Inland Waters Research Articles

National trends in the use of aquatic bioresources

The article examines the domestic trends in the use of aquatic biological resources for more than a century. Until the early 1950s, inland waters, primarily the Caspian and Azov Seas, played a key role. Total catch volumes did not exceed 2 million tons. Anthropogenic impact has led to global negative changes in the ecosystems of the south seas of our country. The fishery importance of inland reservoirs has significantly decreased. The active development of oceanic fishing in the 1960s and 1980s made it possible to increase the volume of extraction of aquatic biological resources to 10−11 million tons. Starting in 2018 Access to the use of aquatic biological resources largely depends on the involvement of domestic industrial companies in the construction of new ships at Russian shipyards. The proven reserves of even traditionally mined hydrobionts make it possible to fully ensure the fishing capacities of all vessels currently under construction and under design. The contribution of commercial fish farming to the total production of domestic fish products in the foreseeable future, apparently, will not exceed 10%.

Sustainable environmental governance as the implementation of state defense policy

Background: Land waters in urban areas often become a source of problems if they are not managed wisely and firmly. The threat and risk of danger, disease and even death always haunt the people who live on the banks of the river. Poverty and slum areas are negative effects of less than optimal land water management in urban areas. The Indonesian government has taken various steps to address this, but the lack of urban land for settlement is the reason why immigrants from other regions reside and reside in dangerous areas such as riverbanks. The compulsion to live minimally in urban areas is a burden for local governments in their efforts to increase welfare as well as improve sustainable urban governance. Many other cities in developed countries have made efforts to improve inland water areas to alleviate poverty and at the same time beautify the urban landscape. The experts agreed to hold discussions to formulate the best policy steps for sustainable urban governance in Indonesia. Methods: In the process of data analysis and decision making related to sustainable environmental governance as implementation of national defense policy, this article utilizes the Analytical Hierarchy Process (AHP) Data Processing Method. Finding: The results of in-depth discussions and interviews with experts in the field of environment, urban governance, economic experts and poverty management experts from various institutions such as the Ministry of Social Affairs, PUPR Ministry, Spatial Planning and City Planning Services, Academics and also the Military were processed using the Analytical Hierarchy Process (AHP). Conclusion: The best decision alternative will be a recommendation for policy makers regarding sustainable urban governance. Novelty/Originality of this study: This study is relevant to the Analytical Hierarchy Process (AHP) Method to formulate sustainable urban water management policies in Indonesia, involving various experts and related institutions to overcome poverty and improve urban landscapes. Therefore, this study can show policy recommendations based on various aspects and views.

Using the Potential Transformation of Dissolved Organic Matter to Understand Carbon Emissions from Inland Rivers.

Understanding the transformation of river dissolved organic matter (DOM) is important for assessing the emissions of greenhouse gases (GHGs) in inland waters. However, the relationships between the variations in DOM components and GHGs remain largely unknown. Here, parallel factor analysis (PARAFAC) was applied to investigate the DOM components in 46 inland rivers in China. We found that the GHG emissions in peri-urban rivers were 1.10-2.15 times greater than those in urban rivers. Microbial and environmental factors (e.g., living cell numbers, microbial activity and pH) explained more than 70% of the total variance in GHG emissions in rivers. DOM variations relationships between different components ware revealed based on compositional data principal component analysis (CoDA-PCA). Microbial-mediated DOM production and degradation were quantified, and the degradation levels in peri-urban rivers were 11.8-25.2% greater than those in urban rivers. Differences in carbon emission potential between urban and peri-urban rivers were related to DOM variances and transformations and were affected by water chemistry (e.g., NH4-N and As). This study clarifies the regulatory effects of DOM composition variations and transformations on GHG emissions, and enhances the understanding of the DOM biogeochemical cycle.

AQUAPONICS: LEADWAY TO A SUSTAINABLE BIOINTEGRATED SAFETY PRODUCTION OF PLANT AND FISH IN AQUACULTURE

Biosafety of food consumed at household level is the key to sustainable health, and part of such food consumed come from aquaculture as source of aquatic food. Mest of the aquatic food produced, such as plants and fishes, could be of a serious public health concern as a result of poor water quality used to raise them. However, aquaponics, as a new concept is undergoing awareness in Nigeria as a sustainable tool to drive organic aquaculture as biosafety tool for protein production to every household. Aquaponics system has been considered as bio-integrated tool to foster the growth of vegetable and rearing of fish together thus maintaining good water quality. This will secure biosafety of aquatic products for future generation. Therefore, the paper reviewed the principles of operation, various growing techniques and different grow media used in aquaponics system, plant pests and diseases control in aquaponics system, advantages of aquaponics culture system, plants and fishes grown in aquaponics system. Aquaponics, therefore, encourages proper land usage and water conservation efficiency, and its possible role as eco-friendly technique is appreciable in plants and fishes production in aquaculture.

Evaluating Lakes Boundary Change: A Case Study from Ward Number 26 of Pokhara Metropolitan City

Lakes are crucial for their multi-faceted services, including drinking water, irrigation, tourism, and more. Understanding their status, including area coverage, is important, and continuous monitoring is essential. Lakes can be monitored through various approaches, ranging from traditional ground-based surveys to advanced earth observation satellites. This study aimed to monitor several lakes in Ward Number 26 of Pokhara Metropolitan City, including Khaste, Neurini, and Gunde Lakes, using high-resolution cadastral maps, ground-based field surveys, and Sentinel-2 earth observation satellites. Additionally, focus group discussions and key informant interviews were conducted. Supervised land use and land cover classification and the Normalized Difference Water Index method were employed to determine the area of each lake in 2017 and 2021. The focus group discussions and key informant interviews investigated factors affecting lake dynamics. The study found that climate change, land use change, floods, water abstraction, and landslides are major factors contributing to changes in lake areas. The results showed that the satellite-derived lake boundaries were smaller than those indicated on the cadastral map. Ground surveys using total station equipment also revealed that Khaste Lake shrunk by 6122.73 m² (0.01 km²), Neurini Lake lost 474.95 m² (0.00005 km²), and Gunde Lake shrunk by 4226 m² (0.004 km²) due to encroachment. Although satellite images are useful for detecting large-scale changes, this study indicates that the lake boundary areas identified through satellite imagery were smaller than those delineated by cadastral maps and ground surveys. This suggests that remote sensing analysis alone is insufficient for studying small lake boundary changes and should be combined with ground-based surveys. Therefore, a combination of satellite images and ground-based surveys is recommended for accurately and comprehensively detecting changes in lake areas.

Evaluation of GPM IMERG Early, Late, and Final Run in Representing Extreme Rainfall Indices in Southwestern Iran

The growing concerns about floods have highlighted the need for accurate and detailed precipitation data as extreme precipitation occurrences can lead to catastrophic floods, resulting in significant economic losses and casualties. Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM IMERG) is a commonly used high-resolution gridded precipitation dataset and is recognized as trustworthy alternative sources of precipitation data. The aim of this study is to comprehensively evaluate the performance of GPM IMERG Early (IMERG-E), Late (IMERG-L), and Final Run (IMERG-F) in precipitation estimation and their capability in detecting extreme rainfall indices over southwestern Iran during 2001–2020. The Asfezari gridded precipitation data, which are developed using a dense of ground-based observation, were utilized as the reference dataset. The findings indicate that IMERG-F performs reasonably well in capturing many extreme precipitation events (defined by various indices). All three products showed a better performance in capturing fixed and non-threshold precipitation indices across the study region. The findings also revealed that both IMERG-E and IMERG-L have problems in rainfall estimation over elevated areas showing values of overestimations. Examining the effect of land cover type on the accuracy of the precipitation products suggests that both IMERG-E and IMERG-L show large and highly unrealistic overestimations over inland water bodies and permanent wetlands. The results of the current study highlight the potential of IMERG-F as a valuable source of data for precipitation monitoring in the region.

Shoreliner: A Sub-Pixel Coastal Waterline Extraction Pipeline for Multi-Spectral Satellite Optical Imagery

Beach morphology can be observed over large spatio-temporal scales, and future shoreline positions can be predicted and coastal risk indicators can be derived by measuring satellite-derived instantaneous waterlines. Long-term satellite missions, such as Landsat and Sentinel-2, provide decades of freely available, high-resolution optical measurement datasets, enabling large-scale data collection and relatively high-frequency monitoring of sandy beaches. Satellite-Derived Shoreline (SDS) extraction methods are emerging and are increasingly being applied over large spatio-temporal scales. SDS generally consists of two steps: a mathematical relationship is applied to obtain a ratio index or pixel classification by machine-learning algorithms, and the land/sea boundary is then determined by edge detection. Indexes from lake waterline detection, such as AWEI or NDWI, are often transferred towards the shore without taking into account that these indexes are inherently affected by wave breaking. This can be overcome by using pixel classification to filter the indices, but this comes at a computational cost. In this paper, we carry out a thorough evaluation of the relationship between scene-dependent variables and waterline extraction accuracy, as well as a robust and efficient thresholding method for coastal land–water classification that optimises the index to satellite radiometry. The method developed for sandy beaches combines a new purpose-built multispectral index (SCoWI) with a refinement method of Otsu’s threshold to derive sub-pixel waterline positions. Secondly, we present a waterline extraction pipeline, called Shoreliner, which combines the SCoWI index and the extraction steps to produce standardised outputs. Implemented on the CNES High Performance Cluster (HPC), Shoreliner has been quantitatively validated at Duck, NC, USA, using simultaneous Sentinel-2 acquisitions and in situ beach surveys over a 3-year period. Out of six dates that have a satellite acquisition and an in situ survey, five dates have a sub-pixel RMS error of less than 10 m. This sub-pixel performance of the extraction processing demonstrates the ability of the proposed SDS extraction method to extract reliable, instantaneous and stable waterlines. In addition, preliminary work demonstrates the transferability of the method, initially developed for Sentinel-2 Level1C imagery, to Landsat imagery. When evaluated at Duck on the same day, Sentinel-2 and Landsat imagery several minutes apart provide similar results for the detected waterline, within the method’s precision. Future work includes global validation using Landsat’s 40 years of data in combination with the higher resolution Sentinel-2 data at different locations around the world.

Effects of land use patterns on seasonal water quality in Chinese basins at multiple temporal and spatial scales

Diverse land use patterns exhibit varying effects on water quality across different seasons and spatial scales. However, current studies on the correlation between land use and water quality in single small-scale basins no longer meet the needs of regional coordinated development. Simultaneous comparative analysis of multiple large-scale basins can promote water environmental protection in different basins, but there is currently limited relevant research. In this study, the data from 86 sampling points across seven major river basins in China were analyzed. Multivariate statistical analysis and the redundancy analysis (RDA) were employed to investigate the influence of land use patterns on water quality at different seasons and spatial scales. The results indicated notable differences in water quality across various seasons and locations. Except for higher pH and permanganate index (COD) concentrations in the wet season in the Songhua River Basin and higher COD concentrations in the Pearl River Basin, the concentrations of all parameters in other basins are higher in the dry season. PH and COD exhibited considerable spatial variations within basins, while dissolved oxygen (DO) and ammonia nitrogen (NH4+-N) showed smaller variations. RDA showed that land use had a more pronounced effect on water quality during the dry season in the Yangtze, Liao and Pearl River Basins, while the impact was greater in the wet season in the four basins of the Yellow, Huai, Hai and Songhua River Basins. At the spatial scale, the 2000 m buffer zone had the most significant impact within the Yangtze, Hai and Liao River Basins, while the 1000 m buffer zone had the greatest impact in the Huai and Pearl River Basins. For the Yellow and Songhua River Basins, the buffer zone was 500 m during the wet season and 1000 m and 2000 m during the dry season, respectively. The research findings can offer a scientific foundation for the development of basin-specific land management policies and water quality protection measures in different basins from a multi-scale perspective.

Resilient riverine social–ecological systems: A new paradigm to meet global conservation targets

AbstractThe United Nations' Convention on Biological Diversity set forth the 30 × 30 target, an agenda for countries to protect at least 30% of their terrestrial, inland water, and coastal and marine areas by 2030. With <6 years to reach that goal, riverine conservation professionals are faced with the difficult decision of prioritizing which rivers or river segments should be conserved (protected and/or restored). While incorporating resilience into conservation planning is essential for enhancing, restoring, and maintaining the vital riverine ecosystem services (ES) most threatened by climate change and other environmental and human stresses, this paradigm is at odds with traditional conservation approaches that are either opportunistic or reactionary, where only unique and highly visible ecosystems have been prioritized. Barriers to implementing resilience‐based riverine conservation planning include: (1) difficulties in conceptualizing and quantifying resilience; (2) insufficient consideration of the social components of riverine systems; (3) the inapplicability of terrestrial‐only conservation models to aquatic systems; and (4) the traditional ad hoc and opportunistic approach to conservation. To overcome these barriers, we propose a resilience‐based riverine conservation framework that includes: (1) assessing riverine resilience using indicator frameworks; (2) considering rivers as dynamically coupled social–ecological systems; (3) explicitly incorporating terrestrial–aquatic network connectivity into conservation decision‐making; and (4) strategic systems planning using a novel resilience–conservation matrix as a tool. This framework has the potential to transform conservation practices around the globe to more effectively protect river systems and enhance their resilience to climate change and human development.This article is categorized under: Water and Life > Conservation, Management, and Awareness Science of Water > Water and Environmental Change Human Water > Water Governance

Simulation of tomato and corn growth using a modified intercropping model considering radiation interception in two-dimensional space and air temperature stress

Intercropping system has been widely applied in the agricultural production worldwide. However, the difference in agricultural productivity in tomato–corn intercropping system with different spatial arrangements has not been determined. Meanwhile, the existing intercropping models cannot precisely capture inter-species crop growth dynamics. Therefore, a 10-year (2010–2019) experimental field study was conducted in Hetao irrigation district, China, for the parameterization and evaluation of the model. The experiment data from the typical years (2018 and 2019) was adopted to analyze the crop growth dynamics in different hydrological years and different systems [two rows of tomato intercropping two rows of corn (IC2–2), four rows of tomato intercropping two rows of corn (IC4–2), sole corn (SC), and sole tomato (ST)]. Moreover, a modified intercropping model considering radiation interception in two-dimensional space and air temperature stress (MICG) was deduced. The results revealed that the MICG model can precisely simulate inter-species crop growth in tomato–corn intercropping system with different spatial arrangements. The mean relative error (MRE), normalized root mean square error (nRMSE), determination coefficient (R2), and percentage bias (PBIAS) of leaf area index (LAI) simulated by the MICG model in different spatial arrangements were 9.0 %, 7.8 %, 0.97, and –5.3 % for corn and 11.0 %, 7.8 %, 0.95, and 0.1 % for tomato, respectively. An apparent difference in the simulation accuracy was observed among different intercropping models in the rapid and senescence crop growth stages. The simulation accuracy of the MICG model was apparently higher than that of ICGw and ICG models. However, the MICG model still needs to be further improved considering its some limitations, e.g., the soil respiration and soil nitrogen transformation modules need be introduced in this model. Additionally, an apparent difference in crop growth dynamics in different spatial arrangements was observed, particularly in different hydrological years. The largest difference in crop growth dynamics in different spatial arrangements was observed in the middle crop growth stage (days after sowing [DAS] 20–100) in the wet year and in the late crop growth stage (DAS 101–140) in the dry year. In general, the highest aboveground biomass and yields of corn and tomato were observed in the IC2–2 and ST systems, respectively. However, the highest water use efficiency for corn (23.9) and tomato (268.7) was observed in the IC4–2 and ST systems, respectively. The agricultural production benefits in the IC4–2 system were better than in the IC2–2 system. Average land equivalent ratio and water equivalent ratio in both years increased by 0.8 % and 12.5 % in the IC4–2 system compared with those in the IC2–2 system, respectively. Overall, the IC4–2 system could be recommended as the most optimal spatial arrangement for the tomato–corn intercropping system.

Patterns and drivers of organic carbon in hydromorphic soils across inland aquatic-terrestrial ecotones at the global scale

The aquatic-terrestrial ecotones of inland waters, including rivers, lakes, and reservoirs, are subject to occasional, recurrent, or even permanent flooding and play a vital role in the carbon cycles of aquatic ecosystems. However, the patterns and drivers of soil organic carbon in aquatic-terrestrial ecosystems have not been clearly documented on a global scale. To address this knowledge gap, we constructed a database of organic carbon content of 1970 globally distributed aquatic-terrestrial ecotone soils and utilized a random forest model to measure the primary drivers at global scale. We found that the average soil organic carbon content was 26, 33, and 18 g kg−1, and the mean soil organic carbon stock was 24.95, 22.38, and 30.66 t ha−1 for the aquatic-terrestrial ecotones of rivers, lakes, and reservoirs, respectively. Notably, the soil organic carbon content in lake ecotones was significantly higher than in river and reservoir ecotones. However, reservoir ecotones stored the highest soil organic carbon compared to lake and river ecotones. The random forest model explained 52 %, 49 %, 58 %, and 28 % variations of soil organic carbon content across all sites, river, lake, and reservoir ecotones, respectively. Soil physiochemical properties exert more pronounced effects across all ecotone types than climate factors when predicting soil organic carbon in global aquatic-terrestrial ecotones. However, it is noteworthy that the primary drivers of soil organic carbon content vary according to ecotone type. For river and lake ecotones, nitrogen content emerges as the dominant factor regulating organic carbon content. Conversely, in reservoir ecotones, pH stands out as the primary driver for soil organic carbon content. Beyond nitrogen content and pH, the composition of silt and clay also proves pivotal in predicting soil organic carbon in aquatic-terrestrial ecotones. These findings underscore the critical determinants of soil organic carbon accumulation in global inland aquatic-terrestrial ecotones.

Enhanced water level monitoring for small and complex inland water bodies using multi-satellite remote sensing

Water level monitoring in lakes and reservoirs is essential for effective water resource management, especially in remote areas where traditional ground sensors are costly and difficult to maintain. Remote sensing offers an alternative, but improving the quality, resolution, and accuracy of satellite data remains crucial. This paper introduces MoRLa (Measurement of Reservoir Level from Altimetry), a data filtering procedure designed to enhance satellite altimetry retrievals. MoRLa increases the acceptance of satellite observations and improves the quality of water level estimates by using physical characteristics of water bodies to exclude non-conforming measurements. Unlike previous studies with static masks, MoRLa employs a dynamic filter adaptable to actual water levels at specific times. Tested on reservoirs in the Korean Peninsula, including the Hwang-Gang dam, MoRLa shows significant improvements in water level measurements using Cryosat-2, ICESat-2, and Sentinel-3A and B satellites.

A multidisciplinary approach using hydrogeochemistry, δ15NNO3 isotopes, land use, and statistical tools in evaluating nitrate pollution sources and biochemical processes in Costa Rican volcanic aquifers

Nitrate pollution threatens the Barva and Colima multi-aquifer system, the primary drinking water source in the Greater Metropolitan Area of Costa Rica. In addressing nitrate contamination dynamics, this study proposes an integrated approach by combining multivariate statistical analyses, hydrochemical parameters, sewage discharge, and regional land-use and land-cover patterns to assess the extent and degree of contamination, dominant biogeochemical processes, and refine the interpretation of nitrate sources previously derived solely from δ15NNO3 information. Over seven years (2015–2022), 714 groundwater samples from 43 sites were analyzed for nitrate and major ions, including two sampling campaigns for dissolved organic and inorganic carbon, nitrite, ammonium, FeTotal, MnTotal, and δ15NNO3 analyses. The findings presented elevated nitrate concentrations in urban and agricultural/urban areas, surpassing the Maximum Concentration Levels on several occasions, and oxidizing conditions favoring mineralization and nitrification processes in unconfined Barva and locally confined Upper Colima/Lower Colima aquifers. Similar nitrate contents and spatial patterns in agricultural and urban zones in the shallow Barva aquifer suggest comparable contributions from nitrogen fertilizers and urban wastewaters despite the gradual increase in urban land cover and the reduction of agricultural areas. Isotopic analyses and dissolved organic carbon (DOC) indicate a shift in nitrate sources from agricultural to urban areas in both Barva and Colima aquifers. Principal Component and Hierarchical Cluster Analyses link land use, nitrate sources, and water quality. Three distinct sample clusters aligned with forest/grassland, agricultural/urban, and urban land use, emphasizing the impact of anthropogenic activities on groundwater quality, even in the deeper Colima aquifers. The study challenges nitrate isotope mixing models, enhancing accuracy in identifying pollution sources and assessing the spatial extent of contamination by incorporating DOC and other hydrochemical parameters. Similar outcomes, with and without the use of nitrate isotopes, reinforce the usefulness of the integrated approach, providing a practical and cost-effective alternative.

How Useful Are Moderate Resolution Imaging Spectroradiometer Observations for Inland Water Temperature Monitoring and Warming Trend Assessment in Temperate Lakes in Poland?

How Useful Are Moderate Resolution Imaging Spectroradiometer Observations for Inland Water Temperature Monitoring and Warming Trend Assessment in Temperate Lakes in Poland?

Improved water management can increase food self-sufficiency in urban foodsheds of Sub-Saharan Africa

Rising urban food demand in Sub-Saharan Africa will put pressure on local resource boundaries, such as the available land area and water resources. In assessing the extent to which urban centres can source from nearby areas in future, earlier analysis has concentrated on agronomic measures, aiming at yield gap closure. Here, we address the potential of local water conservation measures to help achieve food self-sufficiency in Sub-Saharan Africa by 2061–2070, along the concept of urban ‘foodsheds’, matching crop-based food supply and demand in the surroundings of large cities for all major food groups. We find that ambitious but plausible levels of water conservation, primarily raising productivity on rainfed lands, have the potential to increase overall food production by 12% and food self-sufficiency levels in all major foodsheds to over 75%, with the region as a whole becoming self-sufficient. The increase in production could limit the projected required expansion of agricultural land use by more than 25%, which has important implications for biodiversity, land use-related conflicts and carbon sequestration.

Analysis of Urban Form Dynamics in The Suburbs of Surakarta City 2013-2023

Urban Form has become necessary for city planning management to see the sustainability of a city. A better understanding of different urban forms is imperative to facilitate the evolution of cities towards a more sustainable urban development trajectory in the future. The study aims to analyze the dynamics of urban form and the changes in land cover within the peri-urban area of Surakarta City, which is directly influenced by the development of Surakarta City. The analysis was conducted from a landscape ecology perspective, employing a spatial metrics approach at the landscape level to assess the dynamics of urban form using quantitative descriptive, including a spatial approach. A similar approach was adopted at the class level in order to examine the dynamics of land cover changes. The results of the image analysis were validated using the Kappa index, yielding an image accuracy level of 0.86 (86%). The results of this study show that the urban form in the peri-urban area of Surakarta City tends to move towards a compact urban form. Meanwhile, each land cover, vegetation, and water body become increasingly fragmented, with areas becoming narrower as time passes. Built-up and agricultural land are becoming more compact and concentrated along with development. In conclusion, the dynamics of urban form in the peri-urban area of Surakarta City tends to lead to compact urban form.

AN AUTOMATED CROP MONITORING AND IRRIGATION SYSTEM WITH PREDICTIVE ANALYSIS

Background: The rising global population and decreasing agricultural land challenge the food supply, worsened by land degradation and water scarcity. Using IoT solutions, precision farming offers promise for addressing these issues by enhancing productivity, profitability, and environmental sustainability. The paper proposes an IoT-based automated monitoring and irrigation system with predictive analysis as a solution. Aims: To develop an IoT-based irrigation model with cloud computing, a mobile app for remote monitoring and irrigation control, and a predictive analysis method for forecasting weather conditions. Methods: IoT sensors are connected to a node MCU, and they monitor real-time temperature, humidity, and soil moisture. A water pump adjusts irrigation accordingly. Data is sent to ThingSpeak for visualization and Firebase for storage and is accessible via a mobile app. Predictive analysis combines sensor and historical weather data using the Random Forest algorithm to optimize irrigation. This determines the ideal irrigation frequency, duration, and timing based on predicted temperature and soil moisture levels, ensuring optimal soil moisture for plant growth. Results: The system exhibited encouraging outcomes. It displayed transformative potential by harnessing IoT, cloud computing, and predictive analytics. Offering precise soil moisture monitoring, instant data access, and tailored advice, the system can elevate crop management, streamline water consumption, and boost productivity among Indian farmers. Discussion: The automated crop monitoring and irrigation system has transformative potential in farming. Some future scope and enhancements may include broadening crop compatibility, integrating satellite data, enhancing pest monitoring, improving connectivity, enriching the mobile app, scaling up through partnerships, and refining the predictive models. Conclusions: The IoT-driven crop monitoring system revolutionizes Indian agriculture by optimizing irrigation and integrating weather forecasts. With mobile app enhancements and future improvements, it promises sustainable farming and empowerment for farmers.

Effects of Salinity and Ca2+: Mg2+ Ratio on Growth Performance and Survival of Penaeus vannamei (Boone, 1931) Reared in Inland Saline Ground Water

Background: A 60-day experiment was conducted to evaluate the combined effect of salinity and Ca2+: Mg2+ ratio on the growth performance and survival of Penaeus vannamei reared in inland saline ground water (ISGW) at ICAR-Central Institute of Fisheries Education (CIFE), Rohtak Centre, Haryana, India. Methods: The study used three different salinities viz. T1 (5 ppt), T2 (10 ppt) and T3 (15 ppt) with four different level of Ca2+: Mg2+ rations such as 1:1, 1:2, 1:3 and 1:4. juveniles of P. vannamei with average body weight of 3.70±0.02 g, were stocked in 100 L capacity of circular plastic tanks. Total 36 experimental tanks were used as experimental unit. The stocking densities were 20 animals in each tank and each treatment were kept in triplicate followed the factorial design (3×4). Result: P. vannamei expressed better growth performance in terms of SGR, FCR, FER and PER in the T2 and T3 fortified Ca2+: Mg2+ ratio of 1:3. Lowest growth observed in T1 fortified with Ca2+: Mg2+ ratio 1:1. The study found 100% survival in T2 and T3 fortified with Ca2+: Mg2+ ratio of 1:3 compared with other treatment groups, which showed less than 80% survival. Based on the results, it can be concluded that the better growth performance, survival of P. vannamei observed in 10 and 15 ppt salinities of ISGW fortified with 1:3 ratio of Ca2+: Mg2+.

Advances in Vertical Farming: Opportunities and Challenges

Vertical farming has emerged as a promising solution to address the challenges of food security, sustainability, and urbanization in the 21st century. This innovative approach to agriculture involves growing crops in vertically stacked layers within controlled environments, optimizing space, resources, and yields. Vertical farming represents a significant innovation in agriculture, designed to meet the challenges of urban food production with enhanced efficiency and sustainability. This study examines recent technological advancements in vertical farming, emphasizing methods such as automation. By growing crops in vertically stacked layers within controlled environments, vertical farming maximizes space utilization and minimizes resource consumption. The results indicate substantial improvements in crop yields and quality, along with reduced water and pesticide use. Additionally, the proximity of vertical farms to urban centers shortens supply chains, lowering transportation costs and carbon emissions. The discussion highlights the economic benefits, including year-round production and premium pricing for pesticide-free produce, alongside the challenges of high initial investments and energy demands. The environmental impacts are also considered, noting significant reductions in land use and water consumption compared to traditional farming. This review underscores the potential of vertical farming to contribute to global food security and sustainable urban development, while addressing the need for further research and collaboration to overcome existing barriers. The findings suggest that continued innovation and supportive policies are crucial for the widespread adoption and success of vertical farming practices.

Analysis of Land Water Balance in Various Rainfall Conditions and Its Utilization to Determine Planting Patterns of Food Crops in the Eastern Part of Seram District of Seram Island

Soil water balance calculation is one of the methods used to estimate the dynamics of soil water content during plant growth. This study aims to describe rainfall conditions and analyze soil water balance as well as determine the growing season and composition of food crop combination patterns based on the available growing season in East Seram Island. This research uses rainfall data for 30 years of observation period 1992-2021 from Geser Meteorological Station (Data analysis with the following stages: (i) rainfall analysis (ii) calculation of average rainfall (iii) determination of rainfall with a 75% chance (iv) calculation of soil water balance using the Thornthwaite and Mather method (v) determination of the growing season and cropping pattern. The results showed that the average rainfall in East Seram was 2,194 mm/year with a water deficit (D) occurring in October and November, then the rainfall had a 75% chance of being exceeded at 1,439 mm/year with a water deficit of 228 mm/year which lasted for eight months, namely August - March. The growing season under normal rainfall conditions was available throughout the year, while under high rainfall conditions, a 75% chance of the growing season was available for five months, namely May and October. The cropping patterns and crop combinations used were monoculture, polyculture, and intercropping with combinations of cassava, maize, sweet potato, groundnut, mung bean, cassava-corn, cassava-peanuts/green beans, maize-peanuts, cassava-corn-peanuts/green beans, cassava-corn-horticultural crops.