Water Level Changes Research Articles

Rising damp in heritage sites under urban expansion: A comprehensive case study of the Jinsha Earthen Site

Rising damp poses a significant threat to cultural heritage, yet its dynamics within actual heritage sites remain inadequately understood, particularly regarding its evolution and the impact of urbanization. The Jinsha Site, an earthen site from the Shang periods, is primarily composed of silt, with a layer of sand beneath and pebbles at the bottom, making it susceptible to rising damp. This study investigates the Jinsha Site as a case, monitoring soil water content and electrical conductivity, tracking changes in groundwater, precipitation, and river water levels, and investigating the relationship between urbanization and rising damp. The study aims to understand the process, causes, and influencing factors of rising damp and evaluate previous preservation strategies. The findings indicate that groundwater level in the sand layer trigger dampness, whereas the pebble layer exhibits dryness. Urban construction from 2006 to 2013 and 2014–2017 caused fluctuating groundwater levels, leading to repeated transitions between dryness and dampness at the site. Rainfall and river levels have negligible effect; even rainfall exceeding 100 mm (frequency <0.0056) only raises groundwater levels by approximately 1 m and increases water content by less than 2 % for a brief duration, typically less than half a month. The 2022 groundwater pumping strategy effectively maintained levels beneath the pebble layer (506 m), decreasing moisture by 12.71 % and conductivity by 0.27 dS/m. This study reflects on previous protection effortsand offers evidence-based strategies for heritage conservation amidst urban expansion.

Rancang Bangun Sistem Monitoring dan Kontrol Otomatis Water Level pada Tangki Cascade di Mv Prima Andalan 1

From this research, monitoring can be carried out using the XH-M203 water level which can run a wireless sensor to measure the water in the tank and then the results of these measurements will give a command to the pump to fill the tank. This tool is made to automatically control the height and automatically fill the tank. The design of this tool is based on the fact that some ships still use a manual system in the form of a float gauge to monitor water levels, so by designing this tool the monitoring and control process will be easier. System testing shows that the system is able to control water levels with high accuracy and is responsive to changes in water levels. The results of this research are that the XH-M203 water level is able to detect height and automatically control the simulated tank. The results of the detection are processed through a controller and LED as a marker for high and low levels so that all parties can know the water level in the tank. Then automatic control uses a pump which will fill automatically so that the tank capacity can be controlled through this tool. With 6 trials of 90% capacity in calm water there was an error of 0.01% and 90% capacity with the tank shaking there was an error of 0.01%. The next test with a tank capacity of 60% in still water conditions has an error of 0% and a capacity of 60% there is vibration there is a 0% error, and testing with a tank capacity of 30% in still water conditions there is an error of 0% and at 30% capacity there is vibration in the tank there is an error of 0 %. So this tool can work with an accuracy of 99.98% and a tool error of 0.02%.

Analysis of the impact of dam slope modifications on the sensitivity to rapid drawdown, earthquakes, and changes in water level at the Jragung Dam in Semarang Regency

Analysis of the impact of dam slope modifications on the sensitivity to rapid drawdown, earthquakes, and changes in water level at the Jragung Dam in Semarang Regency

Improvement of field falling-head test and determination of hydraulic conductivity using Darcy’s equation

This study presents a novel permeameter design for field falling-head tests to determine vertical hydraulic conductivity (K) using Darcy's equation. The design features an open-ended standpipe with two ports for simultaneous measurement of hydraulic heads at both ends of the sediment column, enabling direct estimation of flow rate (q) and hydraulic gradient (i). Flow rate is calculated by differentiating the best-fit curve for water level change above the sediment, and the hydraulic gradient is derived from the head difference between the ports. Laboratory and field tests consistently demonstrated a strong linear relationship between q and i (R2 > 0.999), validating the applicability of Darcy's equation for this new permeameter design. The K values obtained using the proposed method matched those obtained using the Hvorslev equation method. Furthermore, the design allows for continuous measurement of heads after the falling-head permeameter test, facilitating the collection of time series data for the hydraulic gradient. When combined with a pre-determined K value, this enables calculation of time series for the seepage rate across the surface water/sediment interface. To demonstrate this capability, preliminary tests were conducted using commercially-available pressure transducers to monitor heads and obtain seepage time series. The results of these tests are also presented.

Skill assessment of a total water level and coastal change forecast during the landfall of a hurricane

The Total Water Level and Coastal Change Forecast (TWL&CC Forecast) provides coastal communities with 6-day notice of potential elevated water levels and coastal change (i.e., dune erosion, overwash, or inundation) on sandy beaches that threatens safety, infrastructure, or resources. This continuously operating model provides hourly information for select regions along U.S. Gulf of Mexico and Atlantic Ocean coastlines. The objective of this work is to assess the skill of forecasts during a period of elevated water levels along the coasts of North Carolina (NC) and South Carolina, USA caused by Hurricane Isaias in August 2020, using a combination of observations and model hindcasts. Water levels and waves were observed throughout the storm at three locations near Wrightsville Beach, NC, which provided information to assess forecast skill; a wave buoy offshore, a tide gage at a local pier, and a pressure sensor deployed at the pier. In addition to observations, the non-hydrostatic phase-resolving model SWASH (Simulating WAves till SHore) was forced with hourly wave energy spectra derived from a coupled Delft3D-SWAN simulation during the peak of Isaias, to complement observations by computing nearshore wave height and wave-induced setup and runup at the shoreline. During the storm peak, SWASH-simulated water levels at the sensor position were comparable to those at the maximum landward extent (bias = −0.05 m; gain = 0.26; r2 = 0.99), suggesting that observations at the USGS sensor location were a useful proxy for total water level (TWL; sum of tide, surge and wave runup) at the shoreline that are predicted by the TWL&CC Forecast. The TWL forecast at Wrightsville Beach was consistent with observations from the USGS sensor (bias = −0.38 m and −0.74 m, scatter index = 0.22 and 0.28 for the two forecast model grids considered, respectively; weighted regression considering model uncertainty explained 95 percent of variability in observed TWL). Observed TWL was within the confidence interval of the TWL&CC Forecast for the 5 h at the storm peak. Forecast mean water levels (MWL; sum of tide, surge and wave setup) and tide gage observations were also consistent (bias = 0.07 m and 0.02 m for the forecast model grids; scatter index = 0.46; r2 = 0.80). Forecast MWL at the storm peak was within 0.06 m of the observed MWL from the tide gage for both sites. In the region where Isaias made landfall, eight additional pressure sensors were compared to the peak TWL forecast (bias = 0.14 m; scatter index = 0.18). Forecast TWL explained 90 percent of observed variability in TWL when considering uncertainty of the forecast with a weighted regression. The results demonstrate that wave-driven water levels contributed a significant portion of the forecast TWL during Isaias (52 percent during the three peak hours of the storm), and that TWL were represented using the forecast model. Mean absolute error of the coastal change forecast and observed overwash is 0.4 and 0.14 for the two forecast model grids considered. The skill demonstrated by this computationally efficient method indicates that the forecasting system can provide fast and reliable predictions of TWL across hundreds of km of coastline at sub-km resolution, days to hours in advance of when storms threaten coastal regions.

THE DITCH OF THE 17th CENTURY FOR MOORING BOATS IN THE VOZNESENSKYI MONASTERY NEAR DUBNO: CONSTRUCTION AND MATERIALS

Archaeological research carried out on Dubovets Island in 2022 made it possible to discover and study part of the ditch for mooring boats. The rich collection of materials with a wide range of categories was obtained from the ditches fill due to the fact that it accumulated the garbage and kitchen waste. At a certain point in time, a lot of fish were scaled near it which resulted in a continuous layer of scales. Judging by surface observations, this ditch stretched from the edge of the floodplain, i.e. the former pond bank, to the place where monastery-related objects were concentrated on the top of the hill, some of which were uncovered by excavations. Position and structure of the ditch indicate that it was used as a canal for launching and mooring of boats, which was a quite appropriate engineering solution in the conditions of a changing water levels in the pond and coastal reeds. The regular rows of stakes are the remains of protective wooden structures that strengthened the sandy sides of the ditch, apparently by weaving thin wood between them. The mixed sediments of layer 6 are traces of their destruction during the operation of the ditch. The analysis of archaeological materials from the ditch fill layers indicates that it was used during the 17th and 18th centuries. Object 83 is an important addition to the spatial and planning reconstruction of the monastery territory. It also serves as an example of an archaeological study of a peculiar technical structure that is not often discovered. Obviously, such ditches were built for residential complexes in the past where there was a need and the opportunity to attract the necessary labor. Ostriv Dubovets, as evidenced by the plans of the 17th and 18th centuries, was located near one of the riverbeds of the Ikva, which was more clearly visible during the period of low water in the pond. During the flood season, especially in spring, the valley between the island and the town was completely flooded. Thus, the water level near the island was not constant throughout the year, which made it impossible to arrange a simple berth. In addition, Ostriv Dubovets had a very gentle and elongated coastline, which was flooded for different lengths throughout the year. Therefore, for the convenience of embarkation and debarkation people, as well as loading and unloading boats on a dry section of the island’s shore, the construction of the discovered ditch was a necessary and original solution.

Water Resources Monitoring in a Remote Region: Earth Observation-Based Study of Endorheic Lakes

In the western Andes, climate changes have led to drastic ecological changes during the Pleistocene and Holocene. Given the debate surrounding precipitation pattern changes and the lack of research on lakes in the Chilean Altiplano, this study aims to assess recent climate changes. The paper presents an innovative methodology based on Google Earth Engine (GEE), utilizing fluctuations in water levels in endorheic lakes as natural precipitation indicators. Three lakes (Chungará, Miscanti, and Miniques) in isolated drainage systems were studied, where changes in water levels directly reflect rainfall variations. Data from Landsat-OLI 8, Landsat-ETM+, Landsat-TM 5, and MODIS spanning 31 years were processed using the Google Earth Engine platform. The shapes of the water bodies were extracted using hue saturation value (HSV) composites. The surface areas of the lakes were compared with precipitation data from national meteorological stations and the Tropical Rainfall Measuring Mission (TRMM) using linear regression analyses. Both lake area and rainfall volume showed a decrease over time, with varying trends depending on environmental conditions. However, the analysis consistently indicates a reduction in the area and volume of Chilean lakes corresponding to observed rainfall patterns over the past three decades.

Digital twin-based virtual modeling of the Poyang Lake wetland landscapes

Virtual wetland landscapes of provide fundamental support for digital twin watershed constructions. However, most digital twin applications in natural environments have focused on static digital scenes and little consideration for wetlands. The Poyang Lake is characterized by seasonal hydrologic changes, with periodic plant community successions, making it necessary to capture dynamic changes in the Poyang Lake ecological landscapes through dynamic three-dimensional (3D) scenes. This study selected typical landscapes to establish digital twin scenarios, presenting the virtual landscapes, distribution characteristics of flora and fauna in the Poyang Lake wetland, and seasonal changes in the lake water levels. The results can be used to restore the virtual Poyang Lake landscapes, including seasonal changes in the water surface, vegetation growth, and migratory bird activities. This construction process can be applied to similar digital twin constructs for flood-prone wetland watersheds, providing insights into digital twin watersheds or nature-oriented digital twin development.

Time Series Prediction of Reservoir Bank Slope Deformation Based on Informer and InSAR: A Case Study of Dawanzi Landslide in the Baihetan Reservoir Area, China

Reservoir impoundment significantly impacts the hydrogeological conditions of reservoir bank slopes, and bank slope deformation or destruction occurs frequently under cyclic impoundment conditions. Ground deformation prediction is crucial to the early warning system for slow-moving landslides. Deep learning methods have developed rapidly in recent years, but only a few studies are on combining deep learning and landslide warning. This paper proposes a slow-moving landslide displacement prediction method based on the Informer deep learning model. Firstly, the Sentinel-1 (S1) data are processed to obtain the cumulative displacement time-series image of the bank slope by the Small-BAseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) method. Then, combining data on rainfall, humidity, and horizontal and vertical distances of pixel points from the water table line, this study created a dataset with landslide displacement as the target feature. After that, this paper improves the Informer model to make it applicable to our dataset. This study chose the Dawanzi landslide in the Baihetan reservoir area, China, for validation. After training with 50-time series deformation data points, the model can predict the displacement results of 12-time series deformation data points using 12-time series multi-feature data, and compared with the monitoring values, its Mean Square Error (MSE) was 11.614. The results show that the multivariate dataset is better than the deformation univariate data in predicting the displacement in the large deformation zone of bank slopes, and our model has better complexity and prediction performance than other deep learning models. The prediction results show that among zones I–IV, where the Dawanzi Tunnel is located, significant deformation with the maximum deformation rate detected exceeding –100mm/year occurs in Zones I and III. In these two zones, the initiation of deformation relates to the drop in water level after water storage, with the deformation rate of Zone III exhibiting a stronger correlation with the change in water level. It is expected that deformation in Zone III will either remain slow or stop, while deformation in Zone I will continue at the same or a decreased rate. Our proposed method for slow-moving landslide displacement forecasting offers fast, intuitive, and economically feasible advantages. It can provide a feasible research idea for future deep learning and landslide warning research.

Modelling seasonal variation of sediment connectivity and its interplay with river forms

Functional connectivity refers to the system dynamics and sediment transfer in a geomorphological system. It is usually quantified through digital elevation models of difference at two time-steps but measuring and quantifying sediment connectivity variation between the time-steps remains a challenge. In this study we utilised a combined approach of morphodynamic model and field observation for assessing seasonal spatio-temporal variation of longitudinal functional connectivity over a 6-kilometre sub-arctic river reach. Comprehensive field datasets including sediment sampling, monitoring of morphological change and continuous discharge and water level measurements, were collected multiple times during the year to calibrate and validate the model for one year. The results revealed that connectivity inside the reach is episodical and not all the morphological adjustment was tied to discharge. Connectivity varied spatio-temporally inside the reach and sediment source and sink areas could be detected. Outside of the hydrological controlled episodes, meander evolutional stage and grain size had notable role in sediment connectivity in the short-term, and therefore underlaying morphological adjustment in the long-term. This approach can contribute to enhancing already existing connectivity indices towards a functional model considering the seasonality and periodicity of connectivity in more detail and would therefore enhance river management and prediction of geomorphic systems functioning.

Effects of log booms on physical habitat, water quality, and benthic invertebrates in the lower Fraser River and estuary

To facilitate the movement and processing of timber in some regions of the Pacific Northwest, logs are tied together to form large rectangular rafts (often called “booms”) which are transported and stored in aquatic environments. In the lower Fraser River, British Columbia, some reaches have &gt;50% of shoreline with adjacent log booms, yet our understanding of the effects of log booms on habitats and biota is very limited. We compared sites that have never had log booms to nearby ones with active boom storage occurring to examine differences in environmental characteristics. In contrast to reference sites, nearly all active sites had compacted sediments and little vegetation coverage, likely caused by logs “grounding” onto benthic environments due to tidally influenced water level changes. Total benthic invertebrate abundance was higher at reference sites which had relatively more Amphipoda and Trichoperta, but fewer Haplotaxida, compared to active sites whose compacted and more detrital-laden sediments should favour haplotaxids. Water quality variables generally did not differ between reference and active sites. Grounding of log booms and contact with the below substrate is in contradiction of best management practices and has clear effects on the physical habitat and biota of the area underneath booming sites.

Design and engineering application of 35kV floating photovoltaic power station

Based on the concept of fishery-solar complementary systems, floating photovoltaic (PV) power stations have garnered significant attention in the power industry due to their minimal land use, high power generation efficiency, and improved water quality. However, irregular water level changes and surface disturbances caused by wind or human activities increase the difficulty of maintaining long-term stable operation. This paper, relying on a specific project, thoroughly analyzes and designs the technical scheme for a 35kV floating PV power station. It delves into the design of the floating island platform, anchoring system, shock absorption between the island and equipment, and the overall layout of the power station. These findings provide valuable references for the design, manufacturing, construction, and operation of other floating PV power stations.

The nonlinear impact of climate change on inland waterway transportation in the Upper Mississippi—Illinois River Region

The U.S. inland waterway system has played a critical role in promoting economic growth by efficiently transporting agricultural and manufacturing commodities along major riverine systems, such as the Mississippi River. However, the system faces escalating challenges due to the growing disruptions caused by climate change. For instance, the drought of the Mississippi River during the fall of 2022 resulted in an unprecedented increase in barge shipping rates. While the industry generally recognizes that climate change can significantly impact agricultural supply chains, it remains unclear how various environmental factors, including changes in water levels and temperature, affect inland waterway operations. This study aims to fill this research gap by conducting an empirical assessment of the impact of climate change-related factors on the operations of the inland waterway system in the Upper Mississippi—Illinois River Region. Unlike previous studies using conventional regression analysis, this study investigates the nonlinear relationship between changes in barge shipping rates and various environmental factors using the Gradient Boosting Decision Trees machine-learning method. Our analysis identifies the 29 ft gage height as a pivotal threshold influencing barge rates; rates tend to rise as the gage height decreases, and surpassing this threshold can also lead to increased shipping rates. This new approach enhances the model’s predictive capacity, allowing for a better understanding of the nonlinear effects of climate change on barge rates and productivity. It also enables planners and operational agencies to better understand the uncertainty of environmental conditions on the variations in barge rates and productivity performance. These findings provide valuable insights for decision-makers to understand the threshold effect of environmental conditions on inland waterway operations and facilitate the creation of effective adaptive strategies to mitigate future risks and consequences of climate change-induced disruptions.

Water quality and wetland vegetation responses to water level variations in a university stormwater reuse reservoir: Nature-based approaches to campus water sustainability

In response to climate-driven water shortages, Duke University in 2014 constructed a water reuse reservoir and wetland complex (Pond) to capture urban stormwater and recycle water to provide campus cooling and reduce downstream loading of nutrients and sediment into Jordan Lake, a regional water supply. We postulated that even with significant water level changes due to withdrawals, the Pond would function to reduce downstream nutrients and sediment once wetland plants became established in the littoral zone. Throughout the project (2015–2021), baseflow nutrient concentrations downstream decreased, with Unfiltered Total Nitrogen (UTN) falling by 44 % and Unfiltered Total Phosphorus (UTP) by 50 %. Storm mean concentrations decreased by 31 % for UTN, 54 % for UTP, and 72 % for Total Suspended Solids (TSS). The annual reductions in mass fluxes (UTN, UTP, and TSS) were between 58 and 85 % across a range of storm intensities. Regardless of water level, temperature, pH, and oxygen concentrations downstream were not significantly changed. Between 2015 and 2020, a littoral survey of planted and naturally introduced species showed that wetter years resulted in a greater number of species across a gradient of three inundation zones (i.e., moist, wet, and aquatic). Conversely, dryer years resulted in fewer species across overlapping zones. The dominant plants that successfully colonized the Pond are all obligate wetland species despite the Pond's highly variable water depths and periods of inundation. The final plant populations were dominated by invasive native species supporting the self-design theory of plant succession as nearly half of the original planted species died. The reuse Pond design (pond-wetland complex) showed the capability of using stormwater runoff for campus cooling while improving water quality services and providing habitat for wetland plants. Thus, campuses with watershed runoff capture capability should consider a nature-based recycling approach as part of their water sustainability program.

Altimetry-based ice-marginal lake water level changes in Greenland

Greenland holds over 3300 ice-marginal lakes, serving as natural reservoirs for outflow of meltwater to the ocean. A sudden release of water can largely influence ecosystems, landscape morphology, ice dynamics and cause flood hazards. While large-scale studies of glacial lake outburst floods (GLOFs) have been conducted in many glaciated regions, Greenland remains understudied. Here we use altimetry data to provide the first Greenland-wide inventory of ice-marginal lake water level changes, studying over 1100 lakes from 2003–2023, revealing a diverse range of lake behaviors. Around 60% of the lakes exhibit minimal fluctuations, while 326 lakes have drained, collectively contributing to 541 observed GLOFs from 2008–2022. These GLOFs vary substantially in magnitude and frequency, with the highest concentration observed in the North and Northeast regions. Our results show substantial annual differences in the number of GLOFs with a notable peak in 2019, coinciding with a year marked by extreme runoff. Our method detected a 1200% increase in the number of draining lakes compared to existing historical databases. This highlights a large underreporting of GLOF events and emphasizes the pressing need for a deeper understanding of the mechanisms behind and the consequences of these dramatic events.

Design Constant Head Permeability Meter Digital: A Project-Based Learning Media

The permeability coefficient value is one of the most important parameters in soil mechanics. Quick, simple, and digital direct soil permeability tests in the field are needed to obtain data representing conditions. This research aims to create a portable soil permeability test tool based on microcontroller automation used as a project-based learning for Transportation Cadets peculiarly Palembang Aviation Polytechnic Cadets for new experiences of new learning circumstances. This research method based on the principle of permeability testing using the constant-head method by analyzing the requirements quantitatively. This principle uses water change level parameters, which are used to test the infiltration rate in sample soil. Furthermore, measurements of changes in water level are used by water leveling sensors and processed using Arduino Uno based on fuzzy logic with access to results via the web, tool design, and simulation using SIMULINK software. The results of designing a digital measuring instrument for permeability using the constant head method have been validated for its schematic circuit using SIMULINK and can work without error. In conclusion, a model based on Darcy's Law equation and constant head to find the permeability coefficient can be generated, which can then be a prototype of the tool. It concluded the design of constant head permeability meter digital is useful as project-based leaning media for the Palembang aviation polytechnic. Furthermore, the equipment design will be the first digital measuring tool for permeability coefficient using the constant head method. The design has advantage to measure the soil permeability coefficient at the airport in the fastest way.

Inversion Study on Landslide Seepage Field Based on Swarm Intelligence Optimization Least-Square Support Vector Machine Algorithm

The permeability coefficient of landslide mass, a key parameter in the study of reservoir landslides, is commonly obtained through in situ and laboratory tests; however, the tests are costly and subject to high variability, leading to potential biases. In this paper, a new method was proposed to inversely estimate the permeability coefficient of landslide layers using monitoring data of groundwater level (GWL). First, the landslide transient seepage simulation was conducted to generate sample data for permeability coefficients and GWL during a reservoir operation cycle. Second, using GWL data as input and permeability coefficient data as output, the least-square support vector machine (LSSVM) was trained with two optimization algorithms, the particle swarm optimization (PSO) algorithm and the whale optimization algorithm (WOA), to construct the nonlinear mapping relationship between simulated GWL and permeability coefficients. Third, the accurate permeability coefficients for landslide seepage simulation were inverted or predicted based on the monitored GWL. Finally, using the inverted permeability coefficients for landslide seepage simulation, we compared simulation results with actual monitored GWL and achieved good consistency. In addition, this paper compared the inversion effects of three different algorithms: the standard LSSVM, PSO-LSSVM, and WOA-LSSVM. This study showed that these three algorithms had good nonlinear fitting effects in studying landslide seepage fields. Among them, using the inversion values from PSO-LSSVM for landslide seepage simulation resulted in the smallest relative error compared to actual monitoring data. Within a single reservoir operation cycle, the simulated water level changes were also largely consistent with the monitored water level changes. The results could provide a reference to determine landslide permeability coefficients and seepage.

Analyzing water level variability in Odisha: insights from multi-year data and spatial analysis

A comprehensive analysis of long-term water level trends is essential for freshwater sustainability. Given that Odisha heavily relies on agriculture, the monitoring and management of groundwater and its fluctuations are imperative for ensuring future sustainability in the state. Here, we analyzed the trend in Groundwater using water level data for a 30-year period (1990–2020) for the entire Odisha region. Moreover, to determine the long term variability, critical zones of future groundwater variability and controlling parameters of the water level change, we used spatio-temporal water level data of 746 locations. Water level rise of coastal districts during post-monsoon (POM), corresponds to the intensity of rainfall received, thus rising, however other districts of Odisha, showing decline in water level during the same season is due to shortage of rainfall, increase in population at a sudden, and over pumping due to industrial activities. Similarly, during pre-monsoon (PRM), water level shows an increasing trend in hard rock terrain of Odisha implying rabi crop irrigation, high density drainage network and lesser population density. Feature selection techniques were used in this study to know the parameters controlling most to this water level fluctuation in the entire Odisha state. Precipitation followed by landuse & landcover, lithology and population density are controlling the most for the long term water level change. Drainage, elevation, lithology and slope are positively related to the water level change while others are negatively related. It is also inferred that the districts like Mayurbhanj, Sundargarh, Keonjhar, Kandhamal, Boudh, Dhenkanal, Gajapati, Koraput and Kalahandi contain most of the high critical zone concerning future availability of groundwater while most of the coastal regions are safe.

A simple infiltrometer automated with a user‐friendly pressure datalogger

AbstractWe have constructed a new, simplified constant‐head infiltrometer automated with a self‐contained water level datalogger (HOBO U20L‐01) repurposed to measure changes in gas pressure inside an inverted bottle reservoir. Our field tests of six of these infiltrometers confirmed that recorded changes in gas pressure were strongly correlated with changes in water level in the infiltrometer reservoir (R2 = 0.9998). Further, by using the derived experimental calibration function, we were able to obtain accurate near‐steady‐state infiltration rates. This infiltrometer is cheaper and lighter than current commercially available infiltrometers. It can be easily assembled with materials readily available in most hardware stores, and its user‐friendly datalogger does not require any programming knowledge. This infiltrometer is compatible with various ponding infiltration methods, and its generic design allows for modifications with locally available materials to meet diverse research needs.

Hydrological responses of the Brahmaputra river basin using CMIP6 GCM projections for supporting climate resilient infrastructure design

ABSTRACT The central northern region of Bangladesh has a low density and quality of sustainable rural infrastructures, and it is frequently affected by climate change-induced seasonal flooding and associated river erosion. This study used the Soil and Water Assessment Tool (SWAT) hydrological model to simulate future discharges under moderate and extreme Shared Socio-economic Pathway (SSP) scenarios, utilizing 13 bias-corrected Coupled Model Intercomparison Project Phase 6 (CMIP6) General Circulation Models (GCMs). Using these flow projections, the 1D HEC-RAS hydrodynamic model was then simulated to assess future water level fluctuations in six major rivers in the study region. The results indicate that the dry season will experience a more notable flow increase (up to 45%) than the wet season (up to 42%) compared to the baseline under the extreme scenario by 2100. The subsequent rises in water levels will also be significant in the major rivers in the Brahmaputra-Teesta River system. Based on these future water level changes, the study has prepared a guideline for building climate-resilient infrastructures in the study area.