A method of constructing a dynamic chart depth model for coastal areas.

An interdisciplinary study was carried out to trace the hydrological changes of the Havel River in northeastern central Europe over the last ca. 2000 years. This research was driven by the hypothesis that the present‐day riverscape is to a large degree a result of medieval and modern human transformation of the drainage system. The river system forms a series of dammed lakes and river sections that were greatly altered through hydraulic engineering in the past. Along the middle course of the Havel, 16 sedimentary sequences available for geoarchaeological and paleoecological research were analyzed in order to reconstruct regional water level dynamics. Chronological control was ensured through a multitude of palynological, dendrochronological, archaeological, and radiocarbon data. The sections upriver from the Brandenburg/H. and Spandau weirs, representing sites with historic watermills, reveal substantial water level changes during the late Holocene. Generally, lower water levels before and higher levels during the medieval German colonization of that area (ca. A.D. 1180/1250) can be inferred. This water level increase, which is primarily attributed to dams constructed for watermills and secondarily due to a multitude of fish weirs, took place rapidly and amounted to a relative height of ca. 1.5 m. It enlarged the river's cross‐sections and increased the size of existing lakes or initiated secondary lakes that previously aggraded, and thus caused flooding of large parts of land. The rising water level even influenced the settlement topography to a large degree. Several medieval rural settlements were abandoned due to flooding. In total, a ca. 150‐km long dammed lake cascade was formed.

Lakes are important indicators of climate change. The change in lake water level objectively reflects the availability of regional water resources. Analyzing the changes in water level and climate response of major lakes in countries along the “Belt and Road” is essential for sustainable water use and ecological protection. Based on the water level datasets of 39 large lakes (>400 km2) in China, Mongolia, and Russia (CMR) from 2002 to 2016, this study analyzed the spatiotemporal characteristics of water levels in major lakes of CMR, and their responses to climatic factors containing temperature, precipitation, and evapotranspiration. The results showed that (1) the water level of main lakes in CMR slightly increased with change rates ranged from −0.36 to 0.48 m/a, and the trends varied in lakes, (2) the water level of most lakes was sensitive to temperature with sensitivity value ranged from −2.14 m/°C to 5.59 m/°C, (3) changes of annual cumulative precipitation and evapotranspiration contributed most to the change of lake water level, but key factors affecting water level varied in lakes. Human activity is an important driving factor for the change in water levels and its impacts need further study.

Coseismic water level rises in the 30‐m deep Bourdieu Valley (BV) well near Parkfield, California, have occurred in response to three local and five distant earthquakes. Coseismic changes in static strain cannot explain these water level rises because (1) the well is insensitive to strain at tidal periods; (2) for the distant earthquakes, the expected coseismic static strain is extremely small; and (3) the water level response is of the incorrect sign for the local earthquakes. These water level changes must therefore be caused by seismic waves, but unlike seismic water level oscillations, they are monotonic, persist for days or weeks, and seem to be caused by waves with periods of several seconds rather than long‐period surface waves. Other investigators have reported a similar phenomenon in Japan. Certain wells consistently exhibit this type of coseismic water level change, which is always in the same direction, regardless of the earthquake's azimuth or focal mechanism, and approximately proportional to the inverse square of hypocentral distance. To date, the coseismic water level rises in the B V well have never exceeded the seasonal water level maximum, although their sizes are relatively well correlated with earthquake magnitude and distance. The frequency independence of the well's response to barometric pressure in the frequency band 0.1 to 0.7 cpd implies that the aquifer is fairly well confined. High aquifer compressibility, probably due to a gas phase in the pore space, is the most likely reason why the well does not respond to Earth tides. The phase and amplitude relationships between the seasonal water level and precipitation cycles constrain the horizontal hydraulic diffusivity to within a factor of 4.5, bounding hypothetical earthquake‐induced changes in aquifer hydraulic properties. Moreover, changes of hydraulic conductivity and/or diffusivity throughout the aquifer would not be expected to change the water level in the same direction at every time of the year. The first 2.5 days of a typical coseismic water level rise could be caused by a small coseismic discharge decrease at a point several tens of meters from the well. Alternatively, the entire coseismic water level signal could represent diffusion of an abrupt coseismic pore pressure increase within several meters of the well, produced by a mechanism akin to that of liquefaction. The coseismic water level changes in the BV well resemble, and may share a mechanism with, coseismic water level, stream discharge, and groundwater temperature changes at other locations where preearthquake changes have also been reported. No preearthquake changes have been observed at the BV well site, however.

Quantitative calculations for the effect of a fault creep event on observations of changes in water level in wells provide an approach to the tectonic interpretation of these phenomena. For the pore pressure field associated with an idealized creep event having an exponential displacement versus time curve, an analytic expression has been obtained in terms of exponential‐integral functions. The pore pressure versus time curves for observation points near the fault are pulselike; a sharp pressure increase (or decrease, depending on the direction of propagation) is followed by more gradual decay to the normal level after the creep event. The time function of the water level change may be obtained by applying the filter—derived by A. G. Johnson and others to determine the influence of atmospheric pressure on water level—to the analytic pore pressure versus time curves. The resulting water level curves show a fairly rapid increase (or decrease) and then a very gradual return to normal. The results of this analytic model do not reproduce the steplike changes in water level observed by Johnson and others. If the procedure used to obtain the water level from the pore pressure is correct, these results suggest that steplike changes in water level are not produced by smoothly propagating creep events but by creep events that propagate discontinously, by changes in the bulk properties of the region around the well, or by some other mechanism. In addition, simplistic calculations show that significant pressure field variations and water level changes near the surface may be expected to accompany a propagating creep event on a buried fault. Water level changes of as much as several meters may be expected at the surface for a creep event having a dislocation amplitude of l m on a semi‐infinite dislocation surface extending downward from a depth of 10 km and propagating horizontally at a rate of 10 km/day. The maximum near‐surface effect should be observed at a horizontal distance from the fault about equal to the depth of the top of the dislocation surface. These results are consistent with the observations made in China of large water level changes preceding large earthquakes, if some sort of aseismic creep event at depth precedes these earthquakes.

The Tibetan Plateau is one of the best areas for the study because of its geographical location as well as human disturbance. AS one of the largest lakes in the Qinghai-Tibet Plateau, Nam Co Lake seepage underestimated for a long time. By linear regression analysis of hydrological data from 1970-2005, we qualitatively understands the water level operation mechanism. The result shows that the model deviates from 2000, compared with the actual water level. Correlation analysis indicates the Nam Co Lake seepage flow reduces after 2000. The Three Gorges project resulted in the uplift of the downstream water level, which exacerbates the rise of water level of Nam Co Lake. Owing to the non timeliness of underground seepage recharge, water level of downstream lake is difficult to simulate. According to the result and recent research, underground seepage may be a cycle, affecting the water level of all the lakes.

Rapid Plant Community Response to a Water Level Peak in Northern Lake Huron Coastal Wetlands

Do anthropogenic hydrological alterations in shallow lakes affect the dynamics of plankton?

Exploring whether diatom diversity in a lake sediment core is representative of that of the entire lake is important for determining the response of lake diatom diversity to global climatic warming. In this study, Yunlong Lake, an alpine lake located in Yunnan Province, Southwest China, was investigated to explore this question over both space and time. Spatially, we investigated diatom diversity patterns in 62 surface sediment samples from different locations and depth zones of Yunlong lake and found essentially constant diatom diversity across the entire lake basin. Temporally, we studied a well-dated sediment core from the lake center to explore whether long-term water-level changes influenced diatom diversity over the last ~ 100 years. Changes in the annual average sediment accumulation rates indicate that the water level of Yunlong Lake increased substantially after the construction of a dam. However, there is no obvious relationship between diatom diversity and water-level changes, which suggests at this site long-term water-level changes did not influence diatom diversity. Comparative analysis of the results for Yunlong Lake with those for other lakes indicates that for relatively strongly mixed lakes with a simple morphology and uniform shoreline microhabitat, such as Yunlong Lake, differences in water depth and changes in water level may not influence diatom diversity. In such cases, the diatom diversity from a sediment core is likely to be representative of that of the entire lake during specific time intervals. Therefore, such lakes may be optimal for studies of changes in past diatom diversity using sediment cores.

Inland lakes or reservoirs are the main surface water resources, related to people’s survival and social development. On-site water level data are critical for water resource management, while satellite laser and remote sensing data are a significant tool for long-term change monitoring. In this study, we took the Miyun Reservoir, the most important source of drinking water in Beijing, as the research area. We used Landsat images and the Ice, Cloud, and Land Elevation Satellite (ICESat-2) for small-scale water level change monitoring and inversion across unrecorded periods. First, we proposed a new two-step denoising method based on local statistics to denoise the ATL03 single photon data from 2018 to 2020, and extracted the effective elevation information of Miyun Reservoir. Second, based on Landsat images from 1984 to 2020, the MNDWI index was used to extract the water area and generated a percentage map of water occurrence. Finally, the water and land boundary elevation were selected from the effective photon elevation information according to the boundary position under each percentage of the water generation percentage graph, the area, and the water level elevation model (A–E model) was established, and the water level values of unrecorded periods were inverted. The denoising results showed that the denoising accuracy of all data is higher than 95%. The area of Miyun Reservoir has changed greatly in the past 37 years, especially in the northeast corner and northern region. The inverted water level elevation had a strong correlation with the measured value, the correlation coefficient reached 0.97, the root mean square error (RMSE) was 0.553 m, and the estimated water level value was highly consistent with the recorded value and fluctuated dramatically from 1984 to 2020. This method complements the traditional water level mapping method, provides a new idea for the monitoring of water level changes in lakes or reservoirs without field records, and also contributes to the timely and effective monitoring and management of global lake and reservoir water level and time changes.

ABSTRACT: Federal agencies in the U.S. and Canada continuously examine methods to improve understanding and forecasting of Great Lakes water level dynamics in an effort to reduce the negative impacts of fluctuating levels incurred by interests using the lakes. The short term, seasonal and long term water level dynamics of lakes Erie and Ontario are discussed. Multiplicative, seasonal ARIMA models are developed for lakes Erie and Ontario using standardized, monthly mean level data for the period 1900 to 1986. The most appropriate model identified for each lake had the general form: (1 0 1)(0 1 1)12. The data for each lake were subdivided by time periods (1900 to 1942;1 943 to 1986) and the model coefficients estimated for the subdivided data were similar, indicating general model stability for the entire period of record. The models estimated for the full data sets were used to forecast levels 1,2,3, and 6 months ahead for a period of high levels (1984 to 1986). The average absolute forecast error for Lake Erie was 0.049m, 0.076m, 0.091 m and 0.128m for the 1, 2,3, and 6 month forecasts, respectively. The average absolute forecast error for Lake Ontario was 0.058m, 0.095m, 0.120m and 0.136m for the 1,2,3, and 6 month forecasts, respectively. The ARIMA models provide additional information on water level time series structure and dynamics. The models also could be coordinated with current forecasting methods, possibly improving forecasting accuracy.

There is limited research focusing on Interferometric Synthetic Aperture Radar (InSAR) applications in the Great Lakes coastal wetlands with large water level fluctuations. In this study, we investigated the potential of using C-band SAR data to characterize marsh wetland and monitor water level changes along the coast of the Great Lakes. InSAR analysis was conducted using Radarsat-2 and Sentinel-1 data collected at Long Point, Ontario, Canada over the period of 2016–2018. Observations indicated that both backscattering coefficients and coherence from tall plants (e.g. cattail/Phragmites), short plants (e.g. grass), and water varied with different sensor modes (incidence angles and polarizations) in response to changes in phenology, disturbance, and water level. InSAR phase changes were closely related to fluctuations in water level and flow direction. We evaluated InSAR time series observations using measurements from water level loggers based on correlation and root mean square error (RMSE). It was found that correlation between InSAR measurements and water level changes in the field varied depending on the site, type of wetland vegetation, incidence angle and polarization. Although results from some sensor modes provided good correlation at a few locations, the low fringe rate and RMSE between 9 and 28 cm indicated that InSAR observations of water level changes were generally underestimated.

The dynamics of the mid-channel bars (MCBs) in the Three Gorges Reservoir (TGR) were substantially impacted by the large water-level changes due to the impoundments of the TGR. However, it is still not clear how the morphology of the MCBs changed under the influence of water level and hydrological regime changes induced by the impoundments and operation of the TGR. In this work, the MCBs in the TGR were retrieved using Landsat remote sensing images from 1989 to 2019, and the spatio-temporal variations in the number, area, morphology and location of the MCBs during different impoundment periods were investigated. The results showed that the number and area of MCBs changed dramatically with water-level changes, and the changes were dominated by MCBs with an area less than 0.03 km2 and larger than 1 km2. The area of MCBs decreased progressively with the rising water level, and the number generally showed a decreasing trend, with the minimum number occurring at the third stage when the water level reached 139 m, resulting in the maximum average area at this period. The ratio of length to width of the MCBs generally decreased with the changes in hydrological and sediment regimes, leading to a shape adjustment from narrow–long to relatively short–round with the rising of the water level. The water impoundments of the TGR led to the migration of the dominant area from the upper section to the middle section of the TGR and resulted in a more even distribution of MCBs in the TGR. The results improve our understanding of the mechanisms of the development of MCBs in the TGR under the influence of water impoundment coupled with the annually cyclic hydrological regime and longer periods of inundation and exposure.

In a river with a lack of flood plane so called wando, water level rises up locally during flood. It is important to predict this change in water level for preventing the flood disaster. By using the two-dimensional shallow-water-flow model, it isable to estimate the plane distribution of water level and flow pattern in a river with a wandand it is shown that the calculation results on the longitudinal distribution of water level agree with the model experimental those. It becomes clear that the change in water level occurs mainly due to the local change in cross sectional area and its value relates to the velocity and the length, width, depth of lack. The convenient evaluating method of the change in water-level due to a lack of flood plane is proposed.

Generating accurate monthly estimations of water level fluctuations in reservoirs and lakes is crucial for supporting effective water resource management and protection. The dual-satellite configuration of Sentinel-3 makes it possible to monitor water level changes with great coverage and short time intervals. However, the potential of Sentinel-3’s Synthetic Aperture Radar Altimetry (SRAL) data to enable operational monitoring of water levels across Jiangsu Province on a monthly basis has not yet been fully explored. This study demonstrated and validated the use of Sentinel-3’s SRAL to generate accurate monthly water level estimations needed to inform water management strategies. The monthly water levels of lakes and reservoirs from 2017 to 2021 were produced using Sentinel-3 level-2 land products. Results showed that, compared with in situ data across eight studied lakes, all lakes presented R (Pearson correlation coefficient) values greater than 0.5 and Root Mean Square Error (RMSE) values less than 1 m. Notably, water level estimates for Tai Lake, Gaoyou Lake, and Luoma Lake were particularly accurate, with R above 0.9 and RMSE below 0.5 m. Furthermore, the monthly water level estimates derived from the Sentinel-3 data showed consistent seasonal trends over the multi-year study period. The annual water level of all lakes did not change significantly, except for Shijiu Lake, of which the difference between the highest and lowest water level was up to about 5 m. Our findings confirmed the water level observation ability of Sentinel-3. The accuracy of water level monitoring could be influenced by internal water level differences, terrain features, as well as the area and shape of the lake. Larger lakes with more altimetry sampling points tended to yield higher accuracy estimates of water level fluctuations. These results demonstrate that the frequent, wide-area coverage offered by this satellite platform provides valuable hydrological information, especially across remote regions lacking in situ data. Sentinel-3 has immense potential to support improved water security in data-scarce regions.

The Bureau of Reclamation is developing a water-resource project, the Closed Basin Division, in the San Luis Valley of south-central Colorado that is designed to salvage unconfined ground water that currently is discharged as evapotranspiration. The water table in and near the 130,000-acre Closed Basin Division area will be lowered by an annual withdrawal of as much as 100,000 acre-feet of ground water from the unconfined aquifer. The legislation authorizing the project limits resulting drawdown of the water table in preexisting irrigation and domestic wells outside the Closed Basin Division to a maximum of 2 feet. Water levels in the closed basin in the northern part of the San Luis Valley historically have fluctuated more than 2 feet in response to water-use practices and variation of climatically controlled recharge and discharge. Declines of water levels in nearby wells that are caused by withdrawals in the Closed Basin Division can be quantified if water-level fluctuations that result from other water-use practices and climatic variations can be estimated. This study was done to evaluate water-level change at selected observation wells in and near the Closed Basin Division. Regression models of monthly water-level change were developed to predict monthly water-level change in 46 selected observation wells. Predictions of monthly water-level change are based on one or more of the following: elapsed time, cosine and sine functions with an annual period, streamflow depletion of the Rio Grande, electrical use for agricultural purposes, runoff into the closed basin, precipitation, and mean air temperature. Regression models for five of the wells include only an intercept term and either an elapsed-time term or terms determined by the cosine and sine functions. Regression models for the other 41 wells include 1 to 4 of the 5 other variables, which can vary from month to month and from year to year. Serial correlation of the residuals was detected in 24 of the regression models. These models also include an autoregressive term to account for serial correlation in the residuals. The adjusted coefficient of determination (Ra2) for the 46 regression models range from 0.08 to 0.89, and the standard errors of estimate range from 0.034 to 2.483 feet. The regression models of monthly water- level change can be used to evaluate whether post-1985 monthly water-level change values at the selected observation wells are within the 95-percent confidence limits of predicted monthly water-level change.