Irrigation Water Consumption Research Articles

Contrasting effects of increasing irrigation efficiency on hydrological drought based on hydrological scenario simulations

Over-exploitation of water resources leads to water scarcity and aggravation of hydrological drought. An approach to addressing the problem is to invest in increasing irrigation efficiency (IE). However, higher IE may lead to the paradox of IE, that is, after increasing IE, irrigation water consumption (IWC) could increase rather than decrease. An important cause of the paradox of IE is that increasing IE may lead to an increase in irrigation area (IA). Therefore, an improved understanding of the impacts of such practices on hydrological drought is needed. This study used the PCR-GLOBWB 2.0 model to investigate the effects of increasing IE on hydrological drought for the catchment above Bengbu in the Huaihe River Basin in central eastern China. The hydrological drought was simulated under three scenarios, i.e., a baseline scenario in which IE remains unchanged, an IE increases scenario, and an IE & IA increase scenario. The results show that increasing IE has two contrasting effects: aggravation and alleviation of hydrological drought. For instance, the increase in IE (from 0.562 to 0.601 in Henan, 0.482 to 0.544 in Anhui, and 0.464 to 0.522 in Hubei province) from 2009 to 2019 reduced standardized drought streamflow deficit (SDSD) by about 5 ∼ 60 % in the central parts of the study area, whereas in the northern edge of the study area, it intensified SDSD even by more than 80 %. When water availability (WA) is high and can meet most of the crop water demand, increasing IE will lead to a situation in which the increase of IWC is less than the decrease of irrigation water withdrawal (IWW). In this situation, increasing IE alleviates the hydrological drought as intended. However, when water resources are relatively scarce with limited WA and cannot meet most of the crop water demand, increasing IE could lead to a paradoxical situation where the increase of IWC is higher than the decrease of IWW and thereby aggravates the hydrological drought. Also, increasing IE can aggravate the hydrological drought in water-receiving areas by reducing water supply from outside water supply regions. Results show that the impact of increasing IE and IA on hydrological drought is also two-sided, but the aggravating effect is dominant because the increase in IA leads to a significant increase in IWW and IWC. However, when the irrigation system restricts the increase of IA (the IA cannot increase or only slightly), the intensification effect of increasing IE and IA on hydrological drought will be weakened, and may even alleviate the hydrological drought. These results underline the importance of considering consequences at both local and basin scales, particularly for periods during and following drought, when policy makers consider the promotion of water-saving measures at irrigation-system level.

Joint guarantee rate index assessment of the contribution of agricultural water-saving measures to river ecological flow in water shortage areas

Reconciling higher ecological water demands and economic purposes with finite freshwater resources remains one of the great management dilemmas. Low water efficiency and large water consumption in agricultural irrigation hinder the protection of river ecological flow in the water shortage areas of Northwest China. By analyzing the surplus and shortage of river ecological protection targets, the intensity guarantee rate index is innovatively proposed to quantitatively evaluate the important contribution of improved water-saving measures for river flow restoration. It compensates for the shortcomings of the duration guarantee rate index in evaluation that may mask ecological problems. Considering ecological baseflow, fish species, and landscape water demand, the ecological flow interval (6.00–12.42 m3/s) was determined. Three scenarios are highlighted for different typical years and irrigation regimes in combination with planting structure adjustment and irrigation water utilization coefficient. In 75 %, 90 %, and 95 % typical years, the maximum total annual water-savings (Scenario 3) are 57.3, 57.1, and 87.2 million m3 (sufficient irrigation); 32.2, 33.9, and 35.5 million m3 (deficit irrigation) respectively. The guarantee degree of river ecological flow under both irrigation regimes increased from the previous 65.6 % to a maximum of 91.7 % and 81.2 %. The increase in the daily guarantee rate and decrease in the intensity guarantee rate under the aforementioned three scenarios indicate a reduction of damage depth and duration of ecological flow. By using a quantitative study, it is pointed out that improving agricultural water-saving is a reasonable and necessary way to protect the river flow.

Prediction of reference crop evapotranspiration based on improved convolutional neural network (CNN) and long short-term memory network (LSTM) models in Northeast China

The accurate prediction of reference crop evapotranspiration (ET0) is essential to better manage crop irrigation water consumption and improve crop water use efficiency. To effectively improve the accuracy of ET0 simulated by machine learning models, five meteorological stations in Hailaer, Harbin, Hohhot, Changchun, and Dalian were taken as representative stations, daily and monthly ET0 data from 1952 to 2020 were used, and empirical mode decomposition (EMD) and wavelet threshold denoising (WD) were considered. The convolutional neural network (CNN) and long short-term memory network (LSTM) models were improved, and two new hybrid neural network models (EMD–WD–CNN and EMD–WD–LSTM) were constructed. Using the ET0 calculated using the FAO-56 Penman–Monteith (P–M) formula as the standard value, the applicability of the improved machine learning model was evaluated. Results showed the following: i) the daily ET0-PM minimum values of five stations were close to 0, the average values were not significantly increased, and the maximum values significantly fluctuated (the fluctuations in Hailaer and Hohhot showed an upward trend, and the fluctuations in Harbin, Changchun, and Dalian showed a downward trend). The annual average monthly ET0-PM varied seasonally, with the peak in June in the Hailaer station and May in all other stations (the peak in Hohhot was the largest, and the peak in Dalian was the smallest). ii) The daily and monthly ET0 values predicted by the proposed EMD–WD–CNN and EMD–WD–LSTM models were highly consistent with the calculated results of the P–M model, showing high accuracy on the daily and monthly ET0 of the simulated five stations (daily: mean absolute error (MAE), 0.30–0.41 mm/day; root mean square error (RMSE), 0.46–0.60 mm/day; R2, 0.86–0.95; monthly: MAE, 5.66–13.71 mm/month; RMSE, 8.97–18.04 mm/month; R2, 0.91–0.95). iii) The EMD–WD–CNN model was suitable for daily scale ET0 simulation and prediction in Northeast China and monthly scale in Harbin, Changchun, and Hohhot. The EMD–WD–LSTM model was suitable for monthly ET0 simulation and prediction in Hailaer and Dalian in Northeast China. The mixed models of EMD–WD–CNN and EMD–WD–CNN can effectively improve the prediction accuracy of ET0 and can provide a new method for agricultural development and irrigation regulation in Northeast China.

A network design of a canola-to-biodiesel supply chain by considering the water-energy-food-land-ecosystem-undesirable climate change nexus

Global warming, adverse environmental consequences, and the rapid depletion of oil resources are some of the critical challenges that humanity presently confronts due to the utilization of fossil fuels. Replacing fossil fuels with renewable sources of energy such as biofuel is crucial for a clean environment. In addition to its numerous advantages, the production of biofuels has detrimental effects on natural resources as well. Water, energy, food, and land are all required to produce food and energy, which are inextricably linked as the essential inputs for agriculture and fuel production. Undesirable climate change and its impacts on ecosystems are also consequences of this process. This study offers a two-phase approach to designing a canola-to-biodiesel supply chain. The first phase is concerned with finding appropriate sites for canola cultivation in accordance with climatic, social, economic and design criteria. To achieve an ideal solution, the fuzzy best-worst method andthe fuzzy technique of order preference similarity to the ideal solution are simultaneously used. In the second phase, a new multi-objective integer programming model that involves a water-energy-food-land-ecosystem-undesirable climate change nexus is introduced. The suggested model enhances crop harvest from desirable agricultural areas, maximizes the profit, preserves ecosystem values, mitigates undesirable climate changes, and reduces water and energy consumption. An interactive fuzzy method is used to solve the model, and the efficiency of the proposed model is evaluated through a real case study for Iran. Sensitivity analyses are also performed on the key parameters. According to the findings, production activities are connected with the increase of network costs, adverse changes in climate, and increased use of energy. Thus, using high-yield catalysts, increasing the production scale, complying with environmental regulations, receiving government subsidies, investing in research to improve production technologies, and identifying cost-saving strategies can minimize harmful environmental effects and reduce biodiesel production costs, thereby boosting the profit. Furthermore, given Iran’s water scarcity and reduced rainfall, increasing the canola yield per hectare might lead to less land use and water consumption for irrigation. Utilizing specialized machinery, enhancing farmers’ skills in canola cultivation, supplying seeds on time, planting promptly, providing optimal nutrition, and promoting pest management are all effective methods to boost canola yields. The insights provided in this study can help managers in the canola-based biodiesel production sector make better decisions.

Water Sharing Geopolitics between India and Bangladesh: Recent Trends

The partnership between India and Bangladesh according to water sharing is complex by traditional, geographical, political, sociological, and economical issues. Understanding the present dynamics in water-sharing geopolitics is necessary for understanding the pathways of their bilateral partnership and the conjugation for regional sustainability and improvement. Both countries share almost 54 rivers for example Teesta, Ganges, Brahmaputra, and Meghna. These rivers are lifelines for Bangladesh and India, providing essential irrigation water, communication, and indigenous consumption. However, the unequal distribution of water and the influence of climate change have increased challenges over water management procedures. While both countries have contracted diverse treaties and agreements to manage shared rivers, implementation hazards and occasional breaches of trust have channeled their partners. Subsequently, the increasing demand for water due to population enrichment and industrialization shapes modern challenges for stable water mechanisms. This research aims to describe the present dynamics in water-sharing geopolitics between India and Bangladesh, examining the evolving trends, key factors, and their conjugations for regional sustainability and collaboration. By extending the complexities of this critical view of their partnership, this study seeks to contribute to a deeper realization of South Asia's geopolitical arena and prosecutorial dynamics for cooperative water distribution strategies.

Remote sensing monitoring of irrigated area in the non-growth season and of water consumption analysis in a large-scale irrigation district

Globally, water scarcity threatens food security, especially in arid and semi-arid food-producing regions, such as the Hetao Irrigation District (HID), where the water consumption during the non-growth season (spring irrigation, autumn irrigation) accounts for more than 30 % of the total irrigation volume. Meanwhile, mapping the characteristics of spatial and temporal evolution of the area of cropland irrigated in the spring and autumn and the pattern of water consumption is crucial for strengthening the management of agricultural water use. Evaporation and infiltration of irrigation water are difficult to capture in time due to insufficient timeliness or accuracy of single remote sensing data. This study integrates seven remote sensing datasets (Landsat5, Landsat7, Landsat8, HJ-1A/B, GF-1, Sentinel-2 and MODIS) for the first time to build a high spatial-temporal resolution dataset, and combines the water index NDWI and MNDWI to extract the maximum water range formed after irrigation by manually adjusting the threshold method. In addition to the global land use/cover dataset (GLC FCS30–1985_2020), the cropland layer was superimposed to accurately identify the cropland spring irrigation and autumn irrigation range from 2000 to 2021 in the HID. In the past 20 years, spring-irrigated (SI) areas increased by 1012.60 km2 (+49.96 %), and the autumn-irrigated (AI) areas decreased by 512.63 km2 (-11.02 %). Combined with the quantity of water diversion and displacement, the characteristics of irrigation water consumption in the non-growth season were further analysed. The results showed that the water consumption of spring irrigation increased by 0.67×108 m3 (+22.26 %), and that of autumn irrigation increased by 4.34×108 m3 (+38.82 %). The decrease of autumn- irrigated area and the increase of water consumption were mainly related to the stability of autumn irrigation water, imperfect irrigation and drainage conditions and insufficient field water management. In 2020­2021, the area of non-growth “autumn irrigation - spring irrigation” repeated irrigation is about 1271.52 km2, which can be used as a key control area. This study provides a theoretical basis and direction for rational water use in non-growth seasons of irrigation districts.

Towards the sustainable development of water security: A new copula-based risk assessment system

Water security is deeply intertwined with ecosystems, society and the economy, and is a frequent focal point of sustainable development. This study investigates the water security (WS) of Inner Mongolia, a dryland region in northern China. Specifically, an indicator system integrating the principles of Stability (S), Cooperation (C), and Resilience (R) was constructed to quantitatively and comprehensively assess water security. Risk probability was calculated by the constructed system by combining its output with a copula function. The findings revealed that: (1) WS-SCR levels in the study area gradually increased from 2001 to 2021. The periods multi-year average was 0.42, which is at the threshold level of security; (2) Based on a standard deviation ellipse, the spatial distribution of WS-SCR levels changed from northeast to southwest and back to northeast. The centroid of change shifted from east to west and back to east; (3) Key drivers influencing water security included GDP per capita (S3), agricultural irrigation water consumption per unit area (C4), comprehensive water use per capita (C5), reclaimed water use rate (C8), fertilizer application per unit of farmland (R4), and population density (R5); (4) The S-C, S-R, and C-R relationships within the study area were best modelled by the Clayton copula function, whereas the S-C-R relationship was most accurately modelled by using a Frank copula function. The three-dimensional joint risk probability S-C-R (S≤0.4, C≤0.4, R≤0.4) is 0.226; the probability that R was insecure increased with increasing S or C index values. This study provides a scientific foundation for the long-term planning and management of sustainable water security development in Eurasian drylands.

Effect analysis of government intervention on scale-heterogeneous farmers' behavior of groundwater exploitation.

Government intervention has become an important measure to restrain groundwater overexploitation. This paper analyzes the effect of three types of government intervention measures, namely, guidance, incentive and constraint, on farmers' groundwater utilization behavior, from the perspective of scale-heterogeneity, using general quantile regression model, by survey data of 1122 households in well irrigation area of north China. The results showed that: (1) the incentive and guiding measures have negative effects on farmers' groundwater usage, while the effect of restrictive measures is not obvious. The guided policy is superior to the incentive measure as to governance effect. (2) With the increase of farmers' land scale, the influence of incentive measures shows a trend of weakening, and the effect of guided measures on groundwater demand reduction of farmers is stronger. When it comes to the different point of water consumption, when at the point level of 0.25, the incentive measures have the most obvious inhibitory effect. With the increase of water consumption of farmers, the guided measures begin to play a core role. The effect of restrictive measures is not obvious with the increase of water consumption. (3) In addition, farmers' irrigation water consumption also is affected by gender, cognition of water resources shortage, ecological cognitive level, acquisition ability of disaster information, village rain conditions, the degree of water rights market development, feelings of water fee increase, irrigated disputes in the village, collective economic level of village. The selection of policy tools is flexible according to the farmers' land scale for groundwater over-extraction control.

Crop water productivity assessment and planting structure optimization in typical arid irrigation district using dynamic Bayesian network

Enhancing crop water productivity is crucial for regional water resource management and agricultural sustainability, particularly in arid regions. However, evaluating the spatial heterogeneity and temporal dynamics of crop water productivity in face of data limitations poses a challenge. In this study, we propose a framework that integrates remote sensing data, time series generative adversarial network (TimeGAN), dynamic Bayesian network (DBN), and optimization model to assess crop water productivity and optimize crop planting structure under limited water resources allocation in the Qira oasis. The results demonstrate that the combination of TimeGAN and DBN better improves the accuracy of the model for the dynamic prediction, particularly for short-term predictions with 4 years as the optimal timescale (R2 > 0.8). Based on the spatial distribution of crop suitability analysis, wheat and corn are most suitable for cultivation in the central and eastern parts of Qira oasis while cotton is unsuitable for planting in the western region. The walnuts and Chinese dates are mainly unsuitable in the southeastern part of the oasis. Maximizing crop water productivity while ensuring food security has led to increased acreage for cotton, Chinese dates and walnuts. Under the combined action of the five optimization objectives, the average increase of crop water productivity is 14.97%, and the average increase of ecological benefit is 3.61%, which is much higher than the growth rate of irrigation water consumption of cultivated land. It will produce a planting structure that relatively reduced irrigation water requirement of cultivated land and improved crop water productivity. This proposed framework can serve as an effective reference tool for decision-makers when determining future cropping plans.

The TIMES Land-WEF model: An integrated analysis of the agricultural system of the Basilicata Region (Southern Italy)

The unsustainable use of natural resources, in particular soil degradation and pollution, is one of the main factors contributing to the climate and biodiversity crisis. The European Union has outlined a new European Green Deal, whose objectives include increasing the overall quality of the agri-food chain in relation to environmental sustainability, focusing on reducing the use of pesticides and increasing the share of organic in overall production. A Nexus thinking perspective is applied to analyse this topic over a 50-year time horizon (2010–2060) for the agricultural system of the Basilicata Region (Southern Italy), represented by the TIMES Land-WEF, an optimizing, bottom-up energy-technology model, built to investigate the interactions and interrelations between water, energy food and land. The novelty of this modelling approach is the choice of land use as the guiding parameter of the optimization process. The main objectives of the Farm to Fork Strategy are modelled as system constraints and the scenario analysis allows to characterise their effects on the evolution of the agricultural system over the examined time. The results show that the pesticide reduction constraint leads to an increase in land use by organic crops from 24.6 % to 32.4 % in 2060. In particular, this is due to the increased contribution of cereal, forage, olive growing crops, permanent meadows and pastures, which lead to a 46 % reduction in irrigation water consumption. On the other hand, the reduction in inorganic fertilizers is not accompanied by a significant increase in organic crops, but resulted in the reduction of cereal crops.

Climate-adaptive crop distribution can feed food demand, improve water scarcity, and reduce greenhouse gas emissions

Optimizing crop distribution stands as a pivotal approach to climate change adaption, enhancing crop production sustainability, and has been recognized for its immense potential in ensuring food security while minimizing environmental impacts. Here, we developed a climate-adaptive framework to optimize the distribution of staple crops (i.e., wheat, maize, and rice) to meet the multi-dimensional needs of crop production in China. The framework considers the feasibility of the multiple cropping systems (harvesting more than once on a cropland a year) and adopts a multi-dimensional approach, incorporating goals related to crop production, water consumption, and greenhouse gas (GHG) emissions. By optimizing, the total irrigated area of three crops would decrease by 7.7 % accompanied by a substantial 69.8 % increase in rain-fed areas compared to the baseline in 2010. This optimized strategy resulted in a notable 10.0 % reduction in total GHG emissions and a 13.1 % decrease in irrigation water consumption while maintaining consistent crop production levels. In 2030, maintaining the existing crop distribution and relying solely on yield growth would lead to a significant maize production shortfall of 27.0 %, highlighting a looming challenge. To address this concern, strategic adjustments were made by reducing irrigated areas for wheat, rice, and maize by 2.3 %, 12.8 %, and 6.1 %, respectively, while simultaneously augmenting rain-fed areas for wheat and maize by 120.2 % and 55.9 %, respectively. These modifications ensure that production demands for all three crops are met, while yielding a 6.9 % reduction in GHG emissions and a 15.1 % reduction in irrigation water consumption. This optimization strategy offers a promising solution to alleviate severe water scarcity issues and secure a sustainable agricultural future, effectively adapting to evolving crop production demands in China.

Optimization of the Coupling between Water and Energy Consumption in a Smart Integrated Photovoltaic Pumping Station System

Agricultural irrigation requires significant consumption of freshwater resources and energy. The integration of photovoltaic power generation into irrigation systems has been extensively investigated in order to save the cost of energy. However, current research often neglects the coupling relationship between photovoltaic power generation and irrigation schemes. This study presented a novel smart integrated photovoltaic pump station system to effectively address the issue associated with water and energy consumption in irrigation. An optimization model was proposed to synchronize the energy consumption of irrigation pump stations with photovoltaic power generation, accurately meeting the irrigation water demand while maximizing solar energy utilization. The optimization model incorporates power balance, grid-connected power, and total water demand as constraints while considering pump speed as the decision variable and aiming to minimize daily operational costs. Finally, a high-standard farmland was used as a case study to validate the efficacy of the optimization strategy through two photovoltaic grid-connected policies—one allowing for the sale of surplus power and the other prohibiting it. An improved dynamic programming method was employed to solve for optimal energy consumption schemes under different water demand conditions; the results were compared against traditional methods, revealing potential cost savings ranging from 6.2% to 30.5%. The optimization model and method propose a new operational concept for the irrigation system with photovoltaic generation, effectively utilizing the distinctive features of both irrigation and photovoltaics to optimize water and energy resources.

Water Use Efficiency in a Deficit-Irrigated Orange Orchard

Citrus is a subtropical fruit tree with high water requirements. This study aimed to determine the effects of water deficit on an orange orchard subjected to different water-saving strategies. The study was realised in an orange orchard in a semiarid area by adopting four different water management techniques: 100% crop evapotranspiration (control); SSDI—subsurface sustained deficit irrigation; RDI—regulated deficit irrigation; PRD—partial rootzone drying treatment during five growing seasons. The experimental design foresaw a randomised block design with six replicates per treatment (24 index plants). The results of the study showed that the water-saving strategies reduced irrigation water consumption by 25% (SSDI), 33% (RDI), and 49% (PRD) compared to the fully irrigated treatment without yield reduction, thus increasing water use efficiency. Mineral nutrition of the trees was slightly affected by irrigation treatments; element concentration in leaves was generally in the optimal range; only potassium showed values below the recommended leaf concentrations. Regarding fruit quality parameters, the vitamin C concentration in RDI showed significant differences with a value of 62.7 mg 100 mL−1 compared to 58.5 mg 100 mL−1 in the control. Plants subjected to SSDI and PRD strategies showed increased levels of pulp colour index with significant values of 10 and 9.90, respectively, compared to the control (8.44). By implementing targeted water management, citrus growers could save water and increase the ascorbic acid and sugar concentration in the fruits; anthocyanins also increased but not significantly. These findings open new market opportunities for citrus growers in marginal areas, where they cannot rely solely on producing citrus fruits to remain competitive.

High environmental quality label proposal

Our idea aims to evolve agricultural models and face the growing challenge of resilience of agricultural systems. We offer a high environmental quality label that encourages farmers in developing countries to optimize inputs. It will encourage them to reduce the consumption of pesticides, fertilizers and irrigation water. At present, many decision support tools are widely used in modern agriculture, notably soil tensiometers to control irrigation, the nitrogen balance in the management of fertilization and the I-PHY indicator of pesticide use in the field of plant protection. The use of these three tools is inexpensive and technically affordable by farmers. We offer a framework based on these decision-making tools and agricultural techniques which will allow farmers to have a High Environmental Quality Label.

The allocation of crop production resources in the southeast of Iran: the application of the water-energy-food nexus approach

Introduction: Due to the expansion of population, economic progress, urbanization, increasing food demands, and diversification of food systems, resources are being excessively exploited and degraded. This is compounded by the challenges posed by climate change and limited resources, as well as inadequate management practices. The concept of water-energy-food (WEF) nexus management recognizes the interdependencies among various resources, such as water, food, and energy, in order to promote sustainable resource management. By establishing a harmonious balance among different objectives, this approach aims to safeguard the well-being of both human societies and the environment, ensuring the fulfillment of needs and the preservation of benefits for both parties.Methods: In this study, the water-energy-food (WEF) nexus approach is applied to the Sistan plain, located in the southeastern region of Iran, to effectively redistribute production resources within the agricultural sector. The methodology employed is multi-objective programming, which incorporates various goals. These objectives encompass maximizing farmer revenue and energy derived from food production (measured in calories), while simultaneously minimizing greenhouse gas (GHG) emissions, irrigation water consumption, and overall energy consumption throughout the 2018–2019 crop year.Results: The findings of this study demonstrate that implementing the water-energy-food (WEF) nexus approach in the Sistan plain yields positive outcomes. Despite a reduction in the cultivation area, there is a notable shift towards growing more nutritious crops. This shift not only contributes to food security but also increases crop calorie production from 457.16 million to 565.19 million. Consequently, there is a decrease in irrigation water consumption from 261.62 million to 260.48 million cubic meters, energy consumption from 1400.13 million to 1396.81 million MJ per hectare, and greenhouse gas (GHG) emissions from 0.014 million to 0.0139 million tons per hectare.Discussion: Analyzing the physical and economic productivity reveals that GHG emissions had the highest productivity in terms of both physical and economic measures in Zahak County. As the WEF nexus approach aims to preserve and prevent environmental degradation, it is recommended to implement development and bio-balance policies utilizing this approach to ensure environmental conservation.

The water-food-energy nexus evaluation and optimization of cropping system in the North China Plain: A case of county scale

Water, energy, and food, which are closely related to human beings, have been proposed by the Sustainable Development Goals, and there are closely related but contradictory relationships among the three. As one of China's main grain-producing regions, the North China Plain (NCP) with dominant grain-oriented cropping system is faced with severe challenges for agricultural sustainable development, such as water and energy shortages, as well as grain safeguard. In this study, a “TKL-WEFN” model combining Tapio decoupling, Kaya, and LMDI was used to evaluate the synergistic relationship from the water-energy-food (WEF) and determine the key drivers taking Wuqiao County in the NCP as a case. The results showed as follows: the synergistic relationship between water-food, as well as energy-food, showed a “M” shaped fluctuation trend from 2009 to 2018 in Wuqiao County. The best performance was achieved in 2011 and 2016, with the state of high yield and low resource consumption. Food increased by 9.43% and 3.52%, while water resources decreased by 5.95% and 8.91%, and energy decreased by 5.36% and 2.15% in 2011 and 2016, respectively. The changes in water consumption for irrigation and fossil energy consumption per unit area of maize and cotton, as well as the adjustment of planting structure, are the main factors affecting the sustainability of crop systems from 2009 to 2018. Water-saving irrigation, no-tillage, and cropping system transformation can improve resources supply and demand, saving 4.61%–50.27% (with an average of 19.47%) of water consumption and 1.91%–13.08% (with an average of 6.45%) of energy consumption by scenarios analysis. Therefore, changing grain-oriented cropping system while maintaining food security and developing water-saving irrigation technology can accelerate the realization of green agriculture.

High-Technology Agriculture System to Enhance Food Security: A Concept of Smart Irrigation System Using Internet of Things and Cloud Computing

CONTEXT: Food security is highly reliant on agricultural activity to drive the world economy. However, this activity is in great danger due to climatic changes and improper use of irrigation techniques. Consequently, the lives of numerous individuals worldwide are in jeopardy. In light, this paper investigates the promise of smart irrigation systems based on new technology. OBJECTIVE: To meet the growing demand for water in agriculture, this study presents an intelligent irrigation system that uses cutting-edge technologies of 1) cloud computing, 2) embedded systems, and 3) Internet-of-Things (IoT). The main objective is to demonstrate how this innovative strategy can effectively manage water resources, supporting food security through cutting-edge agricultural technology. METHODS: This paper proposes a smart irrigation system based on cutting-edge technologies like the embedded system, Internet of Things (IoT), and cloud computing as a groundbreaking strategy to improve food security through the implementation of advanced agricultural technology. This system supervises real-time monitoring of crucial environmental factors such as 1) moisture, 2) humidity, 3) temperature, and 4) water levels, in smart agriculture practices. In addition, this system employs the latest sensors, including the module (DHT22), water level sensor, and moisture sensors, which are connected to the widely used embedded system (ESP32). The system uses the ThingSpeak cloud and ThingView app to enable wireless communication between the device and the farm owner, enhancing their interaction. The automated control of the two water pumps is based on the readings of various environmental factors. Moreover, this will also present a mathematical-driven function known as linear interpolation to calibrate the water level sensor in percentage. This system was created using the V-model software development approach. RESULTS AND CONCLUSION: Farmers can access comprehensive farm data from anywhere in the world as the sensor data is transmitted in real-time to both the ThingSpeak cloud and the ThingView. This capability allows for more precise crop irrigation and increased production. The study's findings demonstrate a striking 70% reduction in water consumption for soil irrigation when utilizing the proposed smart irrigation system. This paper underscores the significant promise of smart irrigation systems, driven by IoT, embedded systems, and cloud computing, to conserve water resources and advance food security. SIGNIFICANCE: This article proposes an innovative solution that reduces soil irrigation water consumption by 70% compared to traditional methods. It explores how smart irrigation can improve the sustainability of agriculture and positively influence food security.

Water resource security evaluation and barrier analysis in Henan Province utilizing the DPSIR framework

Water resource health is one of the necessary conditions for society to achieve sustainable development. Due to the predominant focus of most studies on relatively short time spans, with limited attention to long time series and spatial trends, this study, using various regions of Henan Province as a case study, constructs a water resource security assessment framework based on the DPSIR model encompassing Drivers (D), Pressures (P), State (S), Impact (I), and Response (R) dimensions, with a selection of 19 evaluation indicators. Based on this evaluation index system, the CRITIC-TOPSIS evaluation method is formulated by integrating the CRITIC (Criteria Importance Through Intercriteria Correlation) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) models. This method is employed to assess the degree of water resource security in Henan Province from 2013 to 2022. And the Obstruction Degree Model is introduced to diagnose the water resource security levels in various regions of Henan Province. The assessment results indicate that over the past decade, the overall level of water resource security in various regions of Henan Province has shown an increasing trend. Irrigated area, per capita water resources, water consumption per unit of industrial value added, per acre water consumption for agricultural irrigation, the ratio of river length meeting water quality standards, groundwater supply proportion, and sewage treatment rate are identified as the primary obstacles influencing the water resource security levels in different regions of Henan Province. The research outcomes of this study can serve as theoretical foundations to enhance urban water resource security globally, ultimately facilitating sustainable development.

Investigation of Irrigation Erosion in Pseudopodzol Yellow Soils of the Lankaran District

Inclination, length, form and exposition of the slopes affect the irrigation erosion process in the Lankaran district. The artificial rain in a different intensity was created in the tea plantations of the experiment farm of the tea and citrus plants in Lankaran branch in order to study a reason of the surface washing creation in irrigation erosion of the tea plantations more accurately. It was known that a tea plantation in which the rows were built along the slope in 1975, the liquid flow was 125.0 m3/ha, while the rain intensity was 1.0 mm/min., the liquid dissolved dissolved substances flow was 240.0 m3/ha, 2.90 t/ha in the tea plantations built in 1990, while an amount of the leached soil was 0.80 t/ha. Firstly, conduction of the surface smoothing work is recommended in order to prevent from irrigation erosion in irrigated areas with a slope more than 0.02°. Generally, the surface smoothing work is fundamental and current, and it is divided into two places. The current smoothing work begins from preparation of soil for sowing every year and this measure doesn’t require more funds. The fundamental smoothing work is performed for fundamental smoothing of the irrigated sowing areas. At this time an inclination of the areas shouldn’t be more than 0.01. It is recommended to conduct the fundamental smoothing work, then current smoothing work in the areas where the inclination is more than 0.01. Fight against irrigation erosion, definition of the water and irrigation norm, water consumption and realization in the irrigated areas are main problems. The irrigation norm should be determined before for each plant watering. Beside the aforesaid, the technical means (pipes that are made from different materials), including different brands (Fregat, Kuban, KSID-50, Volzhanka, DDA-100 M and so on) rainmaker aggregates, various progressive irrigation methods (artificial precipitation, subsoil irrigation, drip watering, aerosol irrigation, etc.) should be used.

Climate-smart irrigation strategy can mitigate agricultural water consumption while ensuring food security under a changing climate

North China Plain suffers from the world’s most severe water scarcity and groundwater depletion due to intensive irrigation for agricultural production. It is imperative to reduce irrigation water consumption while safeguarding crop production and food security. This study conducted a quantitative analysis with deficit irrigation strategies for winter wheat using a water-driven AquaCrop model. After model calibration and validation with field experimental data, we analyzed the irrigation water demand, crop yield, and water productivity (WP) of winter wheat under various deficit irrigation scenarios. A set of optimal irrigation schedules were proposed for different climate years, which significantly mitigated irrigation water usage while sustaining high yields and WPs. The results indicated that despite the irrigation water demand of winter wheat under the future climate scenario was slightly higher than that in the historical period, their crop water sensitive periods (reviving, jointing, and flowering) remained the same. Therefore, we recommended adopting the same deficit irrigation schedules for the historical and future periods. In wet years, adopting a 50% deficit irrigation strategy only reduced crop yields by less than 5% compared with full irrigation, but it saved 1000–1100 m3 of water per hectare and contributed a WP higher than 1.88 kg/m3. While in normal and dry years, an optimal 25% deficit irrigation could sustain over 96% of the maximum yield, meanwhile it could save 650–800 m3/ha of water and achieve almost the same WP as full irrigation. These climate-smart irrigation strategies adapting to diverse climatic conditions largely mitigate agricultural water consumption while maximizing crop productivity and water use efficiency, which are essential for achieving precision irrigation and sustainable water management under a changing climate.