Water Level Regulation Research Articles

Shallow drainage of agricultural peatlands without land-use change: have your peat and eat it too

IntroductionDrainage for agricultural purposes is one of the main drivers of peatland degradation, leading to significant greenhouse gas (GHG) emissions, biodiversity loss, and soil eutrophication. Rewetting is a potential solution to restore peatlands, but it generally requires a land-use shift to paludiculture or nature areas.MethodsThis study explored whether three different water level management techniques (subsoil irrigation, furrow irrigation, and dynamic ditch water level regulation) could be implemented on dairy grasslands to yield increases in essential ecosystem services (vegetation diversity and soil biogeochemistry) without the need to change the current land use or intensity. We investigated vegetation diversity, soil biogeochemistry, and CO2 emission reduction in fourteen agricultural livestock pastures on drained peat soils in Friesland (Netherlands).ResultsAcross all pastures, Shannon-Wiener diversity was below 1, and the species richness was below 5. The plant-available phosphorus (P) was consistently higher than 3 mmol L−1. None of the water level management (WLM) techniques enhanced vegetation diversity or changed soil biogeochemistry despite a notable increase in water table levels. The potential for CO2 emission reduction remained small or even absent. Indicators of land-use intensity (i.e., grass harvest and fertilization intensity), however, showed a strong negative correlation with vegetation diversity. Furthermore, all sites’ total and plant-available P and nitrate exceeded the upper threshold for species-rich grassland communities.DiscussionIn conclusion, our research suggests that incomplete rewetting (i.e., higher water tables while maintaining drainage) while continuing the current land use does neither effectively mitigate GHG emissions nor benefit vegetation diversity. Therefore, we conclude that combining WLM and reducing land-use intensity is essential to limit the degradation of peat soils and restore more biodiverse vegetation.

Modelling And Research on Water Level Control of Great Lakes Based on Neural Network PID Algorithm

The Great Lakes are situated in the border region between the United States and Canada, which has a significant impact on the climate and the lives of those living in the surrounding areas. The objective of this paper is to establish a network of the Great Lakes through Pearson's correlation coefficient analysis and to construct a two-tank water level model based on a PID control system in order to effectively manage the dynamics of the Great Lakes. Firstly, the strength and direction of the linear relationship between two variables is quantified through Pearson's correlation coefficient analysis, which involves the collection of observational data and the calculation of mean values. This analysis serves as a fundamental basis for predictive modelling and hypothesis testing. Secondly, based on the flow balance principle, mathematical expressions are constructed to simulate the water flow, and a PID control system is constructed to achieve optimal water level maintenance. By analysing the Pearson's correlation coefficient, the interrelationships among the variables in the Great Lakes network can be understood, thereby providing guidance for scientific research and decision-making. The results demonstrate that the constructed two-tank water level model combined with the PID control system and SHAP algotithm can effectively manage the water level of the Great Lakes and achieve optimal water level regulation.

Functional diversity dynamics of waterbird communities driven by water levels at Shengjin Lake, a small river-connected shallow lake in the middle and lower Yangtze River floodplain.

Gate-controlled activities in lakes can directly or indirectly influence the assembly of waterbird communities. Shengjin Lake, a Ramsar site, is a typical river-connected and gate-controlled shallow lake in the lower and middle Yangtze River floodplain in China, comprising three sub-lakes (upper, middle, and lower) based on topographical features. We surveyed wintering waterbirds at Shengjin Lake from October 2022 to March 2023. We divided the winter water level period into nine phases based on the characteristics of water level changes. By measuring functional diversity, we aimed to provide insights into the differences in waterbird communities among the three sub-lakes under different water level conditions. Multiple linear regression was used to analyze the relationship between habitat factors and functional diversity. We further explored the relationship between specific functional traits and habitat factors through a combination of the R-mode linked to the Q-mode and the trait-environment correlation matrix (fourth-corner analyses) to explain the mechanism underlying waterbird community assembly. When the water level fluctuated in the range of 10.43-10.74 m (Huanghai elevation), the three sub-lakes had significant habitat differences and high habitat heterogeneity, increasing functional richness and functional dispersion of the upper and lower lakes, both of which significantly differed from those of the middle lake. Habitat heterogeneity and mudflat habitats have positive effects on functional diversity. The difference in functional diversity was primarily determined based on the foraging traits and strata of waterbirds. Habitat filtering of particular traits is a major driving force underlying the assembly of waterbird communities. Overall, we suggest that the minimum water level in the wintering period at Shengjin Lake should be regulated between 10.43 and 10.74 m. These findings provide reasonable suggestions for water level regulation and a theoretical basis for conserving waterbird diversity at Shengjin Lake.

Deteriorating wintertime habitat conditions for waterfowls in Caizi Lake, China: Drivers and adaptive measures

China has made enormous strides to achieve high-quality development and biodiversity conservation, and the establishment of nature-protected areas is one of the essential initiatives. Caizi Lake involves a natural reserve and two national wetland parks, accommodating winter migratory waterfowl over the middle and lower Yangtze River basin in China. However, the water transfer from the Yangtze River to the Huai River (YR-HR water transfer) has modified the winter hydrological conditions of Caizi Lake, negatively affecting wintertime waterfowl habitats. Hence, conserving wintertime waterfowl habitats necessitates knowledge of the dynamical mechanisms behind the impacts of YR-HR water transfer on wintertime waterfowl habitats and adaptive measures. Here we developed a machine learning model, the normalized difference vegetation index, and on-spot observatory datasets such as the spatial distribution of waterfowl species and underwater topography of Caizi Lake. We found that the rising winter water level of Caizi Lake encroaches on winter waterfowl habitat with extremely high suitability. Meanwhile, rising water levels reduced waterfowl food sources. Thus, rising water levels due to YR-HR water transfer deteriorated waterfowl living conditions over Caizi Lake. Therefore, we proposed adaptive measures to alleviate these negative effects, such as water level regulation, artificial feeding of waterfowls, restoration and reconstruction of contiguous mudflats, grass flats. This study highlights human interferences with waterfowl habitats, necessitating biodiversity conservation at regional scales.

Prediction of long-term changes of weak diurnal stratification in shallow lakes using artificial neural networks

ABSTRACT Thermal stratification plays a key role in lakes' ecosystems. In contrast to deep lakes, the thermal structure of shallow polymictic lakes is characterized by a weak stratification with an apparent diurnal cycle. Long-term changes in stratification are governed by climate change and anthropogenic effects such as water level regulation. We developed a simple and robust model system consisting of an energy balance model to estimate depth-averaged water temperatures and an artificial neural network (ANN) model to predict stratification with high temporal resolution. One novelty of our approach is that instead of directly estimating water temperatures at different depths, we simulated the potential energy anomaly index, the indicator of stratification's strength. The ANN-based model's performance was assessed against a physical-based one-dimensional model (General Ocean Turbulence Model) by modeling a 40-year-long period from 1981 to 2020. The new model accurately predicts a shallow lake's weak stratification and its diurnal cycle. Besides, the model proved reliable on longer time scales, capturing the effect of climate change, anthropogenic water level regulation, and their synergistic interaction on the change of stratification's intensity and duration.

Ecological water level regulation based on aquatic plant restoration in large reservoirs: A case study of Wangying Reservoir

The regulation of water levels based on water level requirements at different life-cycle stages of aquatic plants is a crucial measure for the restoration of aquatic plants. Based on the current situation of aquatic plants in the reservoir and the requirements for the water level of aquatic plants in different life cycle stages, the present study proposes the best ecological water level under different plant coverage restoration targets for the Wangying Reservoir. There were 184 species of aquatic plants in the Wangying Reservoir belonging to 142 genera in 61 families and 32 orders, with an average biomass of 2.35 kg/m2 and average density of 227 plants/m2. The total coverage of aquatic vegetation was 26 %, which included 15 % hygrophytes and emergent plants and 11 % submerged plants. The hygrophytes, emergent, and submerged plants have experienced discrepant life history stages and water level requirement even for the same life history stage. The fluctuations in the water level required for hygrophytes and emergent plants (2 m) were relatively more stable across different life cycle stages than for submerged plants (5 m). These results offer valuable guidance for the recovery of aquatic plants and reservoir management for the lentic water bodies.

Study on Mechanical Properties of Sandy Soil Solidified by Enzyme-Induced Calcium Carbonate Precipitation (EICP)

Earth–rock dams are widely distributed in China and play an important role in flood control, water storage, water-level regulation, and water quality improvement. As an emerging seepage control and reinforcement technology in the past few years, enzyme (urease)-induced calcium carbonate precipitation (EICP) has the qualities of durability, environmental friendliness, and great economic efficiency. For EICP-solidified standard sand, this study analyzes the effect of dry density, amount of cementation, standing time, perfusion method, and other factors on the permeability and strength characteristics of solidified sandy soil by conducting a permeability test and an unconfined compression test and then working out the optimal solidification conditions of EICP. Furthermore, a quantitative relationship is established between the permeability coefficient (PC), unconfined compressive strength (UCS), and CaCO3 generation (CG). The test findings indicate that the PC of the solidified sandy soil decreases and the UCS rises as the starting dry density, amount of cementation, and standing time rise. With the increase of CG, the PC of the solidified sandy soil decreases while the UCS increases, indicating a good correlation among PC, UCS, and CG. The optimal condition of solidification by EICP is achieved by the two-stage grouting method with an initial dry density of 1.65 g/cm3, cementation time of 6 d, and standing time of 5 d. Under such conditions, the permeability of the solidified sandy soil is 6.25 × 10−4 cm/s, and the UCS is 1646.94 kPa. The findings of this study are of great theoretical value and scientific significance for guiding the reinforcement of earth–rock dams.

Large shallow lake response to anthropogenic stressors and climate change: Missing macroinvertebrate recovery after oligotrophication (Lake Balaton, East-Central Europe)

East-Central Europe's largest shallow lake, Balaton, experienced strong eutrophication in the 1970–80s, followed by water quality improvement and oligotrophication by 2010 CE. Recently however, repeated cyanobacterial blooms occurred and warned that internal P-recycling can act similarly to external P load, therefore we need a better understanding of past water level (WL) and trophic changes in the lake. In this study we discuss the last 500-yr trophic, WL and habitat changes of the lake using paleoecological (chironomids, pollen) and geochemical (sediment chlorophyll, TOC, TS, TN, C/H ratio, major and trace element) methods. We demonstrate that the most intensive and irreversible change in the macroinvertebrate fauna occurred during the period of economic boom between the First and Second World War (∼1925–1940 CE), when large-scale built-in and leisure use of the lake has intensified. At that time, the Procladius-Microchironomus-Stempellina dominated community transformed to Procladius-Chironomus plumosus-type-Microchironomus community that coincided with land use changes, intensified erosion and water-level regulation in the lake with the maintenance of year-round high WL. This was followed by the impoverishment and population size decrease of the chironomid fauna and Procladius dominance since 1940 CE, without any recovery after 1994 CE despite the ongoing oligotrophication. Accelerated rate of change and turnover of the fauna was connected to an increase in the benthivorous fish biomass and eutrophication. The basin lost almost completely its once characteristic Stempellina species between 1927 and 1940 CE due to trophic level increase and seasonal anoxia in the Szemes Basin. Reference conditions for ecosystem improvement were assigned to 1740–1900 CE. We conclude that in spite of the ongoing oligotrophication, the re-establishment of the Procladius-Microchironomus-Stempellina assemblage is hampered, and requires fish population regulation.

Strategic water resource management: pump stations in Fayoum City, Egypt

Water scarcity presents significant challenges to sustainable development, particularly in arid regions like Fayoum City, Egypt, which faces particular water challenges due to its unique topography. This study explores the pivotal role of pump stations and wastewater reuse in mitigating water scarcity and promoting sustainable water management practices. Utilizing a comprehensive mixed-method approach, including desk research, field surveys, stakeholder interviews, and integrating the Analytic Hierarchy Process (AHP) into a decision-making framework. The study categorizes pump stations into priority ranking groups based on the evaluation of the following criteria: efficiency, operating hours, working unit ratio, and discharge capacity. The investigation reveals that the 72 pump stations in Fayoum City play a vital role in regulating water levels, optimizing distribution, and facilitating the reuse of irrigation wastewater. Despite operational challenges, such as manpower shortages and maintenance issues, these stations are crucial for sustaining agricultural productivity and addressing water scarcity concerns, including the prevention of recurring inundation events like the one in 2012. Moreover, the study underscores the potential of wastewater reuse as a sustainable solution to water scarcity, particularly in meeting agricultural water demands and mitigating water balance issues, such as inundation. Based on the findings, the study proposes actionable recommendations, including upgrading high-priority pump stations, evaluating lower-priority ones, enhancing canal infrastructure, and promoting water-efficient irrigation methods. In conclusion, this study provides valuable insights into the pivotal role of pump stations and wastewater reuse in addressing water scarcity challenges in arid regions. By implementing the proposed recommendations, Fayoum City can optimize its water management practices, ensure water security, and support the long-term development of the region.

Research on the Reconstruction of Aquatic Vegetation Landscape in Coal Mining Subsidence Wetlands Based on Ecological Water Level

The eastern region of the Huang-Huai area is vital for China’s coal production, with high water table mining causing significant surface subsidence and the formation of interconnected coal mining subsidence wetlands. Restoring these wetlands is crucial for biodiversity, environmental quality, and sustainable development. Aquatic vegetation plays a crucial role in wetland ecosystems, underscoring its importance in restoration efforts. Understanding and managing water level fluctuations is essential due to their impact on vegetation. This study examines the Qianshiliying coal mining subsidence wetland in the Yanzhou Mining Area, China, with the goal of devising a water level regulation plan based on the minimum ecological water level to improve the growth and recovery of aquatic vegetation. The research delves into landscape ecological restoration techniques for aquatic vegetation in coal mining subsidence wetlands in the eastern Huang-Huai region, emphasizing the importance of water level management. The results reveal that the minimum ecological water level in the Qianshiliying coal mining subsidence wetland is 32.50 m, and an area of 78.09 hectares is suitable for the reconstruction of aquatic vegetation. This paper utilizes lake morphology, minimum biological space, and water level demand methods for aquatic plants in the landscape to promote restoration of coal mining subsidence wetlands. A notable strength of this approach is its ability to quantitatively predict the survival range and area of aquatic vegetation in these wetlands, enabling a more scientifically informed restoration of ecological balance and promoting landscape ecological restoration in the eastern Huang-Huai region.

Drainage effects on carbon budgets of degraded peatlands in the north of the Netherlands

Peatlands store vast amounts of carbon (C). However, land-use-driven drainage causes peat oxidation, resulting in CO2 emission. There is a growing need for ground-truthing CO2 emission and its potential drivers to better quantify long-term emission trends in peatlands. This will help improve National Inventory Reporting and ultimately aid the design and verification of mitigation measures. To investigate regional drivers of CO2 emission, we estimated C budgets using custom-made automated chamber systems measuring CO2 concentrations corrected for carbon export and import. Chamber systems were rotated among thirteen degraded peatland pastures in Friesland (the Netherlands). These peatlands varied in water table depth (WTD), drainage-irrigation management (fixed regulated ditch water level (DWL), subsurface irrigation, furrow irrigation, or dynamic regulated DWL), and soil moisture. We investigated (1) whether drainage-irrigation management and related hydrological drivers could explain variation in C budgets, (2) how nighttime ecosystem respiration (Reconight) related to hydrological drivers, and (3) how C budgets compared with estimates from Tier 1 and Tier 2 models regularly used in National Inventory Reporting. Deep-drained peatlands largely overlapped with C budgets from shallow-drained peatlands. The variation in C budgets could not be explained with drainage-irrigation measures or annual WTD, likely because of high variation between sites. Reconightincreased from 85 to 250 kg CO2 ha−1 day−1 as the WTD dropped from 0 to 50 cm across all sites. A deeper WTD had no apparent effect on Reconight, which could be explained by the unimodal relationship we found between Reconight and soil moisture. Finally, C budgets estimated by Tier 1 emission factors and Tier 2 national models mismatched the between-site and between-year variation found in chamber-based estimated NECBs. To conclude, our study showed that shallow WTDs greatly determine C budgets and that regional C budgets, which can be accurately measure with periodic automated chamber measurements, are instrumental for model validation.

Effects of constant high water levels in winter on waterbird diversity in Caizi Lakes: A functional perspective

The middle and lower Yangtze River floodplain lakes are important stopover and wintering sites for migratory birds on the East Asian–Australasian Flyway. The periodic water level fluctuation of the lakes plays a critical role in the aggregation of waterbirds. However, the construction of a series of gates and dams has impeded the hydrological connectivity between rivers and lakes and disrupted the natural water level fluctuation patterns of lakes. The water level status of lakes influences habitat utilization by waterbirds. In recent years, Caizi Lakes, the gate-controlled lakes connected to the Yangtze River due to the need for water level regulation requirements, has experienced sustained high water levels in winter, which can reduce habitat quality and in turn influence waterbirds activity. In the present study, wintering waterbirds in Caizi Lakes were surveyed during the 2021–2022 (W1) and 2022–2023 (W2) wintering periods. Moreover, we explored the effects of constant high water levels in winter on waterbird assemblages by comparing species richness, abundance, and functional alpha and beta diversity. Correlation analyses were then performed to elucidate the relationship between habitat factors and water level changes during the wintering period of migratory waterbirds and between changes in various habitat factors and wintering waterbird assemblages under different hydrological conditions. The results showed that functional beta diversity was more sensitive to changes in waterbird assemblages in Caizi Lakes than functional alpha diversity. Moreover, constant high water levels in the mid-wintering period decreased suitable habitats for wintering waterbirds, increased functional turnover among waterbird assemblages, increased total dissimilarity among assemblages significantly, and decreased the level of functional nestedness significantly. Additionally, the areas of the three wetland habitats in Caizi Lakes were significantly correlated with water level changes during W1 and relatively less affected by water level changes under constant high water level conditions during W2. The changes in habitat area were influenced primarily by anthropogenic activities, with an increase in meadow area favorable for species richness and abundance, as well as functionally nested components. Water level regulation should take into consideration the natural hydrological rhythms of the declining water level to ensure that adequate and suitable habitats are provided for wintering waterbirds.

Reservoir-triggered seismicity: case study of the Dnister Hydro Power Complex (Ukraine)

The work considers the seismic activity around the Dnister Hydro Power Complex in the Dnister Reservoir area from 2012 to 2021. Maximum local magnitude of earthquakes for the studied period is ML=3.4. Hypocenters of earthquakes are at the depth of 1—3 km. They are located nearby to previously established faults and contacts of structures with a different lithological composition. Artificial water level regulation in the reservoir is related to the operation of the Dnister Hydro Power Plant and, according to our results, probably affects the occurrence of seismic events. Although the maximum water level changes only by 8.7 m, the region has increased natural seismicity and is located in the transition zone between 6th and 7th isoseims according to the seismic zoning map of Ukraine. Accumulated natural stresses can be triggered into earthquakes when there is a sudden change in water pressure. The seismicity of the region around the Dnister Reservoir was investigated for 10 years, taking into account the water level data in the reservoir, as well as comparing the location of earthquakes with the State Geological Map of the Crystalline Foundation. The profile of the State Geological Map of the Crystalline Foundation with the projected earthquakes hypocenters allowed to indicate that a significant number of earthquakes are located between different lithological structures. In order to assess the interrelationship between seismicity and water level changes in the reservoir, 111 periods of lowering or filling of the reservoir were selected. Parameters of seismic activity within the periods were calculated and analysed. Correlation between the sum of logarithms of energy with water volume changes and pressure changes in the Dnister Reservoir was established. Considering linear dependence it is possible to predict potential intensity of local seismicity caused by water level changes in the Dnister Reservoir.

Integrated water management practice in tropical peatland agriculture has low carbon emissions and subsidence rates

Hydrological management in the use of peatland for agriculture is the backbone of its sustainability and a critical factor in climate change mitigation. This study evaluates the application of an integrated water management practice known as the “Water Management Trinity” (WMT), implemented since 1986 on a coconut plantation on the eastern coast of Sumatra, in relation to CO2 emissions and subsidence rates. The WMT integrates canals, dikes, and dams with water gates to regulate water levels for both coconut agronomy and the preservation of the peat soil. The WMT has successfully regulated and maintained an average yearly water table depth of −45 to −51 cm below the surface. The methodology involved a closed chamber method for measuring soil CO2 flux using a portable Infrared Gas Analyzer, conducted weekly over a six-month period to cover dry and rainy season at bi-modal climate condition. Subsidence measurements have been ongoing from 1986 to 2022. The results show bare peat soil has heterotrophic respiration CO2 emissions of 7.77 t C–CO2 ha−1 yr−1, while in coconut plantations 7.99 t C–CO2 ha−1 yr−1, similar to emissions in mineral soils. Autotrophic respiration leads to the overestimation of CO2 emissions on peatland and accounts for 212–424% of the total emissions. The cumulative subsidence from 1986 to 2022 is −56.3 cm, with a soil rise of +0.8 cm in 2022, indicating a flattening rate of subsidence. This is characterized by an increase in bulk density at the surface from 0.072 to 0.144 gr/cm3, with approximately 81% of the subsidence being due to compaction. The statistical analysis found no relationship between water table depth and CO2 emissions, indicating that water table depth cannot be used as a predictor for CO2 emissions. In summary, peatland agriculture has a promising future when managed sustainably using an integrated hydrological management system.

Estimation of Plant Height and Biomass of Rice Using Unmanned Aerial Vehicle

Plant height and biomass are important indicators of rice yield. Here we combined measured plant physiological traits with a crop growth model driven by unmanned aerial vehicle spectral data to quantify the changes in rice plant height and biomass under different irrigation and fertilizer treatments. The study included two treatments: I—water availability factor (i.e., three drought objects, optimal, and excess water); and II—two levels of deep percolation and five nitrogen fertilization doses. The introduced model is extreme learning machine (ELM), back propagation neural network (BPNN), and particle swarm optimization-ELM (PSO-ELM), respectively. The results showed that: (1) Proper water level regulation (3~5 cm) significantly increased the accumulation of spike biomass, which was about 6% higher compared to that under flooded conditions. (2) For plant height inversion, the ELM model was optimal with a mean coefficient of determination of 0.78, a mean root mean square error of 0.26 cm, and a mean performance deviation rate of 2.08. For biomass inversion, the PSO-ELM model was optimal with a mean coefficient of determination of 0.88, a mean root mean square error of 3.8 g, and a mean performance deviation rate of 3.29. This study provided the possible opportunity for large-scale estimations of rice yield under environmental disturbances.

Stochastic Model Predictive Control for Water Level Regulation in a Lake

In this paper, we propose a water level regulation framework for systems with uncertain model parameters and subject to additive disturbances. Bayesian system identification is used to estimate the distributions of the uncertain parameters. To regulate water levels, Stochastic Model Predictive Control (SMPC) is applied, using a combination of an average approach and a chance-constrained approach. We adopt a scenario approach to obtain a tractable approximation of the optimisation problem. Simulations based on real data from the upper part of the Murray River in Australia show the efficacy of the proposed framework.

Correlation between <em>Phragmites australis</em> growth and seasonal lake level variations in Lake Maggiore (Italy/Switzerland): common reed management guidelines

The present study investigates the impact of water level regulation on the growth of common reed (Phragmites australis), a globally widespread helophytic plant. The investigation has been carried out in the Bolle di Magadino (municipalities of Locarno, Gambarogno, Gordola and Tenero; Ticino, Switzerland), a lacustrine-riparian nature reserve in the context of the Lake Maggiore (that stretches between Italy and Switzerland). This is an oligotrophic, artificially regulated lake. Our initial hypothesis was that variation in water table regulation is the most influential factor for explaining observed local reed dieback. To test this, culm height of P. australis was measured at each significant change in lake water level (water table height increase greater than 20 cm), or monthly in the case of a relatively constant lake level. The study took place between 2020 and 2022, monitoring 14 plots of 400 m2, placed at three different relative elevation classes with respect to the level of the lake (5 plots at low elevation, <193.475 m; 7 plots at intermediate elevation, 193.476-193.700 m; 2 plots at high elevation, >193.701 m). The results showed that P. australis growth is significantly influenced by the lake water level and thus the relative elevation of the stands, with lower lake levels leading to better growth, especially during the early phases of the growing season. On the other hand, prolonged flooding of shoots significantly impaired common reed growth. The study identifies two relevant relative elevation thresholds for winter mowing, a management practice that enhances reedbeds health. Mowing below 193.20 m elevation is considered risky, as no healthy reedbeds have been observed below this threshold. Mowing below an elevation of 193.50 m was defined as possibly risky, due to observed dieback in some areas as well as healthy reedbeds in other locations at the same or lower elevations. The research also discussed the potential impact of future changes in water level regulation, including the planned change in the spring regulation threshold (+1.50 m above the hydrometric zero in Sesto Calende). This is expected to result in a further rearrangement in lacustrine vegetation, with the growth optimum for P. australis becoming higher and an increase in clumping habit. In conclusion, this study provides valuable insights into the impact of water level regulation on the growth of P. australis in the Bolle di Magadino nature reserve. The research highlights the need for careful management of water level regulation to preserve the reedbed ecosystem and identifies relevant elevation thresholds for winter mowing to mitigate the risks of reed dieback. The findings can inform future management strategies for the Bolle di Magadino reserve and other similar ecosystems facing the challenges of artificial regulation of water levels.

Caddisflies (Trichoptera) of Protected Calcareous Fen Habitats: Assemblages, Environmental Drivers, Indicator Species, and Conservation Issues.

The caddisflies (Trichoptera) of calcareous fen habitats, in contrast to those of other peatland types, have been poorly researched. We thus conducted a two-year study in south-eastern Poland encompassing four types of such habitats-drained and undrained fens and water bodies (pools and ditches) located within the fens-in order to define trichopteran reference assemblages (PCoA), indicator species (IndVal analysis), and the drivers (both natural and those associated with landscape management, including area protection) responsible for caddisfly species distribution (CCA). The most important environmental driver was habitat persistence. Distance-based RDA analysis revealed a distinct pattern in the distribution of species with or without diapause along the persistence gradient. Environmental drivers associated with plants were also crucial for both fens and water bodies. The key factor influencing the caddisfly assemblages of pools and ditches was the use and management of the surrounding land, whereas in the fens, it was the level of area protection. Physical and chemical water parameters had no statistically significant impact on the assemblages. Some factors can be modified by humans (e.g., water level regulation, vegetation, and landscape management) to maintain healthy ecosystems for aquatic insects.

Development and evaluation of the first automated irrigation system for alternate wetting and drying technique in rice cultivation in Bangladesh

Rice stands as one of the most water-intensive crops in agriculture, demanding a substantial volume of water annually for cultivation in Bangladesh. To address this considerable water requirement, the International Rice Research Institute (IRRI) introduced the alternate wetting and drying (AWD) irrigation method. This approach necessitates consistent manual oversight to maintain the desired water levels in the field. In pursuit of reducing this manual effort, a study was conducted at Bangabandhu Sheikh Mujibur Rahman Agricultural University. The study aimed to develop an automated version of the AWD irrigation system, assess its impact on plant growth and yield-contributing factors, and investigate water use efficiency through using that automated system. The automated AWD system incorporated water level controllers, solenoid valves, and water level detection probes to regulate water levels in the paddy field. The experiment followed a Randomized Complete Block Design (RCBD) with three treatments: T1 (Conventional Irrigation - CI), T2 (AWD), and T3 (Automated Alternate Wetting and Drying - AAWD), each replicated four times. The findings indicated minimal variation in growth and development parameters of the rice plants between the CI and AWD treatments. Likewise, yield components demonstrated no significant differences among the various treatments. Notably, the treatment with automated alternate wetting and drying (AAWD), namely T3, displayed the highest water use efficiency (WUE) at 65.20 kg/ha/cm, while the lowest WUE of 52.56 kg/ha/cm was observed in the conventional irrigation (CI) treatment T1. The results underscore the clear advantage of adopting an automated AWD system, yielding a 20% reduction in irrigation water usage compared to the conventional approach. This transition also minimizes the need for labor-intensive interventions in the paddy fields of Bangladesh, illustrating the potential for more efficient and sustainable rice cultivation practices.

Impact of Hydrological Changes on Wetland Landscape Dynamics and Implications for Ecohydrological Restoration in Honghe National Nature Reserve, Northeast China

Marsh wetlands are significant ecosystems located between land and water bodies which can both protect species diversity and provide habitats. Changes in the hydrological situation of marsh wetlands as a result of climate change and human activities have led to the degradation of wetland landscapes. Taking the Honghe National Nature Reserve (HNNR) in Heilongjiang Province, China, as an example, this paper gathered information on the reserve’s wetland landscape before and after dam construction. The information was obtained using field survey data and a random forest classification method based on Landsat data powered by the Google Earth Engine (GEE) cloud platform. Then, on the basis of the water level data and the digital elevation model, the wetland landscape dynamics of HNNR under three water level conditions were simulated. The findings were as follows: (1) From 1998 to 2008, the area of marsh and meadow had a downward trend, while the area of forest, farmland and water showed a gradual and upward trend; a marked rise in the area of marsh and a continued rise in the area of forest, farmland and water, and a sharp decline in the area of meadow during 2008 to 2018 was observed. (2) There was a significant increase in the area of marsh under the 20 and 40 cm water level simulation scenarios, with a decrease in the number of patches, and an increase in the aggregation index with rising water levels; in contrast, when the water level rose to 60 cm, the area of marsh and the number of patches decreased, but the aggregation index continued to increase. (3) The correlation between wetland landscape and the water level was a nonlinear one. The area of marsh increased and then decreased with increasing water level, reaching a maximum at the 40 cm water level; therefore, 40 cm was the optimal water level regulation scenario. Hydrological processes are the most fundamental ecological processes in marsh wetlands. Understanding the scientific pattern of the spatial pattern characteristics of species as a function of water level environment is important for scientifically guiding the restoration of marsh vegetation.