Surface Water Levels Research Articles

Short-term climate change influence on surface water quality impacts from agricultural activities.

Climate change is a global phenomenon that directly affects agriculture by altering crop yield, nutritional quality, pests, and plant diseases. The North Aegean Basin located in Turkey has considerable agricultural importance due to its fertile soils. Agricultural activities have increased significantly and uncontrollably in the last decade, resulting in dramatic changes in nitrate and phosphorus levels in surface water within the watershed. Changes in climatic conditions have the potential to impact the quantity and quality of water resources. Best management practices (BMPs) are presently utilized as a planning tool to enhance the quality of water resources. To develop policies in this regard, it is necessary to evaluate the effectiveness of BMPs. To this end, this study aims to investigate the potential effect of climate change on the surface water quality of the North Aegean Basin. For the period between 2010 and 2030, global climate data retrieved from Concentration Pathway (RCP) scenarios 4.5 and 8.5 and regionally downscaled were used to feed the Soil and Water Assessment Tool (SWAT) model. The various potential BMP scenarios were developed and simulated in the hydrological model by considering the effects of climate change. The RCP4.5 scenario reduced the precipitation by 15.11%, while the RCP8.5 scenario reduced the precipitation by 10.97%. Decreased precipitation also affected the runoff and the nutrient loads and concentrations. As a result of the RCP4.5 simulation, TP and TN concentrations increased by 24.42% and 58.45%, respectively, in the IST_KEN014 station. Improvements were observed in TN and TP concentrations with the effect of applied BMP simulations. Also, the results revealed that the applied BMP scenarios may contribute to considerable reductions in nutrient loads. Considering the RCP4.5 scenario, BMPs reduced TN loads in the basin by 2.42-10.97%, while reducing TP loads by around 3.60-16.81%. Considering the RCP8.5 scenario, the BMPs reduced the TN loads in the basin between 2.21 and 10.04%, while they reduced the TP loads between 3.57 and 16.67%.

Determination of Cyanide Concentration Levels in Surface Water and Soil from Artisanal Small-Scale Gold Mining Villages at Chunya, Mbeya - Tanzania

This study aimed to determine levels of cyanide (CN) pollution in the soil and surface water at selected mining sites of Mbeya region. A total of (n = 124) samples were collected and analyzed by spectrophotometry. The cyanide levels of soil-based samples and water-based samples at Mwasenga, and Ifumbo mining sites were above the permissible limits. This was due to poor disposal of tailing from the gold processing plants and mismanagement of wastewater. On the other hand, the Cyanide was within the allowable limit for both soil and water at Godima, Itewe, Ashishira and Nyatula mining sites. This was attributed by proper management of wastewater by using artificial tanks, ponds and trenches. Also, it was observed that there is a mobility of cyanide from the processing mining site, if the tailings and wastewater are not well managed. The concentration of cyanide in the soil and water samples of about 2 mg/L was observed at distance of more than 70 m from the processing plant at Mwasenga, the situation is even worse at Ifumbo, where the cyanide concentration in soil and water were about 25 and 8 mg/L respectively, at a distance of more than 50 m from processing plant

Effect of wave disturbance on the fluid dynamics of the pump turbine in a seawater pumped storage hydroplant

Compared with conventional pumped-storage hydroplants, seawater pumped-storage hydroplants are constructed in a complex marine environment. The wave disturbance may affect the safety operation of the pump turbine in the seawater pumped hydroplant via affecting the level of the free water surface. To explore the effect of wave disturbance on the operation of the pump turbine in a seawater pumped-storage hydroplant, assuming that the wave disturbance follows a sine function, on the basis of Airy’s micro-amplitude wave theory and the comprehensive characteristic curve of a pump turbine, we use sliding grid technology and the SST k–ω turbulence model to simulate the dynamics of fluid in a full-flow channel. In this study, the unsteady flow field, Q-criterion vorticity, relative pressure pulsation amplitude, and frequency of pressure pulsation are analyzed to determine the internal flow field and pressure pulsation under different wave disturbance conditions and operating loads. The results show that both the pressure pulsation in the pump turbine and its frequency domain are affected by the wave disturbance. In addition, the turbulent flow with a large flow rate tends to produce higher relative pressure pulsation under wave disturbance. Due to the large flow rate and strong static and dynamic interference in the vaneless area, the relative amplitude of the pressure pulsation is significantly affected by wave disturbance. Furthermore, the low-frequency pressure pulsation of the draft tube is superimposed with the wave disturbance frequency.

Variable drivers of surface turbulence under condition of stratified density currents in a tributary bay of Three Gorges Reservoir

Surface turbulence has a direct impact on thermal stratification and important ecological process. The dissipation rate of turbulent kinetic energy (ε), a key parameter to quantify turbulence, also significantly affects the hydrodynamic and biochemical processes. Continuous measurements of high-frequency surface (0.50 m depth) flow velocity, meteorological data, water level and water temperature conducted in Xiangxi Bay (XXB) of the Three Gorges Reservoir (TGR) during summer (2019/6/17–2019/6/24) and winter (2019/12/29–2020/1/4) observational period, have been used to explore the variability of surface turbulence and its possible driving factors. The results show that a two-layered flow structure was clearly visible in summer. The surface water flowed from downstream to upstream (surface intrusion currents), with an average longitudinal velocity of 0.05 m/s and 0.02 m/s during summer and winter observational periods, respectively. Meanwhile, the longitudinal velocity also showed periodic fluctuations at three different time scales, with periods of 1.80 h, 20 min and 1–3 s, respectively. The 1.80 h fluctuation was caused by the flow oscillation driven by daily discharge regulation of TGR. In addition, the surface turbulence dissipation rates varied from 10−8 W/kg to 10−4 W/kg in summer, and from 10−9 W/kg to 10−4 W/kg in winter. In XXB, the movement of surface intrusion currents is an important factor that dominates and maintains the surface turbulence, while the contribution of atmospheric forcing (wind shear and convective cooling) accounts for 27.17 % in summer but 58.95 % in winter. The diurnal water level regulation of reservoir and wind variations are co-driving forces for the diurnal differences of surface turbulence during the observational periods. Therefore, the atmospheric forces and reservoir regulation together determine the variability of surface turbulence. This study will help to deepen the understanding of the hydrodynamic process of large regulated riverine reservoirs.

Use of long short-term memory network (LSTM) in the reconstruction of missing water level data in the River Seine

ABSTRACT This paper aims to fill in the missing time series of hourly surface water levels of some stations installed along the River Seine, using the long short-term memory (LSTM) algorithm. In our study, only the water level data from the same station, containing many missing parts, were used as input and output variables, in contrast to other works where several features are available to take advantage of e.g. other station data/physical variables. A sensitive analysis is presented on both the network properties and how the input and output data are reentered to better determine the appropriate strategy. Numerous scenarios are presented, each an updated version of the previous one. Ultimately, the final version of the model can impute missing values of up to one year of hourly data with great flexibility (one-year Root-Mean-Square Error (RMSE) = 0.14 m) regardless of the location of the missing gaps in the series or their size.

Occurrence, sources, and ecological risks of polycyclic aromatic hydrocarbons (PAHs) in the Amazon river

The Amazon is the largest river by discharge volume and one of the most biodiverse biomes in the world. Lately, there has been a rapid increase of the urban population in the region, which has been translated into a growing emission of organic contaminants such as polycyclic aromatic hydrocarbons (PAHs) into surface water bodies. This study provides the most comprehensive evaluation of the PAH contamination levels in surface waters of the Amazon basin. We investigated the occurrence and potential sources of 16 priority PAHs and characterised their risks for freshwater ecosystems. For this, we took 40 water samples from different sites along the Brazilian part of the Amazon River, including three major tributaries, and smaller rivers crossing the main urban areas. The results of this study show that PAHs are widespread contaminants in rivers of the Brazilian Amazon. The sum of the total concentration of the 16 priority PAHs reached values of 134 ng L−1 in the Amazon River, and 163 ng L−1 near densely populated areas. On the other hand, the total PAH concentration was generally lower in the monitored tributaries. In most samples, the contamination pattern was dominated by high molecular weight PAHs, suggesting a major contribution of pyrogenic sources, although petrogenic contamination was also present in some locations near urban areas. We assessed ecological risks posed by PAH mixtures using a hazard index. The results indicated that PAH contamination is not likely to pose direct toxic effects for Amazonian freshwater organisms, however continued monitoring is recommended near densely populated areas.

Design, development, fabrication and evaluation of the dynamics of a graphene based underwater acoustic vector sensor: A simulation and experimental study

In the last decade, the usage of underwater vector sensor has gained a lot of importance in the detection of low frequency underwater acoustic signals, as the noise level radiated by the submarine has been drastically reduced. Acoustic sensor based on Micro Electro Mechanical Systems (MEMS) technology is the recent advancement in the area of underwater acoustic vector sensors. We are reporting the design, fabrication, preliminary characterization and evaluation of the dynamics of a two-dimensional underwater acoustic vector sensor by simulation and experimental study. The vector sensor is realized using Reduced Graphene Oxide (rGO) as sensing element and Kapton as flexible substrate, to yield better sensitivity compared to the conventional acoustic vector sensor. Design of vector sensor is inspired by the biological sensing system of fish. The application of piezoresistive transduction principle and MEMS technology helps in miniaturisation and low frequency acoustic signal detection. The fabrication process is made simple, scalable and cost minimum by using the method of drop casting for the deposition of rGO on flexible substrate kapton, thereby eliminating the requirement of clean room. COMSOL Multiphysics 5.5 version is used to simulate acoustic vector sensors using polysilicon and rGO on substrates, silicon and flexible kapton respectively. The simulation results indicate that the sensitivity of rGO based acoustic vector sensor is −149.47 dB which is better in comparison with the sensitivity of −173.37 dB of conventional polysilicon vector sensor. By simulation, the natural frequency of the sensor is found to be 46.62 Hz, which closely matches with the theoretical value 41.06 Hz of the device as per the design criteria and hence, it could detect the low frequency acoustic signals. The displacement sensitivity of the fabricated sensor is found to be 0.0264 V/mm and 0.0276 V/mm for applied displacements in axial and radial directions respectively. The device is tested for its performance parameters i.e., sensitivity and directivity, by performing an acoustic test in the presence of an elastic medium, water. This test results infer that, the device is able to detect and give smooth output response for the acoustic signals in the low frequency range. The Y and X-channel receiving sensitivity exhibited by the sensor is found to be −128.04 dB to −134.93 dB and −130.61 dB to −136.78 dB respectively. Directivity pattern of the sensor is found to be in the shape of 8 with symmetry. As the device is a vector sensor, in addition to the scalar pressure measurement, it should be able to provide additional incentives such as acoustic particle displacement and acoustic particle velocity at any point in the acoustic field. In this paper, an experimental setup is made to generate deep and intermediate water waves, thereby attempting to simulate ocean conditions in the laboratory. Subsequently the numerical evaluation of the wave kinematics, i.e., fluid particle displacement and fluid particle velocity are performed by applying Airy's theory. An effort is also made to analyse the wave kinematics for various water depths, varying from Surface Water Level (SWL) till the sea bed. In this study, wave kinematics are analysed numerically by using experimental data and also by modelling Fluid-Structure Interactions in COMSOL Multiphysics environment. Our results show that the fluid flow of velocity 0.31 m/s results in fluid particle velocity of 0.125 m/s at time 0.215 s (around f = 5 Hz) by both the methods and fluid particle displacement is found to be 19.66 μm. The experimental test setup and videos are made publicly available1: 1https://sites.google.com/view/smithapaib/downloads

Model based estimation of climate change impacts on the drainage demand of low lying coastal areas in Northwest Germany along the North Sea

Study regionThe Northwest German part of the North Sea coast Study focusLow lying coastal areas are highly threatened by climate change. This is due to rising sea level and changing water balance caused by climate change. Adaptation of coastal protection and inland drainage to climate change requires precise predictions of future conditions. While information on sea level rise is globally available, coastal water balance projections need to be specific for regions where often no discharge data is available. To serve this demand, a model based scenario analysis was carried out for four water boards in Northwest Germany. These water boards are regional organisations responsible for drainage and surface water level regulation in marsh areas. A water balance model was calibrated and validated against data of pumping stations and tidal water gates. Subsequently, climate change impacts on runoff generation were estimated. New hydrological insights for the regionThe results indicate that runoff generation is expected to increase significantly in the wet season, same as the frequency of periods with large runoff volumes. The climate change impact signal is consistent over all investigated water board areas, indicating that the climate change signal dominates the spatial variability in soil properties and land use. The results emphasize the necessity to consider runoff generation projections for adjusting coastal drainage management. The scenario projections can be directly used for regional adaptation planning processes, taking into account the underlying uncertainties.

A methodological framework for specular return removal from photon-counting LiDAR data

The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) data may contain abundant noise photons induced by specular reflection, which make the signal photon detection and surface elevation extraction challenging, especially on flat surfaces with high reflectivity. However, no efficient algorithm for specular return noise removal has been proposed. Therefore, this study aims to propose a novel methodological framework based on statistical features to remove noise photons induced by specular reflection. First, ICESat-2 data preprocessing was performed to improve the speed and accuracy of subsequent processing. Second, the statistical features of outlier distance were calculated and utilized to filter out noise photons. Third, the specular return noise was removed according to the extreme points in the elevation distribution histogram. Finally, the manually labeled of photons and in-situ data were utilized to evaluate the performance of the proposed framework. Additionally, the proposed framework was compared with three existing signal photon extraction algorithms (ATL03, ATL13, AVEBM) for further assessment. The experimental results show that the F1-score of the proposed framework is 99.9 % and the accuracy of water level estimation is extremely high (bias = 0.041 m, and RMSE = 0.082 m). Further analysis demonstrates that our framework has the high robustness because it is not sensitive to input parameter. Meanwhile, the weak beam achieved higher water elevation accuracy than that of the strong beam. Besides, the proposed framework performs better than the existing methods in extracting water surface photons and water level. All in all, the proposed framework has been shown to effectively remove noise photons of specular returns in the raw ICESat-2 data and reduce the underestimation of the water level.

ASSESSMENT OF THE INTEGRATED ECOLOGICAL AND TECHNOLOGICAL SITUATION (SOLOTVYNO)

An analysis of existing modern ecological problems of the territory of the village was carried Solotvyno, namely: intensive development of deep karst; changes in the hydrogeological regime; violation of the integrity of the salt massif and its destruction with corresponding deformations of suprasalt deposits and surface relief. Analyzed the dynamics of depression formation on the earth's surface within the township. Solotvyno, the dynamics of the expansion of the reservoir area. The methodological aspect of the assessment toolkit of the integrated ecological and technological situation within the Solotvyno territory has been developed. The indicator of transformation in time and space, the index of detection of relative changes in the environment in relation to the development of suffusion-karst processes, which must be taken into account when solving issues of ecological danger, and the normalization of indicators of surface water pollution in the form of a pollution index (I zabr) was made due to the assessment of the chemical components of surface waters of the studied area based on the method of normalization of actual concentrations of monitoring data in the calculation to the MPC. Spatio-temporal maps of the levels of indices of detection of relative changes in the environment (transformation) have been created in the form of cartograms with reference to the area. The index of detection of relative changes in the environment is proposed to be defined as the ratio of the area of transformation for several periods of time, using space monitoring technologies (Landsat 7 satellite images) and performing calculations with the help of Google Earth software, GIS modeling and statistical calculations. It has been established that due to the construction of isolated basins, which local residents fill with oil pumped from the pits above the mines, the complex of significant long-term irreversible changes in the environment increases, which leads to the destruction of the balance in the natural and man-made system and to significant negative consequences. Water withdrawal in modern times provokes the activation of suffusion-karst processes due to the increase in the radius of the depression funnel of the "big well" and contributes to the increase in the area of water catchments. A decrease in the level of the stationary water surface in the lakes above the mines under the condition of pumping creates the conditions for an additional inflow of water from the aeration zone and groundwater into the sinkholes due to the establishment of the level. The formation on the earth's surface of such forms of relief as gouges, sinkholes and displacement funnels flooded with water do not look stable during the period of research (2014-2020). According to the results of modeling the transformation index, it was established that the areas of the listed landforms have increased almost 15 times. It was established that the highest indicator of the first in some areas belongs to chlorine (Cl). That is, the dissolution of salts is prolonged. 

Mapping South Florida Daily Fire Risk for Decision Support Using Fuel Type, Water Levels, and Burn History

Mapping fire risk in South Florida depends on spatially varying water levels, fuel characteristics, and topography. When surface water levels recede below the lowest topographic features (cypress strands, marshes, etc.), the ecosystem loses its natural, wetted fire breaks, and landscape-level fire risk increases. We developed a geospatial method to generate daily, categorical fire risk maps; the maps visualize low-to-high risk areas using a newly developed 100 m DEM, modeled water levels, fuel types, and fire management units. We assigned fire risk by creating a water level distribution for each unique combination of fuel type and fire management unit; fire risk was then assigned for each pixel based on risk percentiles commonly used by fire management agencies. Assigning risk based on unique fuel types and management units helped avoid over- or under-assigning fire risk that may occur when applying landscape-level “average” risk relationships. Daily maps also incorporated (1) energy release component data to better estimate fuel moisture and (2) historical burn footprints to reduce risk in recently burned areas. Our data-driven approach generated at management-relevant spatial scales may enable more informed prescribed burn planning and may increase the efficiency of staff and resource allocation across the landscape on high-wildfire-risk days.

Concentration, distribution, and bioconcentration of short- and long-chain perfluoroalkyl substances in the water, suspended particulate matter, and surface sediment of a typical semi-enclosed bay

This study investigated per- and polyfluoroalkyl substances (PFAS) levels in the surface water, suspended particulate matter (SPM), sediment, and fishes in the Laizhou Bay (LZB) and its inflow river estuaries in dry, normal, and wet seasons. The results demonstrated that the short-chain perfluoroalkyl acids (PFAA) accounted for about 60 % of the total PFAA (∑PFAA) concentration in water, while long-chain PFAA were the dominant compounds in the sediment and SPM. The levels of the ∑PFAA and their precursors decreased from the estuaries to the bay, which implied that terrigenous input (pollutant in land flowed into sea) was the main pollution source of PFAA in the LZB. The PFAAs levels in surface water were ranked as the order of dry > normal > wet season. The distribution coefficients of PFAA showed that the long-chain PFAA were more prone to be adsorbed by sediment and SPM than short-chain PFAA. The increase of ∑PFAA concentrations was in the range of 0.32–36.7 ng·L−1 after the oxidation conversion of water samples. Precursors were the important source of the PFAA in the surface water. The perfluorooctane sulfonate (PFOS) was the dominant compound in fish tissues. These results provide hints for understanding PFAS pollution in LZB.

Influence of seasonal water-level fluctuations on depth-dependent microbial nitrogen transformation and greenhouse gas fluxes in the riparian zone

Greenhouse gas (GHG) emissions from riparian zones affect the global GHG balance, contribute to global warming and climate change, and generate adverse effects on ecological health as well as environmental, economic and social sustainable development. However, the influence of water-level fluctuations on depth-dependent soil properties, nitrogen transformation and GHG emissions in riparian zone ecosystems during wetting–drying cycles remains unclear. In this study, we analyzed seasonal nitrogen dynamics under seasonal water-level fluctuations at seven different depths (0–20, 20–40, 40–60, 60–80, 80–100, 100–120 and 120–140 cm) along a typical transect in the Jianghan Plain, Central China for 2018–2019. Changes in depth-dependent soil physical and chemical properties, soil textural characteristics and mineralogy, potential nitrification rate (PNR) and potential denitrification rate (PDR), as well as soil GHG emission rates were determined across a range of meteorological conditions and surface water and groundwater level fluctuations. Groundwater levels varied significantly between seasons with rising water-levels during the wet seasons and falling water-levels during the dry seasons. The physicochemical properties and chemical composition in the three studied riparian soil textures revealed higher spatiotemporal variability during the wet seasons as compared to the dry seasons. Our results showed that groundwater level depth was a crucial influencing factor controlling the microbial nitrogen transformation in the soil profiles. The PNR values were characterized by substantial seasonal variation with the same or higher metabolic activity in the dry season than in the wet season owing to water-level fluctuations, while they declined with depth. Compared to the wet season, the PDR values in the studied riparian zone were typically lower in the dry season due to extremely low soil water content constrained by fluctuating water-levels. Besides, the PDR values in the silt loam layers were higher than that in the sandy loam layer for most of the monitoring period. The depth-dependent GHG flux rates highlighted that the riparian zone ecosystem was a key source of CO2 and N2O and a sink for CH4. In summary, our findings suggest that fluctuating water table management in riparian ecosystems must be considered to more effectively control seasonal fluctuations of nitrogen dynamics and mitigate GHG emissions. Thus, a suitable riparian groundwater quality control and management scheme is urgently necessary to bring awareness of seasonal water-level fluctuations of riparian zones to catchment managers and policy makers.

Spatial and Temporal Redox Heterogeneity Controlled by a Fe(II), Anoxic Upwelling System in the Early Mesoproterozoic Ocean

AbstractThe availability of oxygen and nutrients during the Mesoproterozoic (1.6–1.0 Ga) is thought to influence the rate of eukaryote evolution. The cause of the transition from low productivity in the upper Wumishan Formation to organic‐rich sediments in the Hongshuizhuang Formation remains unknown. We report FeHR/FeT, Fepy/FeHR, MoEF, UEF, VEF, and [Ce/Ce*]SN in one core of the Yanliao Basin to study the redox evolution and compare it with other sections in different depths of the Yanliao Basin to get clues of the spatial and temporal redox heterogeneity. Mo‐U covariation, low Co × Mn and CoEF × MnEF, and distribution patterns of trace metals indicate the upwelling events. An upwelling system could fuel nutrients to promote productivity levels in surface water and contribute to anoxic deep waters. The uniformly positive δ15N values are interpreted as sufficient NO3− reduction via denitrification and dissimilatory nitrate reduction to ammonium in a ferruginous upwelling condition.

THE GENERAL EFFECT OF ALUMINUM ON THE BODY

Aluminum is ubiquitous; the third most common element of the earth's crust. It is naturally released to the environment from the weathering of rocks and volcanic activity. Human activities such as mining also result in the release of aluminum to the environment. Aluminum levels in environmental media vary widely depending upon the location and sampling site. In general, background levels of aluminum in the atmosphere are low, typically ranging from about 0.005 to 0.18 μg/m3. Much higher levels are routinely observed in urban and industrial locations. Aluminum levels in surface water is usually very low (<0.1 mg/L); however, in acidic waters or water high in humic or fulvic acid content, the concentration of soluble aluminum increases due to the increased solubility of aluminum oxide and aluminum salts. Its concentration in soils varies widely, ranging from about 7 to over 100 g/kg.

Assessing surface-groundwater interactions for sustaining spring wetlands of the Great Artesian Basin, Australia

The Great Artesian Basin (GAB) is one of the world’s largest actively recharging aquifers. Groundwater discharges from the GAB sustain numerous spring wetlands, which have great ecological, scientific, and socio-economic significance. However, groundwater extraction and variation over time have had an impact on the quantity and area of spring wetlands with a 38% decline in extent since 1900. A major barrier to understanding variability in surface–groundwater interactions in spring wetlands of the GAB is the lack of observational data across critical spatial and temporal scales. Satellite observations have the ability to overcome this barrier and allow the evaluation of spring wetland responses to groundwater storage (GWS) variation. We investigated how GWS, and its associated drivers such as evapotranspiration (ET), soil moisture storage (SMS), and rainfall, in the GAB, influence the extent of surface water at five spring supergroups (Eulo, Barcaldine, Flinders, Springsure, and Springvale). We used satellite observations (2002–2017) to assess ET, SMS, rainfall, the normalized difference vegetation index (NDVI) and the modified normalized difference water index (mNDWI) for observing surface–groundwater interactions. NDVI responded positively to the GWS variation over the GAB and varies from sub-basin to sub- basin, with higher correlations in the Carpentaria sub-basin and some parts of Central and Western Eromanga. GWS variations was correlated with ET, SMS, rainfall, NDVI, mNDWI and surface water level (SWL). After a strong La Niña began in 2010, we uncovered relatively higher linear relationships between different components (ET, SMS, rainfall, NDVI, mNDWI, and SWL) and GWS variation (R2 > 0.50) than before the La Niña (R2 < 0.50), with the Flinders spring supergroup being the exception. NDVI and SMS are found to be the most significant predictor variables among ET, rainfall, SWL, and mNDWI components to influence GWS. This study provides improved understanding of surface-ground water interaction in spring wetlands and the influence of different hydrological components on variation in spring wetland extent in the GAB region.

GEDI DATA WITHIN GOOGLE EARTH ENGINE: PRELIMINARY ANALYSIS OF A RESOURCE FOR INLAND SURFACE WATER MONITORING

Abstract. Freshwater is one the most important renewable water resources of the planet but, due to climate change, surface freshwater available in the form of lakes, rivers, reservoirs, snow, and glaciers is becoming significantly threatened. As a result, surface water level monitoring is fundamental for understanding climatic changes and their impact on humans and biodiversity.This study evaluates the accuracy of the Global Ecosystem Dynamics Investigation (GEDI) LiDAR (Light Detection And Ranging) instrument for monitoring inland water levels. Four lakes in northern Italy were selected for comparison with gauge station measurements. To evaluate the accuracy of GEDI altimetric data, two steps of outlier removal are proposed. The first stage employs GEDI metadata to filter out footprints with very low accuracy. Then, a robust version of the standard 3σ test using a 3NMAD (Normalized Median Absolute Deviation) test is iteratively applied.After the outlier removal, which led to the elimination of between 80% to 87% of the data, the remaining footprints show an average standard deviation of 0.36 m, a mean NMAD of 0.38 m, and a Root Mean Square Error (RMSE) of 0.44 m, proving the promising potentialities of GEDI L2A altimetric data for inland water monitoring.

Dryland river regime shifts in Iran: Drivers and feedbacks

AbstractIn the Anthropocene, human activities have created unprecedented changes and nonlinear relationships between humans and nature. These changes can be much faster and more intense in arid and semiarid areas that have been affected by intense human activities. Iran has climates from very humid to very dry, but arid and semiarid climates cover the country's largest area. Many of these arid areas have undergone severe changes in their surface and groundwater ecosystems in recent years, which have caused severe damage to humans and the environment in the area and surrounding areas. Therefore, in this study, using the theory of regime shifts, the time series of the Zayandeh‐Rud River Basin in the center of Iran were analyzed. First, the data of the desired time series in the period of 1986–2018 was arranged seasonally. Then, using the sequential t‐test method, regime shifts in these time series were identified, and then, causal loop diagrams of these shifts and their drivers and feedbacks were interpreted. The results showed that in the time series of quantity and quality of surface water and groundwater level in the studied stations and aquifers, regime shifts can be identified. Regime shifts were also identified in the time series of agricultural land area. These shifts have occurred with the increase in human activities since the early 1950s in the metropolis of Isfahan, the increase in agricultural and industrial exploitation, and consequently, the increase in population. When this reinforcing feedback loop becomes dominant, the Zayandeh‐Rud River system has shifted from a regime of rich water resources to a regime of poor water resources. However, by recognizing and systematically analyzing these shifts, the Zayandeh‐Rud River system can be directed toward a sustainable system through structural reform, negotiation, and redefining goals.

Data integration reveals dynamic and systematic patterns of breeding habitat use by a threatened shorebird

Incorporating species distributions into conservation planning has traditionally involved long-term representations of habitat use where temporal variation is averaged to reveal habitats that are most suitable across time. Advances in remote sensing and analytical tools have allowed for the integration of dynamic processes into species distribution modeling. Our objective was to develop a spatiotemporal model of breeding habitat use for a federally threatened shorebird (piping plover, Charadrius melodus). Piping plovers are an ideal candidate species for dynamic habitat models because they depend on habitat created and maintained by variable hydrological processes and disturbance. We integrated a 20-year (2000–2019) nesting dataset with volunteer-collected sightings (eBird) using point process modeling. Our analysis incorporated spatiotemporal autocorrelation, differential observation processes within data streams, and dynamic environmental covariates. We evaluated the transferability of this model in space and time and the contribution of the eBird dataset. eBird data provided more complete spatial coverage in our study system than nest monitoring data. Patterns of observed breeding density depended on both dynamic (e.g., surface water levels) and long-term (e.g., proximity to permanent wetland basins) environmental processes. Our study provides a framework for quantifying dynamic spatiotemporal patterns of breeding density. This assessment can be iteratively updated with additional data to improve conservation and management efforts, because reducing temporal variability to average patterns of use may cause a loss in precision for such actions.

Long-Term Change of Lake Water Storage and Its Response to Climate Change for Typical Lakes in Arid Xinjiang, China

Lakes play a role as the sentinel of climate change. Surrounded by vast expanses of barren land with limited infrastructure, there is also a lack of knowledge about the dynamics of dryland lakes. The change of lake area can be effectively monitored by remote sensing, and multi-source satellite altimetry datasets provide the possibility to obtain long-term lake water level data. Using the Global Surface Water Monthly Historical dataset and altimetry water level dataset (Hydroweb), we reconstructed a time series of lake water storage changes in Xinjiang, Northwestern China, by establishing the empirical models based on the statistical relationship between the surface area and water level of each lake. We further explored lake response to climate change. The results show that the storage of water at Ayakkum Lake, Aqqikkol Lake and Aksayquin Lake have been undergoing an obvious expanding trend from 2000 to 2020, at a rate of 3.59×108m3/a, 9.43×108m3/a and 0.44×108m3/a, respectively. In the plain and transition zone, Ulungur Lake showed an upward tendency (0.413×108m3/a) in water storage, while Manas Lake and Bosten Lake experienced shrinkage with descending rates of −0.1×108m3/a and −0.86×108m3/a. Temperature changes significantly affect the lake water storage on plateaus, especially those lakes supplied with a large proportion of glacial meltwater. Precipitation is a key factor for changes of lake storage in the plain and transition zones. Meanwhile, extreme weather and man-made factors also play crucial roles. To reduce the risk of flood and drought disasters, rational regulation of water resources is required, and a large-scale integrated catchment management plan can avoid inadvertent trade-offs. This research provides a new perspective for lake water storage inversion, as well as data support for water resources management in arid areas including Xinjiang.