predictors to include annual streamflow reconstructions, reconstructions of global circulation, and potential differences among regional tree-ring chronologies related to tree species and geographic location. This approach is used to reconstruct 600 years of monthly streamflows at two sites on the Bear and Logan rivers in northern Utah. Nash-Sutcliffe Efficiencies remain above zero (0.26-0.60) for all months except April and Pearson’s correlation coefficients (R) are 0.94 and 0.88 for the Bear and Logan rivers, respectively, confirming that the model can adequately reproduce monthly flows during the reference period (10/1942 to 9/2015). Incorporating a flexible transition between the previous and concurrent annual reconstructed flows was the most important factor for model skill. Expanding the model to include global climate indices and regional tree-ring chronologies produced smaller, but still significant improvements in model fit. The model presented here is the only approach currently available to reconstruct monthly streamflows directly from tree-ring chronologies and climate reconstructions, rather than using resampling of the observed record. With reasonable estimates of monthly flow that extend back in time many centuries, water managers can challenge systems models with a larger range of natural variability in drought and pluvial events and better evaluate extreme events with recurrence intervals longer than the observed record. Establishing this natural baseline is critical when estimating future hydrologic risks under conditions of a non-stationary climate.
Effect of Uncertainties on Probabilistic-based Design Capacity of Hydrosystems J. Hydrol. (IF 3.483) Pub Date : 2017-12-27 Yeou-Koung Tung
Hydrosystems engineering designs involve analysis of hydrometric data (e.g., rainfall, floods) and use of hydrologic/hydraulic models, all of which contribute various degrees of uncertainty to the design process. Uncertainties in hydrosystem designs can be generally categorized into aleatory and epistemic types. The former arises from the natural randomness of hydrologic processes whereas the latter are due to knowledge deficiency in model formulation and model parameter specification. This study shows that the presence of epistemic uncertainties induces uncertainty in determining the design capacity. Hence, the designer needs to quantify the uncertainty features of design capacity to determine the capacity with a stipulated performance reliability under the design condition. Using detention basin design as an example, the study illustrates a methodological framework by considering aleatory uncertainty from rainfall and epistemic uncertainties from the runoff coefficient, curve number, and sampling error in design rainfall magnitude. The effects of including different items of uncertainty and performance reliability on the design detention capacity are examined. A numerical example shows that the mean value of the design capacity of the detention basin increases with the design return period and this relation is found to be practically the same regardless of the uncertainty types considered. The standard deviation associated with the design capacity, when subject to epistemic uncertainty, increases with both design frequency and items of epistemic uncertainty involved. It is found that the epistemic uncertainty due to sampling error in rainfall quantiles should not be ignored. Even with a sample size of 80 (relatively large for a hydrologic application) the inclusion of sampling error in rainfall quantiles resulted in a standard deviation about 2.5 times higher than that considering only the uncertainty of the runoff coefficient and curve number. Furthermore, the presence of epistemic uncertainties in the design would result in under-estimation of the annual failure probability of the hydrosystem and has a discounting effect on the anticipated design return period.
Controls on water vapor isotopes over roorkee, india: impact of convective activities and depression systems J. Hydrol. (IF 3.483) Pub Date : 2017-12-27 P. Saranya, Gopal Krishan, M.S. Rao, Sudhir Kumar, Bhishm Kumar
The study evaluates the water vapor isotopic compositions and its controls with special reference to Indian Summer Monsoon (ISM) season at Roorkee, India. Precipitation is usually a discrete event spatially and temporally in this part of the country, therefore, the information provided is limited, while, the vapors have all time availability and have a significant contribution in the hydrological cycle locally or over a regional scale. Hence for understanding the processes altering the various sources, its isotopic signatures were studied. The Isotope Water Vapour Line (Iso Val) was drawn together with the Global Meteoric Water Line (GMWL) and the best fit line was δD= 5.42∗δ18O+27.86. The precipitation samples were also collected during the study period and were best fitted with δD= 8.20(±0.18)∗δ18O+9.04(±1.16) in the Local Meteoric Water Line (LMWL). From the back trajectory analysis of respective vapor samples, it is unambiguous that three major sources viz; local vapor, western disturbance and monsoon vapor are controlling the fate of moisture over Roorkee. The d-excess in ground-level vapor (GLV) reveals the supply of recycled moisture from continental water bodies and evapo-transpiration as additional moisture sources to the study area. The intensive depletion in isotopic ratios was associated with the large-scale convective activity and low-pressure/cyclonic/depression systems formed over Bay of Bengal.
Comparison of a Vertically-averaged and a Vertically-resolved Model for Hyporheic Flow Beneath a Pool-Riffle Bedform J. Hydrol. (IF 3.483) Pub Date : 2017-12-27 Ahmad Ibrahim, Peter Steffler, Yuntong She
The interaction between surface water and groundwater through the hyporheic zone is recognized to be important as it impacts the water quantity and quality in both flow systems. Three-dimensional (3D) modeling is the most complete representation of a real-world hyporheic zone. However, 3D modeling requires extreme computational power and efforts; the sophistication is often significantly compromised by not being able to obtain the required input data accurately. Simplifications are therefore often needed. The objective of this study was to assess the accuracy of the vertically-averaged approximation compared to a more complete vertically-resolved model of the hyporheic zone. The groundwater flow was modeled by either a simple one-dimensional (1D) Dupuit approach or a two-dimensional (2D) horizontal/vertical model in boundary fitted coordinates, with the latter considered as a reference model. Both groundwater models were coupled with a 1D surface water model via the surface water depth. Applying the two models to an idealized pool-riffle sequence showed that the 1D Dupuit approximation gave comparable results in determining the characteristics of the hyporheic zone to the reference model when the stratum thickness is not very large compared to the surface water depth. Conditions under which the 1D model can provide reliable estimate of the seepage discharge, upwelling/downwelling discharges and locations, the hyporheic flow, and the residence time were determined.
Anthropogenic hydrological cycle disturbance at a regional scale: state-wide evapotranspiration trends (1979-2015) across Nebraska, USA J. Hydrol. (IF 3.483) Pub Date : 2017-12-27 Jozsef Szilagyi
Trends in monthly evapotranspiration (ET) rates across Nebraska, the most intensely irrigated state within the US, were calculated by the calibration-free version of the nonlinear complementary relationship of evaporation over the 1979-2015 period utilizing North American Regional Reanalysis (NARR) net radiation, 10-m wind velocity, as well as Parameter Regression Independent Slope Model (PRISM) air- and dew-point temperature data. State-averaged modeled ET rates rose by 5.5 mm decade-1 due to the presence of wide-spread large-scale irrigation projects in accordance with a 2.4 mm decade-1 increase in PRISM precipitation (P) and a simultaneous -2.8 mm decade-1 drop in United States Geological Survey’s state-averaged annual streamflow rates, raising the state-wide ET to P ratio from 0.89 to 0.91 over the modeled time-period. ET rates over irrigated crops increased by 7 mm decade-1 despite a -4.4 mm decade-1 drop in precipitation rates. A similar increase in ET rates (6 mm decade-1) required 8.1 mm decade-1 increase in precipitation rates across the non-irrigated Sand Hills of Nebraska. Published NARR ET rates are unable to pick up this unusual regional trend. Since an increase in precipitation rates should normally decrease the ET ratio, as predicted by the Budyko curve, this study yields evidence on how dramatically sustained large-scale irrigation can alter the regional hydrologic cycle not only through a) trivially depleting streamflow rates and/or lowering groundwater table levels; b) suppressing precipitation locally (while enhancing it a long distance downwind), but also; c) reversing the trajectory of the regional ET ratio under generally increasing trends of precipitation.
Accounting for Rainfall Evaporation Using Dual-Polarization Radar and Mesoscale Model Data J. Hydrol. (IF 3.483) Pub Date : 2017-12-27 Quinn Pallardy, Neil I. Fox
Implementation of dual-polarization radar should allow for improvements in quantitative precipitation estimates due to dual-polarization capability allowing for the retrieval of the second moment of the gamma drop size distribution. Knowledge of the shape of the DSD can then be used in combination with mesoscale model data to estimate the motion and evaporation of each size of drop falling from the height at which precipitation is observed by the radar to the surface. Using data from Central Missouri at a range between 130 and 140 km from the operational National Weather Service radar a rain drop tracing scheme was developed to account for the effects of evaporation, where individual raindrops hitting the ground were traced to the point in space and time where they interacted with the radar beam. The results indicated evaporation played a significant role in radar rainfall estimation in situations where the atmosphere was relatively dry. Improvements in radar estimated rainfall were also found in these situations by accounting for evaporation. The conclusion was made that the effects of raindrop evaporation were significant enough to warrant further research into the inclusion high resolution model data in the radar rainfall estimation process for appropriate locations.
High spatial-temporal resolution and integrated surface and subsurface Precipitation-Runoff modelling for a small stormwater catchment J. Hydrol. (IF 3.483) Pub Date : 2017-12-26 Teklu T. Hailegeorgis, Knut Alfredsen
Reliable runoff estimation is important for design of water infrastructure and flood risk management in urban catchments. We developed a spatially distributed Precipitation-Runoff (P-R) model that explicitly represents the land cover information, performs integrated modelling of surface and subsurface components of the urban precipitation water cycle and flow routing. We conducted parameter calibration and validation for a small (21.255ha) stormwater catchment in Trondheim City during Summer-Autumn events and season, and snow-influenced Winter-Spring seasons at high spatial and temporal resolutions of respectively 5mx5m grid size and 2 minutes. The calibration resulted in good performance measures (Nash-Sutcliffe efficiency, NSE = 0.65-0.94) and acceptable validation NSE for the seasonal and snow-influenced periods. The infiltration excess surface runoff dominates the peak flows while the contribution of subsurface flow to the sewer pipes also augments the peak flows. Based on the total volumes of simulated flow in sewer pipes (Qsim) and precipitation (P) during the calibration periods, the Qsim/P ranges from 21.44% for an event to 56.50% for the Winter-Spring season, which are in close agreement with the observed volumes (Qobs/P). The lowest percentage of precipitation volume that is transformed to the total simulated runoff in the catchment (QT) is 79.77%. Computation of evapotranspiration (ET) indicated that the ET/P is less than 3% for the events and snow-influenced seasons while it is about 18% for the Summer-Autumn season. The subsurface flow contribution to the sewer pipes are markedly higher than the total surface runoff volume for some events and the Summer-Autumn season. The peakiest flow rates correspond to the Winter-Spring season. Therefore, urban runoff simulation for design and management purposes should include two-way interactions between the subsurface runoff and flow in sewer pipes, and snow-influenced seasons. The developed urban P-R model is useful for better computation of runoff generated from different land cover, for assessments of stormwater management techniques (e.g. the Low Impact Development or LID) and the impacts of land cover and climate change. There are some simplifications or limitations such as the runoff routing does not involve detailed sewer hydraulics, effects of leakages from water supply systems and faulty/illegal connections from sanitary sewer are not considered, the model cannot identify actual locations of the interactions between the subsurface runoff and sewer pipes and lacks parsimony.
Comprehensive drought characteristics analysis based on a nonlinear multivariate drought index J. Hydrol. (IF 3.483) Pub Date : 2017-12-26 Jie Yang, Jianxia Chang, Yimin Wang, Yunyun Li, Hui Hu, Yutong Chen, Qiang Huang, Jun Yao
It is vital to identify drought events and to evaluate multivariate drought characteristics based on a composite drought index for better drought risk assessment and sustainable development of water resources. However, most composite drought indices are constructed by the linear combination, principal component analysis and entropy weight method assuming a linear relationship among different drought indices. In this study, the multidimensional copulas function was applied to construct a nonlinear multivariate drought index (NMDI) to solve the complicated and nonlinear relationship due to its dependence structure and flexibility. The NMDI was constructed by combining meteorological, hydrological, and agricultural variables (precipitation, runoff, and soil moisture) to better reflect the multivariate variables simultaneously. Based on the constructed NMDI and runs theory, drought events for a particular area regarding three drought characteristics: duration, peak, and severity were identified. Finally, multivariate drought risk was analyzed as a tool for providing reliable support in drought decision-making. The results indicate that: (1) multidimensional copulas can effectively solve the complicated and nonlinear relationship among multivariate variables; (2) compared with single and other composite drought indices, the NMDI is slightly more sensitive in capturing recorded drought events; and (3) drought risk shows a spatial variation; out of the five partitions studied, the Jing River Basin as well as the upstream and midstream of the Wei River Basin are characterized by a higher multivariate drought risk. In general, multidimensional copulas provides a reliable way to solve the nonlinear relationship when constructing a comprehensive drought index and evaluating multivariate drought characteristics.
Does soil compaction increase floods? A review J. Hydrol. (IF 3.483) Pub Date : 2017-12-26 Abdallah Alaoui, Magdalena Rogger, Stephan Peth, Günter Blöschl
Europe has experienced a series of major floods in the past years which suggests that flood magnitudes may have increased. Land degradation due to soil compaction from crop farming or grazing intensification is one of the potential drivers of this increase. A literature review suggests that most of the experimental evidence was generated at plot and hillslope scales. At larger scales, most studies are based on models. There are three ways in which soil compaction affects floods at the catchment scale: (i) through an increase in the area affected by soil compaction; (ii) by exacerbating the effects of changes in rainfall, especially for highly degraded soils; and (iii) when soil compaction coincides with soils characterized by a fine texture and a low infiltration capacity. We suggest that future research should focus on better synthesising past research on soil compaction and runoff, tailored field experiments to obtain a mechanistic understanding of the coupled mechanical and hydraulic processes, new mapping methods of soil compaction that combine mechanical and remote sensing approaches, and an effort to bridge all disciplines relevant to soil compaction effects on floods.
Exploiting the synergy between SMAP and SMOS to improve brightness temperature simulations and soil moisture retrievals in arid regions J. Hydrol. (IF 3.483) Pub Date : 2017-12-26 Mohsen Ebrahimi-Khusfi, Seyed Kazem Alavipanah, Saeid Hamzeh, Farshad Amiraslani, Najmeh Samani Neysani, Jean-Pierre Wigneron
The objective of this study was to exploit the synergy between SMOS and SMAP based on vegetation optical depth (VOD) to improve brightness temperature (TB) simulations and land surface soil moisture (SM) retrievals in arid regions of the world. In the current operational algorithm of SMAP (level 2), vegetation water content (VWC) is considered as a proxy to compute VOD which is calculated by an empirical conversion function of NDVI. SMOS avoids the empirical estimation of VOD and retrieves simultaneously SM and VOD from TB observations. The present study attempted to improve SMAP TB simulations and SM retrievals by benefiting from the advantages of the SMOS (L-MEB) algorithm. This was achieved by using a synergy method based on replacing the default value of SMAP VOD with the retrieved value of VOD from the SMOS multi angular and bi-polarization observations of TB. The insitu SM measurements, used as reference SM in this study, were obtained from the International Soil Moisture Network (ISMN) over 180 stations located in arid regions of the world. Furthermore, four stations were randomly selected to analyze the temporal variations in VOD and SM. Results of the synergy method showed that the accuracy of the TB simulations and SM retrievals was respectively improved at 144 and 124 stations (out of a total of 180 stations) in terms of coefficient of determination (R2) and unbiased root mean squared error (UbRMSE). Analyzing the temporal variations in VOD showed that the SMOS VOD, conversely to the SMAP VOD, can better illustrate the presence of herbaceous plants and may be a better indicator of the seasonal changes in the vegetation density and biomass over the year.
Description and preliminary results of a 100 square meter rain gauge J. Hydrol. (IF 3.483) Pub Date : 2015-10-13 Salvatore Grimaldi, Andrea Petroselli, Luca Baldini, Eugenio Gorgucci
Rainfall is one of the most crucial processes in hydrology, and the direct and indirect rainfall measurement methods are constantly being updated and improved. The standard instrument used to measure rainfall rate and accumulation is the rain gauge, which provides direct observations. Though the small dimension of the orifice allows rain gauges to be installed anywhere, it also causes errors due to the splash and wind effects. To investigate the role of the orifice dimension, this study, for the first time, introduces and demonstrates an apparatus for observing rainfall called a giant-rain gauge that is characterised by a collecting surface of 100 m2. To discuss the new instrument and its technical details, a preliminary analysis of 26 rainfall events is provided. The results suggest that there are significant differences between the standard and proposed rain gauges. Specifically, major discrepancies are evident for low time aggregation scale (5, 10, and 15 min) and for high rainfall intensity values.
The cumulative effects of forest disturbance and climate variability on streamflow components in a large forest-dominated watershed J. Hydrol. (IF 3.483) Pub Date : 2017-12-21 Qiang Li, Xiaohua Wei, Mingfang Zhang, Wenfei Liu, Krysta Giles-Hansen, Yi Wang
Assessing how forest disturbance and climate variability affect streamflow components is critical for watershed management, ecosystem protection, and engineering design. Previous studies have mainly evaluated the effects of forest disturbance on total streamflow, rarely with attention given to its components (e.g., base flow and surface runoff), particularly in large watersheds (>1000 km2). In this study, the Upper Similkameen River watershed (1810 km2), an international watershed situated between Canada and the USA, was selected to examine how forest disturbance and climate variability interactively affect total streamflow, baseflow, and surface runoff. Baseflow was separated using a combination of the recursive digital filter method and conductivity mass balance method. Time series analysis and modified double mass curves were then employed to quantitatively separate the relative contributions of forest disturbance and climate variability to each streamflow component. Our results showed that average annual baseflow and baseflow index (baseflow/streamflow) were 113.3 ± 35.6 mm year-1 and 0.27 for 1954-2013, respectively. Forest disturbance increased annual streamflow, baseflow, and surface runoff of 27.7 ± 13.7 mm, 7.4 ± 3.6 mm, and 18.4 ± 12.9 mm, respectively, with its relative contributions to the changes in respective streamflow components being 27.0 ± 23.0%, 29.2 ± 23.1%, and 25.7 ± 23.4%, respectively. In contrast, climate variability decreased them by 74.9 ± 13.7 mm, 17.9 ± 3.6 mm, and 53.3 ± 12.9 mm, respectively, with its relative contributions to the changes in respective streamflow components being 73.0 ± 23.0%, 70.8 ± 23.1% and 73.1 ± 23.4%, respectively. Despite working in opposite ways, the impacts of climate variability on annual streamflow, baseflow, and surface runoff were of a much greater magnitude than forest disturbance impacts. This study has important implications for the protection of aquatic habitat, engineering design, and watershed planning in the context of future forest disturbance and climate change.
Non-monotonic permeability variation during colloidal transport: governing equations and analytical model J. Hydrol. (IF 3.483) Pub Date : 2017-12-21 L. Chequer, T. Russell, A. Behr, L. Genolet, P. Kowollik, A. Badalyan, A. Zeinijahromi, P. Bedrikovetsky
Comparison of thermal, salt and dye tracing to estimate shallow flow velocities: Novel triple-tracer approach J. Hydrol. (IF 3.483) Pub Date : 2017-12-20 João R.C.B. Abrantes, Rodrigo B. Moruzzi, Alexandre Silveira, João L.M.P. de Lima
The accurate measurement of shallow flow velocities is crucial to understand and model the dynamics of sediment and pollutant transport by overland flow. In this study, a novel triple-tracer approach was used to re-evaluate and compare the traditional and well established dye and salt tracer techniques with the more recent thermal tracer technique in estimating shallow flow velocities. For this purpose a triple tracer (i.e. dyed-salted-heated water) was used. Optical and infrared video cameras and an electrical conductivity sensor were used to detect the tracers in the flow. Leading edge and centroid velocities of the tracers were measured and the correction factors used to determine the actual mean flow velocities from tracer measured velocities were compared and investigated. Experiments were carried out for different flow discharges (32-1813 ml s-1) on smooth acrylic, sand, stones and synthetic grass bed surfaces with 0.8, 4.4 and 13.2% slopes. The results showed that thermal tracers can be used to estimate shallow flow velocities, since the three techniques yielded very similar results without significant differences between them. The main advantages of the thermal tracer were that the movement of the tracer along the measuring section was more easily visible than it was in the real image videos and that it was possible to measure space-averaged flow velocities instead of only one velocity value, with the salt tracer. The correction factors used to determine the actual mean velocity of overland flow varied directly with Reynolds and Froude numbers, flow velocity and slope and inversely with flow depth and bed roughness. In shallow flows, velocity estimation using tracers entails considerable uncertainty and caution must be taken with these measurements, especially in field studies where these variables vary appreciably in space and time.
A GIS-based model of potential groundwater yield zonation for a sandstone aquifer in the Juye Coalfield, Shangdong, China J. Hydrol. (IF 3.483) Pub Date : 2017-12-20 Huiyong Yin, Yongli Shi, Huigong Niu, Daolei Xie, Jiuchuan Wei, Liliana Lefticariu, Shuanxiang Xu
Resolving the potential groundwater yield zonation of sandstone aquifers occurring at depths of several hundred meters has been an important and challenging objective of the hydrogeological research focused on preventing flood hazards in coal mines. Using accessible geological exploration data we put forward a g method of predicting the spatial distribution of groundwater storage potential in sandstone aquifers from Permian-age coal deposits in Juye Coalfield, Shangdong, China. A Geological, Tectonic and Lithological Composition Index (GTLCI) model was created using the following parameters: sandstone depth and thickness, faults length density (FaLD), faults density (FaD), fault frequency density (FaFD), fault scale density (FaSD), variation coefficient of the slope (VCS) of the coal seam, intensity index of folds in horizontal direction (IIFoH), and lithological composition index (LCI). Each of these factors was subsequently divided into 5 classes. The analytic hierarchy process (AHP) and trapezoidal fuzzy number (TFN) method was applied to calculate the weight of the conditioning factor and their respective sub-classes. Groundwater yield potential contour map, which was initially constructed using the GTLCI values revealed four groundwater abundance zones. The map was further refined by taking into account hydrogeologic data collected during mining activities. The GTLCI model predictive success rate of 80% was explained by the limited number of boreholes available for validation. It is considered that the GTLCI model is effective at predicting zonation of groundwater yield in the sandstone aquifers from Permian- age coal deposits in Juye Coalfield, China.
Prediction of unsaturated flow and water backfill during infiltration in layered soils J. Hydrol. (IF 3.483) Pub Date : 2017-12-19 Guotao Cui, Jianting Zhu
We develop a new analytical infiltration model to determine water flow dynamics around layer interfaces during infiltration process in layered soils. The model mainly involves the analytical solutions to quadratic equations to determine the flux rates around the interfaces. Active water content profile behind the wetting front is developed based on the solution of steady state flow to dynamically update active parameters in sharp wetting front infiltration equations and to predict unsaturated flow in coarse layers before the front reaches an impeding fine layer. The effect of water backfill to saturate the coarse layers after the wetting front encounters the impeding fine layer is analytically expressed based on the active water content profiles. Comparison to the numerical solutions of the Richards equation shows that the new model can well capture water dynamics in relation to the arrangement of soil layers. The steady state active water content profile can be used to predict the saturation state of all layers when the wetting front first passes through these layers during the unsteady infiltration process. Water backfill effect may occur when the unsaturated wetting front encounters a fine layer underlying a coarse layer. Sensitivity analysis shows that saturated hydraulic conductivity is the parameter dictating the occurrence of unsaturated flow and water backfill and can be used to represent the coarseness of soil layers. Water backfill effect occurs in coarse layers between upper and lower fine layers when the lower layer is not significantly coarser than the upper layer.
Going with the flow: hydrologic response of Middle Lena River (Siberia) to the climate variability and change J. Hydrol. (IF 3.483) Pub Date : 2017-12-19 Emmanuèle Gautier, Thomas Dépret, François Costard, Clément Virmoux, Alexander Fedorov, Delphine Grancher, Pavel Konstantinov, Daniel Brunstein
Recent observations indicate that over the last decades, climate change has increasingly influenced the frequency, intensity and duration of extreme climatic and hydrologic events. The main aim of this study is to determine the hydrologic response, especially the flood evolution, of the Lena River in Eastern Siberia to ongoing climate change. Draining the coldest region of the Northern Hemisphere, the Lena River is impacted by global warming, which is particularly pronounced in periglacial areas characterized by deep and continuous permafrost. We document the hydrologic variability of the Middle Lena River, first by characterizing trend and stationarity of monthly discharges. Second, we analyze on the basis of the peak over threshold method (POT) the temporal evolution of intensity and duration of three discharge classes: bar-full discharge, bank-full discharge and large floods. Finally, we also determined the dates of the flood beginning and of the flood peak. Data on mean monthly discharge and flood peaks are available since 1936 and daily discharges since 1954. Our results provide evidence for a net hydrologic change with an increase in the intensity and duration of floods in the two decades ending in 2012. The frequency of high floods is unprecedented, and small floods no longer occur. The tail of the temporal distribution of the flood peak is also changing. More frequent early floods are occurring in spring with secondary flood peaks in summer, the latest probably represents the most striking change. Furthermore, the changes have been accelerating since 2004. Finally, two islands were instrumented (2008-2012) in order to study the flooding dynamics with a better precision.
A non-stationary cost-benefit based bivariate extreme flood estimation approach J. Hydrol. (IF 3.483) Pub Date : 2017-12-19 Wei Qi, Junguo Liu
Cost-benefit analysis and flood frequency analysis have been integrated into a comprehensive framework to estimate cost effective design values. However, previous cost-benefit based extreme flood estimation is based on stationary assumptions and analyze dependent flood variables separately. A Non-Stationary Cost-Benefit based bivariate design flood estimation (NSCOBE) approach is developed in this study to investigate influence of non-stationarites in both the dependence of flood variables and the marginal distributions on extreme flood estimation. The dependence is modeled utilizing copula functions. Previous design flood selection criteria are not suitable for NSCOBE since they ignore time changing dependence of flood variables. Therefore, a risk calculation approach is proposed based on non-stationarites in both marginal probability distributions and copula functions. A case study with 54-year observed data is utilized to illustrate the application of NSCOBE. Results show NSCOBE can effectively integrate non-stationarities in both copula functions and marginal distributions into cost-benefit based design flood estimation. It is also found that there is a trade-off between maximum probability of exceedance calculated from copula functions and marginal distributions. This study for the first time provides a new approach towards a better understanding of influence of non-stationarities in both copula functions and marginal distributions on extreme flood estimation, and could be beneficial to cost-benefit based non-stationary bivariate design flood estimation across the world.
A comparison of large-scale climate signals and the North American Multi-Model Ensemble (NMME) for drought prediction in China J. Hydrol. (IF 3.483) Pub Date : 2017-12-19 Lei Xu, Nengcheng Chen, Xiang Zhang
Drought is an extreme natural disaster that can lead to huge socioeconomic losses. Drought prediction ahead of months is helpful for early drought warning and preparations. In this study, we developed a statistical model, two weighted dynamic models and a statistical-dynamic (hybrid) model for 1-6 month lead drought prediction in China. Specifically, statistical component refers to climate signals weighting by support vector regression (SVR), dynamic components consist of the ensemble mean (EM) and Bayesian model averaging (BMA) of the North American Multi-Model Ensemble (NMME) climatic models, and the hybrid part denotes a combination of statistical and dynamic components by assigning weights based on their historical performances. The results indicate that the statistical and hybrid models show better rainfall predictions than NMME-EM and NMME-BMA models, which have good predictability only in southern China. In the 2011 China winter-spring drought event, the statistical model well predicted the spatial extent and severity of drought nationwide, although the severity was underestimated in the mid-lower reaches of Yangtze River (MLRYR) region. The NMME-EM and NMME-BMA models largely overestimated rainfall in northern and western China in 2011 drought. In the 2013 China summer drought, the NMME-EM model forecasted the drought extent and severity in eastern China well, while the statistical and hybrid models falsely detected negative precipitation anomaly (NPA) in some areas. Model ensembles such as multiple statistical approaches, multiple dynamic models or multiple hybrid models for drought predictions were highlighted. These conclusions may be helpful for drought prediction and early drought warnings in China.
Managing the Water-Energy-Food Nexus: Opportunities in Central Asia J. Hydrol. (IF 3.483) Pub Date : 2017-12-19 Shokhrukh-Mirzo Jalilov, Saud A. Amer, Frank A. Ward
This article examines impacts of infrastructure development and climate variability on economic outcomes for the Amu Darya Basin in Central Asia. It aims to identify the most economically productive mix of expanded reservoir storage for economic benefit sharing to occur, in which economic welfare of all riparians is improved. Policies examined include four combinations of storage infrastructure for each of two climate futures. An empirical optimization model is developed and applied to identify opportunities for improving the welfare of Tajikistan, Uzbekistan, Afghanistan, and Turkmenistan. The analysis 1) characterizes politically constrained and economically optimized water-use patterns for these combinations of expanded reservoir storage capacity, 2) describes Pareto-Improving packages of expanded storage capacity that could raise economic welfare for all four riparians, and accounts for impacts for each of two climate scenarios. Results indicate that a combination of targeted water storage infrastructure and efficient water allocation could produce outcomes for which the discounted net present value of benefits are favorable for each riparian. Results identify a framework to provide economic motivation for all riparians to cooperate through development of water storage infrastructure. Our findings illustrate the principle that development of water infrastructure can expand the negotiation space by which all communities can gain economic benefits in the face of limited water supply. Still, despite our optimistic findings, patient and deliberate negotiation will be required to transform potential improvements into actual gains.
Validation of 2D flood models with insurance claims J. Hydrol. (IF 3.483) Pub Date : 2017-12-19 Andreas Paul Zischg, Markus Mosimann, Daniel Benjamin Bernet, Veronika Röthlisberger
Flood impact modelling requires reliable models for the simulation of flood processes. In recent years, flood inundation models have been remarkably improved and widely used for flood hazard simulation, flood exposure and loss analyses. In this study, we validate a 2D inundation model for the purpose of flood exposure analysis at the river reach scale. We validate the BASEMENT simulation model with insurance claims using conventional validation metrics. The flood model is established on the basis of available topographic data in a high spatial resolution for four test cases. The validation metrics were calculated with two different datasets; a dataset of event documentations reporting flooded areas and a dataset of insurance claims. The model fit relating to insurance claims is in three out of four test cases slightly lower than the model fit computed on the basis of the observed inundation areas. This comparison between two independent validation data sets suggests that validation metrics using insurance claims can be compared to conventional validation data, such as the flooded area. However, a validation on the basis of insurance claims might be more conservative in cases where model errors are more pronounced in areas with a high density of values at risk.
Temporal rainfall disaggregation using a multiplicative cascade model for spatial application in urban hydrology J. Hydrol. (IF 3.483) Pub Date : 2016-01-23 H. Müller, U. Haberlandt
Rainfall time series of high temporal resolution and spatial density are crucial for urban hydrology. The multiplicative random cascade model can be used for temporal rainfall disaggregation of daily data to generate such time series. Here, the uniform splitting approach with a branching number of 3 in the first disaggregation step is applied. To achieve a final resolution of 5 min, subsequent steps after disaggregation are necessary. Three modifications at different disaggregation levels are tested in this investigation (uniform splitting at Δt = 15 min, linear interpolation at Δt = 7.5 min and Δt = 3.75 min). Results are compared both with observations and an often used approach, based on the assumption that a time steps with Δt = 5.625 min, as resulting if a branching number of 2 is applied throughout, can be replaced with Δt = 5 min (called the 1280 min approach). Spatial consistence is implemented in the disaggregated time series using a resampling algorithm. In total, 24 recording stations in Lower Saxony, Northern Germany with a 5 min resolution have been used for the validation of the disaggregation procedure. The urban-hydrological suitability is tested with an artificial combined sewer system of about 170 hectares. The results show that all three variations outperform the 1280 min approach regarding reproduction of wet spell duration, average intensity, fraction of dry intervals and lag-1 autocorrelation. Extreme values with durations of 5 min are also better represented. For durations of 1 h, all approaches show only slight deviations from the observed extremes. The applied resampling algorithm is capable to achieve sufficient spatial consistence. The effects on the urban hydrological simulations are significant. Without spatial consistence, flood volumes of manholes and combined sewer overflow are strongly underestimated. After resampling, results using disaggregated time series as input are in the range of those using observed time series. Best overall performance regarding rainfall statistics are obtained by the method in which the disaggregation process ends at time steps with 7.5 min duration, deriving the 5 min time steps by linear interpolation. With subsequent resampling this method leads to a good representation of manhole flooding and combined sewer overflow volume in terms of hydrological simulations and outperforms the 1280 min approach.
A conditional stochastic weather generator for seasonal to multi-decadal simulations J. Hydrol. (IF 3.483) Pub Date : 2015-12-23 Andrew Verdin, Balaji Rajagopalan, William Kleiber, Guillermo Podestá, Federico Bert
We present the application of a parametric stochastic weather generator within a nonstationary context, enabling simulations of weather sequences conditioned on interannual and multi-decadal trends. The generalized linear model framework of the weather generator allows any number of covariates to be included, such as large-scale climate indices, local climate information, seasonal precipitation and temperature, among others. Here we focus on the Salado A basin of the Argentine Pampas as a case study, but the methodology is portable to any region. We include domain-averaged (e.g., areal) seasonal total precipitation and mean maximum and minimum temperatures as covariates for conditional simulation. Areal covariates are motivated by a principal component analysis that indicates the seasonal spatial average is the dominant mode of variability across the domain. We find this modification to be effective in capturing the nonstationarity prevalent in interseasonal precipitation and temperature data. We further illustrate the ability of this weather generator to act as a spatiotemporal downscaler of seasonal forecasts and multidecadal projections, both of which are generally of coarse resolution.
A preliminary assessment of GPM-based multi-satellite precipitation estimates over a monsoon dominated region J. Hydrol. (IF 3.483) Pub Date : 2016-01-23 Satya Prakash, Ashis K. Mitra, Amir AghaKouchak, Zhong Liu, Hamidreza Norouzi, D.S. Pai
Following the launch of the Global Precipitation Measurement (GPM) Core Observatory, two advanced high resolution multi-satellite precipitation products namely, Integrated Multi-satellitE Retrievals for GPM (IMERG) and Global Satellite Mapping of Precipitation (GSMaP) version 6 are released. A critical evaluation of these newly released precipitation data sets is very important for both the end users and data developers. This study provides a comprehensive assessment of IMERG research product and GSMaP estimates over India at a daily scale for the southwest monsoon season (June to September 2014). The GPM-based precipitation products are inter-compared with widely used TRMM Multi-satellite Precipitation Analysis (TMPA), and gauge-based observations over India. Results show that the IMERG estimates represent the mean monsoon rainfall and its variability more realistically than the gauge-adjusted TMPA and GSMaP data. However, GSMaP has relatively smaller root-mean-square error than IMERG and TMPA, especially over the low mean rainfall regimes and along the west coast of India. An entropy-based approach is employed to evaluate the distributions of the selected precipitation products. The results indicate that the distribution of precipitation in IMERG and GSMaP has been improved markedly, especially for low precipitation rates. IMERG shows a clear improvement in missed and false precipitation bias over India. However, all the three satellite-based rainfall estimates show exceptionally smaller correlation coefficient, larger RMSE, larger negative total bias and hit bias over the northeast India where precipitation is dominated by orographic effects. Similarly, the three satellite-based estimates show larger false precipitation over the southeast peninsular India which is a rain-shadow region. The categorical verification confirms that these satellite-based rainfall estimates have difficulties in detection of rain over the southeast peninsula and northeast India. These preliminary results need to be confirmed in other monsoon seasons in future studies when the fully GPM-based IMERG retrospectively processed data prior to 2014 are available.
Some contents have been Reproduced by permission of The Royal Society of Chemistry.
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- Cryst. Growth Des.
- Curr. Opin. Chem. Eng.
- Curr. Opin. Colloid Interface Sci.
- Curr. Opin. Environ. Sustain
- Curr. Opin. Solid State Mater. Sci.
- Ecotox. Environ. Safe.
- Electrochem. Commun.
- Electrochim. Acta
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- Environ. Sci. Technol. Lett.
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- Eur. J. Inorg. Chem.
- Eur. J. Med. Chem.
- Eur. J. Org. Chem.
- Eur. Polym. J.
- J. Acad. Nutr. Diet.
- J. Agric. Food Chem.
- J. Alloys Compd.
- J. Am. Ceram. Soc.
- J. Am. Chem. Soc.
- J. Am. Soc. Mass Spectrom.
- J. Anal. Appl. Pyrol.
- J. Anal. At. Spectrom.
- J. Antibiot.
- J. Catal.
- J. Chem. Educ.
- J. Chem. Eng. Data
- J. Chem. Inf. Model.
- J. Chem. Phys.
- J. Chem. Theory Comput.
- J. Chromatogr. A
- J. Chromatogr. B
- J. Clean. Prod.
- J. CO2 UTIL.
- J. Colloid Interface Sci.
- J. Comput. Chem.
- J. Cryst. Growth
- J. Dairy Sci.
- J. Electroanal. Chem.
- J. Electrochem. Soc.
- J. Environ. Manage.
- J. Eur. Ceram. Soc.
- J. Fluorine Chem.
- J. Food Drug Anal.
- J. Food Eng.
- J. Food Sci.
- J. Funct. Foods
- J. Hazard. Mater.
- J. Hydrol.
- J. Ind. Eng. Chem.
- J. Inorg. Biochem.
- J. Magn. Magn. Mater.
- J. Mater. Chem. A
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- J. Mater. Chem. C
- J. Mater. Process. Tech.
- J. Mech. Behav. Biomed. Mater.
- J. Med. Chem.
- J. Membr. Sci.
- J. Mol. Catal. A Chem.
- J. Mol. Liq.
- J. Nat. Gas Sci. Eng.
- J. Nat. Prod.
- J. Nucl. Mater.
- J. Org. Chem.
- J. Photochem. Photobiol. C Photochem. Rev.
- J. Phys. Chem. A
- J. Phys. Chem. B
- J. Phys. Chem. C
- J. Phys. Chem. Lett.
- J. Porphyr. Phthalocyanines
- J. Power Sources
- J. Solid State Chem.
- J. Taiwan Inst. Chem. E.
- Macromol. Rapid Commun.
- Mass Spectrom. Rev.
- Mater. Chem. Front.
- Mater. Des.
- Mater. Horiz.
- Mater. Lett.
- Mater. Sci. Eng. A
- Mater. Sci. Eng. R Rep.
- Mater. Today
- Meat Sci.
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- Microchim. Acta
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- Mol. Biosyst.
- Mol. Cancer Ther.
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- Mol. Pharmaceutics
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- Nano Energy
- Nano Lett.
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- Neurochem. Int.
- New J. Chem.
- NPG Asia Mater.
- npj 2D Mater. Appl.
- npj Comput. Mater.
- npj Flex. Electron.
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- npj Sci. Food
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- Photochem. Photobiol. Sci.
- Phys. Chem. Chem. Phys.
- Phys. Life Rev.
- PLOS ONE
- Polym. Chem.
- Polym. Degrad. Stabil.
- Polym. J.
- Polym. Rev.
- Powder Technol.
- Proc. Combust. Inst.
- Prog. Cryst. Growth Ch. Mater.
- Prog. Energy Combust. Sci.
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- Prog. Photovoltaics
- Prog. Polym. Sci.
- Prog. Solid State Chem.