Application of genetic algorithm technique to inverse modeling of tide–aquifer interaction

Modeling of tide–aquifer interaction plays a vital role in the management of coastal aquifer systems. A novel and robust methodology is presented in this paper for estimating aquifer parameters of coastal aquifers from tide–aquifer interaction data using tide–aquifer interaction model and genetic algorithm (GA). Two stand-alone computer programs were developed to optimize hydraulic diffusivities of unconfined and confined coastal aquifers at multiple sites using GA technique and tide–aquifer interaction model and considering two approaches (‘lumped tidal component approach’ and ‘multi-tidal component approach’). Five sets of real-world tide–aquifer interaction data at two sites of an unconfined aquifer and one set of tide–aquifer interaction data at three sites of a confined aquifer were used to demonstrate the efficacy of the methodology. The analysis of the GA-based inverse modeling results indicated that the ‘multi-tidal component approach’ yields more accurate and reliable hydraulic diffusivities for the unconfined aquifer (RMSE = 0.0129–0.0521 m, NSE = 0.70–0.97, and d1 = 0.91–0.99) as well as for the confined aquifer (RMSE = 0.0204–0.0545 m, NSE = 0.95–0.97, and d1 = 0.99) compared with the ‘lumped tidal component approach’. A comparative evaluation of data-size revealed that the short-duration datasets of the unconfined aquifer provide more reliable estimate of hydraulic diffusivity than the long-duration datasets. Further, it was found that the spring and neap tidal data yield unreasonable values of hydraulic diffusivity with considerably high values of RMSE and very low values of r ², NSE, and d1, thereby suggesting that spring and neap tidal data are not suitable for aquifer parameter estimation. Overall, it is concluded that the GA-based tide–aquifer interaction model following ‘multi-tidal component approach’ is the most efficient tool for estimating aquifer parameters of unconfined and confined aquifers from tide–aquifer interaction data. The developed methodology is also applicable to other coastal basins of the world irrespective of hydrogeological settings.     

Analysis of optimal strategies for soft landing on the Moon from lunar parking orbits

Optimal trajectory design of a probe for soft landing on the Moon from a lunar parking orbit by minimizing the fuel required is obtained. The problem is formulated as an optimal control problem with the thrust direction being the control variable. Using the maximum principle of Pontryagin, the control variable is expressed as a function of co-state variables and the problem is converted into a two-point boundary value problem. The two-point boundary value problem is solved using an optimization technique, i.e., controlled random search. The strategies such as

Semiactive fuzzy control of the seismic response of building frames with MR dampers

A fuzzy‐logic control algorithm, based on the fuzzification of the MR damper characteristics, is presented for the semiactive control of building frames under seismic excitation. The MR damper characteristics are represented by force–velocity and force–displacement curves obtained from the sinusoidal actuation test. The method does not require any analytical model of MR damper characteristics, such as the Bouc‐Wen model, to be incorporated into the control algorithm. The control algorithm has a feedback structure and is implemented by using the fuzzy‐logic and Simulink toolboxes of MATLAB. The performance of the algorithm is studied by using it to control the responses of two example buildings taken from the literature—a three‐storey building frame, in which controlled responses are obtained by clipped‐optimal control and a ten‐storey building frame. The results indicate that the proposed scheme provides nearly the same percentage reduction of responses as that obtained by the clipped‐optimal control with much less control force and much less command voltage. Position of the damper is found to significantly affect the controlled responses of the structure. It is observed that any increase in the damper capacity beyond a saturation level does not improve the performance of the controller. Copyright © 2011 John Wiley & Sons, Ltd.     

Numerical groundwater-flow modeling to evaluate potential effects of pumping and recharge: implications for sustainable groundwater management in the Mahanadi delta region,India

Process-based groundwater models are useful to understand complex aquifer systems and make predictions about their response to hydrological changes. A conceptual model for evaluating responses to environmental changes is presented, considering the hydrogeologic framework, flow processes, aquifer hydraulic properties, boundary conditions, and sources and sinks of the groundwater system. Based on this conceptual model, a quasi-three-dimensional transient groundwater flow model was designed using MODFLOW to simulate the groundwater system of Mahanadi River delta, eastern India. The model was constructed in the context of an upper unconfined aquifer and lower confined aquifer, separated by an aquitard. Hydraulic heads of 13 shallow wells and 11 deep wells were used to calibrate transient groundwater conditions during 1997–2006, followed by validation (2007–2011). The aquifer and aquitard hydraulic properties were obtained by pumping tests and were calibrated along with the rainfall recharge. The statistical and graphical performance indicators suggested a reasonably good simulation of groundwater flow over the study area. Sensitivity analysis revealed that groundwater level is most sensitive to the hydraulic conductivities of both the aquifers, followed by vertical hydraulic conductivity of the confining layer. The calibrated model was then employed to explore groundwater-flow dynamics in response to changes in pumping and recharge conditions. The simulation results indicate that pumping has a substantial effect on the confined aquifer flow regime as compared to the unconfined aquifer. The results and insights from this study have important implications for other regional groundwater modeling studies, especially in multi-layered aquifer systems.     

Impacts of payment for ecosystem services of mountain agricultural landscapes on farming women in Nepal

GeoJournal - This study assesses the potential impacts of Payment for Ecosystems Services (PES) of mountain agricultural landscapes, with a specific focus on the implications for Nepalese farming...     

Groundwater response to serial stream stage fluctuations in shallow unconfined alluvial aquifers along a regulated stream (West Virginia,USA)

Groundwater response to stream stage fluctuations was studied in two unconfined alluvial aquifers using a year-long time series of stream stages from two pools along a regulated stream in West Virginia, USA. The purpose was to analyze spatial and temporal variations in groundwater/surface-water interaction and to estimate induced infiltration rate and cumulative bank storage during an annual cycle of stream stage fluctuation. A convolution-integral method was used to simulate aquifer head at different distances from the stream caused by stream stage fluctuations and to estimate fluxes across the stream–aquifer boundary. Aquifer diffusivities were estimated by wiggle-matching time and amplitude of modeled response to multiple observed storm events. The peak lag time between observed stream and aquifer stage peaks ranged between 14 and 95 hour. Transient modeled diffusivity ranged from 1,000 to 7,500 m²/day and deviated from the measured and calculated single-peak stage-ratio diffusivity by 14–82 %. Stream stage fluctuation displayed more primary control over groundwater levels than recharge, especially during high-flow periods. Dam operations locally altered groundwater flow paths and velocity. The aquifer is more prone to surface-water control in the upper reaches of the pools where stream stage fluctuations are more pronounced than in the lower reaches. This method could be a useful tool for quick assessment of induced infiltration rate and bank storage related to contamination investigations or well-field management.     

Evaluating persistence and identifying trends and abrupt changes in monthly and annual rainfalls of a semi-arid region in Western India

In this study, 43-year (1965–2007) monthly and annual rainfall time series of ten rainfall stations in a semi-arid region of western India are analyzed by adopting three tests for testing normality and by applying autoregressive technique for exploring persistence. Gradual trends are identified by three tests, and their magnitudes are assessed by the Sen’s slope estimator. Also, abrupt changes are detected by using four tests and they are further confirmed by two tests. Box-whisker plots revealed that the rainfalls of June and September are right skewed for all the stations. The annual rainfalls of Bhinder, Dhariawad, and Gogunda stations are found considerably right skewed. The normality tests indicated that the rainfall of July does not deviate from the normal distribution at all the stations. However, the annual rainfall is found non-normal at five stations. The monthly rainfalls of June, July, and August have persistence respectively at three (Mavli, Salumber, and Sarada), two (Kherwara and Sarada), and one (Mavli) stations, whereas the annual rainfall has persistence at Girwa and Mavli stations. Significantly increasing trend is detected at Mavli in the rainfall of July and in the annual rainfall (p value?>?0.05), while the negative trend in August rainfall at Dhariawad is found significant (p value?>?0.10). This study revealed that the presence of serial correlation does not affect the performance of the Mann-Kendall test. Mean values of trend magnitudes for the rainfalls of June, July, August, and September are 0.3, 0.8, ?0.4, and 0.4 mm year^?1, respectively, and the overall mean value for the annual rainfall is 0.9 mm year^?1. It is found that the standard normal homogeneity test and the Pettitt test are biased towards the end of the series to locate a change point. Conversely, the Bayesian test has a tendency to look for a change point in the beginning of time series. Confirmed abrupt changes in the rainfall time series are found in the year 2003 (Bhinder) in June; years 1974 (Mavli) and 1989 (Dhariawad and Salumber) in July; years 1972 (Sarada), 1990 (Dhariawad), and 2003 (Mavli) in August; years 1977 (Dhariawad), 1991 (Sarada), and 2004 (Kotra) in September; and in the year 1972 (Mavli and Sarada stations) in the annual series. It is emphasized that the significantly increasing trend of rainfall may have linkages with climate change and/or variability. Finally, this study recommends use of multiple statistical tests for analyzing hydrologic time series in order to ensure reliable decisions.     

Modeling Short-Term Spatial and Temporal Variability of Groundwater Level Using Geostatistics and GIS

Continuous depletion of groundwater levels from deliberate and uncontrolled exploitation of groundwater resources lead to the severe problems in arid and semi-arid hard-rock regions of the world. Geostatistics and geographic information system (GIS) have been proved as successful tools for efficient planning and management of the groundwater resources. The present study demonstrated applicability of geostatistics and GIS to understand spatial and temporal behavior of groundwater levels in a semi-arid hard-rock aquifer of Western India. Monthly groundwater levels of 50 sites in the study area for 36-month period (May 2006 to June 2009; excluding 3 months) were analyzed to find spatial autocorrelation and variances in the groundwater levels. Experimental variogram of the observed groundwater levels was computed at 750-m lag distance interval and the four most-widely used geostatistical models were fitted to the experimental variogram. The best-fit geostatistical model was selected by using two goodness-of-fit criteria, i.e., root mean square error (RMSE) and correlation coefficient (r). Then spatial maps of the groundwater levels were prepared through kriging technique by means of the best-fit geostatistical model. Results of two spatial statistics (Geary’s C and Moran’s I) indicated a strong positive autocorrelation in the groundwater levels within 3-km lag distance. It is emphasized that the spatial statistics are promising tools for geostatistical modeling, which help choose appropriate values of model parameters. Nugget-sill ratio (<0.25) revealed that the groundwater levels have strong spatial dependence in the area. The statistical indicators (RMSE and r) suggested that any of the three geostatistical models, i.e., spherical, circular, and exponential, can be selected as the best-fit model for reliable and accurate spatial interpolation. However, exponential model is used as the best-fit model in the present study. Selection of the exponential model as the best-fit was further supported by very high values of coefficient of determination (r ² ranging from 0.927 to 0.994). Spatial distribution maps of groundwater levels indicated that the groundwater levels are strongly affected by surface topography and the presence of surface water bodies in the study area. Temporal pattern of the groundwater levels is mainly controlled by the rainy-season recharge and amount of groundwater extraction. Furthermore, it was found that the kriging technique is helpful in identifying critical locations over the study area where water saving and groundwater augmentation techniques need to be implemented to protect depleting groundwater resources.