Analysing spatio-temporal process and parameter dynamics in models to characterise contrasting catchments J. Hydrol. (IF 3.727) Pub Date : 2019-01-17 Björn Guse, Matthias Pfannerstill, Jens Kiesel, Michael Strauch, Martin Volk, Nicola Fohrer
The relevance of hydrological processes varies in space and time resulting in typical temporal patterns for catchments. Contrasting catchments moreover differ in their catchment metrics. Hydrological models claim to be able to reproduce typical temporal patterns of dominant processes using site-specific model parameters. Thus, patterns of temporal dynamics in dominant modelled processes and their corresponding dominant parameters are a fingerprint of how a model represents the hydrological behaviour of a catchment and how these process patterns vary between contrasting catchments.In this study, we demonstrate how catchment metrics, modelled processes and parameter dominances can be jointly used to characterise catchments. We assess how catchment characteristics are represented in spatio-temporal process dynamics in models and how to understand the reasons for hydrological (dis)similarity among catchments along a landscape gradient. For this purpose, catchment metrics which characterise contrasting landscapes (lowland, mid-range mountain and alpine catchments) are related to dominant processes and parameters which were provided by a temporally resolved sensitivity analysis (TEDPAS) and simulations of a hydrological model.Our study shows that the applied model is able to represent the different processes and their seasonal variability according to the specific hydrological conditions of the study catchments. By analysing catchment metrics, modelled processes and model parameters jointly, we show that the largest differences are identified for the alpine catchment, whilst similarities are found among the other catchments. Following a landscape gradient, high flow phases are dominated by different flow components. In contrast, the model shows groundwater dominance in low flow phases in non-alpine catchments while in the alpine catchment low flows in winter are mainly controlled by snow processes. The joint analysis of catchment metrics, temporal dynamics of dominant processes and parameters can therefore be used to better disentangle similarities and differences among catchments from different landscapes.
Geochemical evolution of thermal waters in carbonate – evaporitic systems: the triggering effect of halite dissolution in the dedolomitisation and albitisation processes J. Hydrol. (IF 3.727) Pub Date : 2019-01-16 M. Blasco, L.F. Auqué, M.J. Gimeno
A hybrid game theory and mathematical programming model for solving trans-boundary water conflicts J. Hydrol. (IF 3.727) Pub Date : 2019-01-15 Yong Zeng, Jiangbin Li, Yanpeng Cai, Qian Tan, Chao Dai
In this research, a hybrid game theory and mathematical programming model (HGT-MPM) is proposed for solving trans-boundary water conflicts in Guanting reservoir basin (GRB) between two cities (i.e., Zhangjiakou and Beijing) in north China. A water allocation model, which considers both water quality and quantity, is developed for optimizing water use and pollutant discharge in the two cities, maximizing the net aggregate benefits from these activities and reducing the costs for water supply and pollution removal. The initial rights of water use and pollutant discharge are allocated to the cities of Beijing and Zhangjiakou, as two players based on the incorporation of a negotiation method for ill-defined water rights within the watershed. At this stage, equal treatment of every player’s benefit claim can be addressed. The strategy spaces of the two players are delineated through solving the proposed HGT-MPM with mutual benefit claim constraints. The Rubinstein bargaining solution method is employed to identify the equilibrium of bargaining. To achieve maximal benefits for the two players, starting from allocating the results of the second step, the concepts of Core and Nash solutions of cooperative games are used to generate stable basin-wide cooperative solutions. Both players find it beneficial to cooperate with side payment from the downstream to upstream. At this stage, the principle of maximum economic benefits is mainly considered. The results indicate that unclear initial water rights and pollutant discharge rights can be fairly defined through bilateral negotiations between upstream and downstream. Without side payment, the initial water rights and pollutant discharge allocation will be the final outcome, which is suboptimal, although it is better than the status quo in term of both total and individual benefits. Full cooperation with side payment leads to the greatest total net benefits and the greatest benefits to each individual city. The results not only provide a basis to allocate trans-jurisdictional water rights and pollutant discharge rights in an equal and efficient way but also provide certain inspirations for management policy improvement, such as establishing a water right trading system.
A post-event stratified random sampling scheme for monitoring event-based water quality using an automatic sampler J. Hydrol. (IF 3.727) Pub Date : 2019-01-15 J.S. Lessels, T.F.A. Bishop
Short rainfall events contribute to large portions of annual sediment and nutrient exports. Most water quality sampling schemes rely on regularly spaced temporal sampling and increasingly monitoring schemes are including a form of event-based sampling. A typical approach is to sample each event using equal intervals in time using an automatic sampler. The use of this form of sampling is systematic in nature and requires model-based statistics to be analysed correctly. Probabilistic based sampling methods allow for easier and more defendable statistical inference as the assumptions are not based on a model, rather they are based on the sample design. Several probabilistic methods have been developed, however these methods commonly require additional hardware to implement. In this paper we present a method using a stratified random sampling procedure for automatic samplers which does not require any additional hardware. Our approach is to divide the mean event hydrograph into strata based on key features such as the rising and falling limbs. Random sampling is applied within each strata. A problem of this approach is that the length of the event and strata must be defined before each event. We therefore outline how the samples can be post-stratified after each event based on the key hydrological components of each event. The sampling scheme is outlined using continuously sampled electrical conductivity and turbidity data of three events from a creek in south eastern Australia. Limited to 24 samples per event, estimated event mean CIs were within the observed event means for all three events. This method provides a flexible low-cost sampling scheme providing unbiased estimates of key event hydrological components which can be easily adapted by catchment management authorities.
PUB in Québec: A robust geomorphology-based deconvolution-reconvolution framework for the spatial transposition of hydrographs J. Hydrol. (IF 3.727) Pub Date : 2019-01-14 Stéphane Ecrepont, Christophe Cudennec, François Anctil, Anne Jaffrézic
The flexibility and parsimony of transpositioning hydrographs using geomorphology-based deconvolution-reconvolution frameworks is particularly adapted to prediction in ungauged basins. Although already tested in semi-arid and oceanic-temperate hydro-climates, its predictions must be reproducible in a variety of hydrological contexts. The present study explores the nivo-pluvial hydrological regime using geomorphology-based hydrograph transposition between 21 gauged catchments ranging from 1.1 to 4466.4 km2 in Québec, Canada, and constitutes a case study in prediction in ungauged basins. Three metrics were used to assess model performance for each donor-target pair: Nash Sutcliffe Efficiency (NSE), NSE calculated for the square root of discharge (NSEsqrt), and Volumetric Efficiency. The classic transposition of hydrographs using the specific discharge ratio, used as a reference, was almost always outperformed by the geomorphology-based approach. Good but seasonally variable performance values were obtained for several pairs of catchments, revealing simultaneous structural and situational effects. The difference in size, the physical distance between the gauged donor and its target ungauged catchment, and the season influenced the performance of the geomorphology-based transposition.
Is observation uncertainty masking the signal of land use change impacts on hydrology? J. Hydrol. (IF 3.727) Pub Date : 2019-01-14 Solomon Gebreyohannis Gebrehiwot, Giuliano Di Baldassarre, Kevin Bishop, Sven Halldin, Lutz Breuer
Analysis of hydrological impacts of land use change raises questions about whether, and how much, such impacts are misrepresented because of errors in river flow observations. In this paper, land use change impacts (represented by changes in watershed storage) and different ranges of discharge measurement error are compared to assess how errors in discharge measurement can potentially mask a land use change impact. Using a watershed from the Ethiopian highlands to exemplify this, we simulated five different levels of land use change impacts with five levels of watershed storage reductions (from 10% to 50% change) and the associated time series of runoff. Different levels of observation error were then introduced into these artificial time series. Comparison was made between every pair, i.e. a time series derived from a certain level of land use change (storage reduction) versus a time series corresponding to a given level of observation error, using a step-change t-test. Significant step-changes between pairs define the detectability of land use change impact. The analysis was made for the entire 30-year time series as well as for the most extreme annual weather conditions. The results showed that for the average year and wettest year, 75% or more error in observed discharge masks the maximum simulated land use change impact on hydrology. In dry years, a 50% error in discharge is enough to mask the same impact. Knowing (and improving) the level of data quality contributes to a better understanding of hydrological uncertainties and improves the precision in assessing land use change impacts. Both of these are essential elements in water resources development planning.
A depth-averaged non-cohesive sediment transport model with improved discretization of flux and source terms J. Hydrol. (IF 3.727) Pub Date : 2019-01-14 Jiaheng Zhao, Ilhan Özgen–Xian, Dongfang Liang, Tian Wang, Reinhard Hinkelmann
This paper presents novel flux and source term treatments within a Godunov-type finite volume framework for predicting the depth-averaged shallow water flow and sediment transport with enhanced the accuracy and stability. The suspended load ratio is introduced to differentiate between the advection of the suspended load and the advection of water. A modified Harten, Lax and van Leer Riemann solver with the contact wave restored (HLLC) is derived for the flux calculation based on the new wave pattern involving the suspended load ratio. The source term calculation is enhanced by means of a novel splitting-point implicit discretization. The slope effect is introduced by modifying the critical shear stress, with two treatments being discussed. The numerical scheme is tested in five examples that comprise both fixed and movable beds. The model predictions show good agreement with measurement, except for cases where local three-dimensional effects dominate.
Aridland spring response to mesoscale precipitation: implications for groundwater-dependent ecosystem sustainability J. Hydrol. (IF 3.727) Pub Date : 2019-01-14 W.M. Robertson, J.T. Allen, B.D. Wolaver, J.M. Sharp
Aridland springs maintain groundwater-dependent habitats for aquatic and terrestrial species. San Solomon Spring (Texas, USA) is part of a regional karst spring complex in the Chihuahuan Desert that supports several species of federal and state conservation interest. However, drought, climatic variability, and groundwater abstraction threaten discharge and water quality. In the surrounding Delaware Basin, expansion in unconventional oil and gas development using hydraulic fracturing may increase demands on aquifers that also provide flows to the springs. A critical knowledge gap limiting habitat conservation and sustainable groundwater abstraction is that the flow system is not well understood. While the source of most spring discharge is from a Pleistocene-recharged regional flow system, evidence suggests that a modern local flow component provides fresh water influx. However, the exact sources, mechanisms, and timing of localized recharge are unknown. To address these questions, this study combined long-term in-situ spring water quality monitoring (specific conductance, turbidity, and temperature) data with weather station-corrected 4 km gridded precipitation data to quantify the lag response at San Solomon Springs to mesoscale storm events and to delineate potential local recharge zones. Between April 2011 and March 2012, 26 event-flow responses were documented, with an average lag of 43 days between storm event and spring response. Response time varied depending on storm magnitude, spatial extent, and antecedent soil moisture conditions. Cross-correlation analysis of spatially distributed precipitation indicated zones of potential local recharge in the mountain block/mountain front zones and alluvial channels issuing from the Davis Mountains. Some local flow paths appear to cross known watershed boundaries, suggesting that groundwater abstraction in sensitive capture zones should be managed carefully to maintain spring flows and conserve habitats.
The role of landscape properties, storage and evapotranspiration on variability in streamflow recessions in a boreal catchment J. Hydrol. (IF 3.727) Pub Date : 2019-01-14 R.H. Karlsen, K. Bishop, T. Grabs, M. Ottosson-Löfvenius, H. Laudon, J. Seibert
Streamflow recession analysis provides valuable insights into catchment functioning that can be related to runoff generation, storage retention and baseflow dynamics. As an integrated characteristic, recession analysis is particularly useful in catchment comparison studies to help explain drivers of spatial and temporal variability in hydrological behavior. Here, five years of hourly streamflow data from 14, partly nested, catchments within a 68 km2 boreal forest landscape in Northern Sweden were used to explore spatiotemporal variation in hydrological processes through recession analysis. The aim of this study was to better understand spatial variation in runoff generation and storage-discharge dynamics across the landscape, as well as the relation to landscape properties. Due to high collinearity between variables, partial least square regression was used to quantify the associations between recession characteristics and catchment properties, as well as to identify key variables controlling recession behavior. We analyzed recession characteristics using both an aggregated approach including all recession data and individual recession events. The analyses based on individual recession events, indicated that catchment topography, quantified by indices such as mean slope or elevation above the stream network, is a primary control on the recession behavior during relatively high flows, whereas catchment area gains importance when flows are relatively low. The proportion of sediment and deep soils also controlled recession behavior. Furthermore, we found that recession characteristics are influenced by both evapotranspiration (ET) and proxies of antecedent catchment storage, but that the patterns were different depending on catchment properties. ET was less influential in catchments with deeper soils and larger catchment area. Shifts in recession rates were primarily related to variation in storage, with faster streamflow recessions occurring during periods with low storage. The results demonstrate the influence of catchment properties on recession behavior, and we found great value in analyzing individual recession events for an increased understanding of spatial and temporal recession characteristics. When recession properties were lumped together, the relationships to catchment characteristics were obscured. This indicates the value of more detailed analyses, at least under the strongly seasonal hydroclimatic conditions of this site.
The importance of the number of points, transect location and interpolation techniques in the analysis of bathymetric measurements J. Hydrol. (IF 3.727) Pub Date : 2019-01-14 Daniel C. Diaconu, Petre Bretcan, Daniel Peptenatu, Danut Tanislav, Emanuel Mailat
Determining the bathymetric properties of a river, lake or reservoir is important for many reasons because it identifies location of sections with sedimentation or erosion which indicate the key processes and biophysical habitat status. This study used observational data of a 5 km section of the Danube River (transformed into a reservoir after 1972) to determine the best GIS interpolation method and the optimal number of sampling points to get an accurate description of the riverbed. Nine interpolation methods were used to generate bathymetric maps of the Danube course, between km 955 and km 950, in the area of Iron Gates reservoir, using a variable number of points (n = 1943; n = 4328; n = 17139), obtained by single beam echo sounder. Six methods of deterministic interpolation have been used: Inverse Distance Weighting (IDW) - criteria automatically determined (CAD) and manually determined (MD); Local Polynomial Interpolation (LPI) - criteria automatically determined (CAD) and manually determined (MD); Radial Basis Function (RBF) - fully regularized spline CRS; Radial Basis Function RBF - spline with tension SWT, and three geo-statistics methods: Ordinary Kriging - OK, Simple Kriging - SK, Universal Kriging - UK. Cross-validation and bathymetric Digital Elevation Models (DEM‘s) analysis were used to evaluate the accuracy of the estimated data and maps. The two interpolation methods, Inverse Distance Weighting (IDW-MD) and Simple Kriging (SK), provide satisfactory results, even in the case of a small number of points (n = 1943). If the number of measured points grows and a section grid (perpendicular/longitudinal) is developed, the DEM‘s bathymetric accuracy improves significantly, especially in the case of complex morphology, even if the positive and negative forms of the bed lead to sudden changes in the measured values. The obtained results revealed differences between the interpolation methods used, particularly in the case of a small number of points measured per perpendicular trajectories, but by the addition of points on longitudinal paths, a significant improvement of the bathymetric maps is obtained.
Explore an evolutionary recurrent ANFIS for modelling multi-step-ahead flood forecasts J. Hydrol. (IF 3.727) Pub Date : 2019-01-14 Yanlai Zhou, Shenglian Guo, Fi-John Chang
Reliable and precise multi-step-ahead flood forecasts are crucial and beneficial to decision makers for mitigating flooding risks. For a river basin undergoing fast urban development, its regional meteorological condition interacts frequently with intensive human activities and climate change, which gives rise to the non-stationary process between rainfall and runoff whose non-stationary features is difficult to be captured by a non-recurrent data-driven model with a static learning mechanism. This study proposes a recurrent Adaptive-Network-based Fuzzy Inference System (R-ANFIS) embedded with Genetic Algorithm and Least Square Estimator (GL) that optimize model parameters for making multi-step-ahead forecasts. The main merit of the proposed method (R-ANFIS(GL)) lies in capturing the features of the non-stationary process between rainfall and runoff series as well as in alleviating time-lag effects encountered in multi-step-ahead flood forecasting. To demonstrate model reliability and effectiveness, the R-ANFIS(GL) model was implemented to make multi-step-ahead forecasts from horizons t+1 up to t+8 for a famous benchmark chaotic time series and a flood inflow series of the Three Gorges Reservoir (TGR) in China. For comparison purpose, two ANFIS neural networks of different structures (one dynamic and one static neural networks) were also implemented. Numerical and experimental results indicated that the R-ANFIS(GL) model not only outperformed the two comparative networks but significantly enhanced the accuracy of multi-step-ahead forecasts for both chaotic time series and the reservoir inflow case during flood seasons, where effective mitigation of time-lag bottlenecks was achieved. We demonstrated that the R-ANFIS(GL) model could suitably configure the complex non-stationary rainfall-runoff process and effectively integrate the monitored rainfall and discharge data with the latest outputs of the model so that the time shift problem could be alleviated and model reliability as well as forecast accuracy for future horizons could be significantly improved.
Modeling reference evapotranspiration in island environments: Assessing the practical implications J. Hydrol. (IF 3.727) Pub Date : 2019-01-14 Jalal Shiri
Among the reference evapotranspiration (ETo) equations, temperature-based and radiation-based equations have been accepted as promising approaches when the available meteorological data are limited. The present paper aimed at assessing this general implication in island environments, which might be generally volatile than the interior/coastal zones. Using data from five island locations of Iran, daily ETo values were calculated by the benchmark FAO-Penman-Monteith (FAO56-PM) model, then the commonly used temperature-, radiation- and mass transfer-based ETo equations were evaluated against the benchmark values. An additional heuristic modeling of ETo was also performed through employing gene expressions programming (GEP), evaluated by k-fold testing. The obtained outcomes showed that the calibrated mass transfer-based equations and their corresponded GEP models generally surpassed the other applied models in the studied locations. This criticized the commonly accepted implication about applying temperature/radiation- based models in case of data scarcity for different locations. Nevertheless, analysis of the temporal variations of models performance among test years showed that fixing the minimum test size as 1 year for local k-fold testing (that is the case in similar studies) might be misleading as it could not show the fluctuations in modeling accuracy well. A minimum affordable size of at least one growing season was instead selected, tested and recommended in the current research.
Observing water level extremes in the Mekong River Basin: The benefit of long-repeat orbit missions in a multi-mission satellite altimetry approach J. Hydrol. (IF 3.727) Pub Date : 2019-01-14 Eva Boergens, Denise Dettmering, Florian Seitz
Single-mission altimetric water level observations of rivers are spatially and temporally limited, and thus they are often unable to quantify the full extent of extreme flood events. Moreover, only missions with a short-repeat orbit, such as Envisat, Jason-2, or SARAL, could provide meaningful time series of water level variations directly. However, long or non-repeat orbit missions such as CryoSat-2 have a very dense spatial resolution under the trade-off of a repeat time insufficient for time series extraction. Combining data from multiple altimeter missions into a multi-mission product allows for increasing the spatial and temporal resolution of the data. In this study, we combined water level data from CryoSat-2 with various observations from other altimeter missions in the Mekong River Basin between 2008 and 2016 into one multi-mission water level time series using the approach of universal kriging. In contrast to former multi-mission altimetry methods, this approach allows for the incorporation of CryoSat-2 data as well as data from other long or non-repeat orbit missions, such as Envisat-EM or SARAL-DP. Additionally, for the first time, data from tributaries are incorporated. The multi-mission time series including CryoSat-2 data adequately reflects the general inter-annual flood behaviour and the extreme floodings in 2008 and 2011. It performs better than single-mission time series or multi-mission time series based only on short-repeat orbit data. The Probability of Detection of the floodings with the multi-mission altimetry was around 80% while Envisat and Jason-2 single-mission altimetry could only detect around 40% of the floodings correctly. However, small flash floods still remain undetectable.
To what extent does hydrological connectivity control dynamics of faecal indicator organisms in streams? Initial hypothesis testing using a tracer-aided model J. Hydrol. (IF 3.727) Pub Date : 2019-01-14 Aaron J. Neill, Doerthe Tetzlaff, Norval J.C. Strachan, Chris Soulsby
The role of hydrological connectivity in driving the dynamics of faecal indicator organisms (FIOs) in streams is poorly characterised. Here, we demonstrate how a tracer-aided hydrological model can be used within a coupled modelling approach to explore the role of connectivity in governing stream faecal coliform (FC) dynamics. To do so, we tested a hypothesis that in northern upland catchments, the dynamics of hydrological connectivity between major landscape units (hillslopes and riparian zone) and the stream exert a dominant control on stream FC loads by facilitating generation of runoff-driven FC fluxes. This hypothesis was conceptualised within a simple FC model that was coupled to a tracer-aided hydrological model developed for a small (3.2 km2) data-rich catchment in NE Scotland. The model was dual-calibrated to daily discharge and stable isotope data for the period August 2008 to September 2009; stream FC loads were also simulated but not used as a calibration target. Behavioural models successfully captured the general dynamics of the discharge and isotope data (average Kling-Gupta efficiencies of 0.72 and 0.53, respectively), providing confidence in the realism of simulated hydrological processes. The models simulated a seasonally-varying role of connectivity in driving stream FC loads. In summer, connectivity of the catchment hillslope was crucial in providing a source of FC to the riparian zone for transfer to the stream; this countered the decline in fresh FC input to the riparian zone in summer which reflected the seasonal movement of red deer (the principal source of FC) onto higher ground. In winter when this seasonal movement caused FC to be predominantly stored in the riparian zone, simulated hillslope connectivity primarily provided water to the riparian zone that permitted increased runoff generation and associated mobilisation of FC. Comparison of observed and simulated stream FC loads revealed model performance to be variable (R2 range: 0-0.34). The better performance of the model in summer was consistent with hydrological connectivity being a dominant control on stream FC loads at this time. However, failure of the model to capture low FC loads in winter indicated that additional processes not considered in the model may also govern stream FC dynamics during this period. Incorporating the impact of freeze-thaw cycles on FC mortality, or a dilution effect of hillslope connectivity in winter, could be potential next steps in refining the hypothesis conceptualised in the FC model presented here. The novel coupled modelling approach used in this study successfully allowed a hypothesised role of connectivity in driving stream FC dynamics to be tested, contextualised by the accuracy of discharge and isotope-tracer simulations as indicators of hydrological process realism. Therefore, coupling FIO and tracer-aided hydrological models has clear promise for furthering understanding of FIO dynamics, which is a vital precursor to the successful management of microbial water quality. Based on the experiences in this study, a “roadmap” for the future development and application of coupled approaches is also presented.
On the lower bound of Budyko curve: the influence of precipitation seasonality J. Hydrol. (IF 3.727) Pub Date : 2019-01-14 Jianyu Fu, Weiguang Wang
As a boundary condition, the lower bound is a prerequisite for constructing the Budyko framework. However, the traditional lower bound i.e., the horizontal axis is an analytical boundary without considering realistic conditions. In fact, under real-word condition, the lower bound of Budyko curves, representing the maximum value of water yield, should be located above the horizontal axis due to complicated constraints from basin characteristics, especially the precipitation seasonality, a key driver of runoff yield and a dominant factor in constructing Budyko framework. Thus, this study focused on exploring the reasonable location of the lower bound by adequately analyzing potential influence of precipitation seasonality. To do that, multiple hydrological simulations in basins under different climate and topography conditions were developed based on various precipitation scenarios constructed by using Markov chain with full range of precipitation seasonality. To fully understand the influence from precipitation seasonality on the lower bound, the water-energy supply and the basin characteristics were fixed by aridity index and hydrological model parameters, respectively. The results reveal a positive correlation between runoff coefficient and precipitation seasonality with an obvious higher location above the horizontal axis, indicating the horizontal axis is imprecise to describe the upper bound of runoff yield under real-word condition. Furthermore, a potential location of the lower bound above the horizontal axis in Budyko space was found based on runoff yield mechanism under real basin condition, representing a more appropriate boundary condition of Budyko framework.
On Comparison of Two-Level and Global Optimization Schemes for Layout Design of Storage Ponds J. Hydrol. (IF 3.727) Pub Date : 2019-01-14 Wei Lu, Xiaosheng Qin, Jianjun Yu
Optimization techniques have emerged as robust tools to aid the planning and design of urban drainage facilities in cost-effective ways. Such an effort was traditionally aided by heuristic methods (like genetic algorithm), which was generally time-consuming and also challenging in reaching convergence for large-scale problems with wide decision spaces. This study proposed a novel optimization method, denoted as two-level optimization (TO) scheme, for supporting rainwater storage pond design in an urban drainage system. Polynomial regression models were established as surrogate models to facilitate the solution of the optimization framework using traditional iteration algorithm. The TO scheme firstly sought the optimal layout of storage ponds on tributary sub-watersheds, and then proceeded to that of the mainstream one to yield the final solution. Through a case study, the TO scheme was compared with the traditional global optimization (GO) scheme where the physical simulation model was dynamically linked with genetic algorithm (GA) to seek the global optimal solution. The performance of two schemes under different constraint settings was analyzed. Effects of related issues such as start-point selection and mainstream design on tributary sub-watersheds were also discussed. The results showed that the proposed TO scheme is a prominent alternative to the traditional GO scheme to support urban water managers for a more science-based decision making towards storage pond implementation in large-scale practical problems.
The role of cross-correlation between precipitation and temperature in basin-scale simulations of hydrologic variables J. Hydrol. (IF 3.727) Pub Date : 2019-01-14 S.B. Seo, R. Das Bhowmik, A. Sankarasubramanian, G. Mahinthakumar, M. Kumar
Uncertainty in climate forcings causes significant uncertainty in estimating streamflow and other land-surface fluxes in hydrologic model simulations. Earlier studies primarily analyzed the importance of reproducing cross-correlation between precipitation and temperature (P-T cross-correlation) using various downscaling and weather generator schemes, leaving out how such biased estimates of P-T cross-correlation impact streamflow simulation and other hydrologic variables. The current study investigates the impacts of biased P-T cross-correlation on hydrologic variables using a fully coupled hydrologic model (Penn-state Integrated Hydrologic Model, PIHM). For this purpose, a synthetic weather generator was developed to generate multiple realizations of daily climate forcings for a specified P-T cross-correlation. Then, we analyzed how reproducing/neglecting P-T cross-correlation in climate forcings affect the accuracy of a hydrologic simulation. A total of 50 synthetic data sets of daily climate forcings with different P-T cross-correlation were forced into to estimate streamflow, soil moisture, and groundwater level under humid (Haw River basin in NC, USA) and arid (Lower Verde River basin in AZ, USA) hydroclimate settings. Results show that climate forcings reproducing the P-T cross-correlation yield lesser root mean square errors in simulated hydrologic variables (primarily on the sub-surface variables) as compared to climate forcings that neglect the P-T cross-correlation. Impacts of P-T cross-correlation on hydrologic simulations were remarkable to low flow and sub-surface variables whereas less significant to flow variables that exhibit higher variability. We found that hydrologic variables with lower internal variability (for example: groundwater and soil-moisture depth) are susceptible to the bias in P-T cross-correlation. These findings have potential implications in using univariate linear downscaling techniques to bias-correct GCM forcings, since univariate linear bias-correction techniques reproduce the GCM estimated P-T cross-correlation without correcting the bias in P-T cross-correlation.
Quantifying the three-dimensional effects of anisotropic soil horizons on hillslope hydrology and stability J. Hydrol. (IF 3.727) Pub Date : 2019-01-14 Giuseppe Formetta, Giovanna Capparelli
Rainfall-induced shallow landslides cause significant damage involving loss of life and property. Many hydrological processes such as rainfall infiltration, soil water dynamics, and slope stability are controlled by unsaturated soil properties, such as unsaturated hydraulic conductivity. Natural soils often exhibit a certain degree of anisotropy in hydraulic conductivity due to stratification and compaction mechanisms in soil formation processes.In this paper we investigate the effect of soil hydraulic conductivity anisotropy (SHCA) on hillslope hydrology and stability using a three-dimensional hydrological model coupled with a probabilistic infinite slope stability model. The model is applied in two independent case studies. The first aims to quantify the combined effect of different anisotropy ratios (lateral/normal saturated hydraulic conductivity) and hillslope morphologies (convex, concave, and planar) on slope stability. Anisotropy ratios are assumed in this case higher than one (1, 2, 10). Results show that increasing the anisotropy ratio (from 1 to 10) anticipates the failure time (from 12 to 9 hours after the start of rainfall) and that in concave morphologies the unstable area tends to be wider than planar and convex. The second application aims to simulate the soil moisture dynamic and the probability of failure at different depths (100, 500, and 900 mm) of a stratified volcanic soil, making leverage on the model flexibility to accommodate SHCA. No assumptions are made on the anisotropy ratio in this case study. Our results, based on model parameter calibration and verification against in-situ soil moisture measurements during the year 2009, showed good model performance in simulating the soil moisture dynamic (Kling-Gupta Efficiency higher than 0.78) and confirmed no failure for the simulated year. The promising results support the aspiration that the physically based hydrological model can complement and improve the current predictions of landslide early warning systems.
Do debris-covered glaciers demonstrate distinctive hydrological behaviour compared to clean glaciers? J. Hydrol. (IF 3.727) Pub Date : 2019-01-14 C.L. Fyffe, B.W. Brock, M.P. Kirkbride, D.W.F. Mair, N.S. Arnold, C.Smiraglia, G. Diolaiuti, F. Diotri
Supraglacial debris is known to strongly influence the distribution of glacier surface melt. Since melt inputs drive the formation and evolution of glacial drainage systems, it should follow that the drainage systems of debris-covered glaciers will differ from those of debris-free glaciers. This would have implications for the proglacial runoff regime, subglacial erosion and glacier dynamics. This paper presents analysis of return curves from 33 successful dye injections into the extensively debris-covered Miage Glacier, Italian Alps. It demonstrates that the spatial distribution of supraglacial debris influences the structure and seasonal evolution of the glacial drainage system. Where the debris cover is continuous, melt is lower and the surface topography is chaotic, with many small supraglacial catchments. These factors result in an inefficient englacial/subglacial drainage network beneath continuous debris, which drains to the conduit system emanating from the upper ablation zone. Melt rates are high in areas of clean and dirty ice above the continuous debris. Runoff from these areas is concentrated by inter-moraine troughs into large supraglacial streams, which encourages the early-season development of an efficient englacial/subglacial conduit system downstream of this area. Drainage efficiency from the debris-covered area increases over the melt season but dye-trace transit velocity remains lower than from moulins on the upper glacier. Future runoff models should account for the influence of supraglacial debris on the hydrological system.
An analytical solution for cyclic flow of two immiscible phases J. Hydrol. (IF 3.727) Pub Date : 2019-01-14 Avinoam Rabinovich
Characterization of the long-term changes in moisture, clouds and precipitation in the ascending and descending branches of the Hadley Circulation J. Hydrol. (IF 3.727) Pub Date : 2019-01-14 Sneha Susan Mathew, Karanam Kishore Kumar
Climate model simulations and observations show that there is a poleward expansion of the Hadley Circulation (HC) as well as a strengthening of the hydrological cycle in a warming climate. However, to establish a relation between the two phenomena in present day climate, simultaneous investigations of the HC and hydrological cycle changes using observational/reanalysis data are necessary, which is limited as compared to model simulations. In this regard, the present study employs relative humidity (RH), cloud fraction (CF) and precipitation (RF) parameters of the hydrological cycle and analyse their long term changes within the HC ascending and descending regions, simultaneously. Long term RH and CF data (1979-2016) are obtained from ERA-I reanalysis, and RF from GPCP precipitation dataset. The boundaries of the HC are identified using the mass Meridional Stream Function (MSF) metric, a metric that can track the mass motion in the atmosphere in the meridional direction. The analysis brings out the spatial pattern of the distribution of trends in hydrological parameters within the HC boundaries. The trends are observed to be significantly positive at the edges of the HC ascending region and significantly negative in the regions near the HC edges, insignificant (and in some cases, negative) in the deep tropics. This pattern is more or less consistent in RH, CF, as well as RF parameters. Thus the study shows that there are regions of positive as well as negative trends within the both ascending and descending regions. The results are found to be in accordance with the poleward expansion of HC and strengthening of the hydrological cycle. Besides, a northward shift in the HC ascending regions are also indicated from the analysis of the annual cycle of trend in precipitation. The current investigation is thus envisaged to contribute to further exploration on the relation between the HC changes and the intensification of the hydrological cycle in a warmer climate.
Dissipation of water in urban area, mechanism and modelling with the consideration of anthropogenic impacts: A Case Study in Xiamen J. Hydrol. (IF 3.727) Pub Date : 2019-01-14 Jinjun Zhou, Jiahong Liu, Dianyi Yan, Hao Wang, Zhongjing Wang, Weiwei Shao, Yong Luan
Dissipation of water (evapotranspiration and water vapor conversion in human water use activities) is one of the significant hydrological processes in urban area, which becomes more complicated with rapid urbanization. However, there are few systematic studies on water dissipation problems in urban area, and even the related concepts are unclear. This paper proposed the concept of urban water dissipation (UWD) to describe water vapor conversion in urban areas, and presented analysis on mechanism of UWD based on observing and monitoring experiments. The urban underlying surface was divided into five categories: buildings, paved ground, vegetation, water surface, and soil, in which the buildings have been scarcely discussed in terms of water dissipation. The dissipation of water in buildings plays a more and more important role in the urban water circulation system, as the water supply increases in urban areas. To reveal how much water is dissipated in the buildings, the main water dissipation processes in different kinds of buildings were analyzed, and the quantitative model was proposed. Based on the traditional evapotranspiration models for urban underlying surface and the proposed model for water dissipation in buildings, a new modelling system was built to simulate the total UWD. The new model system reflects the impact of human water use activities on urban water dissipation. It was applied in Xiamen city to simulate the UWD in 2000, 2005, 2010, and 2015. The results show that the UWD intensity increased with the urbanization process in Xiamen urban area in past 15 years. The UWD contribution rate increased for most land use types, except green land. For example, the water dissipation on residential land is the fastest growing one of all land use types, and its contribution rate surpassed that of green land to become the largest contributor in 2010. Because of the interference of strong human activities, the contribution rate of water dissipation on the social side continues increasing. The contribution rate of UWD on the social side was more than 40% in 2015, and it is still increasing.
The role of catchment soils and land cover on dissolved organic matter (DOM) properties in temperate lakes J. Hydrol. (IF 3.727) Pub Date : 2019-01-11 Margot Sepp, Toomas Kõiv, Peeter Nõges, Tiina Nõges
Optimization of fuzzy membership function of runoff forecasting error based on the optimal closeness J. Hydrol. (IF 3.727) Pub Date : 2019-01-11 Zhiqiang Jiang, Wenjie Wu, Hui Qin, Dechao Hu, Hairong Zhang
The forecasted runoff is an important input data for the daily operation of hydropower station, and the forecast accuracy directly affects its operation efficiency. However, the forecasting error is inevitable, and it is influenced by the input, the structural parameters and many human factors, it is not only random, but also has great fuzziness. Therefore, it is very important to study the fuzziness of runoff forecasting error and reveal its fuzzy distribution law to guide the actual operation of hydropower station. In view of this, this paper has carried out research work in the following two aspects. At the theoretical level, in order to make the establishment of fuzzy set more objective and scientific, based on different theoretical fuzzy distribution functions and the parameter optimization method, an overall framework of fuzzy membership function optimization model is proposed by coupling the optimal closeness criterion, which can make full use of the guiding role of practical experience and at the same time effectively avoid the difficulty of subjective choice. At the practical level, in order to quantify the fuzzy characteristics of runoff forecasting error, a quantification method for runoff forecasting error in fuzzy environment is proposed based on the Hamming closeness, Cauchy distribution, Normal distribution and Cusp Γ distribution. Taking the Jinxi hydropower station of Yalong River basin as the research object, the fuzzy membership functions of the fuzzy sets of runoff forecasting error under different flow intervals are calculated and optimized by the proposed method. The results show that the optimized Cusp Γ distribution can fit the actual data points better compared with Cauchy distribution and Normal distribution, and its average closeness can reach 0.979. So, the accurate mathematical expression of the fuzzy distribution law of runoff forecasting error under different flow intervals is well realized, which provides a good basis for the fuzzy risk analysis of hydropower station operation.
Two-phase extreme learning machines integrated with complete ensemble empirical mode decomposition with adaptive noise for multi-scale runoff prediction J. Hydrol. (IF 3.727) Pub Date : 2019-01-11 Xiaohu Wen, Qi Feng, Ravinesh C. Deo, Min Wu, Zhenliang Yin, Linshan Yang, Vijay P Singh
Expert systems in multi-scale runoff prediction are useful decision-making tools but the stochastic nature of hydrologic variables can pose challenges in attaining a reliable predictive model. This paper advocates a data-driven approach to design two-phase hybrid model (CVEE-ELM). The model utilizes complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) coupled with variational mode decomposition (VMD) for frequency resolution of the input data and extreme learning machines (ELM) as the objective model. In the first stage of the presented model design, frequencies in predictor-target series are uncovered, utilizing CEEMDAN where inputs are decomposed into Intrinsic Mode Functions (IMFs) and Residual (Res) series. The second stage entails a VMD approach, to decompose the yet-unresolved high frequencies (IMF1) into variational modes, discerning and establishing data attributes to be incorporated in ELM to simulate IMF, Res and VM series, aggregated as an integrative for runoff prediction. In evaluative phase, hybrid CVEE-ELM is cross-validated with a single-phase hybrid ELM and an autoregressive integrated moving average (ARIMA) model to benchmark its accuracy for predicting 1-, 3- and 6-month ahead runoff in Yingluoxia watershed, Northwestern China. Two-phase hybrid model exhibits superior accuracy at all lead times to accord with high correlations between observed and forecasted runoff, a relatively large Nash-Sutcliffe and Legate-McCabe Index. Taylor diagram depict the two-phase hybrid CVEE-ELM forecasts located close to a reference (perfect) model, with lower root-mean square centered difference, and a correspondingly large correlation for all forecast horizons, although the accuracy for shorter lead times (1-month) are better than the 3- and 6-month horizon. The study shows that the two-phase hybrid model is a preferred data-driven tool for decision-systems, particularly for hydrologic problems with stochastic data features, and thus, require reliable forecasts at multi-step horizons.
Experimental and modelling evidence of short-term effect of raindrop impact on hydraulic conductivity and overland flow intensity J. Hydrol. (IF 3.727) Pub Date : 2019-01-11 Claude Mügler, Olivier Ribolzi, Jean-Louis Janeau, Emma Rochelle-Newall, Keooudone Latsachack, Chanthamousone Thammahacksa, Marion Viguier, Emilie Jardé, Thierry Henri-Des-Tureaux, Oloth Sengtaheuanghoung, Christian Valentin
Tropical montane areas of Southeast Asia are exposed to high-intensity rainfall during the monsoon period. This is particularly problematic in areas where soils on steep slopes are cultivated as it can lead to heavy runoff, high soil erosion, and water pollution. The objective of this paper is to analyse the effect of the impact of raindrops on the dynamics of runoff on such steep fields. Experiments under simulated rainfall were performed at the plot scale (1 m2) to quantify water export from the surface of upland agricultural soils during overland flow events. Four 1 m2 plots were divided in duplicated treatment groups: (a) control with no amendments, and (b) amended with pig manure. Each plot was divided into two 0.5 m2 rectangular subplots. One subplot was designated as a rain splash treatment; the other sub-plot was covered with a 2 mm grid size wire screen that was located 12 cm above the soil surface. The purpose of the screen was to break the raindrops into fine droplets and to reduce fall height in order to drastically reduce their kinetic energy. Runoff was measured for each sub-plot. The results show that raindrop impact drastically enhances runoff generation on both bare soils and on manure amended soils. When the impact of raindrops was limited by screening, runoff was higher on amended soils than on bare soils.The temporal evolution of runoff was correctly modelled using a soil hydraulic conductivity that exponentially decreases over time of exposure to rainfall. Both experimental and modelling results showed that droplet energy induces a rapid evolution of the hydraulic properties of the soil surface due to crusting, resulting in a reduction of hydraulic conductivity and a concomitant increase in runoff rate.
Impacts of future land cover and climate changes on runoff in the mostly afforested river basin in North China J. Hydrol. (IF 3.727) Pub Date : 2019-01-11 Wenting Yang, Di Long, Peng Bai
The Luanhe River basin, the mostly afforested river basin in North China, has exhibited significant land use/land cover change (LUCC) under climate change that could jointly affect water availability of the basin in the future. This study examines both impacts of LUCC and climate change on runoff over the upper reaches of the Luanhe River basin. First, the land use in 2020 is predicted based on the Cellular Automata-Markov (CA-Markov). Second, a hydrological model (Soil Water Assessment Tools, SWAT) is set up for the baseline period 1961-1979 and driven primarily by outputs from five general circulation models (GCMs) under four representative concentration pathways (RCPs) (i.e., RCP2.6, RCP4.5, RCP6.0 and RCP8.5) for the period 2020-2030. Results show that the ensemble mean annual precipitation may increase under four RCPs for the period 2020-2030, with the maximum (470 mm/yr) and minimum (444 mm/yr) for RCP8.5 and RCP6.0, respectively, 1%-7% higher than the observed mean annual precipitation (441 mm/yr) during 1961-1979. The relationship between the runoff simulations and the RCPs under the 2020 land use scenario is nonlinear, with the maximum (57 mm/yr) and minimum (50 mm/yr) mean annual runoff depths under the RCP4.5 and RCP6.0 scenarios, respectively, ∼58% and ∼39% higher than the mean annual observed runoff depth (36 mm/yr) for the baseline period. The increase in forestland (∼56%) and decrease in agriculture land (∼ -30%) are remarkable for the period 1970-2020, driven primarily by afforestation implemented in the Luanhe River basin. LUCC would lead to a slight decrease in mean annual runoff, and the runoff only increases in summer but decreases in other three seasons. The decrease in surface runoff and groundwater discharge jointly results in the overall decrease in runoff due to LUCC. In general, the climate change impact will dominate runoff change for the study basin, though marked afforestation has taken place and is likely to continue in the future.
Numerical Test Of The Laboratory Evaporation Method Using Coupled Water, Vapor And Heat Flow Modelling J. Hydrol. (IF 3.727) Pub Date : 2019-01-11 Sascha C. Iden, Johanna R. Blöcher, Efstathios Diamantopoulos, Andre Peters, Wolfgang Durner
Laboratory evaporation experiments are used to determine soil hydraulic properties (SHP). In most cases, data are evaluated with the simplified evaporation method (SEM). Numerical simulations were used before to quantify the accuracy of the SEM and it was found that the method yields accurate estimates of SHP. However, previous tests neither accounted for heat flow, nor thermal fluxes of liquid water and water vapor, nor temperature effects on the transport properties. Since evaporation experiments are under most circumstances non-isothermal, past studies were therefore oversimplified and likely inaccurate. The objective of this article is to test the accuracy of the SEM using numerical simulations with a coupled model of water, vapor, and heat flow which is based on the Philip-de Vries theory and solves the surface energy balance. The model provides a state-of-the-art description of the fluxes of water, vapor and energy during laboratory evaporation from bare soil. We present simulation results for different soil textures and resistances to vapor flow between soil and air, and analyze the accuracy of the SEM using the simulated data. The resulting average error for the water retention curve is smaller than 0.0025 m3 m-3 and the relative error of hydraulic conductivity ranges from 5-15 % for sandy loam and clay loam. For sand, the error in conductivity is higher but the structural shape of the conductivity curve is still identified relatively well. Compared to previous analyses of the evaporation method assuming isothermal flow, the average error of the SEM turned out to be only slightly higher.
Accurate approximate semi-analytical solutions to the Boussinesq groundwater flow equation for recharging and discharging of horizontal unconfined aquifers J. Hydrol. (IF 3.727) Pub Date : 2019-01-11 Mohamed Hayek
The Boussinesq equation is usually used to describe one-dimensional unconfined groundwater movement. Solutions of this equation are important as they provide useful insights regarding the water table response to stream level variations and allow us to quantify the exchange flow between the stream and the aquifer. Due to the nonlinearity of the Boussinesq equation, the solutions are generally obtained using numerical methods. However, for certain classes of initial and boundary conditions there are both exact and approximate analytical solution techniques. This work focuses on the latter approach. A new mathematical technique for approximate solutions of the Boussinesq equation describing flow in horizontal unconfined aquifers induced by sudden change in boundary head is presented. The method applies to the problems of recharging and dewatering of an unconfined aquifer, and approximate solutions to both problems are derived. The solutions were obtained by introducing an empirical function with four parameters which might be obtained using a numerical fitting procedure. Results based on this technique were found to be easily calculated and to be in good agreement with those obtained using numerical calculation based on Runge-Kutta approach. A benchmark between the proposed solutions and five existing approximate analytical solutions shows that the present solutions are the most accurate approximate solutions among those tested. Applications of the solutions are presented in the context of estimating aquifer hydraulic parameters.
Incorporating Climate Model Similarities and Hydrologic Error Models to Quantify Climate Change Impacts on Future Riverine Flood Risk J. Hydrol. (IF 3.727) Pub Date : 2019-01-11 Kuk-Hyun Ahn, Yong-Oh Kim
Quantifying uncertainty in projecting climate change impact on flood frequency analysis is particularly relevant for long-term water resources planning and management. This study examines uncertainties arising from (1) a climate model, with and without accounting of intermodel similarities, (2) a hydrological model with two different error model definitions, which have previously received less attention in studies propagating uncertainty through climate change impacts on flood response. Through a Bayesian modeling framework, a proposed statistical framework is utilized to explore various definitions of sources of uncertainty and to develop a series of nested formulations that can evaluate the leverage of specific uncertainty sources in quantiles of future streamflow. To be specific, climate model similarity, hydrologic prediction error, and frequency analysis are formally modeled with an appropriate likelihood function. The quantiles inferred by each formulation are compared in a case study of the Yongdam Basin in Korea. Results indicate that variance in hydrologic response is underestimated if climate model similarities are ignored, and in many cases, the inferred quantiles of streamflow projection are biased accordingly. Furthermore, a simple error model used in defining hydrologic uncertainty may create incorrect information in determining the quantiles in streamflow projection. The approach presented here of quantifying uncertainty has the potential to better depict overall multi-source uncertainties in projections of climate change impacts on hydrologic response. Finally, our results also indicate that careful flood planning management may be required for the Yongdam Basin in future summers.
Understanding the role of regional water connectivity in mitigating climate change impacts on surface water supply stress in the United States J. Hydrol. (IF 3.727) Pub Date : 2019-01-11 Kai Duan, Peter V. Caldwell, Ge Sun, Steven G. McNulty, Yang Zhang, Erik Shuster, Bingjun Liu, Paul V. Bolstad
Surface water supply for a watershed relies on local water generated from precipitation and water connections with other watersheds. These connections are confined by topography and infrastructure, and respond diversely to stressors such as climate change, population growth, increasing energy and water demands. This study presents an integrative simulation and evaluation framework that incorporates the natural and anthropogenic water connections (i.e., stream flows, inter-basin water transfers, water withdrawals and return flows) among the 2,099 8-digit Hydrologic Unit Code (HUC-8) watersheds across the conterminous United States. The framework is then applied to investigate the potential impacts of changes in climate and water use on regional water availability and water stress (the ratio of demand to supply). Our projections suggest that highly water-stressed areas may expand from 14% to 18% and the stressed population would increase from 19% to 24% by 2070-2099. Climate-change mitigation practices (e.g., energy structure reform, technology innovation) could largely offset these trends by reducing demand and enhancing supply. At the watershed scale, the spatially inhomogeneous responses to future changes suggest that regional water connectivity could significantly buffer the potential stress escalations due to the redistribution of water resources and diverse changes in consumptive uses and water supplies in different source areas. However, the detrimental future changes (e.g., depleting river discharges, larger demands of water withdrawal) may aggravate conflicts over water rights among regions and challenge our current water infrastructure system. This study provides new insights into the critical role of regional water connectivity in water supply security, and highlights the increasing need for integrated monitoring and management of water resources at various spatial levels in a changing world.
Investigating regionalization techniques for large-scale hydrological modelling J. Hydrol. (IF 3.727) Pub Date : 2019-01-11 Liliana Pagliero, Fayçal Bouraoui, Jan Diels, Patrick Willems, Neil McIntyre
This work investigates regionalization techniques for large-scale model applications in the frame of a pan-European assessment of water resources covering approx. 740,000 km2 in Western Europe. Using the SWAT platform, four variants of the similarity based regionalization approach were compared. The first two involved unsupervised clustering to define hydrological regions before performing hydrological model calibration, whereas the last two involved supervised clustering after performing calibration. Similarity is defined using Partial Least Squares Regression (PLSR) analysis that identifies watershed physiographic characteristics that are most relevant for the selected hydrological response indices.The PLSR results indicate that typically available watershed characteristics such as geomorphology, land-use, climate, and soil properties describe reasonably well the average hydrological conditions but poorly the extreme events. Regionalization variants considering unsupervised clustering and supervised clustering performed similarly well when using all available information. However, results indicate that supervised clustering uses data more efficiently and may be more suitable when data are scarce. It is demonstrated that parsimonious use of available data can be achieved using both regionalization techniques. Finally, model performance consistently becomes acceptable by calibrating watersheds covering only 10% of the model domain, thus, making the calibration task affordable in terms of time and computational resources required.
Drywell Infiltration and Hydraulic Properties in Heterogeneous Soil Profiles J. Hydrol. (IF 3.727) Pub Date : 2019-01-11 Salini Sasidharan, Scott A. Bradford, Jiří Šimůnek, Stephen R. Kraemer
Drywells are increasingly used to capture stormwater runoff for surface infiltration and aquifer recharge, but little research has examined the role of ubiquitous subsurface heterogeneity in hydraulic properties on drywell performance. Numerical experiments were therefore conducted using the HYDRUS (2D/3D) software to systematically study the influence of subsurface heterogeneity on drywell infiltration. Subsurface heterogeneity was described deterministically by defining soil layers or lenses, or by generating stochastic realizations of soil hydraulic properties with selected variance (σ) and horizontal (X) and vertical (Z) correlation lengths. The infiltration rate increased when a high permeability layer/lens was located at the bottom of the drywell, and had larger vertical and especially horizontal dimensions. Furthermore, the average cumulative infiltration (I) for 100 stochastic realizations of a given subsurface heterogeneity increased with σ and X, but decreased with Z. This indicates that the presence of many highly permeable, laterally extending lenses provides a larger surface area for enhanced infiltration than the presence of isolated, highly permeable lenses. The ability to inversely determine soil hydraulic properties from numerical drywell infiltration results was also investigated. The hydraulic properties and the lateral extension of a highly permeable lens could be accurately determined for certain idealized situations (e.g., simple layered profiles) using constant head tests. However, variability in soil hydraulic properties could not be accurately determined for systems that exhibited more realistic stochastic heterogeneity. In this case, the heterogeneous profile could be replaced with an equivalent homogeneous profile and values of an effective isotropic saturated conductivity (Ks) and the shape parameter in the soil water retention function (α) could be inversely determined. The average value of Ksfor 100 stochastic realizations showed a similar dependency to I on σ, X, and Z. Whereas, the average value of α had large confidence interval for soil heterogeneity parameters and played a secondary role in drywell infiltration. This research provides valuable insight on the selection of site, design, installation, and long-term performance of a drywell.
Isotopic evidence of nitrate degradation by a zero-valent iron permeable reactive barrier: Batch experiments and a field scale study J. Hydrol. (IF 3.727) Pub Date : 2019-01-11 A. Grau-Martínez, C. Torrentó, R. Carrey, A. Soler, N. Otero
Permeable reactive barriers (PRBs) filled with zero-valent iron (ZVI) are a well-known remediation approach to treat groundwater plumes of chlorinated volatile organic compounds as well as other contaminants. In field implementations of ZVI-PRBs designed to treat these contaminants, nitrate consumption has been reported and has been attributed to direct abiotic nitrate reduction by ZVI or to denitrification by autochthonous microorganisms using the dissolved hydrogen produced from ZVI corrosion. Isotope tools have proven to be useful for monitoring the performance of nitrate remediation actions. In this study, we evaluate the use of isotope tools to assess the effect of ZVI-PRBs on the nitrate fate for the further optimization of full-scale applications. Laboratory batch experiments were performed using granular cast ZVI and synthetic nitrate solutions at pH 4-5.5 or nitrate-containing groundwater (pH=7.0) from a field site where a ZVI-PRB was installed. The experimental results revealed nitrate attenuation and ammonium production for both types of experiments. In the field site, the chemical and isotopic data demonstrated the occurrence of ZVI-induced abiotic nitrate reduction and denitrification in wells located close to the ZVI-PRB. The isotopic characterization of the laboratory experiments allowed us to monitor the efficiency of the ZVI-PRB at removing nitrate. The results show the limited effect of the barrier (nitrate reduction of less than 15-20%), probably related to its non-optimal design. Isotope tools were therefore proven to be useful tools for determining the efficacy of nitrate removal by ZVI-PRBs at the field scale.
Impacts of climate change and human activities on the flow regime of the dammed Lancang River in Southwest China J. Hydrol. (IF 3.727) Pub Date : 2019-01-11 Zhongying Han, Di Long, Yu Fang, Aizhong Hou, Yang Hong
The Lancang River (LR) in China (the upper portion of the Mekong River which is among the world's most important transboundary rivers) originates on the Tibetan Plateau and provides important freshwater resources for living, agriculture, industry, and hydropower generation for millions of people downstream. The natural flow regime of the LR is critical to sustain native biodiversity and ecosystem integrity; however, it has been changing due to the combined effect of climate change and human activities. Accurate quantification of the impacts of climate change and human activities on changes in the flow regime is a prerequisite for water resources and hydropower exploitation and environmental protection. This study aims to evaluate climate- and human-induced impacts on the LR during 1980–2014. A distributed hydrological model CREST-snow combined with remote sensing and streamflow data and the Budyko framework were jointly used to address this scientific question during three time windows determined by the Mann–Kendall test and the history of dam construction. Results show that compared with the baseline period (1980–1986) when no dam was constructed, significant changes (∼-6%) in mean annual streamflow occurred during 1987–2014, particularly after 2008 when the construction of the largest hydropower plant (Nuozhadu) in the Mekong River basin began. Climatic change contributed ∼57% to streamflow changes during the transition period (1987–2007), whereas human activities contributed ∼95% during the post-impact period (2008–2014). At the seasonal scale, climatic variation plays a more significant role during the dry season (December–May), with precipitation the most important factor among climate variables, whereas human activities contributed more during the wet season (June–November), benefiting the downstream areas through mitigating floods. Among human activities, reservoir construction is a dominant factor affecting streamflow over agricultural, industrial, and domestic water uses. The findings of this study enhance our understanding of hydrological changes in the LR basin that may impact the Lower Mekong River, serve as a basis for water resources and hydropower exploitation and environmental protection, and highlight the need for considering reservoir operation strategies in streamflow projections in similar basins globally under climate change scenarios.
Low-cost, high-resolution stemflow sensing J. Hydrol. (IF 3.727) Pub Date : 2019-01-11 Brandon Turner, David J. Hill, Darryl E. Carlyle-Moses, Musfiq Rahman
This study develops and evaluates a sensing system capable of measuring stemflow at high temporal resolutions. Leveraging affordable hobbyist grade electronics has allowed for the development of a system which is low-cost, easy to reproduce and adaptable. Eschewing classic stemflow measurement techniques, the system demonstrated herein utilizes a sensing payload which includes a wetness sensor and ultrasonic rangefinder. Combined, these sensors are capable of determining precise stemflow initiation and cessation times as well as capturing high temporal resolution stemflow volume measurements at 10 second intervals. A case study focusing on stemflow data collected by the sensing system from an isolated green ash (Fraxinus pennsylvanica Marshall) during a May 2016 rainfall event in Kamloops, British Columbia is used to evaluate the performance of the sensing system, demonstrating the accuracy of the collected data and the potential research questions that can be addressed by large scale deployment of the sensor system.
Flood routing methods J. Hydrol. (IF 3.727) Pub Date : 2019-01-11 John D. Fenton
The hierarchy of one-dimensional equations and numerical methods describing the motion of floods and disturbances in streams is studied, critically reviewed, and a number of results obtained. Initially the long wave equations are considered. When presented in terms of discharge and cross-sectional area they enable the development of simple fully-nonlinear advection-diffusion models whose only approximation is that disturbances be very long, easily satisfied in most flood routing problems. Then, making the approximation that changes in surface slope are relatively small such that diffusion terms in the equations are small, various advection-diffusion and Muskingum models are derived. Several well-known Muskingum formulations are tested; one is found to be in error. The three families of the governing equations, the long wave equations, the advection-diffusion and the Muskingum approximations, are linearised and analytical solutions obtained. A dimensionless diffusion-frequency number measures the accuracies of the approximate methods. Criteria for practical use are given, which reveal when they have difficulties for streams of small slope, for fast-rising floods, and/or when shorter period waves are present in an inflow hydrograph. They can probably be used in most flood routing problems with an idealised smooth inflow. However the fact that they cannot be used for all problems requires a general alternative flood routing method, for which it is recommended to use the long wave equations themselves written in terms of discharge and cross-sectional area, when a surprisingly simple physical stream model can be used. An explicit finite difference numerical method is presented that can be used with different inflow specifications and downstream boundary conditions, and is recommended for general use.
Basin-scale hydrology and sediment dynamics of the Kosi River in the Himalayan foreland J. Hydrol. (IF 3.727) Pub Date : 2019-01-11 Rajiv Sinha, Alok Gupta, Kanchan Mishra, Shivam Tripathi, Santosh Nepal, S.M. Wahid, Somil Swarnkar
A reliable linear method for modeling lake level fluctuations J. Hydrol. (IF 3.727) Pub Date : 2019-01-11 Isa Ebtehaj, Hossein Bonakdari, Bahram Gharabaghi
Accurate forecasting of lake level time series (LLTS) is an important but challenging problem with major economic, social and environmental implications. However, in recent years, the level of uncertainty in the existing LLTS forecast methods has increased significantly due to climate change, therefore, the need to develop more accurate models. The main research question for this study is whether it is necessary to use nonlinear methods in LLTS modeling or if linear methods can produce as accurate and reliable forecast tools. We introduce a new linear-based forecast method for LLTS using spectral analysis, seasonal standardization, and stochastic terms. The application of the new LLTS forecast method is tested on two case study Lakes, including the Van Lake, in Turkey and the Michigan-Huron Lake, in North America. A two-step preprocessing techniques based on standardization and differencing was used for the Van Lake, and spectral analysis and differencing was employed for the Michigan-Huron Lake. We then compared the accuracy and uncertainty of the proposed linear method with an artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) methods. The uncertainty of the new linear LLTS forecast model was ±0.00455 and ±0.00264 for the Van Lake and the Michigan-Huron Lake, respectively, compared to ±0.00625 and ±0.00766 for the ANN and the ANFIS (respectively) at the Van Lake and ±0.00312 and ±0.00319 for the ANN and the ANFIS (respectively) at the Michigan-Huron Lake.
Development of a Spatially-Varying Statistical Soil Moisture Profile Model by Coupling Memory and Forcing using Hydrologic Soil Groups J. Hydrol. (IF 3.727) Pub Date : 2019-01-11 Manali Pal, Rajib Maity
Information on vertical Soil Moisture Content (SMC) profile is important for several hydro-meteorological processes. This study borrows the idea of coupling the memory and forcing from a previous study and develops a spatially-varying Statistical Soil Moisture Profile (SSMP) model to estimate the vertical SMC profile. It uses the only surface soil moisture (0-5 cm) values and Hydrological Soil Groups (HSGs) information of the location. The focus of the study is incorporation of the HSG information to ensure the spatial transferability of the proposed model by capturing the spatial variations of soil moisture profile with the change in soil hydraulic properties. The wide range of soil moisture data for model development as well as for spatial validation are obtained from 171 stations from different networks of International Soil Moisture Network (ISMN) at five different depths, i.e., 5, 10, 20, 51 and 102 cm. The HSG information at the locations are extracted from the Web Soil Survey (WSS) database. The potential of spatial transferability of the SSMP model is assessed by applying it to the new stations within the corresponding HSG. Model performances are promising for all four depth pairs (5-10, 10-20, 20-51 and 51-102 cm) of all four HSGs during both model development and spatial validation given the model complexity. Hence, the spatially-varying SSMP model is suitable at the ungauged locations by incorporating the HSG information. The potential application of the proposed model shows the future scope to assimilate the satellite based surface SMC data into the model to develop a vertical soil moisture profile map over a large area.
Using undisturbed soil samples to study how rock fragments and soil macropores affect the hydraulic conductivity of forest stony soils: Some methodological aspects J. Hydrol. (IF 3.727) Pub Date : 2019-01-11 Anna Ilek, Jarosław Kucza, Wojciech Witek
Forest stony soils have rock fragments and many macropores, the latter arising mainly from the activity of soil fauna and plant root decay. We still lack knowledge about the hydraulic properties of this type of soil, especially when considering the influence of both factors – rock fragments and macropores – on the saturated hydraulic conductivity. This research aims to supplement the method we proposed before to test the hydraulic conductivity of undisturbed soil samples (Ilek and Kucza, 2014, Kucza and Ilek, 2016). We propose to enhance the method by taking into account the impact of rock fragments and macropores on the hydraulic conductivity of forest stony soils, particularly on the hydraulic conductivity of the medium conducting water in the soil, that is, soil matrix. We studied, using artificial samples, how rock fragments influence hydraulic conductivity. To test the enhanced method, we used 33 undisturbed samples taken from the top layers (0–12 cm) of forest stony soils. The results show that rock fragments in the soil can both increase and decrease the infiltration of water by the soil matrix. Rock fragments with diameters close to 20 mm had the least influence on water infiltration. Soil macropores in the samples always increased water infiltration. Empty macropores increased it from two to twenty-four times while filled macropores from three to five times. Our method gives the opportunity to study the hydraulic conductivity of macropores and their physical and chemical properties.
A Monte Carlo-Based Multi-Objective Optimization Approach to Merge Different Precipitation Estimates for Land Surface Modeling J. Hydrol. (IF 3.727) Pub Date : 2019-01-11 Abheera Hazra, Viviana Maggioni, Paul Houser, Harbir Antil, Margaret Noonan
Precipitation is a fundamental forcing variable in land surface modeling, controlling several hydrological and biogeochemical processes (e.g., runoff, carbon cycling, evaporation, transpiration, groundwater recharge, and soil moisture). However, precipitation estimates from rain gauges, ground-based radars, satellite sensors, and numerical models are affected by significant uncertainties, which can be amplified when exposed to highly non-linear land model physics. This work tests the hypothesis that precipitation data from different sources can be optimally merged to minimize the hydrologic response error in surface soil moisture simulations and maximize their correlation with ground observations (multi-objective optimization problem). This hypothesis is tested by merging three precipitation products (one satellite product, a ground-based dataset, and model-base estimates) that force a land surface model trained to minimize soil moisture anomalies. A Monte Carlo-based algorithm is developed to generate weights to linearly combine these precipitation datasets. Optimal combinations of weights are identified by minimizing the errors and maximizing the correlation between the model simulated soil moisture and the satellite-based SMOS soil moisture product. The proposed methodology has been tested over Oklahoma where high-quality, high-resolution (independent) ground-based soil moisture observations are available for validation purposes. Results show that there exist optimal combinations of these precipitation datasets that provide smaller errors and larger correlation coefficients between modeled soil moisture estimates and ground-based data with respect to forcing the land surface model with single precipitation datasets. Specifically, combining three precipitation products from different sources provides the largest correlation coefficient and the lowest root mean square error at several locations across Oklahoma.
An Analytical Model for Estimation of Land Surface Net Water Flux from Near-Surface Soil Moisture Observations J. Hydrol. (IF 3.727) Pub Date : 2019-01-11 Morteza Sadeghi, Markus Tuller, Arthur W. Warrick, Ebrahim Babaeian, Kshitij Parajuli, Mohammad R. Gohardoust, Scott B. Jones
The accurate determination of land surface water fluxes at various spatiotemporal scales remains a challenge in hydrological sciences. It is intuitive that land surface net water flux (i.e., infiltration minus evapotranspiration) directly affects near-surface soil moisture. However, there exists no hydrological model suitable to calculate net water flux based on measured near-surface soil moisture data. This is a consequence of the mathematical structure of existing models that use ‘boundary conditions’ to determine ‘internal conditions’, whereas what is needed is a model amenable to use near-surface soil moisture data (an internal condition) to determine the surface water flux (a boundary condition). To pursue the idea of utilizing remotely-sensed or in situ (i.e., sensor networks) near surface soil moisture data for estimation of net water flux, we derived an analytical model via inversion of Warrick’s 1975 analytical solution to the linearized Richards’ equation for arbitrary time-varying surface flux boundary conditions. The applicability of the new analytical solution was evaluated based on actual water flux observations as well as HYDRUS-1D simulations for four vastly different sites in Arizona, California, Idaho, and Indiana. Our results demonstrate that the proposed model reasonably captures net water flux variations in natural settings, including layered and vegetated soils, especially at larger time scales (e.g., monthly). While the model works for a wide range of climatic conditions, the prediction accuracy is somewhat lower for extreme dry or wet conditions. A major advantage of the new model is that it does not require calibration, which provides an unprecedented opportunity for large scale estimation of land surface net water flux using remotely sensed near-surface soil moisture observations.
On the estimation of spatially representative plot scale saturated hydraulic conductivity in an agricultural setting J. Hydrol. (IF 3.727) Pub Date : 2019-01-11 Tommaso Picciafuoco, Renato Morbidelli, Alessia Flammini, Carla Saltalippi, Corrado Corradini, Peter Strauss, Günter Blöschl
Spatially representative estimates of saturated hydraulic conductivity, , are needed for simulating catchment scale surface runoff and infiltration. Classical methods for measuring are time-consuming so sampling campaigns need to be designed economically. Important insights can be obtained by experiments directed to understand the controls of in an agricultural setting and identify the minimum number of samples required for estimating representative plot scale . In this study, a total of 131 double-ring infiltrometer measurements were made on 12 plots in a small Austrian catchment. A statistical analysis of across the catchment suggests to be only slightly influenced by physical and topographical soil characteristics while land use is the main control. The highest values of were observed in arable fields, with a median of about 3 times and a coefficient of variation (CV) of about 75% of those in grassland areas. An uncertainty analysis aimed at determining the minimum number of measurements necessary for estimating the geometric mean of over a given area with a specified accuracy suggests that, beyond a specific and plot-size dependent number of measurements, the benefit of any extra measurement is small. The confidence interval of the geometric mean of decreases with the number of measurements and increases with the size of the plot sampled. Applications of these findings for designing field campaigns are discussed.
Increased organic contaminant residence times in the urban riverbed due to the presence of highly sorbing sediments of the Anthropocene J. Hydrol. (IF 3.727) Pub Date : 2019-01-11 Michael O. Rivett, Rachel S. Roche, John H. Tellam, Alan W. Herbert
Quantifying glacier mass change and its contribution to lake growths in Central Kunlun during 2000-2015 from multi-source remote sensing data J. Hydrol. (IF 3.727) Pub Date : 2019-01-10 Yushan Zhou, Jun Hu, Zhiwei Li, Jia Li, Rong Zhao, Xiaoli Ding
Joint monitoring of the variations of glaciers and lakes within a basin is essential for an accurate understanding of region-wide climate change and the water cycle process. The central Kunlun-KekeXili region is an ideal experimental field due to the wide distribution of glaciers and lakes. In this study, we first investigated the glacier mass balance of 2000−2015/16 for seven major glacier clusters by utilizing high-resolution SPOT-6/7 stereo imagery and the SRTM DEM. The final results revealed an overall mass balance of −0.16 ± 0.05 m w.e./a. for the study region (with a total glacier area of 967 km2). Secondly, ICESat/GLAS altimetry data were used to quantify the water-level change of 2003−2008/09 for the two largest glacier-fed closed lakes (i.e., LexieWudan Lake and KekeXili Lake) in this region. Based on this, we applied a strategy which establishes the statistical relationship between the lake area change and the lake water-level change for 2003−2008/09 to estimate the specific water level using the corresponding lake area. We then further calculated the variation in lake water storage between 2000 and 2015. The results showed that the water storage of LexieWudan Lake and KekeXili Lake increased by 1.82 ± 0.14 km3 and 1.90 ± 0.38 km3, respectively. For each lake basin, meanwhile, the glaciers lost −0.18 ± 0.03 km3 and −0.21 ± 0.04 km3 of water, accounting for 9.9% and 11.1% of the increase in lake water storage for LexieWudan Lake and KekeXili Lake, respectively. Our results not only demonstrate that glacier meltwater has only a limited impact on the lake expansion in this region, but they also provide new evidence for the warming and wetting process of the climate in the northern part of the Qinghai–Tibet Plateau.
Impact of reservoir operation on runoff and sediment load at multi-time scales based on entropy theory J. Hydrol. (IF 3.727) Pub Date : 2019-01-08 Jinping Zhang, Honglin Xiao, Xin Zhang, Fawen Li
Based on the runoff and sediment load data series obtained at the Guide hydrological station (GHS) in the upper reaches of the Yellow River from 1960 to 2013, the varying quasi-periodic fluctuations of runoff and sediment load existing in different decomposed time scales are revealed by using the complementary ensemble empirical mode decomposition (CEEMD) method pre- and post-reservoir operation. Combined with entropy theory, the concepts of multi-time scale entropy (MTSE) and multi-time scale structural entropy (MTSSE) are proposed to analyze the complex fluctuation characteristics of runoff and sediment load at different time scales. The results show that reservoir operation has a greater influence on sediment load than that on runoff at multi-time scales, and that their correlations change as well. Additionally, reservoir operation can aggravate the complexity of the runoff and sediment load, but with longer fluctuation time scales, this complexity decreases and predictability increases. After reservoir operation, the fluctuation period of high frequency components in runoff and sediment load is elongated, and the information content of runoff and sediment load is focused at the short-middle time scale. Therefore, the available and reasonable monitoring and research periods for runoff and sediment load in the upper reaches of the Yellow River are suggested as 4-7 years and 3-4 years, respectively.
Predictive performance of NMME seasonal forecasts of global precipitation: a spatial-temporal perspective J. Hydrol. (IF 3.727) Pub Date : 2019-01-09 Tongtiegang Zhao, Yongyong Zhang, iaohong Chen
Global climate models (GCMs) produce informative seasonal forecasts of global precipitation months ahead of the occurrence for hydrological forecasting. Meanwhile, the skill of GCM forecasts varies by location and initialization time. In this paper, we investigate the anomaly correlation, which indicates the correspondence between forecasts and observations, for 10 sets of global precipitation forecasts in the North American Multi-Model Ensemble (NMME) project. We propose to use principal component analysis to characterize the variation of anomaly correlation. We identify the existence of spatial and temporal patterns at the global scale. The spatial pattern reveals that high (low) anomaly correlation at one initialization time coincides with high (low) anomaly correlation at other initialization times. In other words, for a grid cell, the anomaly correlation at different initialization times tends to be similarly high, or low. It is observed that some of the regions where grid cells are with overall high anomaly correlation tend to exhibit tele-connections with global climate drivers. On the other hand, the temporal pattern suggests that the anomaly correlation tends to improve with initialization time. This pattern is attributable to data assimilation that bases forecasts at a later initialization time on more global observations and simulations. Generally, the two patterns are effective and explain 50% to 70% of the variation of anomaly correlation for the 10 sets of NMME forecasts. The projections of anomaly correlation vectors to the two patterns help illustrate where and when the NMME precipitation forecasts are skillful.
The transferability of SWMM model parameters between green roofs with similar build-up J. Hydrol. (IF 3.727) Pub Date : 2019-01-08 Birgitte Gisvold Johannessen, Vladimír Hamouz, Ashenafi Seifu Gragne, Tone Merete Muthanna
While extensive green roofs are popular measures for reducing and delaying stormwater runoff, design tools are needed to better predict roof performance based on material properties, geometry and climate. This paper investigates the EPA’s Storm Water Management Model’s (SWMM) green roof module for this purpose based on observed runoff from several roofs with different build-ups, geometry, and climates. First, the general model performance was investigated and secondly transferability of model parameters for similar roofs but different geometries and climates was tested. Individual models reproduced runoff hydrographs well (NSE 0.56-0.96), while the long-term modelling showed relatively large volume errors most likely due to insufficient representation of evapotranspiration in the model. Model parameters obtained at one site were only partly transferable to similar roof build-up at other sites. Transferability was better from models calibrated with wetter climates and higher intensity events to drier climates, than the opposite way. Multi-site calibration resulted in model parameters performing well for most sites, giving model parameters that could be used for the design of similar roof build-ups in comparable climates. However, large variability in obtained model parameters, large volume errors and the fact that the calibrated model parameters did not directly correspond to measured material properties, place concerns on the generality of the SWMM green roof module as a design tool.
CO2 emissions from hydroelectric reservoirs in the Tigris River basin, a semi-arid region of southeastern Turkey J. Hydrol. (IF 3.727) Pub Date : 2019-01-04 Memet Varol
Three hydroelectric reservoirs (Kralkızı, Dicle and Batman) in the Tigris River basin (Turkey) were sampled monthly during one year in order to reveal spatial and seasonal changes in aqueous partial pressure of CO2 (pCO2) and to estimate diffusive fluxes of CO2 from the reservoirs’ surface water. pCO2 concentrations did not show significant spatial differences, while they showed significant seasonal variations. Temperature, precipitation and biological CO2 uptake through photosynthesis controlled pCO2 seasonality in the reservoirs, with maximal concentrations in the winter (ranging from 516.9 µatm in Kralkızı to 1299.2 µatm in Dicle) and minimal concentrations in the spring (ranging from 47.7 µatm in Batman to 140.7 µatm in Kralkızı). Most studies reported that reservoirs worldwide are net sources of CO2 to the atmosphere. However, the reservoirs in this study were sinks for atmospheric CO2 during the spring, summer and autumn seasons, while they were CO2 sources to the atmosphere during the winter. Air-water CO2 fluxes in Kralkızı, Dicle and Batman dam reservoirs were 2.39, 32.88 and 8.12 mmol/m2/day in the winter, respectively. On an annual basis, all three reservoirs acted as a sink for atmospheric CO2. These estimated CO2 fluxes were in the lower range for temperate reservoirs, despite the potential for winter conditions that shifted the reservoirs from sink to net source for atmospheric CO2.
Experimental and numerical investigation of evaporation from line sources of water in low porosity surfaces J. Hydrol. (IF 3.727) Pub Date : 2019-01-05 Navneet Kumar, Jaywant H. Arakeri
We report evaporation characteristics due to higher heating from above from surfaces having an array of line sources. The line sources are created by vertically stacked rectangular plates in a box with water. Two different types of plates were used. In one case line source or film thickness was 66 μ m and open area ratio was 4%, and in the second case film thickness was 28 μ m and 20% was the open area ratio. Even at the 4% open area ratio the evaporation rate was ∼85% compared to a bare water surface, at the same heat flux. Lateral conduction of heat from the impervious hotter regions to the line sources and the 2-D nature of diffusion near these tiny line sources enhances the evaporative flux, owing to increase in the concentration gradient of water vapour, explains the high evaporation rate, observed in the present work. This system bridges the gap between the understanding of evaporation from bare water surfaces (1-D vapour diffusion) and leaf surfaces (3-D vapour diffusion). Evaporation rates for the fully saturated conditions are in good agreement with the theoretical predictions of Suzuki and Maeda (1968) and Schlunder (1988). The computed surface temperatures and its width-wise variation match well with the experimental values. We also propose a simple film model for the unsaturated condition of the porous medium and show that the temperature distribution obtained using this model is in reasonably good agreement with the measured values.
A review of the artificial intelligence methods in groundwater level modeling J. Hydrol. (IF 3.727) Pub Date : 2019-01-06 Taher Rajaee, Hadi Ebrahimi, Vahid Nourani
This study is a review to the special issue on artificial intelligence (AI) methods for groundwater level (GWL) modeling and forecasting, and presents a brief overview of the most popular AI techniques, along with the bibliographic reviews of the experiences of the authors over past years, and the reviewing and comparison of the obtained results. Accordingly, 67 journal papers published from 2001 to 2018 were reviewed in the terms of the features and abilities of the modeling approaches, input data consideration, prediction time steps, data division, etc. From the reviewed papers it can be concluded that despite some weaknesses, if the AI methods properly be developed, they can successfully be used to simulate and forecast the GWL time series in different aquifers. Since some of the stages of the AI modeling are based on the experience or trial-and-error procedures, it is useful to review them in the special application on GWL modeling. Many partial and general results were achieved from the reviewed papers, which can provide applicable guidelines for researchers who want to perform similar works in this field. Several new ideas in the related area of research are also presented in this study for developing innovative methods and for improving the quality of the modeling.
Water Resources in Inland Regions of Central Asia: Evidence from Stable Isotope Tracing J. Hydrol. (IF 3.727) Pub Date : 2019-01-06 Zongxing Li, Juan Gui, Xufeng Wang, Qi Feng, Tongtiegang Zhao, Chaojun Ouyang, Xiaoyan Guo, Baijuan Zhang, Yang Shi
Complex hydrological processes affect valuable water resources in inland regions across arid central Asia. Historically, this was a critical part of the Silk Road, and it is now named the modern Silk Road Economic Belt. Using the Qilian Mountains and Hexi Corridor in China as a case-study of the inland region, we collected a total of 2,311 water samples from the area and performed a comprehensive investigation of the water cycle. Results from stable isotope tracing indicate clear spatial patterns. In the upstream mountainous regions, glacier snow meltwater becomes groundwater at the periglacial belt. Supra-permafrost water develops into river runoff in the permafrost region. There are also frequent exchanges between groundwater and river runoff along the vegetation belt. In the middle/downstream region, river runoff becomes groundwater. Throughout these processes, both river runoff and groundwater are consumed by evapotranspiration, are recycled, and make a substantial contribution to precipitation. Overall, the upstream mountainous region is a critical part of the water resources. The cryosphere belt accounts for 44% of the mountainous region but contributes to about 80% of water resources. Recycling of moisture also plays an important role. During the summer months (May to September) moisture recycling accounted for 24% and 14% of precipitation in upstream and middle/downstream regions, respectively. The findings from the stable isotope tracing provide insights into hydrological processes and can help improve water management in inland regions of Central Asia.
Value of distributed water level and soil moisture data in the evaluation of a distributed hydrological model: Application to the PUMMA model in the Mercier catchment (6.6 km2) in France J. Hydrol. (IF 3.727) Pub Date : 2019-01-04 Musandji Fuamba, Flora Branger, Isabelle Braud, Essoyeke Batchabani, Pedro Sanzana, Benoit Sarrazin, Sonja Jankowfsky
This paper emphasizes the importance of integrating outlet discharge and observed internal variables in the evaluation of distributed hydrological models outputs. It proposes a general methodology for a diagnostic evaluation of a complex distributed hydrological model, based on discharge data at the outlet and additional distributed information such as water level and surface soil moisture data. The proposed methodology is illustrated using the PUMMA model in the Mercier sub-catchment (6.6 km2). Model parameters are specified according to field data and a previous study performed in a neighbouring catchment (Jankowfsky et al., 2014), without calibration. The distributed water level and soil moisture network of sensors were useful in the model evaluation process. Thus, model parameters are specified either using in situ information or results from previous studies. A stepwise approach is used for model evaluation. It includes standard water balance assessment as well as comparison of observed and simulated outlet discharge, whether on annual or event timescales. Soil moisture sensors are used to assess the ability of the model to simulate seasonal water storage dynamics based on a normalized index. The water level sensors network is used on two timescales: on a seasonal timescale, sensors network is used to assess the model’s ability to simulate intermittency; whereas on event timescales, sensors network is used in determining the model’s ability to reproduce observed reaction as well as response times. Event timescales do also focus on the correlation between hydrological response and either rainfall event or antecedent soil moisture variables. Results show that the non-calibrated model is quite effective at capturing water flow and soil water-storage dynamics, but it fails to reproduce observed runoff volume during events. There is strong indication of a deficiency in the characterization of catchment storage and upstream flowpath description. The soil water content and a network of water level sensors provide interesting information about soil moisture and river flow dynamics. They however fail to provide quantitative information about catchment storage. This study opens interesting perspectives for the evaluation of distributed hydrological models using hydrological signatures. Furthermore, it highlights the requirement of quantitative as well as qualitative signatures for improving such models.
The combined use of self-organizing map technique and fuzzy c-means clustering to evaluate urban groundwater quality in Seoul metropolitan city, South Korea J. Hydrol. (IF 3.727) Pub Date : 2018-12-28 Kyung-Jin Lee, Seong-Taek Yun, Soonyoung Yu, Kyoung-Ho Kim, Ju-Hee Lee, Seung-Hak Lee
To make an overall assessment of the groundwater quality in Seoul city, we used the self-organizing map (SOM) technique in combination with fuzzy c-means (FCM) clustering. SOM visualizes complicate and multidimensional data structures on a 2D surface while the FCM algorithm creates overlapping cluster boundaries among samples that are continuously distributed over a data space. The combination of SOM and FCM clustering was expected to help characterize highly complicated urban groundwater quality. As a result, the SOM characterized 343 groundwater samples using 91 neurons, which were further classified by FCM clustering into three water groups. Group 1 addressed the least polluted groundwater (17 % of the samples (n = 58), average TDS = 194.5 mg/L and NO3 = 6.9 mg/L) and occurred in the peripheral areas whose land cover is mainly occupied by forests. Increasing pH with increasing sodium and bicarbonate concentrations indicated that the hydrogeochemistry of Group 1 was largely controlled by water-rock interactions. Group 2 included the highly polluted groundwater (24 % of the samples (n = 82), average TDS = 326.2 mg/L and NO3 = 42.6 mg/L), and sporadically occurred in Seoul, with no distinct spatial control. This group seemed to be affected by sewage from broken sewer pipes, which are a primary pollution source of Seoul groundwater and are ubiquitously distributed beneath the city. Group 3 water also represented the highly contaminated groundwater (30 % of the samples (n = 103), average TDS = 527.1 mg/L), but contained low nitrate concentrations (average NO3 = 13.1 mg/L). Based on their spatial locations, intensive groundwater pumping from subway tunnels and other underground spaces at the city center seemed to drive the induced flow of organic contaminants, resulting in local reducing conditions sufficient for denitrification. The remaining 100 samples (29 % of the samples) shared the hydrogeochemical properties of two or three groups. This study successfully characterized the spatial pattern of urban groundwater quality that is complicated by various contamination sources and hydrogeochemical processes. The combined use of SOM and FCM clustering was proven as a powerful tool to interpret nonlinear and highly heterogeneous environmental data for which it is difficult to define cluster boundaries. Taken together, our results contribute to a better management of urban groundwater in metropolitan cities under high risks of anthropogenic contamination.
Quantifying the wetland water balance: A new isotope-based approach that includes precipitation and infiltration J. Hydrol. (IF 3.727) Pub Date : 2018-12-29 Edward K.P. Bam, Andrew M. Ireson
Stable isotopes have been used to quantify lake and wetland pond water loss to evaporation by applying the modified Craig and Gordon (1965) model. This model and its derivatives employ simplifying assumptions that ignore the additions of precipitation and infiltration outputs and assume evaporation is the only loss term over the prediction period. Here we develop a coupled water and isotope mass-balance model to account for precipitation additions. Our model uses physical and isotopic observations to quantify pond evaporation and infiltration losses over the ice-free period. We tested and applied the model to four wetland ponds at the St Denis National Wildlife Research Area, Saskatchewan Canada, where we have long-term datasets. Modeled infiltration rates from the ponds ranged between 0.99 and 9.2 mm/d and open water evaporation rates ranged between 0.88 and 2.8 mm/d. Both were consistent with independent estimates. Infiltration amounts were highest in the ephemeral ponds (that dry out within days or weeks of the spring melt period). In these ponds, infiltration exceeded evaporation. In permanent ponds, that is ponds that do not dry out; evaporation exceeded infiltration. Evaporation amounts were most substantial for permanent ponds that were not sheltered by topography or riparian vegetation. Overall, our coupled water and isotope mass-balance model combined with physical and isotope observations was able to quantify the spatially and temporally variable evaporation and infiltration fluxes within and between ponds.
Vulnerability Mapping of Coastal Aquifers to Seawater Intrusion: Review, Development and Application J. Hydrol. (IF 3.727) Pub Date : 2018-12-30 Esmaeel Parizi, Seiyed Mossa Hosseini, Behzad Ataie-Ashtiani, Craig T. Simmons
In this study, a review of the overlay/index methods served for delineation of vulnerable zones in coastal aquifers affected by SWI is provided. Then, a more realistic presentation of the vulnerability mapping of coastal aquifers to SWI through modified GALDIT index method by incorporating the influential factors on SWI is established. The modifications on GALDIT method including incorporating the seaward hydraulic gradient (i) instead of the height of groundwater level above sea level (L) (so-called GAiDIT), and considering hydraulic gradient (i) as an additional parameter to the GALDIT (so-called GALDIT-i). Three GALDIT, GAiDIT, and GALDIT-i methods were evaluated with data from three coastal confined and phreatic/confined aquifers located in the south of the Caspian Sea, northern Iran. While no highly vulnerable zone was recognized by GALDIT method across three studied aquifers, averagely 43.4% and 50.5% of aquifers area were defined as highly vulnerable zones by GAiDIT and GALDIT-i, respectively. Furthermore, the final vulnerability maps obtained by GALDIT-i and then GAiDIT indicates higher correlation by three groundwater quality indices specific to SWI including f sea ( r =0.72 and 0.63) and G Q I - ( r =0.69 and 0.62) and also the distribution of TDS in groundwater ( r =0.71 and 0.61) compared with GALDIT ( r =0.33, 0.42, and 0.36, respectively). The values of vulnerability index obtained by GALDIT-i and GAiDIT are more strongly correlated with the length of SWI into the aquifer ( L x ) based on Strack's analytical approach than GALDIT ( r =0.52, 0.36, and 0.32, respectively). The results of sensitivity analysis indicated that the hydraulic gradient, height of groundwater level above sea level, aquifer type, and existing status of seawater intrusion has the greatest impact on the groundwater vulnerability across the studied aquifers by GALDIT-i and GAiDIT methods. Results also indicated that serving the influential parameters in GALDIT methods regarding the hydrological and anthropogenic characteristics across the aquifer provide a more realistic characterization of the SWI. This modification leads to an accurate aquifer vulnerability mapping to SWI in aquifers characterized by transient anthropogenic drivers (e.g. pumping) which can be served as a promising tool for decision-making to properly assess and manage risk.
Spatio-temporal Analysis of Urban Changes and Surface Water Quality J. Hydrol. (IF 3.727) Pub Date : 2018-12-31 Dana Carstens, Reda Amer
The combination of remote sensing techniques and Geographic Information Systems (GIS) to measure water quality allows researchers to monitor changes in various water quality parameters over temporal and spatial scales that are not always readily apparent from in situ measurements. This study involves using Landsat images and in situ data within GIS to map urban expansion and its resulting influences on water quality in the Pontchartrain Basin over the last three decades. The Pontchartrain Basin is located in southeast Louisiana and covers an area of 25,000 km2 that encompasses sixteen parishes east of the Mississippi River and four Mississippi Counties. A Landsat Thematic Mapper (TM) image from 1985 and a Landsat Operational Land Imager (OLI) image from 2015 were processed using the Spectral Angle Mapper (SAM) algorithm to map urban expansion. In order to estimate how water quality has changed in the Pontchartrain Basin between 1985 and 2015, in situ water quality data from the Louisiana Department of Environmental Quality was interpolated using Empirical Bayesian Kriging (EBK). Comparing urban expansion produced from SAM classification with urban indices, impervious surfaces were better identified and distinguished from other land cover features. The results of this study demonstrated that high levels of fecal coliform were consistent with increased urbanization in water bodies in the Pontchartrain Basin. Phosphorous levels were higher in 2015 compared to 1985 and were at levels high enough to lead to eutrophic conditions. Dissolved oxygen levels were lower near the mouth of the Mississippi river in 2015 than in 1985. The results indicated that urbanization has negative impact on water quality. The geospatial model is recommended to effectively manage and reduce the processing time of large water quality datasets.
Reconstruction of Annual Runoff since AD 1557 Using Tree-ring Chronologies in the upper Lancang-Mekong River Basin J. Hydrol. (IF 3.727) Pub Date : 2018-12-31 Bing Yang, Xiaohong Chen, Yanhu He, Jiawen Wang, Chengguang Lai
In this study, with the use of a multiple linear regression approach, the tree-ring chronologies of eight sampling sites in the upper Lancang-Mekong River Basin were developed to provide a 449-year (AD 1557-2005) reconstruction of the annual runoff, thus placing recent changes in annual runoff into a long-term context. These eight tree-ring chronologies have recently been archived in publicly available databases through the International Tree-Ring Data Bank. Reconstruction results showed a good correlation coefficient of 0.662 (n = 39, p-value < 0.01) between the reconstructed and the observed annual runoff. The adjusted coefficient (R2) for the degrees of freedom is 42.3%, which meets the precision requirements of reconstruction. The reconstructed runoff displays a trend toward more moist conditions: there were 37 extremely wet years and 23 extremely dry years, exceeding the mean +/- 1 standard deviation, during the past 449 years. Empirical mode decomposition (EMD) was used to fully analyze and understand the multi-scale variation of the reconstructed runoff. Six intrinsic mode function (IMF) components with different scales were obtained and the sum of all components can be reverted to the original variable sequence. The first and second IMF mainly reflect the change characteristics of the interannual scale of reconstructed sequence. Both are likely controlled by the Quasi-Biennial Oscillation (QBO) and the El Niño-Southern Oscillation (ENSO), respectively. The third IMF showed a 10-13 year scale fluctuation, which is very similar to the solar activity of an 11-year cycle. The fourth and fifth IMF mainly represents multidecadal and centennial oscillations, and they have shown coherent variations with predecessors’ reconstructed May-September precipitations in the same time domain. The lowest frequency component (the residue IMF) represents the trend term of the original signal.
SMAP, RS-DTVGM, and in-situ monitoring: which performs best in presenting the soil moisture in the middle-high latitude frozen area in the Sanjiang Plain, China? J. Hydrol. (IF 3.727) Pub Date : 2018-12-26 Hezhen Lou, Shengtian Yang, Fanghua Hao, Lingmei Jiang, Changsen Zhao, Xiaoyu Ren, Yue Wang, Zhiwei Wang
Soil moisture is a core ecohydrological element in the middle–high latitude frozen area, which occupies approximately 30% of the global land area. The Sanjiang Plain, an important commercial grain production area, is the largest swampy low plain in a middle-high latitude frozen area in China. However, no published studies on this region have clarified the accuracy of soil moisture data from in-situ measurements; the performance of ecohydrological models are also unknown. In this study, we compared the ability of the SMAP product, a RS-DTVGM model, and two self-erected soil moisture monitoring stations to capture soil moisture information in the Sanjiang Plain by using the Triple Collocation method. Soil moisture data were collected for 642 continuous days, and the data period was divided into three frozen periods (FT) and two non-frozen (NFT) periods. Valid data supply rates of the three methods were also calculated and compared. From the Triple Collocation method, the root mean square error (RMSE) of the SMAP, model and in-situ monitoring data sets were 0.03, 0.08, and 0.05. The valid data supply rates of the SMAP product in the FT and NFT periods were 27.1% and 57.5%, respectively. The Pearson correlation coefficient between the SMAP product and the in-situ monitoring dataset was 0.301 for the FT period and 0.557 for the NFT period. The RS-DTVGM model had a data supply rate of 100%. The Pearson correlation coefficient for this model was 0.101 for the FT period, but reached 0.726 for the NFT period. For the three soil moisture data sets, the accuracy ranking in this middle-high latitude area was SMAP > in-situ monitoring > model simulation. Although neither SMAP nor the RS-DTVGM model could capture the real soil moisture information for the FT period, both could accurately simulate the soil moisture in the NFT period. The results from the RS-DTVGM model demonstrated a closer relationship with in-situ soil moisture measurement data relative to the SMAP method. The in-situ method provided accurate soil moisture data, but its application is limited by high cost. In the future, the data from the three methods should be assimilated together to measure soil moisture data with high accuracy and high spatial and temporal resolution in this important area.
Some contents have been Reproduced by permission of The Royal Society of Chemistry.
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