Optimize Water Use Research Articles

Optimizing water use efficiency in greenhouse cucumber cultivation: A comparative study of intelligent irrigation systems.

This study investigated the use of an intelligent irrigation system for greenhouse cucumber cultivation, aiming to manage water consumption efficiently. During the initial phase, irrigation was tested at four levels: 80%, 90%, and 100% of Field Capacity (FC), and Conventional Flood Irrigation (CFI). Data on environmental conditions and water usage were meticulously recorded. Optimal yields and crop quality (measured by size and firmness) were achieved at CFI and 100% FC, with CFI consuming the most water (0.148 m3/m2) Consequently, 100% FC was identified as the best practice, informing the intelligent system's calibration in the subsequent phase. This adjustment resulted in reduced water consumption and a 15.6% improvement in Water Use Efficiency (WUE) over CFI. Additionally, by examining the product performance and the color characteristics, chlorophyll content, and photosynthesis of the leaves, it was observed that the quality and optimal water supply and the product performance were maintained in the smart irrigation system. The study concludes that, considering long-term outcomes, the intelligent irrigation system is preferable to CFI, offering significant water savings and enhanced WUE without compromising crop quality.

Water Use Efficiency in Rice Under Alternative Wetting and Drying Technique Using Energy Balance Model with UAV Information and AquaCrop in Lambayeque, Peru

In the context of global warming, rising air temperatures are increasing evapotranspiration (ETc) in all agricultural crops, including rice, a staple food worldwide. Simultaneously, the occurrence of droughts is reducing water availability, affecting traditional irrigation methods for rice cultivation (flood irrigation). The objective of this study was to determine ETc (water use) and yield performance in rice crop under different irrigation regimes: treatments with continuous flood irrigation (CF) and irrigations with alternating wetting and drying (AWD5, AWD10, and AWD20) in an experimental area in INIA–Vista Florida. Water balance, rice physiological data, and yield were measured in the field, and local weather data and thermal and multispectral images were collected with a meteorological station and a UAV (a total of 13 flights). ETc values obtained by applying the METRICTM (Mapping Evapotranspiration at High Resolution using Internalized Calibration) energy balance model ranged from 2.4 to 8.9 mm d−1 for the AWD and CF irrigation regimes. In addition, ETc was estimated by a water balance using the AquaCrop model, previously parameterized with RGB image data and field weather data, soil, irrigation water, and crops, obtaining values between 4.3 and 7.1 mm d−1 for the AWD and CF irrigation regimes. The results indicated that AWD irrigation allows for water savings of 27 to 28%, although it entails a yield reduction of from 2 to 15%, which translates into an increase in water use efficiency (WUE) of from 18 to 36%, allowing for optimizing water use and improving irrigation management.

A Comprehensive Overview on Sustainable Vegetable Gardening: Eco-friendly Approaches to Home Grown Production

Sustainable vegetable gardening is an eco-friendly practice that integrates organic farming principles, resource conservation, and biodiversity promotion to produce nutritious, chemical-free food while minimizing environmental impact. This approach emphasizes soil health through the use of organic amendments, crop rotation, composting, and mulching to improve fertility and water retention. Water conservation techniques, such as drip irrigation and rainwater harvesting, are employed to optimize water use, especially in arid regions. Pest and disease management relies on integrated pest management (IPM), biological controls, companion planting, and the use of organic pesticides to reduce chemical input while maintaining crop health. Sustainable homegrown produce has been shown to have superior nutritional content compared to commercially grown produce, and the avoidance of synthetic chemicals reduces the risk of pesticide residue exposure. Gardening fosters healthy eating habits by connecting individuals to their food sources, encouraging the consumption of fresh, unprocessed vegetables, and contributing to food security. The mental and physical health benefits of gardening, including reduced stress, increased physical activity, and improved mental well-being, further highlight its holistic value. However, challenges such as the initial setup costs, time investment, pest management, and knowledge gaps can hinder widespread adoption. Addressing these challenges requires greater access to resources, educational initiatives, and the development of climate-resilient practices tailored to specific regions. Future trends in sustainable gardening include the adoption of technological innovations, such as smart irrigation systems, automation, and vertical farming, which offer scalable solutions for urban and small-scale gardeners. The COVID-19 pandemic has underscored the importance of resilient, local food systems, and sustainable gardening is poised to play a critical role in addressing future food security concerns.

Preference for water sources and agricultural utilisation among rural households: a case of Akoko district of Ondo State, Nigeria

The increasing challenge of freshwater scarcity amid rising demand and diminishing availability has led to a critical issue threatening sustainable development, especially in rural areas of developing countries like Nigeria. Despite the abundance of studies on rural water use, gaps remain in understanding the interplay between socio-economic factors, and agricultural practices in shaping these preferences and utilisation. Thus, the study investigates the preference for water sources and their utilisation in agricultural activities among rural households in the Akoko district of Ondo State, Nigeria. Cross-sectional data from randomly sampled 240 rural households were collected with the aid of a questionnaire, and employed for the data analysis. Descriptive statistics, logit, and multinomial regressions were used for the data analysis. The findings revealed a dominant preference for rainwater and well water. Factors such as access to safe water sources, time spent, extension service, technology adoption, soil type, experience, and proximity to water sources significantly influence the choice of water source utilization in the area using multinomial logit regression. Again, the results from logit regression revealed that water source, technology adoption, soil type, fish farming, crop farming, farming experience, and distance to water sources significantly affect the use of water for agricultural purposes. Therefore, the policy should enhance water access, consider soil characteristics in agricultural planning, and facilitate knowledge transfer among farmers for optimal water use, recognizing the symbiotic relationship between water access and agricultural sustainability.

Can agricultural water rights trading promote intensive and economical utilization of water resources in China based on the difference-in-differences model?

IntroductionImproving the level of intensive and economical utilization of water resources is an important step towards water and food security.MethodsBased on China’s provincial panel data from 2015 to 2021, this study uses a difference-in-differences (DID) model to examine the effect of agricultural water rights trading on intensive and economical utilization of water resources.ResultsThe results show that agricultural water rights trading can significantly promote an intensive and economical utilization of water resources at the 1% level, and the results remain valid even after a series of robustness tests. Further analysis indicates that agricultural water rights trading can promote better utilization of water resources by significantly reducing agricultural water consumption at the 1% level and reducing the proportion of agricultural water consumption at the 5% level to optimize water use structure. Moreover, in regions with scarce water resources, strong water resource constraints, more farmland water conservancy projects, and greater economic development, the promoting effect of agricultural water rights trading on the intensive and economical use of water resources is more significant.DiscussionThis study provides evidence of the impact of China’s agricultural water rights trading policy and offers new ideas and experiences to improve China’s water resource utilization efficiency. The contributions of this work are mainly threefold. First, this paper clearly distinguishes the intensive conservation of water resources, presents an evaluation index system, and complements the existing literature on measuring the intensive and economical utilization of water resources. Second, the path of agricultural water rights trading is analyzed to improve the level of intensive and economical utilization of water resources, thus enriching related research on transmission mechanisms. Third, the heterogeneity of the influence of different regional conditions on the level of intensive and economical utilization of water resources is discussed to improve relevant policies.

Impact of Stage-Specific Irrigation on the Growth and Yield of Wheat

Stage-specific irrigation is essential for ensuring optimal water use at critical growth stages in wheat (Triticum aestivum), leading to increased yield and improved grain quality. Therefore, determining an appropriate irrigation schedule for wheat is crucial for enhancing productivity. Keeping this view in mind, an experiment was conducted at the farmer’s fields of Dinajpur Sadar Upazila, Dinajpur, Bangladesh from November 2020 to April 2021, aimed to evaluate the impact of irrigation schedules on the growth and yield of wheat (BARI Gom-33). A randomized complete block design (RCBD) with seven treatments and three replications was implemented. Treatments included varying irrigation timings: T0 (no irrigation), T1 (one irrigation at maximum tillering), T2 (one irrigation at booting), T3 (one irrigation at heading), T4 (two irrigations at maximum tillering and heading), T5 (milking dough), and T6(two irrigations at booting and milking dough). Key metrics assessed included plant height, leaf count, tiller number, dry matter, growth stages, grain number, thousand grain weight, and overall yield at different days’ intervals. Results indicated that irrigated treatments (T1-T6) significantly improved the parameters for growth and yield compared to the control (T0). Notably, T4, with two irrigations, yielded the highest grain production at 5.20 t/ha, followed closely by T6. These findings highlight the significance of proper irrigation scheduling for optimizing wheat yield, indicating that applying two irrigations at the maximum tillering and heading stages can significantly enhance agricultural productivity.

A Holistic Irrigation Advisory Policy Scheme by the Hellenic Agricultural Organization: An Example of a Successful Implementation in Crete, Greece

The aim of this communication article is to present a successful irrigation advisory scheme on the island of Crete (Greece) provided by the Hellenic Agricultural Organization (ELGO DIMITRA), which is well adapted to the different needs of farmers and water management agencies. The motivation to create this advisory scheme stems from the need to save water resources while ensuring optimal production in a region like Crete where droughts seem to occur more and more frequently in recent years. This scheme/approach has three different levels of implementation (components) depending on the spatial level and end-users’ needs. The first level concerns the weekly irrigation bulletins in the main agricultural areas of the island with the aim of informing farmers and local water managers about crop irrigation needs. The second level concerns an innovative digital web-based platform for the precise determination of the irrigation needs of Crete’s crops at a parcel level as well as optimal adaptation strategies in the context of climate change. In this platform, important features such as real-time meteorological information, spatial data on the cultivation type of parcels, validated algorithms for calculating crop irrigation needs, an accurate soil texture map derived from satellite images, and appropriate agronomic practices to conserve water based on cultivation and the geomorphology of a farm are considered. The third level of the proposed management approach includes an open-source Internet of Things (IoT) intelligent irrigation system for optimal individual parcel irrigation scheduling. This IoT system includes soil moisture and atmospheric sensors installed on the field, as well as the corresponding laboratory soil hydraulic characterization service. This third-level advisory approach provides farmers with specialized information on the automated irrigation system and optimization of irrigation water use. All the above irrigation advisory approaches have been implemented and evaluated by end-users with a very high degree of satisfaction in terms of effectiveness and usability.

IMPLEMENTASI SISTEM MONITORING AIR DENGANSENSOR ULTRASONIK HC-SR04 DAN WATER FLOW DI ASONE HIDROPONIK BERBASIS INTERNET OF THINGS (IoT) MENGGUNAKAN ENERGI PANEL SURYA(PLTS)

The cultivation system using hydroponics is now widely popular among the community because it does not require large areas of land. Using the hydroponic system results in faster and optimal harvests. However, the busy activities of urban communities often cause them to fail in implementing it due to constraints in controlling and monitoring hydroponic plants. Additionally, PLN electricity is essential for operating the water pump, and the electricity load and tariff increases, along with sudden blackouts, significantly impact business actors. To address this problem, this research creates an Internet of Things (IoT)-based water monitoring system for ACONE Hydroponics partners with solar panel (PLTS) energy sources as an alternative energy in the event of a sudden PLN power outage. The sensors used in this system include the HCR-04 ultrasonic sensor to monitor water availability and the water flow sensor to measure water flow (discharge). Sensor data is processed by the ESP32 microcontroller and sent to the Blynk cloud platform via an internet connection and displayed on an LCD. System testing shows that the system can send sensor data to the cloud platform stably and in real-time. Data visualization on the cloud platform is easy to understand and helps hydroponic owners monitor water conditions in hydroponic systems. This water monitoring system can help users optimize water use in hydroponic systems.

REVIEW AND COMPARATIVE STUDY OF HYDROLOGICAL MODELS FOR RAINFALL-RUNOFF MODELLING

Water is considered as an important resources for human existence on the earth. In order to simulate or optimized hydrological data for various water resources management, several hydrological models are very useful to attain this aim for water resources management and as a decision support tools. A rainfall-runoff model is a quantitative prototype explaining the rainfall-runoff interactions at basin scale. The hydrological models have peculiarities in terms of capabilities for various water resources management. This paper tends to reviewed over fifty (50) papers that are peculiar to hydrological models as applicable to rainfall-runoff modeling. It involved evaluating and comparing different hydrological models used in simulating rainfall process converting into surface runoff for water use efficiency. Several runoff models such as Hydrologic Engineering Center - Hydrologic Modeling System (HEC-HMS), Soil and Water Assessment Tool (SWAT), Precipitation-Runoff Modeling System (PRMS), Variable Infiltration Capacity model (VIC), LISt-based Erosion Model (LISEM), MIKE Surface Water - Groundwater Hydrology (MIKE SHE) and Runoff Prophet were critically assessed. Rainfall-runoff models are globally utilized for different applications to enhance water use efficiency across different sectors. However, types of hydrological models by examining various hydrological models, model accuracy by evaluating the accuracy and reliability of each model in predicting runoff from rainfall data, scope of applications by determining the adequacy of the models for numerous geographical regions and climatic circumstances, complexity and usability by assessing the complexity of the models, their data requirements, ease of use and computational efficiency, also the models advantages and limitations in capturing the dynamics of the rainfall-runoff process were critically assessed. This was to aid modeling objectives. It was inferred that HEC-HMS is widely applied for modelling precipitation-runoff processes in watersheds of various sizes, aiding in flood forecasting, reservoir operation, and water management for agricultural and urban water use efficiency. SWAT is used for assessing the impact of land management practices (e.g., crop rotation, irrigation, land use changes) on water resources, including runoff generation and water quality, thus optimizing water use efficiency in agriculture. PRMS is applied to model the transport of water via complex hydrological systems, aiding in watershed management and water use efficiency assessments. In conclusion, this comparative review seeks to guide water scientists, the users of hydrological models and hydrological engineers in selecting the most suitable models for their specific modelling needs for sustainable water resources management.

Deep Vertical Rotary Tillage: A Sustainable Agricultural Practice to Improve Soil Quality and Crop Yields in China

Deep vertical rotary tillage (DVRT) is an innovative soil tillage technology that has been widely adopted in China and shown significant potential in enhancing soil quality, optimizing water use efficiency, and increasing crop yields across diverse ecological and agronomic conditions. DVRT utilizes a vertical spiral drill bit for deep plowing, which preserves soil structure, reduces soil compaction, and improves water retention, making it particularly effective in regions facing climatic challenges such as drought. This review synthesizes the effects of DVRT on soil’s physical and chemical properties, crop root systems, photosynthesis, and water use efficiency, demonstrating its advantages in promoting robust root development and improving nutrient utilization. Although the technology has been applied successfully across various crops and regions, its nationwide adoption remains limited. This paper emphasizes the need for further research to refine the theoretical framework of DVRT and develop tailored strategies for different local conditions. Additionally, integrating DVRT with other agronomic practices and advancing machinery design, supported by policy measures, is essential for maximizing its benefits. In conclusion, DVRT presents a promising approach for sustainable agriculture in China, contributing to improved soil quality, increased crop yields, and enhanced food security.

Analysis of the Status of Irrigation Management in North Carolina

Farmers in North Carolina are turning to irrigation to reduce the impacts of droughts and rainfall variability on agricultural production. Droughts, rainfall variability, and the increasing demand for food, feed, fiber, and fuel necessitate the urgent need to provide North Carolina farmers with tools to improve irrigation management and maximize water productivity. This is only possible by understanding the current status of irrigated agriculture in the state and investigating its potential weaknesses and opportunities. Thus, the objective of this study was to perform a comprehensive analysis of the current state of irrigation management in North Carolina based on 15-year data from the Irrigation and Water Management Survey by the United States Department of Agriculture–National Agricultural Statistics Service (USDA-NASS). The results indicated a reduction in irrigation acres in the state. Also, most farms in the state have shifted to efficient sprinkler irrigation systems from gravity-fed surface irrigation systems. However, many farms in North Carolina still rely on traditional irrigation scheduling methods, such as examining crop conditions and the feel of soil in deciding when to irrigate. Hence, there are opportunities for enhancing the adoption of advanced technologies like soil moisture sensors and weather data to optimize irrigation schedules for improving water efficiency and crop production. Precision techniques and data-based solutions empower farmers to make informed, real-time decisions, optimizing water use and resource allocation to match the changing environmental conditions. The insights from this study provide valuable information for policymakers, extension services, and farmers to make informed decisions to optimize agricultural productivity and conserve water resources.

Cultivating sustainability: a multi-assessment of groundwater quality and irrigation suitability in the arid agricultural district of Dzira (Ksour Mountains, Algeria).

Groundwater serves a range of essential functions such as supplying drinking water, facilitating agricultural practices, and supporting industrial processes. This study examines with multiple methods the quality of groundwater in the agricultural region of Dzira, Algeria. By collecting 38 groundwater samples of different wells and boreholes, valuable awareness of the aptness of groundwater for irrigation in this arid landscape was gained. Most wells met Food and Agriculture Organization (FAO) criteria for the total dissolved solids (TDS) and the potential of hydrogen pH, but some areas had higher mineral content and electrical conductivity. Results show significant TDS variations, with 10.81% of wells exceeding limits and acceptable pH levels. Elevated EC values in 67.57% of wells show high salinity, affecting soil and plant growth. Major ions such as Mg2+ and SO4- exceeded FAO standards in 43.24% and 64.86% of wells, respectively, highlighting substantial mineral content in the groundwater. Suitability indices reveal that most wells pose low sodium hazards and are generally suitable for irrigation, though some areas face moderate to high restrictions. The irrigation water quality index (IWQI) ranged from 45.36 to 96.30, averaging 80.77, with 54.04% classified as "low restriction," suitable for sandy soils with good permeability but requiring caution on salt-sensitive soils. Hydrogeochemical analysis using principal component analysis (PCA) and hierarchical cluster analysis (HCA) identifies rapid evaporite dissolution from Triassic saline formations, with a correlation matrix showing associations between TDS and Ca2⁺, Mg2⁺, Na⁺, Cl⁻, and SO₄2⁻. This mineralization is likely from gypsum and halite. Zoning maps based on IWQI and other parameters depicted spatial variations in groundwater quality, guiding effective irrigation management strategies. Overall, the study underscores the importance of comprehensive water quality assessment for sustainable agriculture and emphasizes the need for targeted interventions to mitigate potential challenges associated with soil salinity and sodicity. Therefore, these findings can be useful to decision-makers and stakeholders in order to optimize water use and protect this vital resource.

Optimal use of irrigation water and fertilizer for strawberry based on weighing production benefits and soil environment

Optimal use of irrigation water and fertilizer for strawberry based on weighing production benefits and soil environment

Harnessing rain hose technology for water-saving sustainable irrigation and enhancing blackgram productivity in garden land

Blackgram, a protein-rich pulse crop (24%), is crucial for combating food insecurity, particularly in malnourished and economically weak countries. Enhancing blackgram production requires improved, input-saving management practices. Given the challenges of climate change and population growth, efficient water management is vital for increasing pulse productivity and water use efficiency with minimal investment. This study aimed to identify cost-effective irrigation methods to optimise blackgram yields. Experiments were conducted at the National Pulses Research Centre in Vamban, Pudukkottai, and the Agricultural College and Research Institute in Kumulur, Tiruchirappalli, during the kharif season of 2021 and 2022. The study compared different treatments of irrigation methods, such as check basin, raised bed, drip, sprinkler and rain hose irrigation. Results showed that the rain hose system maintained the highest soil moisture (23.93% at 10 cm depth and 19.71% at 20 cm depth). Even though drip irrigation resulted in a higher seed yield (1363 kg ha−1), the rain hose system proved to be more cost-effective, saving 27.09% in costs and achieving a 15.23% higher benefit–cost ratio. These findings suggest that the rain hose method, combined with current agronomic practices, is a viable low-cost technique for sustainable blackgram cultivation, optimising water use and maximising profits. This research provides valuable insights into water-saving irrigation methods for pulse crops.

Environmental factors affecting tomato growth for industrial processing in the Brazilian Savannah of Goiás State

This study investigates the meteorological variables exerting the most significant influence on the growth and productivity of four tomato hybrids cultivated for industrial processing in the Brazilian Savannah of Goiás State. Data on morphological and meteorological variables were collected in five locations (Hidrolândia, Itaberaí, Palmeiras de Goiás, Piracanjuba, and Silvânia) during the year 2020. Morphological characteristics assessed included plant height, number of branches, and leaf area index (LAI). Meteorological variables considered were average air temperature, global solar irradiance, thermal sum, and soil water availability. Pearson correlations, canonical correlations, and multivariate Stepwise regression were employed to analyze the relationships between morphological and meteorological variables. The study revealed that soil water availability significantly impacts tomato crop development, indicating the need for improved irrigation management. Adequate irrigation management contributed to an 86.1% increase in plant height and a 79.7% boost in leaf area index, while average air temperature influenced a 34% increase in the number of branches. In conclusion, proper irrigation management is crucial for enhancing tomato crop growth and development and optimizing water use.

Bio-economic analysis of irrigation schedules considering shallow groundwater: lessons from South Africa

Due to the pressure on South Africa’s irrigated agriculture to improve efficiency and optimal water use, irrigators must consider alternative water sources, such as root-accessible shallow groundwater tables, to supply the crop evapotranspiration requirement. Devising irrigation scheduling strategies that will optimize conjunctive water use is difficult because the contribution of shallow groundwater tables is not directly observed and is a function of irrigation management decisions; as a result, very few irrigators use these strategies. This paper aims to evaluate the profitability of using shallow groundwater tables as a source of irrigation water to satisfy crop evapotranspiration requirements. A bio-economic simulation model consisting of the soil–water–atmosphere–plant model and an economic accounting module was developed to calculate the profitability of conjunctive irrigation practices under different states of nature. The bio-economic simulation model was linked to a differential evolutionary algorithm to optimize the irrigation scheduling decisions. The results showed that irrigators could substantially increase profitability and water use efficiency if they consider the shallow groundwater table in their irrigation decision. About 51% of crop evapotranspiration could originate from shallow groundwater tables, reducing the irrigation requirements substantially without impacting crop yields. Sequential adaptive irrigation decision-making does not improve the bio-economic indicators much since using the shallow groundwater table mitigates the risk of undersupplying water. Therefore, conjunctive water use strategies using shallow groundwater tables economically benefit irrigators. However, a complex interplay exists between irrigation adjustments, crop yields and economic performance in different states, emphasizing the careful consideration of context-specific factors in irrigation management decisions.

Beyond dams: Assessing integrated water storage in the Shashe catchment, Limpopo River Basin

Study regionThe Shashe catchment, Limpopo River Basin, Botswana, and Zimbabwe. Study focusThe Shashe catchment is the third largest flow contributor to the Limpopo River Basin. Water availability in the Shashe catchment is highly seasonal due to high seasonal rainfall variability. The seasonality and inter-annual variability cause shortfalls (demand exceeds the average water availability) in certain months and years. Storage is needed to bridge the seasonal water availability “gap” and mitigate the deficits in drought years, i.e., inter-annual variability. While the need for water storage through grey infrastructure such as dams has long been known, there is growing recognition of the need for approaches to water storage that capitalize on all storage types. However, the current capacity to plan in ways that utilize all storage types is limited. The analyses conducted for this paper assessed the volume and spatial and temporal variability of different storage options – large and small dams, sand dams, soil moisture, and aquifers – in the Shashe catchment of the Limpopo River Basin. An integrated SWAT-MODFLOW model and remote sensing approach were developed for 2015–2020. New hydrological insights for the regionThe total annual water storage in the Shashe catchment is approximately 44,000 Mm3, dominated by groundwater. The annual storage is about 42,000 Mm3 in aquifers, 1500 Mm3 in soil, 700 Mm3 in large dam reservoirs, 45 Mm3 in small dams/ponds, and 0.13 Mm3 in sand dams. There is high seasonality in water storage availability. Soil moisture storage is at its maximum from January to March and lowest from July to September. Dam storage is at its maximum from March to May, and the water storage is relatively stable throughout the year. Aquifer storage is relatively stable during the dry seasons compared to other storage options. Optimizing water use considering the seasonal variation in different storage types could improve water availability and climate resilience.

Optimisation of Water-Use in Pulp and Paper Mills: A Streamlined Review of Scientific Journal Publications

The water-, and energy footprints of the processes in the pulp and paper industry are sizable enough to warrant investment of money and commitment of time truncate the same. Besides, there is also a nexus between water and energy here, with optimisation of the use of one of these resoruces enabling that of the other too. This streamlined review focuses on journal publications (originating from different parts of the world, and targeted at researchers and decision-makers in the industry) which train the lens on the optimisation of water use in this particular sector of the (forestry) bioeconomy. The synergies and complementarities which exist among different sustainable development goals (SDGs) , promise positive ripple effects, caused by attending to the truncation of the water footprint. The articles, in general, recommend effective in-plant wastewater treatment in combinaton with recirculating the treated effluent, and looking upon the water streams as carriers or bearers of valorisable substances – organics which can yield a host of bio-products in bio-refineries, including bio-energy. Availing of water-pinch analysis as a tool to uncover possibilities of water use in a cascade (depending upon the requirements imposed on the water, by processes downstream in the cascade), has been shown to aid in the optimisation of both water use and energy demand within the plant. One case study, for example, showed that the demand for steam can be decreased by about 4 GJ per ton of output, by recovering the waste heat in the water streams.

Comparative analysis of data-driven models and signal processing techniques in the monthly maximum daily precipitation prediction of El Kerma station Northeast of Algeria

The availability of a climate database is an essential requirement for modeling and mapping hydrological and environmental processes. Regardless of the nature and structure of these models, most of them require a complete and reliable dataset on a spatiotemporal basis. Unfortunately, the measurement of hydrological variables (precipitation, flow, etc.) can be affected by systematic errors, gaps and random data. The watershed of Seybouse located in the North-East of Algeria, has a network that has gaps in the monthly data with an average error percentage of 20.46% over the period of 1970–2008 on all the stations in operation. The current study combines support vector regression, artificial neural networks, boosted tree, bagged tree, gaussian processes regression and linear regression techniques with empirical mode decomposition and discrete wavelet transform techniques to fill the missing precipitation gaps. This study aims to determine which kernel function, regression type, tree and network structure and data decomposition technique will produce the best outputs in predicting missing rainfall. For this purpose, it aims to comprehensively evaluate various soft computing and signal processing models and use strengthened hybrid approaches by combining them. While modeling, 70% of the data was used for training and the rest for testing. Mean absolute error (MAE), root mean square error (RMSE), determination coefficient (R2), Taylor diagram and Violin plots were used to find the best model. As a result of the analysis, it was concluded that the SVM model produced superior outputs compared to other machine learning models. The single LSVM model had an R2 value of 0.78, RMSE of 8.18, and MAE of 5.90. The W-LSVM model had an R2 value of 0.78, RMSE of 8.10, and MAE of 5.90. The EMD-CGSVM model had an R2 value of 0.69, RMSE of 10.43, and MAE of 7.10. These results indicate that the W-LSVM models provided the most accurate rainfall forecast outputs. The results showed that the wavelet-based linear support vector regression model in precipitation prediction is the most successful artificial intelligence model. Finally, using the W-LSVM model to predict rainfall in the study area can significantly improve water resources management and flood strategies and help optimize water use and structures.

Geospatial identification of possible rainwater harvesting locations within a high-altitude Gilgit River basin, Pakistan

The management of water resources is no longer an option but a necessity especially in countries with a high rate of population growth like Pakistan. Pakistan has a high-water scarcity, an extremely varying topography, and is also one of the countries encountering the problem of climate change. Therefore, prudent utilization of available water resources is a matter in the plains of Pakistan as in its high-altitude regions. Instead of wasting water which is a valuable resource, rainwater harvesting is a way of saving rainwater as an alternative source of fresh water for better use. The aim of this study was to search for potential rainwater-harvesting areas in a high-altitude Gilgit River basin. This research employed the SCS-CN technique in estimating surface runoff in the GIS environment. The geospatial study used four input parameters: slope of the land, land covers, surface runoff and drainage density. The research concluded that some lands, especially those that are deserted in dry area and agricultural lands, can serve as the sites of rainwater harvesting, with only 4% of area that was highly suitable for the purpose. Nevertheless, 37% of the investigated area was shown as totally unviable for rainwater collection installations because of steep slopes and substantial volume of snow. Simultaneously, the rainwater storage design solutions suggested were check dam, percolation tank, and agricultural ponds with the area of 3.5%, 1%, and 0.75% of the given land area, respectively, for rainwater harvesting. The locations of potential catchment and planned rainwater harvesting structures would assist the local authorities and the policy makers to provide plans and design on the construction of water storages and also the optimization of water use.