A data-driven approach for analyzing dynamics of tide–aquifer interaction in coastal aquifer systems

Analysis of tidal effects on aquifer systems plays an important role in coastal aquifer management owing to various hydrological, engineering and environmental problems in coastal areas. Using the real-world data of unconfined and confined aquifers, a data-driven approach is presented in this study for the analysis of tide–aquifer interaction in coastal aquifers. Six analytical tide–aquifer interaction models were selected which take into account the effects of vertical beach, sloping beach, tidal loading, aquifer leakage, outlet capping, and combined leakage and outlet capping on tide-induced groundwater fluctuations. The tide–aquifer interaction datasets were obtained from the Konan groundwater basin (unconfined aquifer) of Japan and the Dridrate groundwater basin (confined aquifer) of Morocco. The analysis of the results obtained by the sloping beach model revealed that for a given beach slope, the amplitude of groundwater level increases with an increase in aquifer diffusivity and a decrease in aquifer thickness. However, no significant effect of beach slope was observed in this study at unconfined sites for all the datasets. The influence of tidal loading was found to be considerably less for all the three confined sites. Further, the analysis of the results of the leakage model indicated that with an increase in leakage into the aquifer, the amplitude of groundwater level as well as the phase shift (time lag) decreases. Of all the confined and unconfined datasets, only two confined sites were found to be affected by outlet capping. Overall, it is concluded that the coastal beach bordering the Konan basin is not significantly sloping, the contribution of tidal loading to tide-induced groundwater fluctuations in the Dridrate aquifer is not appreciable, and that the aquifer leakage and outlet capping do not exist at the unconfined sites under investigation.     

Urban base flow with low impact development

A novel form of urbanization, low impact development (LID), aims to engineer systems that replicate natural hydrologic functioning, in part by infiltrating stormwater close to the impervious surfaces that generate it. We sought to statistically evaluate changes in a base flow regime because of urbanization with LID, specifically changes in base flow magnitude, seasonality, and rate of change. We used a case study watershed in Clarksburg, Maryland, in which streamflow was monitored during whole‐watershed urbanization from forest and agricultural to suburban residential development using LID. The 1.11‐km² watershed contains 73 infiltration‐focused stormwater facilities, including bioretention facilities, dry wells, and dry swales. We examined annual and monthly flow during and after urbanization (2004–2014) and compared alterations to nearby forested and urban control watersheds. We show that total streamflow and base flow increased in the LID watershed during urbanization as compared with control watersheds. The LID watershed had more gradual storm recessions after urbanization and attenuated seasonality in base flow. These flow regime changes may be because of a reduction in evapotranspiration because of the overall decrease in vegetative cover with urbanization and the increase in point sources of recharge. Precipitation that may once have infiltrated soil, been stored in soil moisture to be eventually transpired in a forested landscape, may now be recharged and become base flow. The transfer of evapotranspiration to base flow is an unintended consequence to the water balance of LID. © 2016 The Authors Hydrological Processes Published by John Wiley & Sons Ltd.     

Sedimentological analysis of a Late Quaternary coastal dune system: An example from Gopnath,south‐east Saurashtra,Western India

Coastal dune systems consisting of allochemical grains are important sedimentary archives of Pleistocene age in both of the hemispheres between the latitudes of 20° to 40°. The south Saurashtra coast in western India exhibits a large section of Middle Pleistocene aeolianites in the form of coastal cliffs, which is famous as ‘Miliolite’. Miliolites of Gopnath in south‐east Saurashtra are the oldest known coastal aeolianite deposits (age >156 ka which corresponds to Marine Isotope Stage 6) in western India. Aeolian deposits of similar ages have also been reported from the Thar Desert in north‐west India and from Southern Arabia which were largely controlled by the south‐west monsoon wind system that affects the entire belt corresponding to Sahara–Sahel, the Arabian Peninsula and north‐western India. Miliolite deposits in Gopnath are characterized by grainfall, grainflow and wind ripple laminations. At least three types of aeolian bounding surfaces have been identified. Five major facies have been identified which represent the dune and interdune relationship within the coastal aeolian system. The major dune bodies are identified as transverse dune types. The Gopnath aeolianites were deposited under dominantly dry aeolian conditions. Facies association reveals two different phases of aeolian accumulation, namely initiation of aeolian sedimentation after a prolonged hiatus and the establishment of a regularized aeolian sedimentation system. While initiation of aeolian sedimentation is marked by vast stretches of sheet sand with occasional dune bodies, the overlying thick, tabular, laterally extensive cross‐stratified units manifest regular aeolian sedimentation. However, the dune building events in Gopnath were interrupted by development of laterally extensive palaeosol horizons. Eustasy and climate exerted the major allogenic controls on the aeolian sedimentation by affecting the sediment budget as well as influencing the sedimentation pattern.     

Parameter identification and uncertainty analysis for simulating streamflow in a river basin of Eastern India

Uncertainty is inherent in modelling studies. However, the quantification of uncertainties associated with a model is a challenging task, and hence, such studies are somewhat limited. As distributed or semi‐distributed hydrological models are being increasingly used these days to simulate hydrological processes, it is vital that these models should be equipped with robust calibration and uncertainty analysis techniques. The goal of the present study was to calibrate and validate the Soil and Water Assessment Tool (SWAT) model for simulating streamflow in a river basin of Eastern India, and to evaluate the performance of salient optimization techniques in quantifying uncertainties. The SWAT model for the study basin was developed and calibrated using Parameter Solution (ParaSol), Sequential Uncertainty Fitting Algorithm (SUFI‐2) and Generalized Likelihood Uncertainty Estimation (GLUE) optimization techniques. The daily observed streamflow data from 1998 to 2003 were used for model calibration, and those for 2004–2005 were used for model validation. Modelling results indicated that all the three techniques invariably yield better results for the monthly time step than for the daily time step during both calibration and validation. The model performances for the daily streamflow simulation using ParaSol and SUFI‐2 during calibration are reasonably good with a Nash–Sutcliffe efficiency and mean absolute error (MAE) of 0.88 and 9.70 m³/s for ParaSol, and 0.86 and 10.07 m³/s for SUFI‐2, respectively. The simulation results of GLUE revealed that the model simulates daily streamflow during calibration with the highest accuracy in the case of GLUE (R² = 0.88, MAE = 9.56 m³/s and root mean square error = 19.70 m³/s). The results of uncertainty analyses by SUFI‐2 and GLUE were compared in terms of parameter uncertainty. It was found that SUFI‐2 is capable of estimating uncertainties in complex hydrological models like SWAT, but it warrants sound knowledge of the parameters and their effects on the model output. On the other hand, GLUE predicts more reliable uncertainty ranges (R‐factor = 0.52 for daily calibration and 0.48 for validation) compared to SUFI‐2 (R‐factor = 0.59 for daily calibration and 0.55 for validation), though it is computationally demanding. Although both SUFI‐2 and GLUE appear to be promising techniques for the uncertainty analysis of modelling results, more and more studies in this direction are required under varying agro‐climatic conditions for assessing their generic capability. Copyright © 2015 John Wiley & Sons, Ltd.     

SST and ENSO variability and change simulated in historical experiments of CMIP5 models

This work documents the diversity in Coupled Model Inter-comparison Project Phase 5 (CMIP5) models in simulating different aspects of sea surface temperature (SST) variability, particularly those associated with the El Niño–Southern Oscillation (ENSO), as well as the impact of low-frequency variations on the ENSO variability and its global teleconnection. The historical simulations (1870–2005) include 10 models with ensemble member ranging from 3 to 10 that are forced with observed atmospheric composition changes reflecting both natural and anthropogenic forcings. It is shown that the majority of the CMIP5 models capture the relative large SST anomaly variance in the tropical central and eastern Pacific, as well as in North Pacific and North Atlantic. The frequency of ENSO is not well captured by almost all models, particularly for the period of 5–6 years. The low-frequency variations in SST caused by external forcings affect the SST variability and also modify the global teleconnection of ENSO. The models reproduce the global averaged SST low-frequency variations, particularly since 1970s. However, majority of the models are unable to correctly simulate the spatial pattern of the observed SST trends. These results suggest that it is still a challenge to reproduce the features of global historical SST variations with the state-of-the-art coupled general circulation model.     

Stormwater management network effectiveness and implications for urban watershed function: A critical review

Deleterious effects of urban stormwater are widely recognized. In several countries, regulations have been put into place to improve the conditions of receiving water bodies, but planning and engineering of stormwater control is typically carried out at smaller scales. Quantifying cumulative effectiveness of many stormwater control measures on a watershed scale is critical to understanding how small‐scale practices translate to urban river health. We review 100 empirical and modelling studies of stormwater management effectiveness at the watershed scale in diverse physiographic settings. Effects of networks with stormwater control measures (SCMs) that promote infiltration and harvest have been more intensively studied than have detention‐based SCM networks. Studies of peak flows and flow volumes are common, whereas baseflow, groundwater recharge, and evapotranspiration have received comparatively little attention. Export of nutrients and suspended sediments have been the primary water quality focus in the United States, whereas metals, particularly those associated with sediments, have received greater attention in Europe and Australia. Often, quantifying cumulative effects of stormwater management is complicated by needing to separate its signal from the signal of urbanization itself, innate watershed characteristics that lead to a range of hydrologic and water quality responses, and the varying functions of multiple types of SCMs. Biases in geographic distribution of study areas, and size and impervious surface cover of watersheds studied also limit our understanding of responses. We propose hysteretic trajectories for how watershed function responds to increasing imperviousness and stormwater management. Even where impervious area is treated with SCMs, watershed function may not be restored to its predevelopment condition because of the lack of treatment of all stormwater generated from impervious surfaces; non‐additive effects of individual SCMs; and persistence of urban effects beyond impervious surfaces. In most cases, pollutant load decreases largely result from run‐off reductions rather than lowered solute or particulate concentrations. Understanding interactions between natural and built landscapes, including stormwater management strategies, is critical for successfully managing detrimental impacts of stormwater at the watershed scale.