Fourier analysis of short-period water level variations in the Rotorua geothermal field, New Zealand

Geothermics ◽  
2007 ◽  
Vol 36 (6) ◽  
pp. 539-557 ◽  
Author(s):  
Jonathan D. Leaver ◽  
Charles P. Unsworth
Keyword(s):  
New Zealand ◽  
Fourier Analysis ◽  
Water Level ◽  
Geothermal Field ◽  
Short Period ◽  
Water Level Variations

scholarly journals Comparative Analysis of Runoff and Evaporation Assessment Methods to Evaluate Wetland–Groundwater Interaction in Mediterranean Evaporitic-Karst Aquatic Ecosystem

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1482
Author(s):  
José Manuel Gil-Márquez ◽  
Bartolomé Andreo ◽  
Matías Mudarra
Keyword(s):  
Water Level ◽  
Water Budget ◽  
Aquatic Ecosystems ◽  
Hydrological Model ◽  
Control Period ◽  
Curve Number ◽  
Model Fit ◽  
Morphometrical Analysis ◽  
Short Period ◽  
Water Level Variations

This work compares the applicability of several free-surface evaporation and runoff equations in simulating water level variations of small Mediterranean wetlands. The Amarga and Jarales wetland are two pilot sites with an evaporite-karst genesis located in southern Spain. The water level was continuously recorded in both wetlands, and exhaustive weather monitoring was performed. The combined datasets have permitted quantification of the surficial elements of their water budget (precipitation, runoff, and evaporation). Several campaigns of groundwater level measurements were also done to characterize the direction of groundwater flows. The morphometrical analysis of the Jarales wetland was accurately performed based on a LiDAR dataset. A total of 225 limnimetric simulations of the Jarales (90) and Amarga (135) wetlands were performed, combining different evaporation and runoff equations. During the study period, the curve number method, coupled with the Penman equation, reached the Jarales wetland’s best calibrations. The Vardavas–Fountoulakis modification of the Penman model fit better with the Amarga wetland record. The obtained results permit specification of the water budget of both wetlands during several years and confirm that the groundwater–surface water relationship affects the wetland hydric dynamic to different degrees. Nonetheless, the limnimetric models were calibrated for a short period, including dry years, making it necessary to extend the control period longer and validate the models under different hydroclimatic conditions. Finally, the differences between wetland functioning are explained in a conceptual hydrological model that can be useful for wetland conservation and management of related aquatic ecosystems. The understanding of the origin and fate of water in wetlands permits assessment of how future scenarios would affect hydric functioning and suggests adequate conservation measurements.

scholarly journals Spatial distribution of water level impact to back-barrier bays

2018 ◽  
Author(s):  
Alfredo L. Aretxabaleta ◽  
Neil K. Ganju ◽  
Zafer Defne ◽  
Richard P. Signell
Keyword(s):  
Water Level ◽  
Sea Level ◽  
Water Levels ◽  
Analytical Models ◽  
Barnegat Bay ◽  
Sea Level Fluctuations ◽  
Flooding Hazard ◽  
Short Period ◽  
Inlet Geometry ◽  
Spatial Estimates

Abstract. Water level in semi-enclosed bays, landward of barrier islands, is mainly driven by offshore sea level fluctuations that are modulated by bay geometry and bathymetry, causing spatial variability in the ensuing response (transfer). Local wind setup can have a secondary role that depends on wind speed, fetch, and relative orientation of the wind direction and the bay. Inlet geometry and bathymetry primarily regulate the magnitude of the transfer between open ocean and bay. Tides and short-period offshore oscillations are more damped in the bays than longer-lasting offshore fluctuations, such as storm surge and sea level rise. We compare observed and modeled water levels at stations in a mid-Atlantic bay (Barnegat Bay) with offshore water level proxies. Observed water levels in Barnegat Bay are compared and combined with model results from the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) modeling system to evaluate the spatial structure of the water level transfer. Analytical models based on the dimensional characteristics of the bay are used to combine the observed data and the numerical model results in a physically consistent approach. Model water level transfers match observed values at locations inside the Bay in the storm frequency band (transfers ranging from 70–100 %) and tidal frequencies (10–55 %). The contribution of frequency-dependent local setup caused by wind acting along the bay is also considered. The approach provides transfer estimates for locations inside the Bay where observations were not available resulting in a complete spatial characterization. The approach allows for the study of the Bay response to alternative forcing scenarios (landscape changes, future storms, and rising sea level). Detailed spatial estimates of water level transfer can inform decisions on inlet management and contribute to the assessment of current and future flooding hazard in back-barrier bays and along mainland shorelines.

Presentation and assessment of tides and water level records for geophysical investigations

1970 ◽  
Vol 7 (2) ◽  
pp. 607-625 ◽  
Author(s):  
G. C. Dohler ◽  
L. F. Ku
Keyword(s):  
Water Level ◽  
Power Spectra ◽  
Rate Of Change ◽  
Regression Technique ◽  
Level Data ◽  
Water Level Data ◽  
Geophysical Investigations ◽  
Water Level Variations ◽  
Mean Water Level ◽  
Change In Mean

The methods and problems involved in collecting water level data are explained, and the processing and formats of the data are illustrated. The trend of the change in mean water level is plotted and the corresponding rate of change is estimated by the regression technique. The power spectra of the water level variations are plotted to illustrate these variations in terms of frequencies.

scholarly journals The lunar and solar diurnal variations of water-level in a well at Kew observatory, Richmond

1918 ◽  
Vol 94 (663) ◽  
pp. 476-478
Keyword(s):  
Water Level ◽  
Royal Society ◽  
Correlation Coefficients ◽  
Barometric Pressure ◽  
Diurnal Variations ◽  
Range Of Movement ◽  
Nearest Point ◽  
Similar Relation ◽  
Short Period ◽  
The Mean

In a paper communicated to the Royal Meteorological Society, it was shown that the experimental well at Kew Observatory responded to the lunar fortnightly oscillation of mean level in the River Thames, which is 300 yards from the Observatory at its nearest point. The sensitiveness of the water-level to barometric pressure has also been investigated, and the results have been given in a paper recently read before the Royal Society. The present paper deals with the effects of the short-period tides in the solar and lunar series, S 1 , S 2 , S 3 , S 4 , and M 1 , M 2 , M 3 , M 4 . Two-hourly measurements, both in lunar and solar time, were made on the traces obtained during the first two years, August, 1914-August, 1916, omitting days of very irregular movement. Monthly mean inequalities were then computed. Well marked solar and lunar diurnal variations were found in each month, taking the form of double oscillations with two maxima and two minima during the 24 hours. The range of movement was in each case found to be highly associated with the mean height of the water in the well, the correlation coefficients being 0·89 (lunar) and 0·90 (solar). A similar relation had been previously found to exist in the case of barometric pressure.

Revised hydrogeological model of the hydrothermal system Waiwera (New Zealand)

2021 ◽  
Author(s):  
Andreas Grafe ◽  
Thomas Kempka ◽  
Michael Schneider ◽  
Michael Kühn
Keyword(s):  
Water Management ◽  
New Zealand ◽  
Water Level ◽  
Hot Water ◽  
Hydrogeology Journal ◽  
Natural State ◽  
Geothermal System ◽  
Geological Model ◽  
Species Transport ◽  
Study Region

<p>The geothermal hot water reservoir underlying the coastal township of Waiwera, northern Auckland Region, New Zealand, has been commercially utilized since 1863. The reservoir is complex in nature, as it is controlled by several coupled processes, namely flow, heat transfer and species transport. At the base of the aquifer, geothermal water of around 50°C enters. Meanwhile, freshwater percolates from the west and saltwater penetrates from the sea in the east. Understanding of the system’s dynamics is vital, as decades of unregulated, excessive abstraction resulted in the loss of previously artesian conditions. To protect the reservoir and secure the livelihoods of businesses, a Water Management Plan by The Auckland Regional Council was declared in the 1980s [1]. In attempts to describe the complex dynamics of the reservoir system with the goal of supplementing sustainable decision-making, studies in the past decades have brought forth several predictive models [2]. These models ranged from being purely data driven statistical [3] to fully coupled process simulations [1].<br><br>Our objective was to improve upon previous numerical models by introducing an updated geological model, in which the findings of a recently undertaken field campaign were integrated [4]. A static 2D Model was firstly reconstructed and verified to earlier multivariate regression model results. Furthermore, the model was expanded spatially into the third dimension. In difference to previous models, the influence of basic geologic structures and the sea water level onto the geothermal system are accounted for. Notably, the orientation of dipped horizontal layers as well as major regional faults are implemented from updated field data [4]. Additionally, the model now includes the regional topography extracted from a digital elevation model and further combined with the coastal bathymetry. Parameters relating to the hydrogeological properties of the strata along with the thermophysical properties of water with respect to depth were applied. Lastly, the catchment area and water balance of the study region are considered.<br><br>The simulation results provide new insights on the geothermal reservoir’s natural state. Numerical simulations considering coupled fluid flow as well as heat and species transport have been carried out using the in-house TRANSport Simulation Environment [5], which has been previously verified against different density-driven flow benchmarks [1]. The revised geological model improves the agreement between observations and simulations in view of the timely and spatial development of water level, temperature and species concentrations, and thus enables more reliable predictions required for water management planning.<br><br>[1] Kühn M., Stöfen H. (2005):<br>      Hydrogeology Journal, 13, 606–626,<br>      https://doi.org/10.1007/s10040-004-0377-6<br><br>[2] Kühn M., Altmannsberger C. (2016):<br>      Energy Procedia, 97, 403-410,<br>      https://doi.org/10.1016/j.egypro.2016.10.034<br><br>[3] Kühn M., Schöne T. (2017):<br>      Energy Procedia, 125, 571-579,<br>      https://doi.org/10.1016/j.egypro.2017.08.196<br><br>[4] Präg M., Becker I., Hilgers C., Walter T.R., Kühn M. (2020):<br>      Advances in Geosciences, 54, 165-171,<br>      https://doi.org/10.5194/adgeo-54-165-2020<br><br>[5] Kempka T. (2020):<br>      Adv. Geosci., 54, 67–77,<br>      https://doi.org/10.5194/adgeo-54-67-2020</p>

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