Water Level Decline Research Articles

Multi-parameter study of Aculeo lagoon (Chile)

Abstract. The Aculeo Lagoon, located in the Santiago Metropolitan Region, was one of the main water reservoirs of central Chile. It has experienced a decline in water levels since 2009 and completely dried up in 2018. It was unable to recover until 2023 due to sustained demand for water resources associated with population growth, changes in land use, and years of drought. The objective of this study is to estimate how anthropogenic factors and climate change have influenced the drying of the lagoon. Parameters considered include population growth, housing increases, changes in land use within the Aculeo basin, local temperature and precipitation variations, and global El Niño Southern Oscillation (ENSO) phenomena. Input data included multi-year Landsat images, census data, and a systematic review of the literature on the study area. Furthermore, applying geospatial data analysis techniques such as satellite image processing, supervised classification of land cover/use, and calculation of spectral indices, it is possible to conclude that the Aculeo Lagoon dried out due to a significant precipitation deficit over nearly a decade, exacerbated by the overexploitation of land for agricultural activities.

The Next 2 Billion: Can the World Support 10 Billion People?

AbstractThe UN projects that world population will peak at 10.3 billion in 2084, a 2.1 billion increase from 2024. Can the world provide food, water, and other resources to 10.3 billion people? How will additional population exacerbate resource challenges and worsen climate change? This paper analyzes these questions by looking at the last 60 years and by simulating the future impact of population growth and rising incomes on food, water, energy, and CO2 emissions. Looking back, food production has increased faster than the population in all regions, and we have not experienced significant shortages in nonrenewable resources. The history of water and CO2 emissions is less encouraging, however, with declining water levels in many aquifers and global warming threatening to undermine progress in all areas. Looking forward, population growth will be concentrated in poor countries, while rich countries, with higher consumption levels and emissions, will experience population decline. Population growth is projected to significantly increase demand for food and water in coming decades but is projected to have only modest impacts on energy and CO2, with population decline in high‐emission higher income countries more than offsetting the impact of population growth in low‐emission lower‐income countries.

Rescue and return: Translocating a semi‐wild platypus (Ornithorhynchus anatinus) population during the 2019 drought

SummaryPlatypus (Ornithorhynchus anatinus) are an endemic Australian freshwater mammal, impacted by synergistic threats across their range. During the extreme drought of 2017–2019, declining water levels threatened Platypus at Tidbinbilla Nature Reserve (TNR), Australian Capital Territory (ACT), Australia. TNR supports a population of Platypus, occupying interconnected ponds within a predator proof fence. During drought conditions in 2019, Platypuses could not move out of the fenced area to refugia as floodgates were closed due to low water levels. In winter of 2019, eight Platypuses were found deceased resulting from starvation. By December, water levels were extremely low and ponds were continuing to dry. Given these circumstances, a rescue intervention was undertaken to capture stranded Platypuses. They were temporarily relocated and housed at Taronga Zoo, Sydney, until they were returned when conditions at TNR improved. Seven Platypuses were rescued, with five successfully housed at Taronga for 5 months. One Platypus was lost after escaping from its enclosure and another Platypus died when trapped in a crevice. The Platypuses were returned after water levels increased at TNR and were monitored for 500 days post‐release, demonstrating successful repatriation. This case study outlines the key stages and considerations required for this intervention, providing critical information for rescue attempts on drought‐affected Platypus populations. There is a need to continue developing a decision framework for interventions of climate‐affected populations, including quantifying trigger thresholds and conservation prioritisation of populations. This will become increasingly necessary given the trajectories of habitat degradation, coupled with the increasingly frequent and severe droughts, expected under anticipated climate change scenarios.

Temporal Patterns of Fish Occurrence in the Colorado River, Grand Canyon in Response to Temperature, Largescale Drought, and Newly Exposed Habitat

ABSTRACTTwo large dams on the Colorado River, Glen Canyon and Hoover Dam, have profoundly altered the river within Grand Canyon. Owing to widespread drought and increased water usage throughout the Southwest, water levels in Lake Mead declined by over 40 m since 2000, exposing over 80 km of newly emerged riverine habitat in the western Grand Canyon that experiences higher water temperatures and increased turbidity relative to upstream portions of the Colorado River within the Grand Canyon. Our objective was to investigate how the probability of fish occurrence has changed within the Colorado River in Grand Canyon as abiotic conditions have shifted in relation to these altered environmental conditions. We used 22 years of long‐term fish monitoring data, from 2000 to 2022, on the mainstem of the Colorado River in the Grand Canyon to map the probability of occurrence based upon modeled water temperature for native and common nonnative salmonid species through space (river kilometer) and time in relation to declining water levels in Lake Mead. Our results suggest that native fish occurrence is strongly correlated with longitudinally increasing water temperature, while nonnative trout species were negatively correlated with increased water temperature downstream from the dam. Further, we found that nonnative trout species have experienced decreases in their probability of occurrence through time, while natives have experienced an increase in probability of occurrence. Information on distribution of fish prior to reservoir declines, and how the fish assemblage has shifted coincident with environmental changes, can help inform future management of native and nonnative fish in highly regulated river systems.

The Financial Challenges of Developing Countries for Climate Change Mitigation and Sustainable Development Under UN Agenda 2030

The study seeks to analyze the financial obstacles confronting poor nations in mitigating the effects of climate change and shifting towards sustainable development trajectories, as outlined in the 2030 Agenda. The paper examines Iraq to highlight difficulties and possibilities pertinent to its context, while the analysis and policy implications extend to several other nations in other areas with analogous concerns. The study employs a quantitative analytical methodology using secondary data on sustainable development indicators, emissions, mortality rates, and finance sources for a sample of 18 developing nations from 2010 to 2020, together with projected data for specific economic indicators extending to 2050. The findings indicate that emerging nations, particularly impoverished ones, would encounter the most significant dangers from climate change while not being accountable for its causation. Developing nations are experiencing escalating environmental concerns due to climate change, including floods, droughts, pollution, desertification, and declining water levels. Consequently, these nations must intensify their efforts to address these difficulties and develop measures to safeguard the environment and natural resources. Numerous developing nations depend significantly on the agricultural sector for revenue and employment, confronting emerging difficulties from climate change that result in diminished agricultural output and land degradation, impacting food security and the local economy. Climate change may adversely affect emerging nations' economies, leading to agricultural land degradation and heightened expenses for infrastructure reconstruction.

Rising temperatures and sinking hopes: An in-depth analysis of the interplay between climate change, land use patterns, and the desiccation of a global biosphere reserve

Global ecosystems and communities are significantly impacted by climate change and extreme events. The rapid desiccation of massive wetlands, which are essential for controlling water cycles, and biodiversity, preventing floods, and supplying essential ecosystem services, is one of the most upsetting effects. The once-largest lake in the Middle East, Lake Urmia, had a significant impact on ecology, economy, and human life contributing to climate regulation, species preservation, habitat conservation, tourism and recreation, and a wide range of other ecosystem services. The Ramsar Convention classified the lake as a Wetland of International Importance, and UNESCO designated it as a Biosphere Reserve. The ecological, agricultural, and societal challenges caused by rising temperatures, improper water resource management and overuse, enhanced salinity, and declining water levels have made Lake Urmia an acute symbol of environmental vulnerability. Using Landsat imagery, this study begins a thorough analysis of changes in the Lake Urmia basin from 1990 to 2020. The endeavor aims to develop effective conservation and restoration strategies by identifying the multiple reasons that led to its vulnerable situation. The study attempts to identify the role of precipitation, temperature trends, agricultural development, population growth, water consumption, evapotranspiration, and atmospheric salt and aerosol concentrations in the desiccation of the lake. This study presents a comprehensive knowledge of the complex interplay between climate change, human activity, and water management and may have implications for the holistic recovery of the lake. The findings have the potential to improve prognostic models and inform targeted mitigation strategies for not only Lake Urmia but also for other globally threatened wetlands.

The effect of geology and agricultural development on the groundwater, West Minia, Egypt

Fifty groundwater samples were collected from the Oligocene sand and Middle Eocene limestone aquifers and analyzed for major ions and stable isotopes. Aquifer sediment samples were examined to determine hydraulic properties, and sixty-six well logs were investigated to understand the subsurface geology. The study reveals that lithofacies, mineral composition, and geologic structures significantly influence groundwater quality and behavior. Karst features in the Middle Eocene limestone aquifer create subsurface caves, leading to challenges such as abrupt salinization and well failure. In the Oligocene aquifer, groundwater is predominantly of the sodium chloride type. In the Middle Eocene aquifer, 80 % of samples are sodium chloride, with variations of sodium bicarbonate (10 %) and sodium sulfate (10 %) types. Remote sensing from 2013 to 2021 shows significant agricultural expansion, with vegetation increasing by over 227 km². This growth, driven by large agricultural projects, has led to substantial groundwater consumption, resulting in a 5-meter decline in water levels within just one year (from 2020 to 2021). The over-extraction poses a risk to the aquifers, threatening long-term sustainability. Understanding the region's geology is crucial for mitigating these issues and ensuring sustainable groundwater management.

Spatiotemporal variation of water level in wetlands based on multi-source remote sensing data and responses to changing environments

Under changing environmental conditions, water level is a crucial indicator for assessing the wetland hydrological cycle. However, due to some wetlands being located in remote and widely dispersed areas, acquiring data on wetland water level changes presents significant challenges, making wetland water level monitoring exceptionally difficult. Wetlands are extensively distributed in western Jilin Province, China, and are experiencing significant degradation due to various factors including natural conditions, agricultural activities, and social development. To address this challenge, this study proposes a monitoring method that combines Sentinel-3 radar altimetry satellites with optical remote sensing images to obtain wetland water level data. Additionally, the study takes into account the Chinese government's Interconnected River System Network Project (IRSNP), classifying wetlands in western Jilin Province into three different water recharge scenarios: direct recharge through main and branch canals, indirect recharge through ditches, and no recharge to isolated wetlands. This study analyses the relationship between wetland water level changes and climatic factors, and assesses how IRSNP can mitigate the negative impacts of climate factors on wetland water levels across different recharge scenarios. The results show that: (1) the wetland water level monitoring method, has high accuracy and feasibility. The average difference between the in-situ measured and satellite-monitored water levels was 0.254 m. (2) There was an overall increasing trend in wetland water levels directly influenced by IRSNP, an insignificant decreasing trend in wetland water levels indirectly influenced by IRSNP. (3) Increased precipitation and decreased evaporation are the predominant climatic factors contributing to rising wetland water levels. Conversely, lower relative humidity and higher temperatures primarily lead to declining water levels. The construction of IRSNP can mitigate the impact of climate change on water levels. Thus, under changing environmental conditions, the implementation of IRSNP has positively impacted wetland protection and provides valuable insights for understanding wetland water level changes and managing water resources effectively.

Climate-driven decline in water level causes earlier onset of hypoxia in a subtropical reservoir

Hypoxia, especially in the bottom water, is occurring in deep and stratified reservoirs worldwide, threatening aquatic biodiversity, ecosystem functions and services. However, little is known about the timing of onset and ending of hypoxia, especially in subtropical reservoirs. Based on five-year (from April 2015 to January 2020) sampling of a subtropical monomictic deep reservoir (Tingxi Reservoir) in southeast China, we found the evidence of about 40 days earlier onset of hypolimnion hypoxia during low water level periods in dry years compared to wetter high water level years. We explored the effects of stratification and mixing conditions on hypoxia, cyanobacterial biomass, and nutrient dynamics; and revealed the physical and biochemical conditions that drove hypoxia. The results indicated that 1) The decline in water level increased the intensity of thermal stratification, resulting in 40 days earlier onset of hypolimnion hypoxia in dry years than in wet years; 2) The decline in water level expanded the extent of hypoxia by promoting nutrient accumulation and phytoplankton biomass growth; 3) Warmer climate and less precipitation (drought) significantly promoted the risk of hypoxic expansion and endogenous phosphorus release in subtropical reservoirs. We suggest that more attention needs to be paid to the early onset of hypoxia and its consequences on water quality in subtropical stratified reservoirs during low water level periods in a changing climate.

Short-Term Groundwater Level Fluctuations Drive Subsurface Redox Variability.

As global change processes modify the extent and functions of terrestrial-aquatic interfaces, the variability of critical and dynamic transitional zones between wetlands and uplands increases. However, it is still unclear how fluctuating water levels at these dynamic boundaries alter groundwater biogeochemical cycling. Here, we used high-temporal resolution data along gradients from wetlands to uplands and during fluctuating water levels at freshwater coastal areas to capture spatiotemporal patterns of groundwater redox potential (Eh). We observed that topography influences groundwater Eh that is higher in uplands than in wetlands; however, the high variability within TAI zones challenged the establishment of distinct redox zonation. Declining water levels generally decreased Eh, but most locations exhibited significant Eh variability, which is associated with rare instances of short-term water level fluctuations, introducing oxygen. The Eh-oxygen relationship showed distinct hysteresis patterns, reflecting redox poising capacity at higher Eh, maintaining more oxidizing states longer than the dissolved oxygen presence. Surprisingly, we observed more frequent oxidizing states in transitional areas and wetlands than in uplands. We infer that occasional oxygen entering specific wetland-upland boundaries acts as critical biogeochemical control points. High-resolution data can capture such rare yet significant biogeochemical instances, supporting redox-informed models and advancing the predictability of climate change feedback.

Efficient fruit disease diagnosis on resource-constrained agriculture devices

Climate change in recent years has caught the attention of researchers worldwide, with drastic effects on many economic sectors, especially agriculture and livestock. Due to global warming and declining water levels, food security is becoming an increasingly urgent concern. The situation is more challenging in underdeveloped nations such as Pakistan, where little attention has been paid to improving the processes to produce effective seeds and herbicides. The problem has been exacerbated due to financial constraints and a lack of technology to monitor crops. It has been observed that even a noncritical disease can ruin the crop if timely inspections aren’t performed. Although many solutions have been proposed recently, most are based on heavy mobile applications and cloud-based solutions, which results in considerable computational cost, power consumption, and latency. This work proposes a Deep Neural Networks (DNNs)-based light-weight solution for diagnosing and classifying apple crop diseases for farmers working in rural places (where the internet is not accessible). With the increasing need for efficient and robust Machine Learning (ML) applications on edge devices, such as mobile phones, Raspberry Pi, and Jetson Nano-based devices, there has been a demand for more efficient Deep Neural Networks (DNN) models. To meet this demand, various DNN-based models have been experimented with, including Basic CNN Architecture, AlexNet, and EfficientNet Lite to measure performance After a thorough examination and evaluation of each model’s performance, efficiency, and resource usage, the most optimal model was picked and developed applications for classifying apple crop disease. Using a transfer learning strategy on a specially developed EfficientNet DNN architecture, achieving 85% test accuracy.

Experimental study on migration characteristics of LNAPL in the aquitard under pumping conditions.

Research on the migration behaviors of contaminants in the aquitard has been deficient for an extended period. Clay is commonly employed as an impermeable layer or barrier to stop the migration of contaminants. However, under certain conditions, the clay layer may exhibit permeability to water, thereby allowing contaminants to infiltrate and potentially contaminate adjacent aquifers. Consequently, it holds immense importance to scrutinize and investigate the migration characteristics of light non-aqueous phase liquid (LNAPL) within the aquitard for the purposes of groundwater pollution control and remediation. To evaluate the environmental risk posed by organic contaminants in the aquitard, an experimental model was formulated and devised to monitor the LNAPL concentration in the aquitard under pumping conditions. The correlation between pumping rate and LNAPL concentration was investigated. A self-developed plexiglass sandbox model was used to simulate the migration characteristics of LNAPL in the aquitard under pumping conditions. Four experimental scenarios were designed, varying pumping rates, aquitard thicknesses, and groundwater level changes. The LNAPL concentration curve was derived by systematically tracking and analyzing LNAPL levels at various locations within the aquitard. The results indicated that higher pumping rates corresponded to increased migration of LNAPL, resulting in greater LNAPL ingress into the pumping well during extraction. A thicker aquitard demonstrated a more pronounced inhibitory effect on LNAPL, leading to an extended penetration time of LNAPL within the aquitard. The drawdown within the aquitard exerted a discernible influence on LNAPL migration, with the LNAPL concentration continuing to decrease in tandem with declining water levels during pumping. These research findings can establish a scientific foundation for the control and remediation of contaminants within aquitards.

Satellite gravimetry observations on the state of groundwater level variability in the Arabian Peninsula Region and the associated socio-economic sustainability challenges

Groundwater is an important resource for the Arabian Peninsula Region. The population increase, rise in agricultural activities, and Gulf Cooperation Council (GCC) countries (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates) inclination towards economic diversification and tourism promotion have heightened the freshwater demand. As a result of climate change and varying weather patterns, the situation has become more complicated. Due to arid conditions, recharge is mostly less than withdrawal which consequently results in underground water level decline over time. In the research, we have used Gravity Recovery and Climate Experiment (GRACE/GRACE-FO) MASCON solutions, Global Land Data Assimilation System (GLDAS) soil moisture, and the Integrated Multi-satellite Retrievals for Global Precipitation Mission (IMERG) rainfall data to observe the Equivalent Water Thickness (EWT), and rainfall patterns in this region for the past two decades (2002–2023). The results indicate that in Saudi Arabia the water level is declining nearly at a linear rate and the linear regression model fits well with the data (R2 value, the coefficient of determination, for different cities of Saudi Arabia is ≥ 0.94). In the Al Jouf Area, the water decline is the highest at −1.69 cm/year which is 43% greater than the previous calculations. The lowest decline rate is in Sanaa (Yemen) which is −0.13 cm/year. Furthermore, all the other studied locations show a groundwater declining trend. In Saudi Arabia's Makkah, Madina, Riyadh, and Damam the reduction rate is −0.36, −0.48, −0.72, and −0.48 (cm/year) respectively. Kuwait, UAE's Dubai, and Al Ain show a similar groundwater reduction rate of −0.19 cm/year. In Oman's Masqat, the groundwater decline rate is −0.22 cm/year. Also, in the recent data, one can see the higher seasonal amplitudes that are indicative of greater fluctuations in EWT data in recent times. If water mining continues at the same pace, this important resource can become a rare commodity. Limited water supply can likely become a limiting factor for further social, agricultural, and industrial development. That's why major reviews and shifts are necessary in the current policies related to water resource management and conservation.

Impacts of droughts and human activities on water quantity and quality: Remote sensing observations of Lake Qadisiyah, Iraq

Water quantity and quality in lakes are closely linked to the compounding effects of climate change and human activities in their catchments, especially for lakes located in semi-arid and arid regions where water resources are scarce. Whilst knowledge gaps exist for these effects in semi-arid and arid region lakes due mainly to the lack of long-term in situ monitoring data. By using satellite remote sensing data, this study firstly investigated the variations of water level, chlorophyll-a concentration (Chl-a) and turbidity in Lake Qadisiyah, Iraq between 2000 and 2019. Results showed that the average water level was 138.3 m in 2000–2019, it decreased clearly in 2001, 2009, 2015 and 2018 with the lowest value of 120 m in July 2015. The mean Chl-a was 6.3 mg/m3 and it showed an overall increasing trend during 2000 and 2019. Turbidity showed extremely high values (>10 NTU) in 2009 and 2017–2018 compared to the mean value of 3.6 NTU in 2000–2019. The boosted regression tree (BRT) was then used to explore the relationship between those variations and El Niño-Southern Oscillation, droughts, meteorological factors and land use land cover changes in the catchment. Results revealed that water level declines were mainly associated with droughts led by La Niña events. Chl-a increase in the lake were mainly explained by built-up area increase and water area decrease in the catchment, with a relative contribution of 29.2 % and 28.6 % respectively. Water area changes in the catchment were the main factor influencing turbidity explaining 55.3 % of the variation. An exception water level decline in 2014–2016 was also observed when there was no drought, which was most likely caused by the cut off of water flow upstream and the release of water from the dam during periods of war. The findings in this study underscored the impacts of climate and human activities on water quantity and quality in semi-arid region lakes. Actions such as improving water use efficiency, establishing water storages, and enhancing cross-border cooperation are therefore recommended to deal with extreme events. Pollution control measures in the catchment are also suggested to prevent water quality deterioration in the lake.

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.

Unravelling the spatiotemporal variation in the water levels of Poyang Lake with the variational mode decomposition model

AbstractPoyang Lake is a dynamic floodplain lake system that exhibits complex water level fluctuations and experiences significant regime changes over space and time, which remains to be further explored. This study used the variational mode decomposition (VMD) model to decompose the Poyang Lake's water levels from 1960 to 2022 at four key stations into six intrinsic mode functions (IMFs), namely IMF1–IMF6, representing variations on different time scales. The results present significant spatiotemporal heterogeneity. The multi‐year variation (IMF1) accounts for 5.6%–12.4% of the total variation and displays a northward decreasing trend, reflecting the lake's river‐like characteristics. The spectrum of IFM1 also reveals a significant 3.6‐year fluctuation mainly attributed to the tributary inflow, especially the Ganjiang River. The IMF1 differences between stations show abrupt decreases since the 2000s, indicating the impact of concentrated sand mining activities on the northern and central regions. The annual variation (IMF2) is the most prominent, contributing 76.1%–88.4% of the total variation, and shows a southward attenuation trend, likely due to the weakening influence of the Yangtze River flow. The intra‐annual scale (IMF3–IMF6) represents 6.0%–11.5% of the total variation and exhibits less spatial difference compared to the multi‐year and annual variations. The VMD model effectively separates the water level signals into different frequency bands, providing insights into the complex interactions between the lake, tributaries, and Yangtze River, as well as the impacts of human activities like sand mining, enhancing understanding of floodplain lake dynamics. The results also imply the importance of coping with the water level decline of Poyang Lake.

Mapping and projecting spatiotemporal trends in groundwater levels and flow direction in Pakistan's water-scarce aquifer system

Groundwater is the most vital and reliable source of fresh water globally. This study examined the variability in Depth to Water table (DTW) below ground level in agriculture-dominated Bari interfluve, Pakistan. Observing water levels empowers access and management of water resources ensuring long-term availability. Changes in the DTW were observed by preparing spatiotemporal maps using piezometric data for both pre-monsoon and post-monsoon seasons by five-year difference intervals from 2005 to 2020. Piezometric observations offer more precise real-time monitoring of subsurface water levels. The trend of the groundwater table was analyzed by non-parametric methods i.e., Mann-Kendall (MK) and Sen's slope estimator in all observation wells of districts at a significance level of 5 percent for sustainable groundwater resource management. The resulting trend of fluctuating water table showed a progressive decline in water level in all districts except a minor increase was also noticed. The seasonal fluctuation (between pre-monsoon and post-monsoon seasons) showed that the average DTW was found to be high in 46% of the total tehsils in the post-monsoon season while in 42% it was low and 12% depicted no change compared to pre-monsoon season. Piezometric observation points of DTW exhibiting a trend at a 5 percent significance level were used to project future water table depths that indicated a further alarming depleting trend for both the pre-monsoon and post-monsoon seasons in lower districts of Bari interfluve. The groundwater pattern calls for precautionary measures to see a reversal in trend or even maintain the groundwater levels for future needs.

Quantifying land subsidence and its nexus with groundwater depletion in isfahan-borkhar plain: An integrated approach using radar interferometry and spatial bivariate relationships

Land subsidence has emerged as a significant global concern, particularly in arid regions like Iran. Among these vulnerable areas, the Isfahan-Borkhar plain stands out due to its strategic importance and critical high-population settlements. In this study, we focus specifically on land subsidence within this plain. This study specifically examines land subsidence in this plain. Utilizing the precise radar interferometry technique, considered the most accurate method, this study investigates the vertical changes of the Earth's surface in the Isfahan-Borkhar plain between 2015 and 2022 by analyzing Sentinel-1 satellite data. To establish causality, we correlate these subsidence patterns with spatial water extraction data, employing a spatial bivariate relationship model. The results obtained from this seven-year monitoring period reveal that average annual subsidence in different areas of the Isfahan-Borkhar plain ranges from 25 to 45 cm, while the average annual decline in the water table in this aquifer is 230 cm. The pronounced subsidence observed aligns with areas experiencing the highest water level decline, emphasizing the critical role of water table depletion. In summary, our study underscores the need for sustainable water management practices to mitigate land subsidence risks in this strategically vital region.

Reservoir regulation-induced variations in water level impacts cyanobacterial bloom by the changing physiochemical conditions

Gaining insight into the impact of reservoir regulation on algal blooms is essential for comprehending the dynamic changes and response mechanisms in the reservoir ecosystem. In this study, we conducted a comprehensive field investigation linking physiochemical parameters, and phytoplankton community to different water regimes in the Three Gorges Reservoir. Our aim was to explore the effects of reservoir regulation on the extinction of cyanobacterial blooms. The results showed that during the four regulatory events, the water levels decreased by 2.02–4.33 m, and the average water velocity increased 68 % compared to before. The average total phosphorus and total nitrogen concentrations reduced by up to 20 %, and the cyanobacterial biomass correspondingly declined dramatically, between 66.94 % and 75.17 %. As the change of water level decline increasing, there was a significant increase of algal diversity and a notable decrease of algal cell density. Additionally, a shift in the dominant phytoplankton community from Cyanobacteria to Chlorophyceae was observed. Our analysis indicated that water level fluctuations had a pronounced effect on cyanobacterial extinction, with hydrodynamic changes resulting in a reduction of cyanobacterial biomass. This research underlined the potential for employing hydrodynamic management as a viable strategy to mitigate the adverse ecological impacts of cyanobacterial blooms, providing a solution for reservoir's eco-environmental management.

Reservoir Filling Up Problems in a Changing Climate: Insights From CryoSat‐2 Altimetry

AbstractRecent droughts have severely threatened water security in many regions worldwide. Reservoirs, designed to combat droughts and secure water supply partially, are reported failing to fill up to the total capacity due to severe droughts. How bad is climate affecting reservoir filling up on a global scale? This issue has not been studied. We present a big picture of reservoirs in crisis using satellite altimetry. Thanks to the unique characteristics of CryoSat‐2, 525 reservoirs worldwide were investigated during 2010–2022. Results show that most reservoirs (93%) are found not fully filled up at least once. About 21% of reservoirs, which are mainly located in the Southern Hemisphere, show a significant decline in water levels. Moreover, about 20% of reservoirs with larger level fluctuations (>3 m) are located in less developed economies, indicating informed operation rules are needed. Further analyses indicate reservoirs are largely affected by extreme climate events, such as ENSO.